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Bioimaging and Biomedical Optics Commons™
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Articles 1 - 19 of 19
Full-Text Articles in Bioimaging and Biomedical Optics
Differentiating Axonal From Demyelinating Neuropathies Using Multiparametric Quantitative Mri Of Peripheral Nerves, Jacob D. Baraz, Stephanie Xuan, Sadaf Saba, Xue Yang, Ryan Castoro, Yang Xuan, Alison Roth, Richard D. Dortch, Jun Li, Yongsheng Chen
Differentiating Axonal From Demyelinating Neuropathies Using Multiparametric Quantitative Mri Of Peripheral Nerves, Jacob D. Baraz, Stephanie Xuan, Sadaf Saba, Xue Yang, Ryan Castoro, Yang Xuan, Alison Roth, Richard D. Dortch, Jun Li, Yongsheng Chen
Medical Student Research Symposium
Objectives: To develop a multiparametric quantitative MRI (qMRI) method to track pathological changes in the peripheral neuropathies.
Background: Irrespective of the causes or types of polyneuropathies, peripheral nerves are mainly afflicted by two kinds of pathologies – axonal loss and demyelination. It is critical to differentiate between the two as treatments are different for the two conditions. While nerve conduction studies (NCS) have been used to differentiate the two pathologies in the distal nerves, there are no tools to probe the pathologies in the proximal peripheral nerves. This is particularly needed when distal nerves become non-responsive in NCS.
Methods: We …
Nanoanalytical Analysis Of Bisphosphonate-Driven Alterations Of Microcalcifications Using A 3d Hydrogel System And In Vivo Mouse Model, Jessica L. Ruiz, Joshua D. Hutcheson, Luis Cardoso, Amirala Bakhshian Nik, Alexandra Condado De Abreu, Tan Pham, Fabrizio Buffolo, Sara Busatto, Stefania Frederici, Andrea Ridolfi, Masanori Aikawa, Sergio Bertazzo, Paolo Bergese, Sheldon Weinbaum, Elena Aikawa
Nanoanalytical Analysis Of Bisphosphonate-Driven Alterations Of Microcalcifications Using A 3d Hydrogel System And In Vivo Mouse Model, Jessica L. Ruiz, Joshua D. Hutcheson, Luis Cardoso, Amirala Bakhshian Nik, Alexandra Condado De Abreu, Tan Pham, Fabrizio Buffolo, Sara Busatto, Stefania Frederici, Andrea Ridolfi, Masanori Aikawa, Sergio Bertazzo, Paolo Bergese, Sheldon Weinbaum, Elena Aikawa
Publications and Research
Vascular calcification predicts atherosclerotic plaque rupture and cardiovascular events. Retrospective studies of women taking bisphosphonates (BiPs), a proposed therapy for vascular calcification, showed that BiPs paradoxically increased morbidity in patients with prior acute cardiovascular events but decreased mortality in event-free patients. Calcifying extracellular vesicles (EVs), released by cells within atherosclerotic plaques, aggregate and nucleate calcification. We hypothesized that BiPs block EV aggregation and modify existing mineral growth, potentially altering microcalcification morphology and the risk of plaque rupture. Three-dimensional (3D) collagen hydrogels incubated with calcifying EVs were used to mimic fibrous cap calcification in vitro, while an ApoE−/− mouse was used …
Bibliometric Review On Applications Of Disease Detection Using Digital Image Processing Techniques, Jayant Jagtap, Rahil Sharma, Aryan Sinha, Nikhil Panda, Amulya Reddy
Bibliometric Review On Applications Of Disease Detection Using Digital Image Processing Techniques, Jayant Jagtap, Rahil Sharma, Aryan Sinha, Nikhil Panda, Amulya Reddy
Library Philosophy and Practice (e-journal)
Advances around the field of deep learning and cognitive computing have allowed mankind to look and solve the problems of the world in a completely new way. Deep learning has been making huge advancements in the field of healthcare, which most importantly focuses upon disease detection and disease prediction. Techniques such as these have been conceptualized the idea of early detection and economical ways of treating the predicted disease in particular. Still, it has been observed that there seems to be no change in the way diagnosis of a particular disease takes place even in the 21st generation of …
Scalable Profiling And Visualization For Characterizing Microbiomes, Camilo Valdes
Scalable Profiling And Visualization For Characterizing Microbiomes, Camilo Valdes
FIU Electronic Theses and Dissertations
Metagenomics is the study of the combined genetic material found in microbiome samples, and it serves as an instrument for studying microbial communities, their biodiversities, and the relationships to their host environments. Creating, interpreting, and understanding microbial community profiles produced from microbiome samples is a challenging task as it requires large computational resources along with innovative techniques to process and analyze datasets that can contain terabytes of information.
The community profiles are critical because they provide information about what microorganisms are present in the sample, and in what proportions. This is particularly important as many human diseases and environmental disasters …
Seeing Eye To Eye: A Machine Learning Approach To Automated Saccade Analysis, Maigh Attre
Seeing Eye To Eye: A Machine Learning Approach To Automated Saccade Analysis, Maigh Attre
Honors Scholar Theses
Abnormal ocular motility is a common manifestation of many underlying pathologies particularly those that are neurological. Dynamics of saccades, when the eye rapidly changes its point of fixation, have been characterized for many neurological disorders including concussions, traumatic brain injuries (TBI), and Parkinson’s disease. However, widespread saccade analysis for diagnostic and research purposes requires the recognition of certain eye movement parameters. Key information such as velocity and duration must be determined from data based on a wide set of patients’ characteristics that may range in eye shapes and iris, hair and skin pigmentation [36]. Previous work on saccade analysis has …
Glioma Grading Using Structural Magnetic Resonance Imaging And Molecular Data, Syed M.S. Reza, Manar D. Samad, Zeina A. Shboul, Karra A. Jones, Khan M. Iftekharuddin
Glioma Grading Using Structural Magnetic Resonance Imaging And Molecular Data, Syed M.S. Reza, Manar D. Samad, Zeina A. Shboul, Karra A. Jones, Khan M. Iftekharuddin
Electrical & Computer Engineering Faculty Publications
A glioma grading method using conventional structural magnetic resonance image (MRI) and molecular data from patients is proposed. The noninvasive grading of glioma tumors is obtained using multiple radiomic texture features including dynamic texture analysis, multifractal detrended fluctuation analysis, and multiresolution fractal Brownian motion in structural MRI. The proposed method is evaluated using two multicenter MRI datasets: (1) the brain tumor segmentation (BRATS-2017) challenge for high-grade versus low-grade (LG) and (2) the cancer imaging archive (TCIA) repository for glioblastoma (GBM) versus LG glioma grading. The grading performance using MRI is compared with that of digital pathology (DP) images in the …
Manganese-Enhanced Magnetic Resonance Imaging: Overview And Central Nervous System Applications With A Focus On Neurodegeneration, Ryan A. Cloyd, Shon A. Koren, Jose F. Abisambra
Manganese-Enhanced Magnetic Resonance Imaging: Overview And Central Nervous System Applications With A Focus On Neurodegeneration, Ryan A. Cloyd, Shon A. Koren, Jose F. Abisambra
Physiology Faculty Publications
Manganese-enhanced magnetic resonance imaging (MEMRI) rose to prominence in the 1990s as a sensitive approach to high contrast imaging. Following the discovery of manganese conductance through calcium-permeable channels, MEMRI applications expanded to include functional imaging in the central nervous system (CNS) and other body systems. MEMRI has since been employed in the investigation of physiology in many animal models and in humans. Here, we review historical perspectives that follow the evolution of applied MRI research into MEMRI with particular focus on its potential toxicity. Furthermore, we discuss the more current in vivo investigative uses of MEMRI in CNS investigations and …
In Vivo Brainstem Imaging In Alzheimer’S Disease: Potential For Biomarker Development, David J. Braun, Linda J. Van Eldik
In Vivo Brainstem Imaging In Alzheimer’S Disease: Potential For Biomarker Development, David J. Braun, Linda J. Van Eldik
Neuroscience Faculty Publications
The dearth of effective treatments for Alzheimer’s disease (AD) is one of the largest public health issues worldwide, costing hundreds of billions of dollars per year. From a therapeutic standpoint, research efforts to date have met with strikingly little clinical success. One major issue is that trials begin after substantial pathological change has occurred, and it is increasingly clear that the most effective treatment regimens will need to be administered earlier in the disease process. In order to identify individuals within the long preclinical phase of AD who are likely to progress to dementia, improvements are required in biomarker development. …
Objectively Measuring Effects Of Electro-Acupuncture In Parkinsonian Rhesus Monkeys, Rui Zhang, Anders H. Andersen, Peter A. Hardy, Eric Forman, April Evans, Yi Ai, Jin Yue, Guihua Yue, Don M. Gash, Richard Grondin, Zhiming Zhang
Objectively Measuring Effects Of Electro-Acupuncture In Parkinsonian Rhesus Monkeys, Rui Zhang, Anders H. Andersen, Peter A. Hardy, Eric Forman, April Evans, Yi Ai, Jin Yue, Guihua Yue, Don M. Gash, Richard Grondin, Zhiming Zhang
Magnetic Resonance Imaging and Spectroscopy Center Faculty Publications
Acupuncture has increasingly been used as an alternative therapy for treatment of Parkinson’s disease (PD). However, the efficacy of acupunture for PD still remains unclear. The present study was designed to objectively and safely monitor anti-parkinsonian effects of electroacupuncture (EA) and brain activity in nonhuman primates modeling human PD. Six middle-aged rhesus monkeys were extensively studied by a computerized behavioral testing battery and by pharmacological MRI (phMRI) scans with specific dopaminergic drug stimulations. All animals were evaluated for behavior and phMRI responses under normal, parkinsonian, parkinsonian with EA treatment and parkinsonian after EA treatment conditions. Stable parkinsonian features were observed …
Pattern Discovery In Brain Imaging Genetics Via Scca Modeling With A Generic Non-Convex Penalty, Lei Du, Kefei Liu, Xiaohui Yao, Jingwen Yan, Shannon L. Risacher, Junwei Han, Lei Guo, Andrew J. Saykin, Li Shen, Michael W. Weiner, Paul Aisen, Ronald Petersen, Clifford R. Jack, William Jagust, John Q. Trojanowki, Arthur W. Toga, Laurel Beckett, Robert C. Green, John Morris, Leslie M. Shaw, Zaven Khachaturian, Greg Sorensen, Maria Carrillo, Lew Kuller, Marc Raichle, Steven Paul, Peter Davies, Howard Fillit, Franz Hefti, David Holtzman, Charles D. Smith, Gregory Jicha, Peter A. Hardy, Partha Sinha, Elizabeth Oates, Gary Conrad
Pattern Discovery In Brain Imaging Genetics Via Scca Modeling With A Generic Non-Convex Penalty, Lei Du, Kefei Liu, Xiaohui Yao, Jingwen Yan, Shannon L. Risacher, Junwei Han, Lei Guo, Andrew J. Saykin, Li Shen, Michael W. Weiner, Paul Aisen, Ronald Petersen, Clifford R. Jack, William Jagust, John Q. Trojanowki, Arthur W. Toga, Laurel Beckett, Robert C. Green, John Morris, Leslie M. Shaw, Zaven Khachaturian, Greg Sorensen, Maria Carrillo, Lew Kuller, Marc Raichle, Steven Paul, Peter Davies, Howard Fillit, Franz Hefti, David Holtzman, Charles D. Smith, Gregory Jicha, Peter A. Hardy, Partha Sinha, Elizabeth Oates, Gary Conrad
Neurology Faculty Publications
Brain imaging genetics intends to uncover associations between genetic markers and neuroimaging quantitative traits. Sparse canonical correlation analysis (SCCA) can discover bi-multivariate associations and select relevant features, and is becoming popular in imaging genetic studies. The L1-norm function is not only convex, but also singular at the origin, which is a necessary condition for sparsity. Thus most SCCA methods impose ℓ1-norm onto the individual feature or the structure level of features to pursuit corresponding sparsity. However, the ℓ1-norm penalty over-penalizes large coefficients and may incurs estimation bias. A number of non-convex penalties are proposed to reduce …
Resting State Functional Network Disruptions In A Kainic Acid Model Of Temporal Lobe Epilepsy., Ravnoor Singh Gill, Seyed M Mirsattari, L Stan Leung
Resting State Functional Network Disruptions In A Kainic Acid Model Of Temporal Lobe Epilepsy., Ravnoor Singh Gill, Seyed M Mirsattari, L Stan Leung
Physiology and Pharmacology Publications
We studied the graph topological properties of brain networks derived from resting-state functional magnetic resonance imaging in a kainic acid induced model of temporal lobe epilepsy (TLE) in rats. Functional connectivity was determined by temporal correlation of the resting-state Blood Oxygen Level Dependent (BOLD) signals between two brain regions during 1.5% and 2% isoflurane, and analyzed as networks in epileptic and control rats. Graph theoretical analysis revealed a significant increase in functional connectivity between brain areas in epileptic than control rats, and the connected brain areas could be categorized as a limbic network and a default mode network (DMN). The …
Spectral Discrimination Of Breast Pathologies In Situ Using Spatial Frequency Domain Imaging, Ashley M. Laughney, Venkataramanan Krishnaswamy, Elizabeth J. Rizzo, Mary C. Schwab, Richard J. Barth, David J. Cuccia, Bruce J. Tromberg, Keith D. Paulsen, Brian W. Pogue, Wendy A. Wells
Spectral Discrimination Of Breast Pathologies In Situ Using Spatial Frequency Domain Imaging, Ashley M. Laughney, Venkataramanan Krishnaswamy, Elizabeth J. Rizzo, Mary C. Schwab, Richard J. Barth, David J. Cuccia, Bruce J. Tromberg, Keith D. Paulsen, Brian W. Pogue, Wendy A. Wells
Dartmouth Scholarship
Introduction: Nationally, 25% to 50% of patients undergoing lumpectomy for local management of breast cancer require a secondary excision because of the persistence of residual tumor. Intraoperative assessment of specimen margins by frozen-section analysis is not widely adopted in breast-conserving surgery. Here, a new approach to wide-field optical imaging of breast pathology in situ was tested to determine whether the system could accurately discriminate cancer from benign tissues before routine pathological processing.
Dynamic Dual-Tracer Mri-Guided Fluorescence Tomography To Quantify Receptor Density In Vivo, Scott C. Davis, Kimberley S. Samkoe, Kenneth M. Tichauer, Kristian J. Sexton, Jason R. Gunn, Sophie J. Deharvengt, Tayyaba Hasan, Brian W. Pogue
Dynamic Dual-Tracer Mri-Guided Fluorescence Tomography To Quantify Receptor Density In Vivo, Scott C. Davis, Kimberley S. Samkoe, Kenneth M. Tichauer, Kristian J. Sexton, Jason R. Gunn, Sophie J. Deharvengt, Tayyaba Hasan, Brian W. Pogue
Dartmouth Scholarship
The up-regulation of cell surface receptors has become a central focus in personalized cancer treatment; however, because of the complex nature of contrast agent pharmacokinetics in tumor tissue, methods to quantify receptor binding in vivo remain elusive. Here, we present a dual-tracer optical technique for noninvasive estimation of specific receptor binding in cancer. A multispectral MRI-coupled fluorescence molecular tomography system was used to image the uptake kinetics of two fluorescent tracers injected simultaneously, one tracer targeted to the receptor of interest and the other tracer a nontargeted reference. These dynamic tracer data were then fit to a dual-tracer compartmental model …
Scanning In Situ Spectroscopy Pplatform For Imaging Surgical Breast Tissue Specimens, Venkataramanan Krishnaswamy, Ashley M. Laughney, Wendy A. Wells, Keith D. Paulsen, Brian W. Pogue
Scanning In Situ Spectroscopy Pplatform For Imaging Surgical Breast Tissue Specimens, Venkataramanan Krishnaswamy, Ashley M. Laughney, Wendy A. Wells, Keith D. Paulsen, Brian W. Pogue
Dartmouth Scholarship
A non-contact localized spectroscopic imaging platform has been developed and optimized to scan 1 x 1 cm² square regions of surgically resected breast tissue specimens with ~150-micron resolution. A color corrected, image-space telecentric scanning design maintained a consistent sampling geometry and uniform spot size across the entire imaging field. Theoretical modeling in ZEMAX allowed estimation of the spot size, which is equal at both the center and extreme positions of the field with ~5% variation across the designed waveband, indicating excellent color correction. The spot sizes at the center and an extreme field position were also measured experimentally using the …
Characterizing Accuracy Of Total Hemoglobin Recovery Using Contrast-Detail Analysis In 3d Image-Guided Near Infrared Spectroscopy With The Boundary Element Method, Hamid R. Ghadyani, Subhadra Srinivasan, Brian W. Pogue, Keith D. Paulsen
Characterizing Accuracy Of Total Hemoglobin Recovery Using Contrast-Detail Analysis In 3d Image-Guided Near Infrared Spectroscopy With The Boundary Element Method, Hamid R. Ghadyani, Subhadra Srinivasan, Brian W. Pogue, Keith D. Paulsen
Dartmouth Scholarship
The quantification of total hemoglobin concentration (HbT) obtained from multi-modality image-guided near infrared spectroscopy (IG-NIRS) was characterized using the boundary element method (BEM) for 3D image reconstruction. Multi-modality IG-NIRS systems use a priori information to guide the reconstruction process. While this has been shown to improve resolution, the effect on quantitative accuracy is unclear. Here, through systematic contrast-detail analysis, the fidelity of IG-NIRS in quantifying HbT was examined using 3D simulations. These simulations show that HbT could be recovered for medium sized (20mm in 100mm total diameter) spherical inclusions with an average error of 15%, for the physiologically …
Statistical Hypothesis Testing For Postreconstructed And Postregistered Medical Images, Eugene Demidenko
Statistical Hypothesis Testing For Postreconstructed And Postregistered Medical Images, Eugene Demidenko
Dartmouth Scholarship
Postreconstructed and postregistered medical images are typically treated as the raw data, implicitly assuming that those operations are error free. We question this assumption and explore how the precision of reconstruction and affine registration can be assessed by the image covariance matrix and confidence interval, called the confidence eigenimage, using a statistical model-based approach. Various hypotheses may be tested after image reconstruction and registration using classical statistical hypothesis testing vehicles: Is there a statistically significant difference between images? Does the intensity at a specific location or area of interest belong to the “normal” range? Is there a tumor? Does the …
In Vitro Ovarian Tumor Growth And Treatment Response Dynamics Visualized With Time-Lapse Oct Imaging, Conor L. Evans, Imran Rizvi, Tayyaba Hasan, Johannes F. De Boer
In Vitro Ovarian Tumor Growth And Treatment Response Dynamics Visualized With Time-Lapse Oct Imaging, Conor L. Evans, Imran Rizvi, Tayyaba Hasan, Johannes F. De Boer
Dartmouth Scholarship
In vitro three-dimensional models for metastatic ovarian cancer have been useful for recapitulating the human disease. These spheroidal tumor cultures, however, can grow in excess of 1 mm in diameter, which are difficult to visualize without suitable imaging technology.Optical coherence tomography (OCT) is an ideal live imaging method for non-perturbatively visualizing these complex systems. OCT enabled detailed observations of the model at both nodular and cellular levels, revealing growth dynamics not previously observed. The development of a time-lapse OCT system, capable of automated, multidimensional acquisition, further provided insights into the growth and chemotherapeutic response of ovarian cancer.
Automatic Diagnosis For Prostate Cancer Using Run-Length Matrix Method, Xiaoyan Sun, Shao-Hui Chuang, Jiang Li, Frederic Mckenzie, Nico Karssemeijer (Ed.), Maryellen L. Giger (Ed.)
Automatic Diagnosis For Prostate Cancer Using Run-Length Matrix Method, Xiaoyan Sun, Shao-Hui Chuang, Jiang Li, Frederic Mckenzie, Nico Karssemeijer (Ed.), Maryellen L. Giger (Ed.)
Electrical & Computer Engineering Faculty Publications
Prostate cancer is the most common type of cancer and the second leading cause of cancer death among men in US1. Quantitative assessment of prostate histology provides potential automatic classification of prostate lesions and prediction of response to therapy. Traditionally, prostate cancer diagnosis is made by the analysis of prostate-specific antigen (PSA) levels and histopathological images of biopsy samples under microscopes. In this application, we utilize a texture analysis method based on the run-length matrix for identifying tissue abnormalities in prostate histology. A tissue sample was collected from a radical prostatectomy, H&E fixed, and assessed by a pathologist …
Methodology Development For Three-Dimensional Mr-Guided Near Infrared Spectroscopy Of Breast Tumors, Colin M. Carpenter, Subhadra Srinivasan, Brian W. Pogue, Keith D. Paulsen
Methodology Development For Three-Dimensional Mr-Guided Near Infrared Spectroscopy Of Breast Tumors, Colin M. Carpenter, Subhadra Srinivasan, Brian W. Pogue, Keith D. Paulsen
Dartmouth Scholarship
Combined Magnetic Resonance (MR) and Near Infrared Spectroscopy (NIRS) has been proposed as a unique method to quantify hemodynamics, water content, and cellular size and packing density of breast tumors, as these tissue constituents can be quantified with increased resolution and overlaid on the structural features identified by the MR. However, the choices in how to reconstruct and visualize this information can have a dramatic impact on the feasibility of implementing this modality in the clinic. This is especially true in 3 dimensions, as there is often limited optical sampling of the breast tissue, and methods need to accurately reflect …