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@article{Canales-Benavides2019,
author = {Canales-Benavides, Arturo
and Zhuo, Yue
and Amitrano, Andrea M.
and Kim, Minsoo
and Hernandez-Aranda, Raul I.
and Carney, P. Scott
and Schnell, Martin},
title = {{A}ccessible quantitative phase imaging in confocal microscopy with sinusoidal-phase synthetic optical holography},
journal = {Applied Optics},
year = {2019},
publisher = {OSA},
volume = {58},
number = {5},
pages = {A55--A64},
optkeywords = {Confocal laser scanning microscopy; Image processing; Medical imaging; Mirau interferometry; Phase imaging; Phase modulation},
abstract = {We present a technically simple implementation of quantitative phase imaging in confocal microscopy based on synthetic optical holography with sinusoidal-phase reference waves. Using a Mirau interference objective and low-amplitude vertical sample vibration with a piezo-controlled stage, we record synthetic holograms on commercial confocal microscopes (Nikon, model: A1R; Zeiss: model: LSM-880), from which quantitative phase images are reconstructed. We demonstrate our technique by stain-free imaging of cervical (HeLa) and ovarian (ES-2) cancer cells and stem cell (mHAT9a) samples. Our technique has the potential to extend fluorescence imaging applications in confocal microscopy by providing label-free cell finding, monitoring cell morphology, as well as non-perturbing long-time observation of live cells based on quantitative phase contrast.},
issn = {1539-4522},
doi = {10.1364/Ao.58.000a55},
opturl = {http://ao.osa.org/abstract.cfm?URI=ao-58-5-A55},
opturl = {https://doi.org/10.1364/Ao.58.000a55},
file = {docs/Canales-Benavides2019.pdf}
}
@article{Chen2013,
author = {Chen, Weili
and Long, Kenneth D.
and Lu, Meng
and Chaudhery, Vikram
and Yu, Hojeong
and Choi, Ji Sun
and Polans, James
and Zhuo, Yue
and Harley, Brendan A. C.
and Cunningham, Brian T.},
title = {{P}hotonic crystal enhanced microscopy for imaging of live cell adhesion},
journal = {The Analyst},
year = {2013},
volume = {138},
number = {20},
pages = {5886--5894},
optkeywords = {Animals; Biosensing Techniques/*methods; Cell Adhesion/physiology; Cells; Cultured; *Chemotaxis/physiology; Crystallization/*methods; Mice; Microscopy; Confocal/methods; *Optical Phenomena; Stem Cells/chemistry/*cytology/physiology},
abstract = {A form of microscopy that utilizes a photonic crystal biosensor surface as a substrate for cell attachment enables label-free, quantitative, submicron resolution, time-resolved imaging of cell-surface interactions without cytotoxic staining agents or temporally-unstable fluorophores. Other forms of microscopy do not provide this direct measurement of live cell-surface attachment localization and strength that includes unique, dynamic morphological signatures critical to the investigation of important biological phenomena such as stem cell differentiation, chemotaxis, apoptosis, and metastasis. Here, we introduce Photonic Crystal Enhanced Microscopy (PCEM), and apply it to the study of murine dental stem cells to image the evolution of cell attachment and morphology during chemotaxis and drug-induced apoptosis. PCEM provides rich, dynamic information about the evolution of cell-surface attachment profiles over biologically relevant time-scales. Critically, this method retains the ability to monitor cell behavior with spatial resolution sufficient for observing both attachment footprints of filopodial extensions and intracellular attachment strength gradients.},
note = {[PMID: \href{https://pubmed.ncbi.nlm.nih.gov/23971078}{23971078}]},
issn = {0003-2654},
doi = {10.1039/c3an01541f},
opturl = {http://www.ncbi.nlm.nih.gov/pubmed/23971078},
opturl = {https://doi.org/10.1039/c3an01541f},
file = {docs/Chen2013.pdf}
}
@inproceedings{Choi2015,
author = {Choi, Ji Sun
and Ilin, Yelena
and Zhuo, Yue
and Cunningham, Brian
and Kraft, Mary
and Harley, Brendan},
title = {{L}abel-{F}ree {A}nalysis of {S}ingle {H}ematopoietic {S}tem and {P}rogenitor {C}ells},
booktitle = {{T}issue {E}ngineering {P}art {A}},
year = {2015},
volume = {21},
number = {1},
pages = {S237--S238},
issn = {1937-3341},
opturl = {https://www.researchgate.net/publication/317378910_Label-Free_Analysis_of_Single_Hematopoietic_Stem_and_Progenitor_Cells}
}
@inproceedings{Choi2014,
author = {Choi, Ji Sun
and Ilin, Yelena
and Zhuo, Yue
and Cunningham, Brian
and Kraft, Mary
and Harley, Brendan},
title = {{S}ingle-{C}ell {A}pproaches to {A}ssess {H}ematopoietic {S}tem {C}ell {R}esponses to {M}atrix {C}ues},
booktitle = {{B}iomedical {E}ngineering {S}ociety {A}nnual {M}eeting},
year = {2014},
opturl = {https://www.researchgate.net/publication/317379314_Single-Cell_Approaches_to_Assess_Hematopoietic_Stem_Cell_Responses_to_Matrix_Cues}
}
@inproceedings{Choi2016,
author = {Choi, Ji Sun
and Ilin, Yelena
and Zhuo, Yue
and Cunningham, Brian
and Kraft, Mary
and Harley, Brendan},
title = {{T}racing of individual hematopoietic stem cell specification events using {R}aman {S}pectroscopy and photonic crystal enhanced microscopy},
booktitle = {{F}rontiers in {B}ioengineering and {B}iotechnology},
year = {2016},
volume = {4},
optkeywords = {Cell Differentiation; stem cell; biosensing; matrix-cell interaction},
abstract = {Hematopoietic stem cells (HSC) are rare adult stem cells residing in the bone marrow that are responsible for life-long hematopoiesis. To enhance our understanding of the underlying mechanisms of HSC regulation and facilitate the clinical use of HSCs, it is desirable to engineer their specific fate decision events (self-renewal vs. differentiation) in vitro. Such efforts are limited by the lack of functional markers that enable non-invasive, dynamic analysis of individual HSCs in situ. Raman Spectroscopy is a promising chemical imaging tool that provides unique molecular fingerprints of individual, live cells in situ in a label-free manner. Similarly, photonic crystal enhanced microscopy (PCEM) is a label-free imaging platform that enables dynamic quantification of single HSC adhesion profiles. Here, we demonstrate the feasibility of applying Raman Spectroscopy and PCEM for screening HSC phenotype via the identification of primary hematopoietic cell populations and the segmentation of primitive hematopoietic progenitor cell populations during their differentiation to granulocytes.},
issn = {2296-4185},
doi = {10.3389/conf.FBIOE.2016.01.00701},
opturl = {https://www.frontiersin.org/10.3389/conf.FBIOE.2016.01.00701/event_abstract},
opturl = {https://doi.org/10.3389/conf.FBIOE.2016.01.00701},
file = {docs/Choi2016.pdf}
}
@inproceedings{Choi2016a,
author = {Choi, Ji Sun
and Ilin, Yelena
and Zhuo, Yue
and Kraft, Mary
and Cunningham, Brian
and Harley, Brendan},
title = {{I}n vitro control of hematopoietic stem cell fate decisions and analysis in a bone marrow-inspired synthetic niche},
booktitle = {{NIH}-{NIDDK} {E}ffects of {A}ging on {H}ematopoiesis {W}orkshop},
year = {2016},
opturl = {https://www.researchgate.net/publication/317379126_In_vitro_control_of_hematopoietic_stem_cell_fate_decisions_and_analysis_in_a_bone_marrow-inspired_synthetic_niche}
}
@inbook{Choi2017,
author = {Choi, Ji Sun
and Zhuo, Yue
and Cunningham, Brian T.
and Harley, Brendan A.},
title = {{N}on-invasive optical imaging on photonic crystalsurface of stem cell differentiation in biomaterials},
booktitle = {Monitoring and Evaluation of Biomaterials and their Performance in vivo},
year = {2017},
publisher = {Elsevier Inc.},
pages = {195--207},
isbn = {9780081006030},
file = {docs/Choi2017.pdf}
}
@inproceedings{Cunningham2015a,
author = {Cunningham, Brian T.
and Chen, Weili
and Long, Kenneth D.
and Zhuo, Yue
and Choi, Ji Sun
and Harley, Brendan A.},
title = {{P}hotonic crystal enhanced microscopy},
booktitle = {2015 {C}onference on {L}asers and {E}lectro-{O}ptics ({CLEO})},
year = {2015},
pages = {1--2},
optkeywords = {biological techniques; cellular biophysics; hyperspectral imaging; nanoparticles; optical microscopy; photonic crystals; reflectivity; photonic crystal enhanced microscopy; reflectance; spatially resolved imaging; cell-nanoparticle interaction; Optical surface waves; Microscopy; Fluorescence; Surface morphology},
abstract = {By modifying a microscope to perform hyperspectral imaging of reflectance from a photonic crystal, we describe a new microscopy approach that enables quantitative, spatially resolved imaging of the interaction of cells and nanoparticles with surfaces.},
issn = {2160-8989},
doi = {10.1364/CLEO_AT.2015.AW4K.1},
opturl = {https://doi.org/10.1364/CLEO_AT.2015.AW4K.1},
file = {docs/Cunningham2015a.pdf}
}
@article{Cunningham2016,
author = {Cunningham, Brian T.
and Zhang, Meng
and Zhuo, Yue
and Kwon, Lydia
and Race, Caitlin},
title = {{R}ecent {A}dvances in {B}iosensing {W}ith {P}hotonic {C}rystal {S}urfaces: {A} {R}eview},
journal = {IEEE Sensors Journal},
year = {2016},
volume = {16},
number = {10},
pages = {3349--3366},
abstract = {Photonic crystal surfaces that are designed to function as wavelength-selective optical resonators have become a widely adopted platform for label-free biosensing, and for enhancement of the output of photon-emitting tags used throughout life science research and in vitro diagnostics. While some applications, such as analysis of drug-protein interactions, require extremely high resolution and the ability to accurately correct for measurement artifacts, others require sensitivity that is high enough for detection of disease biomarkers in serum with concentrations less than 1 pg/ml. As the analysis of cells becomes increasingly important for studying the behavior of stem cells, cancer cells, and biofilms under a variety of conditions, approaches that enable high resolution imaging of live cells without cytotoxic stains or photobleachable fluorescent dyes are providing new tools to biologists who seek to observe individual cells over extended time periods. This paper will review several recent advances in photonic crystal biosensor detection instrumentation and device structures that are being applied towards direct detection of small molecules in the context of high throughput drug screening, photonic crystal fluorescence enhancement as utilized for high sensitivity multiplexed cancer biomarker detection, and label-free high resolution imaging of cells and individual nanoparticles as a new tool for life science research and single-molecule diagnostics.},
note = {[PMCID: \href{https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5021450}{PMC5021450}]},
issn = {1530-437X},
doi = {10.1109/JSEN.2015.2429738},
opturl = {http://www.ncbi.nlm.nih.gov/pubmed/27642265},
opturl = {https://doi.org/10.1109/JSEN.2015.2429738},
file = {docs/Cunningham2016.pdf}
}
@inproceedings{Cunningham2015,
author = {Cunningham, Brian T.
and Zhang, Meng
and Zhuo, Yue
and Kwon, Lydia
and Race, Caitlin},
title = {{R}eview of {R}ecent {A}dvances in {B}iosensing with {P}hotonic {C}rystal {S}urfaces},
booktitle = {{S}pecial {I}ssue on {S}elected {P}apers {F}rom {T}he {IEEE} {S}ensors 2014 {C}onference},
year = {2015},
abstract = {Photonic crystal surfaces that are designed to function as wavelength-selective optical resonators have become a widely adopted platform for label-free biosensing, and for enhancement of the output of photon-emitting tags used throughout life science research and in vitro diagnostics. While some applications, such as analysis of drug-protein interactions, require extremely high resolution and the ability to accurately correct for measurement artifacts, others require sensitivity that is high enough for detection of disease biomarkers in serum with concentrations less than 1 pg/ml. As the analysis of cells becomes increasingly important for studying the behavior of stem cells, cancer cells, and biofilms under a variety of conditions, approaches that enable high resolution imaging of live cells without cytotoxic stains or photobleachable fluorescent dyes are providing new tools to biologists who seek to observe individual cells over extended time periods. This paper will review several recent advances in photonic crystal biosensor detection instrumentation and device structures that are being applied towards direct detection of small molecules in the context of high throughput drug screening, photonic crystal fluorescence enhancement as utilized for high sensitivity multiplexed cancer biomarker detection, and label-free high resolution imaging of cells and individual nanoparticles as a new tool for life science research and single-molecule diagnostics.},
doi = {doi10.1109/JSEN.2015.2429738},
opturl = {https://www.semanticscholar.org/paper/Review-of-Recent-Advances-in-Biosensing-with-Cunningham-Zhang/3c447139785555f61c530e73473c8c04547cd6f3},
opturl = {https://doi.org/doi10.1109/JSEN.2015.2429738},
file = {docs/Cunningham2015.pdf}
}
@misc{Cunningham2019,
author = {Cunningham, Brian T.
and Zhuo, Yue
and Harley, Brendan A.
and Choi, Ji Sun
and Marin, Thibault
and Lu, Yi},
title = {{P}hotonic {R}esonator {A}bsorption {M}icroscopy ({PRAM}) for {D}igital {R}esolution {B}iomolecular {D}iagnostics},
year = {2019},
abstract = {A digital assay for a micro RNA (miRNA) or other target analyte in a sample makes use of nanoparticles that absorb light at the resonant wavelength of a photonic crystal (PC). Such nanoparticles locally quench the resonant reflection of light from the PC when present on the surface of the PC. The nanoparticles are functionalized to specifically bind to the target analyte, and the PC surface is functionalized to specifically bind to the nanoparticles that have bound to the target analyte. The sample is exposed to the functionalized nanoparticles, and the individual nanoparticles bound to the PC surface can be identified and counted based on reduced intensity values in the reflected light from the PC. The number of bound nanoparticles that are counted in this way can be correlated to the abundance of the target analyte in the sample.},
doi = {https://www.patentguru.com/US2019127784A1},
opturl = {https://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20190502&DB=EPODOC&locale=&CC=US&NR=2019127784A1$\#$},
opturl = {https://doi.org/https://www.patentguru.com/US2019127784A1},
file = {docs/Cunningham2019.pdf}
}
@misc{Cunningham2019a,
author = {Cunningham, Brian T.
and Zhuo, Yue
and Harley, Brendan A.
and Choi, Ji Sun
and Marin, Thibault},
title = {{P}hotonic {R}esonator {O}utcoupler {M}icroscopy ({PROM})},
year = {2019},
abstract = {Photonic Resonator Outcoupler Microscopy (PROM) is a novel, label-free approach for dynamic, long-term, quantitative imaging of a sample on a surface of a photonic crystal (PC) biosensor, in which components of the sample outcouple photons from the resonant evanescent field, resulting in highly localized reductions of the reflected light intensity. By mapping changes in the resonant reflected peak intensity from the PC surface, components of a sample (e.g., focal adhesions) can be detected and dynamically tracked. To demonstrate the simplicity and utility of PROM for focal adhesion imaging, PROM images are compared with biosensor images of surface-bound dielectric permittivity and with fluorescence microscopy images of labeled adhesion molecules in dental stem cells. PROM can dynamically quantify the surface-attached cellular mass density and lateral dimensions of focal adhesion clusters.},
doi = {https://www.patentguru.com/US2019120766A1},
opturl = {https://worldwide.espacenet.com/publicationDetails/biblio?CC=US&NR=2019120766A1&KC=A1&FT=D$\#$},
opturl = {https://doi.org/https://www.patentguru.com/US2019120766A1},
file = {docs/Cunningham2019a.pdf}
}
@article{Dannenberg2021,
author = {Dannenberg, Paul H.
and Wang, Jie
and Zhuo, Yue
and Cho, Sangyeon
and Kim, Kwon-Hyeon
and Yun, Seok-Hyun},
title = {{D}roplet microfluidic generation of a million optical microparticle barcodes},
journal = {Optics Express},
year = {2021},
doi = {10.1364/OE.439143},
opturl = {https://doi.org/10.1364/OE.439143}
}
@article{Han2021,
author = {Han, Paul K.
and Marin, Thibault
and Djebra, Yanis
and Landes, Vanessa
and Zhuo, Yue
and El Fakhri, Georges
and Ma, Chao},
title = {{F}ree-breathing 3{D} {C}ardiac {T}1 {M}apping with {T}ransmit {B}1 {C}orrection at 3{T}},
journal = {Magnetic Resonance in Medicine},
year = {2021},
optkeywords = {Cardiac T1 Mapping; Myocardial T1 Mapping; Free-breathing; Inversion Recovery; Transmit B1 Inhomogeneity; Low-Rank; Spoiled Gradient-echo; 3T},
abstract = {Purpose: To develop a cardiac T1 mapping method for free-breathing 3D T1 mapping of the whole heart at 3T with transmit B1 (B1+) correctionMethods: A free-breathing, ECG-gated inversion recovery sequence with spoiled gradient-echo readout was developed and optimized for cardiac T1 mapping at 3T. High-frame rate dynamic images were reconstructed from sparse (k,t)-space data acquired along a stack-of-stars trajectory using a subspace-based method for accelerated imaging. Joint T1 and flip-angle (FA) estimation was performed in T1 mapping to improve its robustness to B1+ inhomogeneity. Subject-specific timing of data acquisition was utilized in the estimation to account for natural heart-rate variations during the imaging experiment.Results: Simulations showed that accuracy and precision of T1 mapping can be improved with joint T1 and FA estimation and optimized ECG-gated SPGR-based IR acquisition scheme. The phantom study showed good agreement between the T1 maps from the proposed method and the reference method. 3D cardiac T1 maps (40 slices) were obtained at a 1.9 mm in-plane and 4.5 mm through-plane spatial resolution from healthy subjects (n=6) with an average imaging time of 14.2 {\textpm} 1.6 min (heartbeat rate: 64.2{\textpm}7.1 bpm), showing myocardial T1 values comparable to those obtained from MOLLI. The proposed method generated B1 + maps with spatially smooth variation showing 21-32{\%} and 11-15{\%} variations across the septal-lateral and inferior-anterior regions of the myocardium in the left ventricle.Conclusion: The proposed method allows free-breathing 3D T1 mapping of the whole-heart with transmit B1 correction in a practical imaging time.},
doi = {10.1002/mrm.29097},
opturl = {https://arxiv.org/abs/2111.07901},
opturl = {https://doi.org/10.1002/mrm.29097},
file = {docs/Han2021.pdf}
}
@article{Han2023a,
author = {Han, Paul Kyu
and Marin, Thibault
and Zhuo, Yue
and Ouyang, Jinsong
and El Fakhri, Georges
and Ma, Chao},
title = {{A}rterial spin labeled perfusion imaging with balanced steady-state free precession readout and radial sampling},
journal = {Magnetic Resonance Imaging},
year = {2023},
volume = {102},
pages = {126--132},
optkeywords = {3t; arterial spin labeling; balanced steady-state free precession; perfusion; phase-cycling; radial},
abstract = {Purpose: To develop an arterial spin labeling (ASL) perfusion imaging method with balanced steady-state free precession (bSSFP) readout and radial sampling for improved SNR and robustness to motion and off-resonance effects.Methods: An ASL perfusion imaging method was developed with pseudo-continuous arterial spin labeling (pCASL) and bSSFP readout. Three-dimensional (3D) k-space data were collected in segmented acquisitions following a stack-of-stars sampling trajectory. Multiple phase-cycling technique was utilized to improve the robustness to off-resonance effects. Parallel imaging with sparsity-constrained image reconstruction was used to accelerate imaging or increase the spatial coverage.Results: ASL with bSSFP readout showed higher spatial and temporal SNRs of the gray matter perfusion signal compared to those from spoiled gradient-recalled acquisition (SPGR). Cartesian and radial sampling schemes showed similar spatial and temporal SNRs, regardless of the imaging readout. In case of severe B0 inhomogeneity, single-RF phase incremented bSSFP acquisitions showed banding artifacts. These artifacts were significantly reduced when multiple phase-cycling technique (N = 4) was employed. The perfusion-weighted images obtained by the Cartesian sampling scheme showed respiratory motion-related artifacts when a high segmentation number was used. The perfusion-weighted images obtained by the radial sampling scheme did not show these artifacts. Whole brain perfusion imaging was feasible in 1.15 min or 4.6 min for cases without and with phase-cycling (N = 4), respectively, using the proposed method with parallel imaging.Conclusions: The developed method allows non-invasive perfusion imaging of the whole-brain with relatively high SNR and robustness to motion and off-resonance effects in a practically feasible imaging time.},
issn = {0730-725x},
doi = {10.1016/j.mri.2023.05.005},
opturl = {https://doi.org/10.1016/j.mri.2023.05.005},
file = {docs/Han2023a.pdf}
}
@inproceedings{Han2023,
author = {Han, Paul Kyu
and Marin, Thibault
and Zhuo, Yue
and Ouyang, Jinsong
and El Fakhri, Georges
and Ma, Chao},
title = {{B}alanced {S}teady-{S}tate {F}ree {P}recession and {R}adial {S}ampling for {A}rterial {S}pin {L}abeled {P}erfusion {I}maging},
booktitle = {{P}roc. {ISMRM}},
year = {2023},
abstract = {Arterial spin labeling (ASL) is a non-invasive MRI technique that allows to quantitatively measure cerebral blood flow. However, the major limitation of ASL is in the intrinsically low signal-to-noise ratio (SNR). Balanced steady-state free precession (bSSFP) sequence has been proposed to mitigate this limitation, however, bSSFP is sensitive to off-resonance effects. Also, bSSFP can be sensitive to motion and flow when combined with cartesian sampling scheme for segmented 3D acquisitions for ASL perfusion imaging. This work proposes to utilize ASL with bSSFP and radial sampling to allow perfusion imaging with relatively high SNR and robustness to motion.},
file = {docs/Han2023.pdf}
}
@article{Hu2014,
author = {Hu, Huan
and Zhuo, Yue
and Oruc, Muhammed E.
and Cunningham, Brian T.
and King, William P.},
title = {{N}anofluidic channels of arbitrary shapes fabricated by tip-based nanofabrication},
journal = {Nanotechnology},
year = {2014},
volume = {25},
number = {45},
pages = {455301},
abstract = {Nanofluidic channels have promising applications in biomolecule manipulation and sensing. While several different methods of fabrication have been demonstrated for nanofluidic channels, a rapid, low-cost fabrication method that can fabricate arbitrary shapes of nanofluidic channels is still in demand. Here, we report a tip-based nanofabrication (TBN) method for fabricating nanofluidic channels using a heated atomic force microscopy (AFM) tip. The heated AFM tip deposits polymer nanowires where needed to serve as etch mask to fabricate silicon molds through one step of etching. PDMS nanofluidic channels are easily fabricated through replicate molding using the silicon molds. Various shapes of nanofluidic channels with either straight or curvilinear features are demonstrated. The width of the nanofluidic channels is 500 nm, and is determined by the deposited polymer nanowire width. The height of the channel is 400 nm determined by the silicon etching time. Ion conductance measurement on one single curvy shaped nanofluidic channel exhibits the typical ion conductance saturation phenomenon as the ion concentration decreases. Moreover, fluorescence imaging of fluid flowing through a fabricated nanofluidic channel demonstrates the channel integrity. This TBN process is seamlessly compatible with existing nanofabrication processes and can be used to achieve new types of nanofluidic devices.},
note = {[PMID: \href{https://pubmed.ncbi.nlm.nih.gov/25327873}{25327873}]},
issn = {0957-4484},
doi = {10.1088/0957-4484/25/45/455301},
opturl = {http://www.ncbi.nlm.nih.gov/pubmed/25327873},
opturl = {https://doi.org/10.1088/0957-4484/25/45/455301},
file = {docs/Hu2014.pdf}
}
@article{Liao2013,
author = {Liao, Xiaoling
and Lu, Shaoying
and Wu, Yiqian
and Xu, Wenfeng
and Zhuo, Yue
and Peng, Qin
and Li, Bo
and Zhang, Ling
and Wang, Yingxiao},
title = {{T}he effect of differentiation induction on {FAK} and {S}rc activity in live {HMSC}s visualized by {FRET}},
journal = {PloS one},
year = {2013},
volume = {8},
number = {8},
pages = {e72233},
optkeywords = {CSK Tyrosine-Protein Kinase; *Cell Differentiation; Cells; Cultured; Enzyme Activation; Feedback; Physiological; Fluorescence Resonance Energy Transfer; Focal Adhesion Kinase 1/*metabolism; Humans; Mesenchymal Stem Cells/*physiology; Proto-Oncogene Proteins/metabolism; Proto-Oncogene Proteins p21(ras); Signal Transduction; Tissue Engineering; ras Proteins/metabolism; src-Family Kinases/*metabolism},
abstract = {FAK and Src signaling play important roles in cell differentiation, survival and migration. However, it remains unclear how FAK and Src activities are regulated at the initial stage of stem cell differentiation. We utilized fluorescence resonance energy transfer (FRET)-based FAK and Src biosensors to visualize these kinase activities at the plasma membrane of human mesenchymal stem cells (HMSCs) under the stimulation of osteogenic, myoblastic, or neural induction reagents. Our results indicate that the membrane FAK and Src activities are distinctively regulated by these differentiation induction reagents. FAK and Src activities were both up-regulated with positive feedback upon osteogenic induction, while myoblastic induction only activated Src, but not FAK. Neural induction, however, transiently activated FAK and subsequently Src, which triggered a negative feedback to partially inhibit FAK activity. These results unravel distinct regulation mechanisms of FAK and Src activities during HMSC fate decision, which should advance our understanding of stem cell differentiation in tissue engineering.},
note = {[PMCID: \href{https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3754985}{PMC3754985}]},
issn = {1932-6203},
doi = {10.1371/journal.pone.0072233},
opturl = {http://www.ncbi.nlm.nih.gov/pubmed/24015220},
opturl = {https://doi.org/10.1371/journal.pone.0072233},
file = {docs/Liao2013.pdf}
}
@article{Liao2011,
author = {Liao, Xiaoling
and Lu, Shaoying
and Zhuo, Yue
and Winter, Christina
and Xu, Wenfeng
and Li, Bo
and Wang, Yingxiao},
title = {{B}one {P}hysiology, {B}iomaterial and the {E}ffect of {M}echanical/{P}hysical {M}icroenvironment on {MSC} {O}steogenesis: {A} {T}ribute to {S}hu {C}hien{\textquoteright}s 80th {B}irthday},
journal = {Cellular and Molecular Bioengineering},
year = {2011},
volume = {4},
number = {4},
pages = {579--590},
optkeywords = {Bone cells; Bone repair; Mechanical Environment; Tissue engineering; scaffolds},
abstract = {Professor Shu Chien is a world-renowned leader and founder of Bioengineering. In particular, he has made seminal contributions to advancing our systematic and insightful understanding of how cells perceive their physical/mechanical environment and coordinate cellular functions. In this review, as part of a tribute to Prof. Shu Chien{\textquoteright}s scientific achievement, we summarize the research progress in understanding the physiology of bone cells interacting with different mechanical/physical environments during bone tissue regeneration/repair. We first introduce the cellular composition of the bone tissue and the mechanism of the physiological bone regeneration/repair process. We then describe the properties and development of biomaterials for bone tissue engineering, followed by the highlighting of research progresses on the cellular response to mechanical environmental cues. Finally, several latest advancements in bone tissue regeneration and remaining challenges in the field are discussed for future research directions.},
note = {[PMCID: \href{https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4288028}{PMC4288028}]},
issn = {1865-5025},
doi = {10.1007/s12195-011-0204-9},
opturl = {http://www.ncbi.nlm.nih.gov/pubmed/25580165},
opturl = {https://doi.org/10.1007/s12195-011-0204-9},
file = {docs/Liao2011.pdf}
}
@article{Liao2012,
author = {Liao, Xiaoling
and Lu, Shaoying
and Zhuo, Yue
and Winter, Christina
and Xu, Wenfeng
and Wang, Yingxiao},
title = {{V}isualization of {S}rc and {FAK} {A}ctivity during the {D}ifferentiation {P}rocess from {HMSC}s to {O}steoblasts ({S}rc and {FAK} {A}ctivity during {D}ifferentiation)},
journal = {PloS one},
year = {2012},
publisher = {Public Library of Science},
address = {San Francisco, USA},
volume = {7},
number = {8},
pages = {e42709},
optkeywords = {Research Article; Biology; Physiology; Biotechnology; Developmental Biology},
abstract = {Non-receptor protein kinases FAK and Src play crucial roles in regulating cellular adhesions, growth, migration and differentiation. However, it remains unclear how the activity of FAK and Src is regulated during the differentiation process from mesenchymal stem cells (MSCs) to bone cells. In this study, we used genetically encoded FAK and Src biosensors based on fluorescence resonance energy transfer (FRET) to monitor the FAK and Src activity in live cells during the differentiation process. The results revealed that the FAK activity increased after the induction of differentiation, which peaked around 20--27 days after induction. Meanwhile, the Src activity decreased continuously for 27 days after induction. Therefore, the results showed significant and differential changes of FAK and Src activity upon induction. This opposite trend between FAK and Src activation suggests novel and un-coupled Src/FAK functions during the osteoblastic differentiation process. These results should provide important information for the biochemical signals during the differentiation process of stem cells toward bone cells, which will advance our understanding of bone repair and tissue engineering.},
issn = {1932-6203},
doi = {10.1371/journal.pone.0042709},
opturl = {https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0042709},
opturl = {https://doi.org/10.1371/journal.pone.0042709},
file = {docs/Liao2012.pdf}
}
@inproceedings{Lu2021,
author = {Lu, Tianjian
and Marin, Thibault
and Zhuo, Yue
and Chen, Yi-Fan
and Ma, Chao},
title = {{N}onuniform {F}ast {F}ourier {T}ransform on {TPU}s},
booktitle = {{IEEE} {I}nternational {S}ymposium on {B}iomedical {I}maging},
year = {2021},
optkeywords = {nonuniform fast Fourier transform; Nufft; magnetic resonance imaging; parallel computing; TensorFlow; tensor processing unit},
abstract = {This work presents a parallel algorithm for implementing the nonuniform Fast Fourier transform (NUFFT) on Google{\textquoteright}s Tensor Processing Units (TPUs). TPU is a hardware accelerator originally designed for deep learning applications. NUFFT is considered as the main computation bottleneck in magnetic resonance (MR) image reconstruction when k-space data are sampled on a nonuniform grid. The computation of NUFFT consists of three operations: an apodization, an FFT, and an interpolation, all being formulated as tensor operations in order to fully utilize TPU{\textquoteright}s strength in matrix multiplications. The implementation is with TensorFlow. Numerical examples show 20x{\~}80x acceleration of NUFFT on a single-card TPU compared to CPU implementations. The strong scaling analysis shows a close-to-linear scaling of NUFFT on up to 64 TPU cores. The proposed implementation of NUFFT on TPUs is promising in accelerating MR image reconstruction and achieving practical runtime for clinical applications.},
file = {docs/Lu2021.pdf}
}
@inproceedings{Lu2020,
author = {Lu, Tianjian
and Marin, Thibault
and Zhuo, Yue
and Chen, Yi-Fan
and Ma, Chao},
title = {{A}ccelerating {MRI} {R}econstruction on {TPU}s},
booktitle = {{IEEE} {H}igh {P}erformance {E}xtreme {C}omputing {C}onference},
year = {2020},
publisher = {Ieee},
pages = {1--9},
optkeywords = {compressed sensing; non-Cartesian MR image reconstruction; parallel computing; parallel imaging; TensorFlow; tensor processing unit},
abstract = {The advanced magnetic resonance (MR) image reconstructions such as the compressed sensing and subspace-based imaging are considered as large-scale, iterative, optimization problems. Given the large number of reconstructions required by the practical clinical usage, the computation time of these advanced reconstruction methods is often unacceptable. In this work, we propose using Google{\textquoteright}s Tensor Processing Units (TPUs) to accelerate the MR image reconstruction. TPU is an application-specific integrated circuit (ASIC) for machine learning applications, which has recently been used to solve large-scale scientific computing problems. As proof-of-concept, we implement the alternating direction method of multipliers (ADMM) in TensorFlow to reconstruct images on TPUs. The reconstruction is based on multi-channel, sparsely sampled, and radial-trajectory k-space data with sparsity constraints. The forward and inverse non-uniform Fourier transform operations are formulated in terms of matrix multiplications as in the discrete Fourier transform. The sparsifying transform and its adjoint operations are formulated as convolutions. The data decomposition is applied to the measured k-space data such that the aforementioned tensor operations are localized within individual TPU cores. The data decomposition and the inter-core communication strategy are designed in accordance with the TPU interconnect network topology in order to minimize the communication time. The accuracy and the high parallel efficiency of the proposed TPU-based image reconstruction method are demonstrated through numerical examples.},
doi = {10.1109/Hpec43674.2020.9286192},
opturl = {https://arxiv.org/pdf/2006.14080.pdf},
opturl = {https://doi.org/10.1109/Hpec43674.2020.9286192},
file = {docs/Lu2020.pdf}
}
@article{Ma2022,
author = {Ma, Chao
and Han, Paul Kyu
and Zhuo, Yue
and Djebra, Yanis
and Marin, Thibault
and El Fakhri, Georges},
title = {{J}oint spectral quantification of {MR} spectroscopic imaging using linear tangent space alignment ({LTSA})-based manifold learning},
journal = {Magnetic Resonance in Medicine},
year = {2022},
optkeywords = {Mrsi; spectral quantification; manifold learning; linear tangent space alignment (LTSA)},
abstract = {Purpose: To develop a manifold learning-based method that leverages the intrinsic low-dimensional structure of MR Spectroscopic Imaging (MRSI) signals for joint spectral quantification.Methods: A linear tangent space alignment (LTSA) model was proposed to represent MRSI signals. In the proposed model, the signals of each metabolite were represented using a subspace model and the local coordinates of the subspaces were aligned to the global coordinates of the underlying low-dimensional manifold via linear transform. With the basis functions of the subspaces pre-determined via quantum mechanics simulations, the global coordinates F and the matrices for the local-to-global coordinate alignment were estimated by fitting the proposed LTSA model to noisy MRSI data with a spatial smoothness constraint on the global coordinates and a sparsity constraint on the matrices.Results: The performance of the proposed e method was validated using numerical simulation data and in vivo proton-MRSI experimental data acquired on healthy volunteers at 3T. The results of the proposed method were compared with the QUEST method and the subspace-based method. In all the compared cases, the proposed method achieved superior performance over the QUEST and the subspace-based methods both qualitatively in terms of noise and artifacts in the estimated metabolite concentration maps, and quantitatively in terms of spectral quantification accuracy measured by normalized root mean square errors.Conclusion: Joint spectral quantification using linear tangent space alignment-based manifold learning improves the accuracy of MRSI spectral quantification.},
doi = {10.1002/MRM.29526},
opturl = {https://doi.org/10.1002/MRM.29526},
file = {docs/Ma2022.pdf}
}
@inproceedings{Marin2021,
author = {Marin, Thibault
and Djebra, Yanis
and Han, Paul K.
and Landes, Vanessa
and Zhuo, Yue
and Su, Kuan-Hao
and El Fakhri, Georges
and Ma, Chao},
title = {{C}omparison of deformable registration techniques for real-time {MR}-based motion correction in {PET}/{MR}},
booktitle = {{P}roc. {ISMRM}},
year = {2021},
abstract = {Motion during acquisition of PET/MR data can severely degrade image quality of PET/MR studies. We have previously reported an MR-based motion correction technique capable of correcting for irregular motion patterns such as bulk motion and irregular respiratory motion. The method is based on a subspace MR model enabling reconstruction of real-time volumetric MR images (9 frames per second). In this work, we present improvements to the motion estimation method used to obtain motion fields from real-time MR images. We compare the performance of three packages for irregular motion patterns.},
file = {docs/Marin2021.pdf}
}
@inproceedings{Marin2021a,
author = {Marin, Thibault
and Han, Paul K.
and Zhuo, Yue
and Djebra, Yanis
and Liu, Fang
and El Fakhri, Georges
and Ma, Chao},
title = {{T}hree-dimensional cardiac {T}1 mapping using subspace and sparsity constrained direct estimation},
booktitle = {{P}roc. {ISMRM}},
year = {2021},
abstract = {Cardiac T1 mapping is a powerful MR imaging technique for quantitative assessment of microstructural changes in myocardial tissues. Existing methods are limited in terms of spatial coverage and through-plane resolution due to limitations in acquisition speed and the presence of cardiac and respiratory motion. This work presents a direct reconstruction framework, which allows estimation of 3D T1 maps from sparsely sampled k-space data using physical modeling through the Bloch equation, low-rank constraints on the dynamic images and sparsity constraints on the estimated T1 maps.},
file = {docs/Marin2021a.pdf}
}
@article{Marin2021b,
author = {Marin, Thibault
and Zhuo, Yue
and Lahoud, Rita Maria
and Tian, Fei
and Ma, Xiaoyue
and Xing, Fangxu
and Moteabbed, Maryam
and Liu, Xiaofeng
and Grogg, Kira
and Shusharina, Nadya
and Woo, Jonghye
and Ma, Chao
and Chen, Yen-Lin
and El Fakhri, Georges},
title = {{D}eep learning-based {GTV} contouring modeling inter- and intra- observer variability in sarcomas},
journal = {Radiotherapy and Oncology},
year = {2021},
optkeywords = {sarcoma; radiotherapy planning; computer-assisted; deep learning},
abstract = {Background and purposeThe delineation of the gross tumor volume (GTV) is a critical step for radiation therapy treatment planning. The delineation procedure is typically performed manually which exposes two major issues: cost and reproducibility. Delineation is a time-consuming process that is subject to inter- and intra-observer variability. While methods have been proposed to predict GTV contours, typical approaches ignore variability and therefore fail to utilize the valuable confidence information offered by multiple contours.Materials and methodsIn this work we propose an automatic GTV contouring method for softtissue sarcomas from X-ray computed tomography (CT) images, using deep learning by integrating inter- and intra-observer variability in the learned model. Sixty-eight patients with soft tissue and bone sarcomas were considered in this evaluation, all underwent pre-operative CT imaging used to perform GTV delineation. Four radiation oncologists and radiologists performed three contouring trials each for all patients. We quantify variability by defining confidence levels based on the frequency of inclusion of a given voxel into the GTV and use a deep convolutional neural network to learn GTV confidence maps.ResultsResults were compared to confidence maps from the four readers as well as groundtruth consensus contours established jointly by all readers. The resulting continuous Dice score between predicted and true confidence maps was 87{\%} and the Hausdorff distance was 14 mm. Conclusion: Results demonstrate the ability of the proposed method to predict accurate contours while utilizing variability and as such it can be used to improve clinical workflow.},
doi = {10.1016/j.radonc.2021.09.034},
opturl = {https://arxiv.org/abs/2110.04721},
opturl = {https://doi.org/10.1016/j.radonc.2021.09.034},
file = {docs/Marin2021b.pdf}
}
@inproceedings{Marin2023,
author = {Marin, Thibault
and Zhuo, Yue
and Orehar, Matic
and Razdev{\v{s}}ek, Ga{\v{s}}per
and Dolenec, Rok
and Mounime, Ismael
and Alamo, Jorge
and Barbera, Julio
and Benlloch Baviera, Jose Maria
and Chemli, Yanis
and Fernandez-Tenllado, Jose Maria
and Gascon Fora, David
and Gola, Alberto Giacomo
and Gomez, Sergio
and Grogg, Kira
and Guberman, Daniel Alberto
and Korpar, Samo
and Kri{\v{z}}an, Peter
and Majewski, Stan
and Manera, Rafel
and Mariscal-Castilla, Antonio
and Mauricio, Joan
and Merzi, Stefano
and Morera, Constantino
and Normandin, Marc D.
and Pav{\'o}n, Gabriel
and Penna, Michele
and Seljak, Andrej
and Studen, Andrej
and Pestotnik, Rok
and El Fakhri, Georges},
title = {{S}imulation results for limited-angle ultra-high time-of-flight resolution {PET} system},
booktitle = {{IEEE} {N}uclear {S}cience {S}ymposium},
year = {2023},
optkeywords = {total-body PET; time-of-flight; depth-of-interaction},
abstract = {Positron emission tomography (PET) has become standard practice in many clinical applications including oncology, cardiology and neurology. Recent developments in PET scanners have pushed the limits of these applications, thanks to long axial field of view scanners which can improve system sensitivity and the use of time-of-flight (TOF) information which can improve spatial resolution. However, the cost and space requirements for total-body PET systems has created a need for flexible, low-cost yet high-sensitivity systems with large axial field of view. Additionally, currently achievable TOF resolutions (around 200 ps for current clinical scanners) limit the gains in image resolution. In this work, we present the first reconstructions for a flexible two-panel ultra-high TOF resolution PET system expected to achieve 75 ps full-width at half maximum (FWHM). The scanner relies on pixelated L(Y)SO scintillators with novel detectors with dual readout measuring depth-of-interaction (DOI) information. The performance of the new system is demonstrated on Monte-Carlo simulations of an anthropomorphological numerical phantom reconstructed using a newly developed TOF+DOI-enabled reconstruction engine. The presented reconstructions exhibit high image quality, demonstrating the promise of the proposed PET system.},
doi = {10.1109/NSSMICRTSD49126.2023.10337821},
opturl = {https://doi.org/10.1109/NSSMICRTSD49126.2023.10337821},
file = {docs/Marin2023.pdf}
}
@inproceedings{Najem2023,
author = {Najem, Elie
and Marin, Thibault
and Lahoud, Rita Maria
and Tian, Fei
and Xing, Fangxu
and Moteabbed, Maryam
and Zhuo, Yue
and Lim, Ruth
and Liu, Xiaofeng
and Woo, Jonghye
and Ma, Chao
and Chen, Yen-Lin
and El Fakhri, Georges},
title = {{FDG} {PET} decreases intra- and inter-observer variabilities in {GTV} delineation of soft tissue sarcomas in radiotherapy planning when used in conjunction with {CT} and {MR}},
booktitle = {{S}ociety of {N}uclear {M}edicine {\&} {M}olecular {I}maging {C}onference},
year = {2023},
volume = {64},
number = {supplement 1},
pages = {P119--P119},
abstract = {P119 Introduction: Soft tissue sarcomas are rare heterogenous tumors of mesenchymal origin. While surgical resection remains the mainstay treatment, radiation therapy often used pre or post-surgery has shown to decrease local recurrence rate. Accurate delineation of gross tumor volume is a critical step in radiotherapy planning. However, it is observer dependent, hence susceptible to both intra and inter-observer variabilities. Typically, CT and MR scans are performed including T1, T2 and contrast enhanced T1 weighted images. FDG-PET/CT is performed for staging purposes and rarely used for gross tumor volume (GTV) delineation. In this abstract we assess the effect of including FDG-PET/CT in the radiotheraphy planning of soft tisse sarcomas. We hypothesize that adding FDG PET/CT would decrease both intra and inter-observer variabilities. Methods: A total of 61 patients with soft tissue sarcomas were included. All patients had CT, MR and FDG-PET/CT images acquired within a 4-week window period. Three trained physicians (observers) performed GTV delineation of soft tissue sarcomas using first CT and MR images only. Observers then performed GTV delineation using CT, MR and FDG-PET/CT images. Each observer performed three delineations per patient in a randomized order with at least one-month interval between trials.DICE score and Hausdorff distance (HD) were used to assess both intra and inter-observer variabilities. For intraobserver variability, we plotted each GTV delineation drawn by each observer against its corresponding STAPLE reference for modality group. For each observer, we calculated one STAPLE per patient over the three trials drawn by the same observer. For interobserver variability, each trial was studied separately. For each trial, we calculated the DICE score between each contour drawn by the three reader and its corresponding STAPLE. For each patient, we calculated one STAPLE per trial over the contours drawn by the three observers. The DICE scores and Hausdorff distance obtained on CT and MR images were compared to the ones obtained from CT, MR and FDG-PET/CT images. Statistical analysis was performed using a Wilcoxon signed-ranked test. A one-sided p-value of 0.025 was used as a threshold for statistical significance. Results: For intraobserver variability, observer A had a DICE score of 90.3 when using CT, MR and FDG-PET/CT images vs. 89.3 when using CT and MR images only (p-value = 0.0018). Observers B and C had a DICE score of 92 and 95.3 when using CT, MR and FDG-PET/CT images vs. 90.2 and 94.8 respectively when using CT and MR images only (p-value < 0.0001 and p-value = 0.0022 respectively). Similarly, Hausdorff distances on CT, MR and PET images were significantly smaller for all observers. HD on CT, MR and PET measured 8.6mm, 5.7mm and 4mm vs. 9.1mm, 7.9mm and 5mm on CT and MR for observers A, B and C respectively (p-value = 0.015, p-value <0.001, p-value = 0.0003 respectively).For interobserver variability, there is a statistically significant increase in the DICE score in all three trials when using CT, MR and FDG-PET/CT vs. CT and MR only. For trial one, the DICE score was 91.1 on CT, MR and FDG-PET/CT vs. 89 on CT and MR only (p-value = 0.0004). The DICE score was 90.3 on CT, MR and FDG-PET/CT vs. 89.3 on CT and MR only (p-value = 0.0052) and 91.1 on CT, MR and FDG-PET/CT vs. 88.8 on CT and MR only (p-value = 0.0002) for trial 2 and 3 respectively. Equally, all measured HD on CT, MR and PET images were significantly smaller across all trials. HD on CT, MR and PET was 7.7mm, 8.6mm and 7.1mm vs. 10.1mm, 9.2mm and 9.3mm on CT and MR for trials 1, 2 and 3 respectively (p-value < 0.001, p-value = 0.0017, p-value < 0.001 respectively).Conclusions: The incorporation of FDG-PET/CT to CT and MR for the GTV delineation of soft tissue sarcomas significantly decreased both intra and interobserver variabilities. Research support:TR32EB013180;R01CA165221;P41EB022544},
opturl = {http://jnm.snmjournals.org/content/64/supplement_1/P119.abstract},
file = {docs/Najem2023.pdf}
}
@article{Najem2024,
author = {Najem, Elie
and Marin, Thibault
and Zhuo, Yue
and Lahoud, Rita Maria
and Tian, Fei
and Beddok, Arnaud
and Rozenblum, Laura
and Xing, Fangxu
and Moteabbed, Maryam
and Lim, Ruth
and Liu, Xiaofeng
and Woo, Jonghye
and Lostetter, Stephen John
and Lamane, Abdallah
and Chen, Yen-Lin Evelyn
and Ma, Chao
and El Fakhri, Georges},
title = {{T}he role of (18){F}-{FDG} {PET} in minimizing variability in gross tumor volume delineation of soft tissue sarcomas},
journal = {Radiotherapy and Oncology},
year = {2024},
volume = {194},
pages = {110186},
optkeywords = {GTV delineation; Pet; sarcoma; variability},
abstract = {BACKGROUND: Accurate gross tumor volume (GTV) delineation is a critical step in radiation therapy treatment planning. However, it is reader dependent and thus susceptible to intra- and inter-reader variability. GTV delineation of soft tissue sarcoma (STS) often relies on CT and MR images. PURPOSE: This study investigates the potential role of (18)F-FDG PET in reducing intra- and inter-reader variability thereby improving reproducibility of GTV delineation in STS, without incurring additional costs or radiation exposure. MATERIALS AND METHODS: Three readers performed independent GTV delineation of 61 patients with STS using first CT and MR followed by CT, MR, and (18)F-FDG PET images. Each reader performed a total of six delineation trials, three trials per imaging modality group. Dice Similarity Coefficient (DSC) score and Hausdorff distance (HD) were used to assess both intra- and inter-reader variability using generated simultaneous truth and performance level estimation (STAPLE) GTVs as ground truth. Statistical analysis was performed using a Wilcoxon signed-ranked test. RESULTS: There was a statistically significant decrease in both intra- and inter-reader variability in GTV delineation using CT, MR (18)F-FDG PET images vs. CT and MR images. This was translated by an increase in the DSC score and a decrease in the HD for GTVs drawn from CT, MR and (18)F-FDG PET images vs. GTVs drawn from CT and MR for all readers and across all three trials. CONCLUSION: Incorporation of (18)F-FDG PET into CT and MR images decreased intra- and inter-reader variability and subsequently increased reproducibility of GTV delineation in STS.},
issn = {0167-8140},
doi = {10.1016/j.radonc.2024.110186},
opturl = {https://doi.org/10.1016/j.radonc.2024.110186},
file = {docs/Najem2024.pdf}
}
@article{Seong2011,
author = {Seong, Jihye
and Ouyang, Mingxing
and Kim, Taejin
and Sun, Jie
and Wen, Po-Chao
and Lu, Shaoying
and Zhuo, Yue
and Llewellyn, Nicholas M.
and Schlaepfer, David D.
and Guan, Jun-Lin
and Chien, Shu
and Wang, Yingxiao},
title = {{D}etection of focal adhesion kinase activation at membrane microdomains by fluorescence resonance energy transfer},
journal = {Nature Communications},
year = {2011},
volume = {2},
pages = {406},
optkeywords = {Animals; Cell Adhesion; Cell Membrane/*chemistry/*enzymology/genetics; Enzyme Activation; Fluorescence Resonance Energy Transfer/*methods; Focal Adhesion Protein-Tyrosine Kinases/*chemistry/genetics/*metabolism; Mice; Knockout; Platelet-Derived Growth Factor/metabolism; Protein Structure; Tertiary},
abstract = {Proper subcellular localization of focal adhesion kinase (FAK) is crucial for many cellular processes. It remains, however, unclear how FAK activity is regulated at subcellular compartments. To visualize the FAK activity at different membrane microdomains, we develop a fluorescence resonance energy transfer (FRET)-based FAK biosensor, and target it into or outside of detergent-resistant membrane (DRM) regions at the plasma membrane. Here we show that, on cell adhesion to extracellular matrix proteins or stimulation by platelet-derived growth factor (PDGF), the FRET responses of DRM-targeting FAK biosensor are stronger than that at non-DRM regions, suggesting that FAK activation can occur at DRM microdomains. Further experiments reveal that the PDGF-induced FAK activation is mediated and maintained by Src activity, whereas FAK activation on cell adhesion is independent of, and in fact essential for the Src activation. Therefore, FAK is activated at membrane microdomains with distinct activation mechanisms in response to different physiological stimuli.},
note = {[PMCID: \href{https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3373894}{PMC3373894}]},
issn = {2041-1723},
doi = {10.1038/ncomms1414},
opturl = {http://www.ncbi.nlm.nih.gov/pubmed/21792185},
opturl = {https://doi.org/10.1038/ncomms1414},
file = {docs/Seong2011.pdf}
}
@inproceedings{Sun2012,
author = {Sun, Jie
and Lu, Shaoying
and Ouyang, Mingxing
and Lin, Li-Jung
and Zhuo, Yue
and Liu, Bo
and Chan, Richard
and Chien, Shu
and Neel, Benjamin G.
and Wang, Yingxiao},
title = {{C}ircuit algorithm of tunable intramolecular interactions embedded within {S}hp2 revealed by {FRET}},
booktitle = {{ACS} {N}ational {M}eeting {B}ook of {A}bstracts},
year = {2012},
volume = {243},
opturl = {https://www.researchgate.net/publication/296024466_Circuit_algorithm_of_tunable_intramolecular_interactions_embedded_within_Shp2_revealed_by_FRET}
}
@article{Sun2013,
author = {Sun, Jie
and Lu, Shaoying
and Ouyang, Mingxing
and Lin, Li-Jung
and Zhuo, Yue
and Liu, Bo
and Chien, Shu
and Neel, Benjamin G.
and Wang, Yingxiao},
title = {{A}ntagonism between binding site affinity and conformational dynamics tunes alternative cis-interactions within {S}hp2},
journal = {Nature Communications},
year = {2013},
volume = {4},
pages = {2037},
optkeywords = {Amino Acid Sequence; Animals; Binding Sites; Embryo; Mammalian/cytology; Extracellular Signal-Regulated MAP Kinases/metabolism; Fibroblasts/metabolism; Fluorescence Resonance Energy Transfer; GRB2 Adaptor Protein/chemistry/metabolism; Genes; Reporter; HEK293 Cells; Humans; Kinetics; Mice; Molecular Sequence Data; Mutant Proteins/metabolism; Mutation/genetics; Peptides/chemistry/metabolism; Phosphorylation; Phosphotyrosine/metabolism; Protein Binding; Protein Conformation; Protein Tyrosine Phosphatase; Non-Receptor Type 11/antagonists {\&} inhibitors/*chemistry/*metabolism},
abstract = {Protein functions are largely affected by their conformations. This is exemplified in proteins containing modular domains. However, the evolutionary dynamics that define and adapt the conformation of such modular proteins remain elusive. Here we show that cis-interactions between the C-terminal phosphotyrosines and SH2 domain within the protein tyrosine phosphatase Shp2 can be tuned by an adaptor protein, Grb2. The competitiveness of two phosphotyrosines, namely pY542 and pY580, for cis-interaction with the same SH2 domain is governed by an antagonistic combination of contextual amino acid sequence and position of the phosphotyrosines. Specifically, pY580 with the combination of a favourable position and an adverse sequence has an overall advantage over pY542. Swapping the sequences of pY542 and pY580 results in one dominant form of cis-interaction and subsequently inhibits the trans-regulation by Grb2. Thus, the antagonistic combination of sequence and position may serve as a basic design principle for proteins with tunable conformations.},
note = {[PMCID: \href{https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3777412}{PMC3777412}]},
issn = {2041-1723},
doi = {10.1038/ncomms3037},
opturl = {http://www.ncbi.nlm.nih.gov/pubmed/23792876},
opturl = {https://doi.org/10.1038/ncomms3037},
file = {docs/Sun2013.pdf}
}
@inproceedings{Sutton2009,
author = {Sutton, Bradley P.
and Zhuo, Yue},
title = {{S}usceptibility, echo time shifts, and {T}2* considerations for functional magnetic resonance imaging},
booktitle = {2009 {IEEE} {I}nternational {S}ymposium on {B}iomedical {I}maging: {F}rom {N}ano to {M}acro},
year = {2009},
pages = {710--713},
optkeywords = {biomedical MRI; blood; brain; data acquisition; magnetic susceptibility; echo time shifts; T2* considerations; functional magnetic resonance imaging; magnetic susceptibility difference; air-tissue interface; ventral brain; field inhomogeneity; image artifacts; gradients echo acquisition; effective k-space trajectory; R2* decay map; blood oxygenation level dependent fMRI; Magnetic resonance imaging; Magnetic fields; Pixel; Magnetic properties; Tellurium; Spirals; Magnetic field measurement; Biomedical engineering; Echo time shift; BOLD fMRI},
abstract = {Magnetic susceptibility differences exist near the interface of air/tissue in the ventral brain in fMRI (functional magnetic resonance imaging). These susceptibility differences will not only cause field inhomogeneity and its gradients which will result in image artifacts, but also cause shifts in the echo time for gradients echo acquisitions. The echo time shifts are caused by shifts in the effective k-space trajectory due to the gradients of the field inhomogeneity. Previous work has shown and validated methods for estimating the echo time shift based on the effective k-space trajectory. In this work, we demonstrate that accurate estimation of the R2* decay map (R2*=1/T2*) not only need to account for the field map and its gradients, but also needs to include the echo time shift. These changes in T2* sensitivity are directly related to changes in sensitivity in BOLD (blood oxygenation level dependent) fMRI studies.},
doi = {10.1109/ISBI.2009.5193146},
opturl = {https://doi.org/10.1109/ISBI.2009.5193146},
file = {docs/Sutton2009.pdf}
}
@article{Tang2021,
author = {Tang, Shui-Jing
and Dannenberg, Paul H.
and Liapis, Andreas C.
and Martino, Nicola
and Zhuo, Yue
and Xiao, Yun-Feng
and Yun, Seok-Hyun},
title = {{L}aser particles with omnidirectional emission for cell tracking},
journal = {Light, Science {\&} Applications},
year = {2021},
volume = {10},
number = {1},
pages = {23},
abstract = {The ability to track individual cells in space over time is crucial to analyzing heterogeneous cell populations. Recently, microlaser particles have emerged as unique optical probes for massively multiplexed single-cell tagging. However, the microlaser far-field emission is inherently direction-dependent, which causes strong intensity fluctuations when the orientation of the particle varies randomly inside cells. Here, we demonstrate a general solution based on the incorporation of nanoscale light scatterers into microlasers. Two schemes are developed by introducing either boundary defects or a scattering layer into microdisk lasers. The resulting laser output is omnidirectional, with the minimum-to-maximum ratio of the angle-dependent intensity improving from 0.007 (-24 dB) to > 0.23 (-6 dB). After transfer into live cells in vitro, the omnidirectional laser particles within moving cells could be tracked continuously with high signal-to-noise ratios for 2 h, while conventional microlasers exhibited frequent signal loss causing tracking failure.},
note = {[PMCID: \href{https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7835369}{PMC7835369}]},
issn = {2047-7538},
doi = {10.1038/s41377-021-00466-0},
opturl = {http://www.ncbi.nlm.nih.gov/pubmed/33495436},
opturl = {https://doi.org/10.1038/s41377-021-00466-0},
file = {docs/Tang2021.pdf}
}
@inproceedings{Wu2011,
author = {Wu, Xiao-Long
and Gai, Jiading
and Lam, Fan
and Fu, Maojing
and Haldar, Justin P.
and Zhuo, Yue
and Liang, Zhi-Pei
and Hwu, Wen-Mei
and Sutton, Bradley P.},
title = {{I}mpatient {MRI}: {I}llinois {M}assively {P}arallel {A}cceleration {T}oolkit for image reconstruction with enhanced throughput in {MRI}},
booktitle = {2011 {IEEE} {I}nternational {S}ymposium on {B}iomedical {I}maging: {F}rom {N}ano to {M}acro},
year = {2011},
publisher = {IEEE},
pages = {69--72},
optkeywords = {magnetic resonance imaging; graphics processing cards; field inhomogeneity; image regularization},
abstract = {Much progress has been made in the design of efficient acquisition trajectories for high spatial and temporal resolution in magnetic resonance imaging (MRI). Additionally, significant developments in image reconstruction have enabled the reconstruction of reasonable images from massively undersampled or noisy data that is corrupted by a variety of physical effects, including magnetic field inhomogeneity. Translation of these techniques into clinical imaging has been impeded by the need for expertise and computational facilities to realize the potential of these methods. We present the Illinois Massively Parallel Acceleration Toolkit for Image reconstruction with ENhanced Throughput in MRI (IMPATIENT MRI), a reconstruction utility that enables advanced techniques within clinically relevant computation times by using the computational power available in low-cost graphics processing cards.},
isbn = {9781424441273},
issn = {1945-7928},
doi = {10.1109/ISBI.2011.5872356},
opturl = {https://doi.org/10.1109/ISBI.2011.5872356},
file = {docs/Wu2011.pdf}
}
@inproceedings{Wu2011a,
author = {Wu, Xiao-Long
and Gai, Jiading
and Lam, Fan
and Fu, Maojing
and Haldar, Justin P.
and Zhuo, Yue
and Liang, Zhi-pei
and Hwu, Wen-Mei
and Sutton, Bradley P.},
title = {{I}mpatient {MRI}: {I}llinois {M}assively {P}arallel {A}cceleration {T}oolkit for {I}mage reconstruction with {EN}hanced {T}hroughput in {MRI}},
booktitle = {2011 {T}he {I}nternational {S}ociety for {M}agnetic {R}esonance in {M}edicine ({ISMRM})},
year = {2011},
abstract = {Significant progress has been made in optimizing imaging trajectories and reconstruction approaches for a variety of MRI application areas. Often these acquisitions result in high resolution 2D or 3D data acquired with non-Cartesian trajectories that have been significantly under-sampled. Image reconstruction is then performed either in unacceptably long times or with highly optimized code that includes several approximations and interpolation steps in order to keep the reconstruction time low. In this work, we introduce the Illinois Massively Parallel Acceleration Toolkit for Image reconstruction with ENhanced Throughput in MRI (IMPATIENT MRI) package to speed image reconstruction to acceptable times while still taking advantage of a variety of advanced image acquisitions and reconstruction techniques. We provide an open source, highly optimized implementation on graphics processing units (GPUs) which allow for massively parallel computation to greatly reduce image reconstruction times.},
opturl = {https://cds.ismrm.org/protected/11MProceedings/files/4396.pdf},
file = {docs/Wu2011a.pdf}
}
@inproceedings{Wu2011b,
author = {Wu, Xiao-Long
and Zhuo, Yue
and Gai, Jiading
and Lam, Fan
and Fu, Maojing
and Haldar, Justin P.
and Hwu, Wen-Mei
and Liang, Zhi-Pei
and Sutton, Bradley P.},
editor = {Owens, John D.
and Lin, I-Jong
and Zhang, Yu-Jin
and Beretta, Giordano B.},
title = {{A}dvanced {MRI} reconstruction toolbox with accelerating on {GPU}},
booktitle = {{P}arallel {P}rocessing for {I}maging {A}pplications},
year = {2011},
publisher = {Spie},
volume = {7872},
pages = {241--250},
optkeywords = {MRI; GPU; SENSE; total variation regularization; field inhomogeneity; susceptibility},
abstract = {In this paper, we present a fast iterative magnetic resonance imaging (MRI) reconstruction algorithm taking advantage of the prevailing GPGPU programming paradigm. In clinical environment, MRI reconstruction is usually performed via fast Fourier transform (FFT). However, imaging artifacts (i.e. signal loss) resulting from susceptibility-induced magnetic field inhomogeneities degrade the quality of reconstructed images. These artifacts must be addressed using accurate modeling of the physics of the system coupled with iterative reconstruction. We have developed a reconstruction algorithm with improved image quality at the expense of computation time and hence an implementation on GPUs achieving significant speedup. In this work, we extend our previous work on GPU implementation by adding several new features. First, we enable Sensitivity Encoding for Fast MRI (SENSE) reconstruction (from data acquired using a multi-receiver coil array) which can reduce the acquisition time. Besides, we have implemented a GPU-based total variation regularization in our SENSE reconstruction framework. In this paper, we describe the different optimizations employed from levels of algorithm, program code structures, and specific architecture performance tuning, featuring both our MRI reconstruction algorithm and GPU hardware specifics. Results show that the current GPU implementation produces accurate image estimates while significantly accelerating the reconstruction.},
issn = {0277-786X},
doi = {10.1117/12.872204},
opturl = {https://doi.org/10.1117/12.872204},
file = {docs/Wu2011b.pdf}
}
@inbook{Zhuo2016a,
author = {Zhuo, Yue
and Cunningham, Brian T.},
title = {{L}abel-{F}ree {B}iosensor {I}maging on {P}hotonic {C}rystal {S}urfaces ({C}hpater 2)},
booktitle = {Label-Free Sensing},
year = {2016},
pages = {31--55},
isbn = {978-3-03842-211-2},
opturl = {https://www.mdpi.com/journal/biosensors/special_issues/Label_free_biosensing},
file = {docs/Zhuo2016a.pdf}
}
@inproceedings{Zhuo2024,
author = {Zhuo, Yue
and Choi, Ji Sun
and Marin, Thibault
and Yu, Hojeong
and Harley, Brendan A.
and Cunningham, Brian},
title = {{L}abel-{F}ree {I}maging {W}ith {P}hotonic {C}rystal {S}urface for {H}ematopoietic {S}tem {C}ell {D}ifferentiation},
booktitle = {{O}ptica {B}iophotonics {C}ongress},
year = {2024},
abstract = {With the Photonic Resonator Outcoupler Microscopy (PROM), it is possible to detect and monitor weak-adhesive HSC adhesion without labeling. These findings indicate that PROM can be used to quantitatively and dynamically study HSC adhesion.},
file = {docs/Zhuo2024.pdf}
}
@inproceedings{Zhuo2018b,
author = {Zhuo, Yue
and Choi, Ji Sun
and Marin, Thibault
and Yu, Hojeong
and Harley, Brendan A.
and Cunningham, Brian T.},
title = {{S}tem {C}ell {A}dhesion {I}maging with {P}hotonic {R}esonator {O}utcoupler {M}icroscopy ({PROM})},
booktitle = {{B}iomedical {E}ngineering {S}ociety {A}nnual {M}eeting},
year = {2018},
abstract = {Focal adhesions (FAs) are critical cellular membrane components that regulate cell adhesion and migration [1]. We developed a label-free imaging biosensor approach, named Photonic Resonator Outcoupler Microscopy (PROM), for dynamic, long-term, quantitative imaging of cell-surface interactions [2-7]. Our measurements show that membrane-associated adhesion protein aggregates scatter photons from the resonant electromagnetic standing wave on a photonic crystal surface, resulting in a highly localized reduction of the reflected light intensity.},
file = {docs/Zhuo2018b.pdf}
}
@inproceedings{Zhuo2018a,
author = {Zhuo, Yue
and Choi, Ji Sun
and Marin, Thibault
and Yu, Hojeong
and Harley, Brendan A.
and Cunningham, Brian T.},
title = {{P}hotonic {R}esonator {O}utcoupler {M}icroscopy ({PROM}) for {Q}uantitative {M}onitoring of {S}tem {C}ell {F}ocal {A}dhesion {A}rea},
booktitle = {{F}rontiers in {O}ptics},
year = {2018},
publisher = {Optical Society of America},
pages = {JTu3A.119},
abstract = {We developed a novel label-free imaging approach, named Photonic Resonator Outcoupler Microscopy (PROM) utilizing the reduction of the peak-resonance intensity reflected from a photonic crystal surface. PROM can monitor the variation of focal adhesion areas in live cells dynamically and quantitatively for extended time.},
isbn = {978-1-943580-46-0},
doi = {10.1364/FIO.2018.JTu3A.119},
opturl = {https://www.osapublishing.org/abstract.cfm?uri=FiO-2018-JTu3A.119},
opturl = {https://doi.org/10.1364/FIO.2018.JTu3A.119},
file = {docs/Zhuo2018a.pdf}
}
@article{Zhuo2018,
author = {Zhuo, Yue
and Choi, Ji Sun
and Marin, Thibault
and Yu, Hojeong
and Harley, Brendan A.
and Cunningham, Brian T.},
title = {{Q}uantitative analysis of focal adhesion dynamics using photonic resonator outcoupler microscopy ({PROM})},
journal = {Light: Science {\&} Applications},
year = {2018},
volume = {7},
number = {1},
pages = {9},
abstract = {Focal adhesions are critical cell membrane components that regulate adhesion and migration and have cluster dimensions that correlate closely with adhesion engagement and migration speed. We utilized a label-free approach for dynamic, long-term, quantitative imaging of cell--surface interactions called photonic resonator outcoupler microscopy (PROM) in which membrane-associated protein aggregates outcoupled photons from the resonant evanescent field of a photonic crystal biosensor, resulting in a highly localized reduction of the reflected light intensity. By mapping the changes in the resonant reflected peak intensity from the biosensor surface, we demonstrate the ability of PROM to detect focal adhesion dimensions. Similar spatial distributions can be observed between PROM images and fluorescence-labeled images of focal adhesion areas in dental epithelial stem cells. In particular, we demonstrate that cell--surface contacts and focal adhesion formation can be imaged by two orthogonal label-free modalities in PROM simultaneously, providing a general-purpose tool for kinetic, high axial-resolution monitoring of cell interactions with basement membranes.},
issn = {2047-7538},
doi = {10.1038/s41377-018-0001-5},
opturl = {https://doi.org/10.1038/s41377-018-0001-5},
file = {docs/Zhuo2018.pdf}
}
@inproceedings{Zhuo2017a,
author = {Zhuo, Yue
and Choi, Ji Sun
and Marin, Thibault
and Yu, Hojeong
and Harley, Brendan A.
and Cunningham, Brian T.},
title = {{Q}uantitative {L}abel-free {I}maging of {L}ive-cell {A}dhesion {U}sing {P}hotonic {C}rystal {E}nhanced {M}icroscopy ({PCEM})},
booktitle = {{C}onference on {L}asers and {E}lectro-{O}ptics ({CLEO})},
year = {2017},
abstract = {To quantify live-cell adhesion, a photonic crystal biosensor surface with an extracellular matrix coating is monitored within a PCEM instrument to dynamically image changes in attached cell mass-density during live-cell attachment, spreading, and drug response.},
isbn = {978-1-5386-2019-9},
doi = {10.1364/CLEO_SI.2017.SM1C.2},
opturl = {https://doi.org/10.1364/CLEO_SI.2017.SM1C.2},
file = {docs/Zhuo2017a.pdf}
}
@inproceedings{Zhuo2017,
author = {Zhuo, Yue
and Choi, Ji Sun
and Marin, Thibault
and Yu, Hojeong
and Harley, Brendan A.
and Cunningham, Brian T.},
title = {{C}ell {A}dhesion {P}henotype {L}ibrary with {P}hotonic {C}rystal {E}nhanced {M}icroscopy},
booktitle = {{O}ptics in the {L}ife {S}ciences {C}ongress},
year = {2017},
pages = {BoS2A7},
abstract = {We apply PCEM to investigate adhesion of different types of cells as a cell adhesion phenotype library. PCEM imaging provides a new tool to gain a deeper understanding of the fundamental mechanisms involved with cell-adhesion.},
doi = {10.1364/BODA.2017.BoS2A.7},
opturl = {https://doi.org/10.1364/BODA.2017.BoS2A.7},
file = {docs/Zhuo2017.pdf}
}
@inproceedings{Zhuo2017b,
author = {Zhuo, Yue
and Choi, Ji Sun
and Marin, Thibault
and Yu, Hojeong
and Harley, Brendan A.
and Cunningham, Brian T.},
title = {{L}abel-free {I}maging of {S}tem {C}ell {A}dhesion and {D}ynamic {T}racking of {B}oundary {E}volution {U}sing {P}hotonic {C}rystal {E}nhanced {M}icroscopy ({PCEM})},
booktitle = {{P}roceedings of {M}icroscopy {\&} {M}icroanalysis},
year = {2017},
volume = {23},
pages = {1142--1143},
abstract = {Cell adhesion provides structural support and contributes to functional processes crucial for cellular proliferation and survival. We apply a new form of label-free biosensor imaging called Photonic Crystal Enhanced Microscopy (PCEM) to investigate adhesion/migration of stem cells [1-4]. By applying image processing algorithms to analyze the PCEM images, we offer insight into how the cellular membrane is dynamically organized during cell adhesion.},
doi = {10.1017/S1431927617006377},
opturl = {https://www.cambridge.org/core/journals/microscopy-and-microanalysis/article/labelfree-imaging-of-stem-cell-adhesion-and-dynamic-tracking-of-boundary-evolution-using-photonic-crystal-enhanced-microscopy-pcem/C54B2C17D8D358188F5A0D74BD4A4651},
opturl = {https://doi.org/10.1017/S1431927617006377},
file = {docs/Zhuo2017b.pdf}
}
@inproceedings{Zhuo2016b,
author = {Zhuo, Yue
and Choi, Ji Sun
and Marin, Thibault
and Yu, Hojeong
and Harley, Brendan A.
and Cunningham, Brian T.},
title = {{P}hotonic {C}rystal {E}nhanced {M}icroscopy ({PCEM}) for {M}ultimode {D}ynamic {Q}uantitative {I}maging of {C}ell {A}dhesion},
booktitle = {{I}nternational {E}ngineering in {M}edicine and {B}iology {C}onference ({EMBC})},
year = {2016},
abstract = {We describe a novel label-free biosensor imaging modality within Photonic Crystal Enhanced Microscopy in which cell membrane components locally reduce resonantreflection efficiency through photon out-scattering caused by protein clusters within focal adhesion sites.},
file = {docs/Zhuo2016b.pdf}
}
@article{Zhuo2016,
author = {Zhuo, Yue
and Choi, Ji Sun
and Marin, Thibault
and Yu, Hojeong
and Harley, Brendan A.
and Cunningham, Brian T.},
title = {{Q}uantitative imaging of cell membrane-associated effective mass density using {P}hotonic {C}rystal {E}nhanced {M}icroscopy ({PCEM})},
journal = {Progress in Quantum Electronics},
year = {2016},
volume = {50},
pages = {1--18},
optkeywords = {photonic crystal enhanced microscopy (PCEM); photonic crystal (PC); photonic crystal slab; photonic crystal biosensor; live cell imaging; label-free imaging; stem cell; cancer cell; refractive index (RI); peak wavelength value (PWV); peak wavelength shift (PWS); mass density (MD); cell membrane-associated effective mass density},
abstract = {Adhesion is a critical cellular process that contributes to migration, apoptosis, differentiation, and division. It is followed by the redistribution of cellular materials at the cell membrane or at the cell-surface interface for cells interacting with surfaces, such as basement membranes. Dynamic and quantitative tracking of changes in cell adhesion mass redistribution is challenging because cells are rapidly moving, inhomogeneous, and nonequilibrium objects, whose physical and mechanical properties are difficult to measure or predict. Here, we report a novel biosensor based microscopy approach termed Photonic Crystal Enhanced Microscopy (PCEM) that enables the movement of cellular materials at the plasma membrane of individual live cells to be dynamically monitored and quantitatively imaged. PCEM utilizes a photonic crystal biosensor surface, which can be coated with arbitrary extracellular matrix materials to facilitate cellular interactions, within a modified brightfield microscope with a low intensity non-coherent light source. Benefiting from the high sensitivity, narrow resonance peak, and tight spatial confinement of the evanescent field atop the photonic crystal biosensor, PCEM enables label-free live cell imaging with high sensitivity and high lateral and axial spatial-resolution, thereby allowing dynamic adhesion phenotyping of single cells without the use of fluorescent tags or stains. We apply PCEM to investigate adhesion and the early stage migration of different types of stem cells and cancer cells. By applying image processing algorithms to analyze the complex spatiotemporal information generated by PCEM, we offer insight into how the plasma membrane of anchorage dependent cells is dynamically organized during cell adhesion. The imaging and analysis results presented here provide a new tool for biologists to gain a deeper understanding of the fundamental mechanisms involved with cell adhesion and concurrent or subsequent migration events.},
doi = {10.1016/j.pquantelec.2016.10.001},
opturl = {https://doi.org/10.1016/j.pquantelec.2016.10.001},
file = {docs/Zhuo2016.pdf}
}
@inproceedings{Zhuo2015b,
author = {Zhuo, Yue
and Choi, Ji Sun
and Yu, Hojeong
and Harley, Brendan A.
and Cunningham, Brian T.},
title = {{D}ynamic label-free imaging of live-cell adhesion using photonic crystal enhanced microscopy ({PCEM})},
booktitle = {{C}onference on {L}asers and {E}lectro-{O}ptics ({CLEO})},
series = {2015 Conference on Lasers and Electro-Optics (CLEO)},
year = {2015},
pages = {1--2},
optkeywords = {adhesion; biological techniques; biomechanics; biosensors; cell motility; optical images; optical microscopy; optical sensors; photonic crystals; dynamic label-free imaging; live-cell adhesion; photonic crystal enhanced microscopy; cell attachment; photonic-crystal biosensor surface; live-cell movement; spatiotemporal-distribution; cellular material; Adhesives; Imaging; Stem cells; Optical surface waves; Image color analysis},
abstract = {We demonstrate label-free imaging of cell attachment upon a photonic-crystal biosensor surface. Newly-implemented PCEM image-analysis software is used to dynamically visualize individual live-cell movement and demonstrate the spatiotemporal-distribution of cellular material during adhesion and motion.},
isbn = {978-1-55752-968-8},
issn = {2160-8989},
opturl = {https://ieeexplore.ieee.org/document/7184049},
file = {docs/Zhuo2015b.pdf}
}
@inproceedings{Zhuo2015c,
author = {Zhuo, Yue
and Choi, Ji Sun
and Yu, Hojeong
and Harley, Brendan A.
and Cunningham, Brian T.},
title = {{S}urface {A}ttachment {P}rofiling of {S}tem {C}ell {D}ifferentiation {U}sing {P}hotonic {C}rystal {E}nhanced {M}icroscopy ({PCEM})},
booktitle = {{T}he {A}merican {S}ociety of {M}echanical {E}ngineers -- {N}ano{E}ngineering for {M}edicine and {B}iology ({ASME}-{NEMB})},
year = {2015},
file = {docs/Zhuo2015c.pdf}
}
@article{Zhuo2015a,
author = {Zhuo, Yue
and Cunningham, Brian T.},
title = {{L}abel-{F}ree {B}iosensor {I}maging on {P}hotonic {C}rystal {S}urfaces},
journal = {Sensors (Basel, Switzerland)},
year = {2015},
volume = {15},
number = {9},
pages = {21613--21635},
optkeywords = {*Biocompatible Materials; Biosensing Techniques/*methods; Equipment Design; *Nanoparticles; *Photons; Protein Binding; biomaterial detection; label-free bioimaging; live cell imaging; nanoparticle detection; nanophotonics; photonic crystal; photonic crystal biosensor; photonic crystal enhanced fluorescence (PCEF); photonic crystal enhanced microscopy (PCEM); photonic crystal surface; protein-protein binding detection},
abstract = {We review the development and application of nanostructured photonic crystal surfaces and a hyperspectral reflectance imaging detection instrument which, when used together, represent a new form of optical microscopy that enables label-free, quantitative, and kinetic monitoring of biomaterial interaction with substrate surfaces. Photonic Crystal Enhanced Microscopy (PCEM) has been used to detect broad classes of materials which include dielectric nanoparticles, metal plasmonic nanoparticles, biomolecular layers, and live cells. Because PCEM does not require cytotoxic stains or photobleachable fluorescent dyes, it is especially useful for monitoring the long-term interactions of cells with extracellular matrix surfaces. PCEM is only sensitive to the attachment of cell components within {\~}200 nm of the photonic crystal surface, which may correspond to the region of most interest for adhesion processes that involve stem cell differentiation, chemotaxis, and metastasis. PCEM has also demonstrated sufficient sensitivity for sensing nanoparticle contrast agents that are roughly the same size as protein molecules, which may enable applications in {\textquoteleft}{\textquoteleft}digital{\textquoteright}{\textquoteright} diagnostics with single molecule sensing resolution. We will review PCEM{\textquoteright}s development history, operating principles, nanostructure design, and imaging modalities that enable tracking of optical scatterers, emitters, absorbers, and centers of dielectric permittivity.},
note = {[PMCID: \href{https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4610529}{PMC4610529}]},
issn = {1424-8220},
doi = {10.3390/s150921613},
opturl = {http://www.ncbi.nlm.nih.gov/pubmed/26343684},
opturl = {https://doi.org/10.3390/s150921613},
file = {docs/Zhuo2015a.pdf}
}
@inproceedings{Zhuo2014b,
author = {Zhuo, Yue
and Hu, Huan
and Chen, Weili
and Lu, Meng
and Tian, Limei
and Yu, Hojeong
and Long, Kenneth D.
and Chow, Edmond
and King, William P.
and Singamaneni, Srikanth
and Cunningham, Brian T.},
title = {{D}etection of single nanoparticles using photonic crystal enhanced microscopy},
booktitle = {2014 {C}onference on {L}asers and {E}lectro-{O}ptics ({CLEO}) -- {L}aser {S}cience to {P}hotonic {A}pplications},
year = {2014},
pages = {1--2},
optkeywords = {biomedical optical imaging; biosensors; nanomedicine; nanoparticles; nanosensors; optical microscopy; optical sensors; photonic crystals; plasmons; single nanoparticle detection; photonic crystal-enhanced microscopy; label-free biosensor imaging approach; photonic-crystal surface; nanoparticle plasmon resonant-frequency; photonic-crystal resonance; Optical surface waves; Surface waves; Educational institutions},
abstract = {We demonstrate a label-free biosensor imaging approach that utilizes a photonic-crystal surface to detect attachment of individual nanoparticles down to ~65{\texttimes}30{\texttimes}30nm3. Matching nanoparticle plasmon resonant-frequency to the photonic-crystal resonance substantially increases sensitivity of the approach.},
issn = {2160-8989},
doi = {10.1364/CLEO_SI.2014.SM4P.6},
opturl = {https://doi.org/10.1364/CLEO_SI.2014.SM4P.6},
file = {docs/Zhuo2014b.pdf}
}
@article{Zhuo2014,
author = {Zhuo, Yue
and Hu, Huan
and Chen, Weili
and Lu, Meng
and Tian, Limei
and Yu, Hojeong
and Long, Kenneth D.
and Chow, Edmond
and King, William P.
and Singamaneni, Srikanth
and Cunningham, Brian T.},
title = {{S}ingle nanoparticle detection using photonic crystal enhanced microscopy},
journal = {The Analyst},
year = {2014},
volume = {139},
number = {5},
pages = {1007--1015},
optkeywords = {Biosensing Techniques/*methods; Crystallization/*methods; Microscopy/methods; Nanoparticles/*analysis; *Photons},
abstract = {We demonstrate a label-free biosensor imaging approach that utilizes a photonic crystal (PC) surface to detect surface attachment of individual dielectric and metal nanoparticles through measurement of localized shifts in the resonant wavelength and resonant reflection magnitude from the PC. Using a microscopy-based approach to scan the PC resonant reflection properties with 0.6 mum spatial resolution, we show that metal nanoparticles attached to the biosensor surface with strong absorption at the resonant wavelength induce a highly localized reduction in reflection efficiency and are able to be detected by modulation of the resonant wavelength. Experimental demonstrations of single-nanoparticle imaging are supported by finite-difference time-domain computer simulations. The ability to image surface-adsorption of individual nanoparticles offers a route to single molecule biosensing, in which the particles can be functionalized with specific recognition molecules and utilized as tags.},
note = {[PMID: \href{https://pubmed.ncbi.nlm.nih.gov/24432353}{24432353}]},
issn = {0003-2654},
doi = {10.1039/c3an02295a},
opturl = {http://www.ncbi.nlm.nih.gov/pubmed/24432353},
opturl = {https://doi.org/10.1039/c3an02295a},
file = {docs/Zhuo2014.pdf}
}
@article{Zhuo2019,
author = {Zhuo, Yue
and Hu, Huan
and Wang, Yifei
and Marin, Thibault
and Lu, Meng},
title = {{P}hotonic crystal slab biosensors fabricated with helium ion lithography ({HIL})},
journal = {Sensors and Actuators A: Physical},
year = {2019},
volume = {297},
pages = {111493},
issn = {0924-4247},
doi = {10.1016/j.sna.2019.07.017},
opturl = {https://linkinghub.elsevier.com/retrieve/pii/S0924424719305217},
opturl = {https://doi.org/10.1016/j.sna.2019.07.017},
file = {docs/Zhuo2019.pdf}
}
@inproceedings{Zhuo2023,
author = {Zhuo, Yue
and Marin, Thibault
and Orehar, Matic
and Dolenec, Rok
and Chemli, Yanis
and Benlloch Baviera, Jose Maria
and Gascon Fora, David
and Gola, Alberto Giacomo
and Gomez Fernandez, Sergio
and Montoro, Andrea Gonzalez
and Gonzalez Martinez, Antonio
and Grogg, Kira
and Guberman, Daniel Alberto
and Korpar, Samo
and Krizan, Peter
and Majewski, Stan
and Manera, Rafel
and Mariscal Castilla, Antonio
and Mauricio Ferre, Joan
and Merzi, Stefano
and Moliner Martinez, Laura
and Moretti, Elena
and Normandin, Marc D.
and Parellada Monreal, Laura
and Paternoster, Giovanni
and Penna, Michele Francesco
and Razdevsek, Gasper
and Sabet, Hamid
and Sanuy, Andreu Charles
and Seljak, Andrej
and Studen, Andrej
and Pestotnik, Rok
and El Fakhri, Georges},
title = {{U}ltra-high spatial and time of flight resolution brain {PET} reconstruction},
booktitle = {{S}ociety of {N}uclear {M}edicine {\&} {M}olecular {I}maging {C}onference},
year = {2023},
abstract = {Purpose/Background:Despite recent advances in PET detectors and image reconstruction algorithms, the spatial resolution of clinical PET systems is in the range of 3 mm for best dedicated brain PET systems, and the time of flight (TOF) coincidence timing resolution (CTR) is limited to 200 ps FWHM. To address these limitations, we are developing a dedicated brain PET scanner expected to achieve ultrahigh TOF resolution (~75 ps FWHM), and spatial resolution (~1.2 mm), substantially improving upon existing scanners. We also take advantage of the faster timing resolution to revolutionize the conventional cylindrical geometry of current PET scanners. In this work, we present results of a Monte Carlo simulation study demonstrating the performance of the proposed brain PET system and how this compares to existing commercial PET scanners.Methods:The proposed PET system is composed of 1x1x10 mm3 LSO crystals arranged in 8x4 modules, each with 32x32 channels and a crystal-crystal pitch of 1.6 mm to match the photodetectors (Figure 1.A). The scanner radius is 17 cm and the height is 22 cm. Ultra-high TOF resolution (75 ps FWHM) is achieved by using multiplexed SiPMs [1] with improved photon detection efficiency (PDE) in combination with FastIC ASIC chips [2, 3]. This ground-breaking TOF resolution enables the use of smaller scintillators which will enhance the intrinsic spatial resolution and minimize resolution-degrading parallax effects. To demonstrate the performance of the proposed system, acquisitions of a high-resolution brain phantom (BigBrain) using the proposed scanner were simulated using GATE. Similar simulations were performed for a state-of-the-art clinical PET scanner (Siemens Biograph Vision with 200 ps FWHM TOF resolution). For both scanners, 140 million recorded coincidences were collected.Results:The simulated list-mode data were reconstructed using an in-house reconstruction engine which implements the ML-EM algorithm with a TOF-enabled distance-driven projector. Images were reconstructed with an isotropic pixel size of 0.8 mm. The number of iterations was selected to match the noise level between the two scanners. For the brain phantom, the imaging model of the proposed scanner included point-spread function (PSF) modeling simultaneously in the image and projection domains. Image domain PSF was modeled by a spatially invariant Gaussian blurring kernel with FWHM of 1 mm. Projection domain PSF modeling was implemented via a distance-dependent in-plane Gaussian kernel. Gaussian kernels for different radial positions were estimated from GATE simulations of point sources at different distances from the isocenter, followed by a quadratic fit of the point response FWHM as a function of the radial distance. Reconstructions of our model of Siemens Biograph scanner were simply post-processed by a Gaussian filter with FWHM of 1.5 mm.Figure 1.B shows the ground truth simulation phantom along with reconstructions from the proposed scanner and our model of the Siemens Biograph system. The proposed ultra-high TOF resolution system results in the best visual image quality and allows the visualization of small cortical brain structures. This improvement in spatial resolution is confirmed by the line profiles shown on Figure 1.C.Conclusion:A novel ultra-high TOF resolution PET system was evaluated and compared to an existing state-of-the-art TOF PET scanner, showing substantially improved spatial resolution, thanks to the ultra-high TOF resolution and advanced system model. These results suggest that the proposed system may allow the visualization of small brain structures which are typically not visible with existing systems. This could enable new opportunities for neurobiology research in aging and related fields.},
file = {docs/Zhuo2023.pdf}
}
@inproceedings{Zhuo2012,
author = {Zhuo, Yue
and Qian, Tongcheng
and Lu, Shaoying
and Wang, Yingxiao},
title = {{S}rc {A}ctivity {D}ynamic {D}etection {I}n {T}he {I}nitiation {O}f {T}ension-released {C}ell {M}igration},
booktitle = {{BMES}},
year = {2012},
abstract = {Cell migration is critical for embryonic development, wound healing and cancer metastasis. Protein tyrosine kinase Src plays important roles in cell migration and thus it is important to understand how molecular signals of Src regulate cellular migration and function. Here we present a live cell imaging and analysis system to observe and quantify the coupling between molecular activities and the initiation of migration. This system combines three technologies, including micro-pattern, genetic encoded fluorescent biosensor based on fluorescence resonant energy transfer (FRET) and automated analysis. This system allowed the detection of down-regulation of Src activity coupled with the membrane protrusion at cell front when migration was initiated.},
opturl = {https://www.bmes.org/files/Annual\%20Meeting\%20Program\%20Guides/2012AnnualMeetingProgram.pdf},
file = {docs/Zhuo2012.pdf}
}
@article{Zhuo2015,
author = {Zhuo, Yue
and Qian, Tongcheng
and Wu, Yiqian
and Seong, Jihye
and Gong, Ya
and Ma, Hongwei
and Wang, Yingxiao
and Lu, Shaoying},
title = {{S}ubcellular and {D}ynamic {C}oordination between {S}rc {A}ctivity and {C}ell {P}rotrusion in {M}icroenvironment},
journal = {Scientific Reports},
year = {2015},
volume = {5},
pages = {12963},
optkeywords = {Cell Movement/genetics; Cell Polarity/genetics; Cell Surface Extensions/genetics; Cellular Microenvironment/*genetics; Endothelial Cells/*cytology/metabolism; Fluorescence Resonance Energy Transfer; Humans; Neovascularization; Physiologic/genetics; Wound Healing/*genetics; src-Family Kinases/genetics/*metabolism},
abstract = {Migration of endothelial cells is essential for wound healing and angiogenesis. Src kinase activity plays important roles at the protrusions of migrating endothelial cells. However, the spatiotemporal coordination between Src kinase activity and the protrusion of cell edge remains unclear. Therefore, we investigate these coordinated molecular events at the initiation of cell migration, by integrating microfabrication, fluorescence resonance energy transfer (FRET)-based biosensors, and automated computational image analysis. We demonstrate that the physical release of restrictive micropattern triggered a significant decrease of Src activity at the protrusive edge of endothelial cells. Computational cross-correlation analysis reveals that the decrease of Src activity occurred earlier in time, and was well-coordinated with the protrusion of cell edge in polarized cells, but not in non-polarized cells. These results suggest that the spatiotemporal control of Src kinase activity is well-coordinated with cell polarization and protrusion in endothelial cells upon the release of physical constraint, as that experienced by endothelial cells sprouting from stiff tumor micro-environment during angiogenesis. Therefore, our integrative approach enabled the discovery of a new model where Src is de-activated in coordination with membrane protrusion, providing important insights into the regulation of endothelial migration and angiogenesis.},
note = {[PMCID: \href{https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4531316}{PMC4531316}]},
issn = {2045-2322},
doi = {10.1038/srep12963},
opturl = {http://www.ncbi.nlm.nih.gov/pubmed/26261043},
opturl = {https://doi.org/10.1038/srep12963},
file = {docs/Zhuo2015.pdf}
}
@inproceedings{Zhuo2010a,
author = {Zhuo, Yue
and Sutton, Bradley P.},
title = {f{MRI} calibration using effective {BOLD} signals estimated from susceptibility-induced echo-time-shift},
booktitle = {{OHBM}},
year = {2010},
file = {docs/Zhuo2010a.pdf}
}
@inproceedings{Zhuo2010b,
author = {Zhuo, Yue
and Sutton, Bradley P.},
title = {{S}usceptibility-induced {BOLD} {S}ensitivity {V}ariation in {B}reath {H}old {T}ask},
booktitle = {{ISMRM}},
year = {2010},
opturl = {https://pdfs.semanticscholar.org/888f/27835ccfc546b38697b493ba445e870d2819.pdf},
file = {docs/Zhuo2010b.pdf}
}
@article{Zhuo2009,
author = {Zhuo, Yue
and Sutton, Bradley P.},
title = {{E}ffect on {BOLD} sensitivity due to susceptibility-induced echo time shift in spiral-in based functional {MRI}},
journal = {IEEE Engineering in Medicine and Biology Society},
year = {2009},
volume = {2009},
pages = {4449--4452},
optkeywords = {Artifacts; Brain/*physiology; Humans; Magnetic Resonance Imaging/*methods; Models; Theoretical; Oxygen/blood; *Signal Processing; Computer-Assisted},
abstract = {Susceptibility artifacts induced by the magnetic field inhomogeneity exist near the air/tissue interfaces at the ventral brain in functional magnetic resonance imaging (fMRI). These susceptibility artifacts will cause geometric distortions and signal loss in reconstructed images. Additionally, the in-plane susceptibility gradients will cause a shift in effective echo time, and therefore influence the blood-oxygen-level dependent (BOLD) sensitivity since it is proportional to effective echo time. In this work, we examine the effective echo time shift and the change of the BOLD sensitivity based on susceptibility gradients. The analysis results show that there are regions, such as the orbitofrontal cortex, that suffer from significant loss of BOLD sensitivity using spiral-in trajectory in BOLD fMRI.},
note = {[PMID: \href{https://pubmed.ncbi.nlm.nih.gov/19964630}{19964630}]},
issn = {1557-170X},
doi = {10.1109/IEMBS.2009.5333815},
opturl = {http://www.ncbi.nlm.nih.gov/pubmed/19964630},
opturl = {https://doi.org/10.1109/IEMBS.2009.5333815},
file = {docs/Zhuo2009.pdf}
}
@article{Zhuo2009a,
author = {Zhuo, Yue
and Sutton, Bradley P.},
title = {{I}terative image reconstruction model including susceptibility gradients combined with {Z}-shimming gradients in f{MRI}},
journal = {IEEE Engineering in Medicine and Biology Society},
year = {2009},
volume = {2009},
pages = {5721--5724},
optkeywords = {*Algorithms; Brain/*physiology; Evoked Potentials/*physiology; Humans; Image Enhancement/methods; Image Interpretation; Computer-Assisted/*methods; Magnetic Resonance Imaging/*methods; *Models; Neurological; Phantoms; Imaging; Reproducibility of Results; Sensitivity and Specificity},
abstract = {Magnetic susceptibility artifacts, including both image distortions and signal losses, exist near air/tissue interfaces in the ventral brain in standard blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI). Although several acquisition-based approaches exist to address the signal losses, they require increased acquisition time or patient customization. In this work, we propose a statistical estimation model that includes the effects of magnetic field gradients (both within-plane and through-plane gradients) and uses an iterative reconstruction algorithm to reconstruct images corrected for both magnetic field distortion and signal losses. Besides, we combine our reconstruction approach with a recently proposed MRI sequence with Z-shimming gradient between the spiral-in and spiral-out acquisition to enhance the compensation for signal losses. Therefore, we extend our forward MR signal model to include the physics of Susceptibility-induced magnetic Field (SF), Susceptibility-induced magnetic Field Gradients (SFG), and the application of the data acquisition technique with Z-shimming Gradients (ZShG). The results show that not only signal distortions but also significant signal losses can be compensated by considering both the modeling of field-inhomogeneity effects along with the acquisition using Z-shimming.},
note = {[PMID: \href{https://pubmed.ncbi.nlm.nih.gov/19963915}{19963915}]},
issn = {1557-170X},
doi = {10.1109/IEMBS.2009.5332669},
opturl = {http://www.ncbi.nlm.nih.gov/pubmed/19963915},
opturl = {https://doi.org/10.1109/IEMBS.2009.5332669},
file = {docs/Zhuo2009a.pdf}
}
@inproceedings{Zhuo2008,
author = {Zhuo, Yue
and Sutton, Bradley P.},
title = {{I}terative, {F}ield-inhomogeneity {C}ompensated {I}mage {R}econstruction for {MRI} with {Z}-shim {G}radient},
booktitle = {2008 {C}onference: {B}iomedical {E}ngineering {S}ociety ({BMES})},
year = {2008},
file = {docs/Zhuo2008.pdf}
}
@inproceedings{Zhuo2014a,
author = {Zhuo, Yue
and Tian, Limei
and Chen, Weili
and Yu, Hojeong
and Singamaneni, Srikanth
and Cunningham, Brian T.},
title = {{P}rotein-protein binding detection with nanoparticle photonic crystal enhanced microscopy ({NP}-{PCEM})},
booktitle = {36th {A}nnual {I}nternational {C}onference of the {IEEE} {E}ngineering in {M}edicine and {B}iology {S}ociety},
year = {2014},
publisher = {IEEE},
pages = {2069--2072},
optkeywords = {adsorption; biochemistry; biosensors; finite difference time-domain analysis; molecular biophysics; nanobiotechnology; nanoparticles; nanosensors; photonic crystals; proteins; surface plasmon resonance; protein-protein binding detection; nanoparticle photonic crystal enhanced microscopy; Np-Pcem; microscopy-based biosensing approach; photonic crystal surface; PC surface; functionalized nanoparticles; localized shift measurement; resonant wavelength; resonant reflection magnitude; localized surface plasmon resonant frequency; PC biosensor; PCEM imaging; single nanoparticle resolution; finite-difference time-domain computer simulations; FDTD computer simulations; surface adsorption; Optical surface waves; Surface waves; Plasmons; Gold; Animals; Antibodies; Antigens; Computer Simulation; Crystallization; Electromagnetic Fields; Metal Nanoparticles; Microscopy; Photons; Protein Binding; Protein Interaction Mapping; Rabbits; Spectrophotometry; Ultraviolet},
abstract = {We demonstrate a novel microscopy-based biosensing approach that utilizes a photonic crystal (PC) surface to detect protein-protein binding with the functionalized nanoparticles as tags. This imaging approach utilizes the measurement of localized shifts in the resonant wavelength and resonant reflection magnitude from the PC biosensor in the presence of individual nanoparticles. Moreover, it substantially increases the sensitivity of the imaging approach through tunable localized surface plasmon resonant frequency of the nanoparticle matching with the resonance of the PC biosensor. Experimental demonstrations of photonic crystal enhanced microscopy (PCEM) imaging with single nanoparticle resolution are supported by Finite-Difference Time-Domain (FDTD) computer simulations. The ability to detect the surface adsorption of individual nanoparticles as tags offers a route to single molecule biosensing with photonic crystal biosensor in the future.},
isbn = {978-1-4244-7929-0},
doi = {10.1109/EMBC.2014.6944023},
opturl = {https://doi.org/10.1109/EMBC.2014.6944023},
file = {docs/Zhuo2014a.pdf}
}
@inproceedings{Zhuo2010c,
author = {Zhuo, Yue
and Wu, Xiao-Long
and Haldar, Justin P.
and Hwu, Wen-mei W.
and Liang, Zhi-Pei
and Sutton, Bradley P.},
title = {{M}ulti-{GPU} {I}mplementation for {I}terative {MR} {I}mage {R}econstruction with {F}ield {C}orrection},
booktitle = {{ISMRM}},
year = {2010},
abstract = {Many advanced MRI image acquisition and reconstruction methods see limited application due to high computational cost in MRI. For instance, iterative reconstruction algorithms (e.g. non-Cartesian k-space trajectory, or magnetic field inhomogeneity compensation) can improve image quality but suffer from low reconstruction speed. General-purpose computing on graphics processing units (GPU) have demonstrated significant performance speedups and cost reductions in science and engineering applications. In fact, GPU can offer significant speedup due to MRI parallelized-data structure, e.g. multi-shots, multi-coil, multi-slice, multi-time-point, etc. We propose an implementation of iterative MR image reconstruction with magnetic field inhomogeneity compensation on multi-GPUs. The MR image model is based on non-Cartesian trajectory (i.e. spiral) in k-space, and can compensate for both geometric distortion and some signal loss induced by susceptibility gradients.},
opturl = {https://www.semanticscholar.org/paper/Multi-GPU-Implementation-for-Iterative-MR-Image-Zhuo-Wu/3a4f5ef8217c02e29bbbfc8b4603ba58c964c97d},
file = {docs/Zhuo2010c.pdf}
}
@inproceedings{Zhuo2010,
author = {Zhuo, Yue
and Wu, Xiao-Long
and Haldar, Justin P.
and Hwu, Wen-mei W.
and Liang, Zhi-Pei
and Sutton, Bradley P.},
title = {{S}parse regularization in {MRI} iterative reconstruction using {GPU}s},
booktitle = {2010 3rd {I}nternational {C}onference on {B}iomedical {E}ngineering and {I}nformatics},
year = {2010},
volume = {2},
pages = {578--582},
optkeywords = {biomedical MRI; image reconstruction; iterative methods; medical image processing; sparse matrices; sparse regularization; Mri; iterative reconstruction; Gpu; graphics processing unit; susceptibility-induced field inhomogeneity effects; quadratic regularization; Magnetic resonance imaging; Central Processing Unit; Reconstruction algorithms; Regularization; Sparse matrix; Graphics Processing Unit (GPU); Cuda; magnetic resonance imaging (MRI); biomedical optical imaging; biosensors; nanomedicine; nanoparticles; nanosensors; optical microscopy; optical sensors; photonic crystals; plasmons; single nanoparticle detection; photonic crystal-enhanced microscopy; label-free biosensor imaging approach; photonic-crystal surface; nanoparticle plasmon resonant-frequency; photonic-crystal resonance; Optical surface waves; Surface waves; Educational institutions},
abstract = {Regularization is a common technique used to improve image quality in inverse problems such as MR image reconstruction. In this work, we extend our previous Graphics Processing Unit (GPU) implementation of MR image reconstruction with compensation for susceptibility-induced field inhomogeneity effects by incorporating an additional quadratic regularization term. Regularization techniques commonly impose the prior information that MR images are relatively smooth by penalizing large changes in intensity between neighboring voxels. However, the associated computations often increase data access and the overall computational load, which can lead to slower image reconstruction. This motivates us to adopt a GPU-enabled implementation of spatial regularization using sparse matrices. This implementation enables the computations for the entire reconstruction procedure to be done on the GPU, which avoids the memory bandwidth bottlenecks associated with frequent communications between the GPU and CPU. Both the CPU and GPU code of this implementation will be available for release at the time of the conference.},
doi = {10.1109/BMEI.2010.5640008},
opturl = {https://doi.org/10.1109/BMEI.2010.5640008},
file = {docs/Zhuo2010.pdf}
}
@inproceedings{Zhuo2010d,
author = {Zhuo, Yue
and Wu, Xiao-Long
and Haldar, Justin P.
and Hwu, Wen-mei W.
and Liang, Zhi-Pei
and Sutton, Bradley P.},
title = {{A}ccelerating iterative field-compensated {MR} image reconstruction on {GPU}s},
booktitle = {2010 {IEEE} {I}nternational {S}ymposium on {B}iomedical {I}maging: {F}rom {N}ano to {M}acro},
year = {2010},
pages = {820--823},
optkeywords = {biomedical MRI; brain; computer graphics; conjugate gradient methods; image reconstruction; medical image processing; neurophysiology; iterative field-compensated MR image reconstruction; graphics processing units; conjugate gradient algorithms; magnetic field inhomogeneity; susceptibility differences; air-tissue interface; human brain; orbitofrontal cortex; field inhomogeneity compensation; magnetic field map; parallel computational hardware; field inhomogeneity compensation technique; Nvida Cuda; compute unified device architecture; Acceleration; Iterative algorithms; Magnetic fields; Graphics; Magnetic resonance imaging; Brain modeling; Physics; Magnetic susceptibility; Humans; Mri; Gpu; Cuda; Conjugate Gradient; Iterative reconstruction; Field inhomogeneity},
abstract = {We propose a fast implementation for iterative MR image reconstruction using Graphics Processing Units (GPU). In MRI, iterative reconstruction with conjugate gradient algorithms allows for accurate modeling the physics of the imaging system. Specifically, methods have been reported to compensate for the magnetic field inhomogeneity induced by the susceptibility differences near the air/tissue interface in human brain (such as orbitofrontal cortex). Our group has previously presented an algorithm for field inhomogeneity compensation using magnetic field map and its gradients. However, classical iterative reconstruction algorithms are computationally costly, and thus significantly increase the computation time. To remedy this problem, one can utilize the fact that these iterative MR image reconstruction algorithms are highly parallelizable. Therefore, parallel computational hardware, such as GPU, can dramatically improve their performance. In this work, we present an implementation of our field inhomogeneity compensation technique using NVIDA CUDA(Compute Unified Device Architecture)-enabled GPU. We show that the proposed implementation significantly reduces the computation times around two orders of magnitude (compared with non-GPU implementation) while accurately compensating for field inhomogeneity.},
doi = {10.1109/ISBI.2010.5490112},
opturl = {https://doi.org/10.1109/ISBI.2010.5490112},
file = {docs/Zhuo2010d.pdf}
}
@inbook{Zhuo2011,
author = {Zhuo, Yue
and Wu, Xiao-Long
and Haldar, Justin P.
and Marin, Thibault
and Hwu, Wen-mei W.
and Liang, Zhi-Pei
and Sutton, Bradley P.},
title = {{U}sing {GPU}s to {A}ccelerate {A}dvanced {MRI} {R}econstruction with {F}ield {I}nhomogeneity {C}ompensation},
booktitle = {GPU Computing Gems},
year = {2011},
publisher = {Elsevier Science},
isbn = {9780123849885},
doi = {10.1016/B978-0-12-384988-5.00044-9},
opturl = {https://www.sciencedirect.com/science/article/pii/B9780123849885000449},
opturl = {https://doi.org/10.1016/B978-0-12-384988-5.00044-9},
file = {docs/Zhuo2011.pdf}
}