Bioimaging and Biomedical Optics Commons^™

Fill The Void - An Introductory Guide For Learning Medical Imaging, Reid Faith, Peter Gahan, Adam Trusty, Aleksandr Zyskin, Chukwuka Ukekwe, Denise Nchinda, Amanda K. Burbage, Alberto E. Musto

EVMS School of Health Professions Faculty Publications

No standardized, comprehensive approach for radiological image interpretation exists among medical schools in the United States of America. In order to rectify this, we outline a model aimed to help improve how medical imaging can be taught in medical schools. The VOID (Visualization, Orientation/Observation, Identification, Description) guide is a proposed universal, stepwise approach to medical image identification, interpretation, and communication. This structured guideline is aimed at building a foundation for students in early medical education. The VOID was applied to CT (Computed Tomography), MRI (Magnetic Resonance Imaging), and x-ray modalities as integrated sessions for medical students during human anatomy laboratory. …

Towards The Performance Characterization Of A Robotic Multimodal Diagnostic Imaging System, George Papaioannou, Christos Mitrogiannis, Mark Schweitzer, Nikolaos Michailidis, Maria Pappa, Pegah Khosravi, Apostolos Karantanas, Sean Starling, Christian Ruberg

Publications and Research

Characterizing imaging performance requires a multidisciplinary approach that evaluates various interconnected parameters, including dosage optimization and dynamic accuracy. Radiation dose and dynamic accuracy are challenged by patient motion that results in poor image quality. These challenges are more prevalent in the brain/cardiac pediatric patient imaging, as they relate to excess radiation dose that may be associated with various complications. Scanning vulnerable pediatric patients ought to eliminate anesthesia due to critical risks associated in some cases with intracranial hemorrhages, brain strokes, and congenital heart disease. Some pediatric imaging, however, requires prolonged scanning under anesthesia. It can often be a laborious, suboptimal …

Synthesis, Radiolabeling And Evaluation Of A Suite Of Tracers With 44Sc For Detecting Extracellular Dna, Zhiyao Li

McKelvey School of Engineering Graduate Student Theses & Dissertations

Neutrophil extracellular traps involve the rapid translocation of DNA to the outside of the cell under certain stimuli. This structure forms a fibrous network that is able to limit the spread of pathogens and to kill microorganisms. It has also been shown to be present in various pathological processes such as inflammation, autoimmune diseases, and cancer metastasis. Currently, the formation process of NETs in vivo is being extensively studied. However noninvasive detection and quantitation has yet to be achieved. A class of PET tracers are described here that consists of a DNA dye as the backbone that is labeled with …

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 …

Verification Of Proton Range Predictions In Proton Treatment Planning Using X-Ray Ct Or Proton Ct Imaging, Nicholas S. Yee

Graduate Research Theses & Dissertations

The objective of this paper is to compare the range errors for two treatment plans; one using x-ray CT and the other using proton CT for calculating dose distributions in an animal tissue phantom. We shot 150 MeV proton beam through a meat phantom to a film stack to measure the exponential drop of dose at the Bragg peak until zero dose remained. Plotting the depth dose curves and performing gamma analyses are two ways to quantify the proton range errors when comparing them to depth dose curves from film measurements in the phantom. The depth dose curves give us …

Machine Learning And Scalable Informatics Methods To Predict Disease Status From Multimodal Biomedical Data, Hossein Mohammadian Foroushani

McKelvey School of Engineering Graduate Student Theses & Dissertations

Biological understanding of complex diseases such as stroke and obesity is critical for the advancement of medicine. Further knowledge discovery can provide effective biomarkers to improve disease diagnosis and prognosis, identify driver mutations, predict individual genetic susceptibility for early prevention and effective disease management, and facilitate development of personalized drugs. Stroke is the second leading cause of death and long-term disability in the world. Thus, stroke management is a time-sensitive emergency. The initial hours after stroke onset map the trajectory of subsequent neurologic complications. Cerebral edema develops hours to days after acute ischemic stroke and may result in midline shift …

Evaluation And Clinical Implementation Of A Dual-Energy Ct Stopping-Power Ratio Mapping Technique For Proton-Therapy Treatment Planning, Maria Jose Medrano Matamoros

McKelvey School of Engineering Graduate Student Theses & Dissertations

Proton radiotherapy has the potential to treat tumors with better conformal dose distribution than competing modalities when the rapid dose falloff at the end of the proton-beam range is correctly aligned to the edge of the clinical target volume (CTV). However, its clinical potential is dependent on the accurate localization of the Bragg-peak position from predicted stopping-power ratio maps. The method that is most commonly used in today’s clinical practice for predicting stopping-power ratio (SPR) consists of a stoichiometric calibrationtechnique based on single-energy CT (SECT) for direct estimation of patient-specific SPR distribution from vendor-reconstructed Hounsfield Unit (HU) images. Unfortunately, this …

Advancing The Portability, Field Of View, And Spatiotemporal Resolution Of Multi-Parametric Photoacoustic Microscopy, Fenghe Zhong

McKelvey School of Engineering Graduate Student Theses & Dissertations

Capable of structural, functional, molecular, and metabolic imaging with high spatial resolution in vivo, photoacoustic microscopy (PAM) is an emerging tool in biomedical research. Further, recent advances in multi-parametric acquisition and analysis make PAM uniquely capable of simultaneously mapping the total concentration of hemoglobin (CHb), oxygen saturation of hemoglobin (sO2), and blood flow speed. However, there are multiple major limitations, including, the large footprint, low imaging speed, limited imaging contrast, and insufficient axial resolution, which impedance its applications in basic and translational research. In this dissertation, I presented potential solutions to overcome the limitations above.In the first part of this …

Using Deep Learning To Analyze Materials In Medical Images, Carson Molder

Computer Science and Computer Engineering Undergraduate Honors Theses

Modern deep learning architectures have become increasingly popular in medicine, especially for analyzing medical images. In some medical applications, deep learning image analysis models have been more accurate at predicting medical conditions than experts. Deep learning has also been effective for material analysis on photographs. We aim to leverage deep learning to perform material analysis on medical images. Because material datasets for medicine are scarce, we first introduce a texture dataset generation algorithm that automatically samples desired textures from annotated or unannotated medical images. Second, we use a novel Siamese neural network called D-CNN to predict patch similarity and build …

Focused Ultrasound-Mediated Drug Delivery To The Brainstem, Dezhuang Ye

McKelvey School of Engineering Graduate Student Theses & Dissertations

Brainstem gliomas are tumors that occur in the brainstem, the brain region that connects the brain to the spinal cord and controls vital body functions. The critical anatomic location of the brainstem precludes surgical intervention and limits the use of invasive therapeutic techniques. Moreover, the frequently intact blood-brain barrier (BBB) of most brainstem gliomas prevents therapeutic agents from reaching the diseased site. The currently available techniques for brain drug delivery are either invasive (e.g., convection-enhanced delivery) or lack targeting to the diseased site (e.g., intranasal brain drug delivery). Novel techniques that can noninvasively overcome the BBB are critically needed for …

Multi-Dimensional Extension Of The Alternating Minimization Algorithm In X-Ray Computed Tomography, Jingwei Lu

McKelvey School of Engineering Graduate Student Theses & Dissertations

X-ray computed tomography (CT) is an important and effective tool in medical and industrial

imaging applications. The state-of-the-art methods to reconstruct CT images have had

great development but also face challenges. This dissertation derives novel algorithms to

reduce bias and metal artifacts in a wide variety of imaging modalities and increase performance

in low-dose scenarios.

The most widely available CT systems still use the single-energy CT (SECT), which is

good at showing the anatomic structure of the patient body. However, in SECT image

reconstruction, energy-related information is lost. In applications like radiation treatment

planning and dose prediction, accurate energy-related information …

Multi-Dimensional Extension Of The Alternating Minimization Algorithm In X-Ray Computed Tomography, Jingwei Lu

McKelvey School of Engineering Graduate Student Theses & Dissertations

X-ray computed tomography (CT) is an important and effective tool in medical and industrial imaging applications. The state-of-the-art methods to reconstruct CT images have had great development but also face challenges. This dissertation derives novel algorithms to reduce bias and metal artifacts in a wide variety of imaging modalities and increase performance in low-dose scenarios. The most widely available CT systems still use the single-energy CT (SECT), which is good at showing the anatomic structure of the patient body. However, in SECT image reconstruction, energy-related information is lost. In applications like radiation treatment planning and dose prediction, accurate energy-related information …

Calibrated Short Tr Recovery Mri For Rapid Measurement Of Brain-Blood Partition Coefficient And Correction Of Quantitative Cerebral Blood Flow, Scott William Thalman

Theses and Dissertations--Biomedical Engineering

The high prevalence and mortality of cerebrovascular disease has led to the development of several methods to measure cerebral blood flow (CBF) in vivo. One of these, arterial spin labeling (ASL), is a quantitative magnetic resonance imaging (MRI) technique with the advantage that it is completely non-invasive. The quantification of CBF using ASL requires correction for a tissue specific parameter called the brain-blood partition coefficient (BBPC). Despite regional and inter-subject variability in BBPC, the current recommended implementation of ASL uses a constant assumed value of 0.9 mL/g for all regions of the brain, all subjects, and even all species.

The …

Renal Granulomatosis Post Intravesical Bacillus Calmette-Guerin Therapy For Non-Muscle-Invasive Bladder Cancer, Karen Tran-Harding, Rashmi T. Nair, Halemane S. Ganesh

Radiology Faculty Publications

Intravesical Bacillus Calmette–Guerin (BCG) immunotherapy is a proven, effective treatment for intermediate- and high-risk non-muscle-invasive bladder cancer. Minor side effects are common and expected but systemic effects can occur in < 5% of treated patients. We present a rare case of a 49-year-old male that presented with fever and chills after 3 weeks of intravesical BCG therapy post transurethral resection of bladder tumor. New renal lesions were present on contrast-enhanced computed tomography scan which was histologically proven to be necrotizing renal granulomatosis.

Chelator-Free Radiolabeling Of Serrs Nanoparticles For Whole-Body Pet And Intraoperative Raman Imaging, Matthew A. Wall, Travis Shaffer, Stefan Harmsen, Darjus-Felix Tschaharganeh, Chun-Hao Huang, Scott W. Lowe, Charles Michael Drain, Moritz F. Kircher

Publications and Research

A single contrast agent that offers whole-body non-invasive imaging along with the superior sensitivity and spatial resolution of surface-enhanced resonance Raman scattering (SERRS) imaging would allow both pre-operative mapping and intraoperative imaging and thus be highly desirable. We hypothesized that labeling our recently reported ultrabright SERRS nanoparticles with a suitable radiotracer would enable pre-operative identification of regions of interest with whole body imaging that can be rapidly corroborated with a Raman imaging device or handheld Raman scanner in order to provide high precision guidance during surgical procedures. Here we present a straightforward new method that produces radiolabeled SERRS nanoparticles for …

Validation, Optimization, And Image Processing Of Spiral Cine Dense Magnetic Resonance Imaging For The Quantification Of Left And Right Ventricular Mechanics, Gregory J. Wehner

Theses and Dissertations--Biomedical Engineering

Recent evidence suggests that cardiac mechanics (e.g. cardiac strains) are better measures of heart function compared to common clinical metrics like ejection fraction. However, commonly-used parameters of cardiac mechanics remain limited to just a few measurements averaged over the whole left ventricle. We hypothesized that recent advances in cardiac magnetic resonance imaging (MRI) could be extended to provide measures of cardiac mechanics throughout the left and right ventricles (LV and RV, respectively).

Displacement Encoding with Stimulated Echoes (DENSE) is a cardiac MRI technique that has been validated for measuring LV mechanics at a magnetic field strength of 1.5 T but …

Diffuse Optical Measurements Of Head And Neck Tumor Hemodynamics For Early Prediction Of Chemoradiation Therapy Outcomes, Lixin Dong, Mahesh Kudrimoti, Daniel Irwin, Li Chen, Sameera Kumar, Yu Shang, Chong Huang, Ellis L. Johnson, Scott D. Stevens, Brent J. Shelton, Guoqiang Yu

Biomedical Engineering Faculty Publications

This study used a hybrid near-infrared diffuse optical instrument to monitor tumor hemodynamic responses to chemoradiation therapy for early prediction of treatment outcomes in patients with head and neck cancer. Forty-seven patients were measured once per week to evaluate the hemodynamic status of clinically involved cervical lymph nodes as surrogates for the primary tumor response. Patients were classified into two groups: complete response (CR) (n = 29) and incomplete response (IR) (n = 18). Tumor hemodynamic responses were found to be associated with clinical outcomes (CR/IR), wherein the associations differed depending on human papillomavirus (HPV-16) status. In HPV-16 …

Portable, Parallel 9-Wavelength Near-Infrared Spectral Tomography (Nirst) System For Efficient Characterization Of Breast Cancer Within The Clinical Oncology Infusion Suite, Yan Zhao, Brian W. Pogue, Steffen J. Haider, Jiang Gui, Roberta Diflorio-Alexander, Keith Paulsen, Shudong Jiang

Dartmouth Scholarship

A portable near-infrared spectral tomography (NIRST) system was developed with simultaneous frequency domain (FD) and continuous-wave (CW) optical measurements for efficient characterization of breast cancer in a clinical oncology setting. Simultaneous FD and CW recordings were implemented to speed up acquisition to 3 minutes for all 9 wavelengths, spanning a range from 661nm to 1064nm. An adjustable interface was designed to fit various breast sizes and shapes. Spatial images of oxy- and deoxy-hemoglobin, water, lipid, and scattering components were reconstructed using a 2D FEM approach. The system was tested on a group of 10 normal subjects, who were examined bilaterally …

The Connectivity Domain: Analyzing Resting State Fmri Data Using Feature-Based Data-Driven And Model-Based Methods, Armin Iraji, Vince D. Calhoun, Natalie M. Wiseman, Esmaeil Davoodi-Bojd, Mohammad R. N. Avanaki, Zhifeng Kou

Biomedical Engineering Faculty Research Publications

Spontaneous fluctuations of resting state functional MRI (rsfMRI) have been widely used to understand the macro-connectome of the human brain. However, these fluctuations are not synchronized among subjects, which leads to limitations and makes utilization of first-level model-based methods challenging. Considering this limitation of rsfMRI data in the time domain, we propose to transfer the spatiotemporal information of the rsfMRI data to another domain, the connectivity domain, in which each value represents the same effect across subjects. Using a set of seed networks and a connectivity index to calculate the functional connectivity for each seed network, we transform data into …

Feasibility Of Using Raman-Based Techniques For Breast Cancer Detection, Sara Mollamohammada

Department of Civil and Environmental Engineering: Dissertations, Theses, and Student Research

Breast cancer is one of the common types of cancer among women all over the world. Early diagnosis is an effective way that improve the treatment process and gives the patients a better chance of survival. Many of the patients infected by breast cancer choose breast conservation surgery (BCS). However, some of those will be subjected to mastectomy, and many will have tumor recurrence as there is no precise technique to show the tumor margins. Raman-based methods are powerful techniques with potential to rapidly differentiate normal from tumor tissues and provides a solution to detect tumor margin. This is because …

Calibration And Optimization Of 3d Digital Breast Tomosynthesis Guided Near Infrared Spectral Tomography, Kelly E. Michaelsen, Venkataramanan Krishnaswamy, Linxi Shi, Srinivasan Vedantham, Steven Poplack, Andrew Karellas, Brian Pogue, Keith Paulsen

Dartmouth Scholarship

Calibration of a three-dimensional multimodal digital breast tomosynthesis (DBT) x-ray and non-fiber based near infrared spectral tomography (NIRST) system is challenging but essential for clinical studies. Phantom imaging results yielded linear contrast recovery of total hemoglobin (HbT) concentration for cylindrical inclusions of 15 mm, 10 mm and 7 mm with a 3.5% decrease in the HbT estimate for each 1 cm increase in inclusion depth. A clinical exam of a patient's breast containing both benign and malignant lesions was successfully imaged, with greater HbT was found in the malignancy relative to the benign abnormality and fibroglandular regions (11 μM vs. …

Characterization Of Low Density Intracranial Lesions Using Dual-Energy Computed To Mography, Jessica L. Nute

Dissertations and Theses (Open Access)

Calcific and hemorrhagic foci of susceptibility are frequently encountered on routine brain MR studies. Both etiologies cause variations in local magnetic field strength, leading to dark regions on the MR images that cannot be classified. Single-energy CT (SECT) can be used to identify lesions with attenuation over 100 HU as calcific, however lesions with lower attenuation cannot be reliably identified. While calcific lesions are unlikely to cause harm, hemorrhagic lesions carry a risk of subsequent intracranial bleeding; as such, identification of hemorrhage is vital in preventing the inappropriate use of anticoagulant medications in patients with hemorrhagic lesions.

Given there currently …

Computer Aided Detection Of Oral Lesions On Ct Images, Shaikat Mahmood Galib

Masters Theses

"Oral lesions are important findings on computed tomography images. They are difficult to detect on CT images because of low contrast, arbitrary orientation of objects, complicated topology and lack of clear lines indicating lesions. In this thesis, a fully automatic method to detect oral lesions from dental CT images is proposed to identify (1) Closed boundary lesions and (2) Bone deformation lesions. Two algorithms were developed to recognize these two types of lesions, which cover most of the lesion types that can be found on CT images. The results were validated using a dataset of 52 patients. Using non training …

Computer Aided Diagnosis Of Oral Cancer: Using Time-Step Ct Images, Jonathan T. Scott

Masters Theses

"In medical imaging it is a very common practice to use a technique known as Time-Step imaging in patients who might develop cancer. Time-Step imaging it a very powerful technique, however it can lead to unmanageable amounts of image data. Previously the only way to search all of this data was to manually look through all of the files. This had to be done by trained professionals who knew what to look for within the images and make a judgment about the patient based on the images. This paper discusses the development of an algorithm to have a computer search …

Sensitivity Of Mri-Guided Near-Infrared Spectroscopy Clinical Breast Exam Data And Its Impact On Diagnostic Performance, Michael A. Mastanduno, Junqing Xu, Fadi El-Ghussein, Shudong Jiang, Hong Yin, Yan Zhao, Kelly E. Michaelson, Ke Wang, Fang Ren, Brian W. Pogue, Keith D. Paulsen

Dartmouth Scholarship

In this study, data from breast MRI-guided near infrared spectroscopy (NIRS) exams delivered to 44 patients scheduled for surgical resection (ending in 16 benign and 28 malignant diagnoses) were analyzed using a spatial sensitivity metric to quantify the adequacy of the optical measurements for interrogating the tumor region of interest, as derived from the concurrent MRI scan. Along with positional sensitivity, the incorporation of spectral priors and the selection of an appropriate regularization parameter in the image reconstruction were considered, and found to influence the diagnostic accuracy of the recovered images. Once optimized, the MRI/NIRS data was able to differentiate …

Utilizing Fast Spin Echo Mri To Reduce Image Artifacts And Improve Implant/Tissue Interface Detection In Refractory Parkinson’S Patients With Deep Brain Stimulators, Subhendra N. Sarkar, Pooja R. Sarkar, Efstathios Papavassiliou, Rafael Rojas

Publications and Research

Introduction. In medically refractory Parkinson’s disease (PD) deep-brain stimulation (DBS) is an effective therapeutic tool. Postimplantation MRI is important in assessing tissue damage and DBS lead placement accuracy. We wanted to identify which MRI sequence can detectDBS leads with smallest artifactual signal void, allowing better tissue/electrode edge conspicuity.

Methods. Using an IRB approved protocol 8 advanced PDpatientswere imagedwithinMRconditional safety guidelines at lowRF power (SAR ≤ 0.1 W/kg) in coronal plane at 1.5T by various sequences.The image slices were subjectively evaluated for diagnostic quality and the lead contact diameters were compared to identify a sequence least affected by metallic leads.

Results …

Cervical Cancer Histology Image Feature Extraction And Classification, Peng Guo

Masters Theses

"Cervical cancer, the second most common cancer affecting women worldwide and the most common in developing countries can be cured if detected early and treated. Expert pathologists routinely visually examine histology slides for cervix tissue abnormality assessment. In previous research, an automated, localized, fusion-based approach was investigated for classifying squamous epithelium into Normal, CIN1, CIN2, and CIN3 grades of cervical intraepithelial neoplasia (CIN) based on image analysis of 62 digitized histology images obtained through the National Library of Medicine. In this research, CIN grade assessments from two pathologists are analyzed and are used to facilitate atypical cell concentration feature development …

A Nonrigid Registration Method For Correcting Brain Deformation Induced By Tumor Resection, Yixun Liu, Chengjun Yao, Fotis Drakopoulos, Jinsong Wu, Liangfu Zhou, Nikos Chrisochoides

Computer Science Faculty Publications

Purpose: This paper presents a nonrigid registration method to align preoperative MRI with intraoperative MRI to compensate for brain deformation during tumor resection. This method extends traditional point-based nonrigid registration in two aspects: (1) allow the input data to be incomplete and (2) simulate the underlying deformation with a heterogeneous biomechanical model.

Methods: The method formulates the registration as a three-variable (point correspondence, deformation field, and resection region) functional minimization problem, in which point correspondence is represented by a fuzzy assign matrix; Deformation field is represented by a piecewise linear function regularized by the strain energy of a heterogeneous biomechanical …

Towards Omni-Tomography -- Grand Fusion Of Multiple Modalities For Simultaneous Interior Tomography, Ge Wang, Jie Zhang, Hao Gao, Victor Weir, Hengyong Yu, Wenxiang Cong, Xiaochen Xu, Haiou Shen, James Bennett, Mark Furth, Yue Wang, Michael Vannier

Radiology Faculty Publications

We recently elevated interior tomography from its origin in computed tomography (CT) to a general tomographic principle, and proved its validity for other tomographic modalities including SPECT, MRI, and others. Here we propose "omni-tomography", a novel concept for the grand fusion of multiple tomographic modalities for simultaneous data acquisition in a region of interest (ROI). Omni-tomography can be instrumental when physiological processes under investigation are multi-dimensional, multi-scale, multi-temporal and multi-parametric. Both preclinical and clinical studies now depend on in vivo tomography, often requiring separate evaluations by different imaging modalities. Over the past decade, two approaches have been used for multimodality …

A Review Of Autoimmune Diseases Associated With Cancer, Patricia Tai, Edward Yu, Kurian Joseph, Thomas Miale

Oncology Publications

The focus of this review is on the relationships between autoimmune diseases and cancer from two closely related perspectives: 1.Those autoimmune diseases which are often associated with malignancies. 2.Those prevalent cancers which may increase the risks of developing autoimmune disorders. The review concludes with a brief discussion of some selected innovative approaches to cancer immunotherapy.