Radiology Commons^™

Pseudotumoral Hemicerebellitis In A Young Male Sailor With Complete Recovery After Steroid Therapy, Khizer Masroor Anns, Faheem Ullah Khan, Muhammad Aman, Anwar Ahmad, Kumail Khandwala, Zainab Aslam Saeed Memon, Izaz Ahmad, Muhammad Ismail Safi

Medical College Documents

Pseudotumoral hemicerebellitis is a rare presentation of acute cerebellitis, which involves the inflammation of a single cerebellar hemisphere and most commonly affects children. It mimics a tumor on imaging, hence given the name. In this report, we present a case of pseudotumoral hemicerebellitis in a 30-year-old male who presented to the emergency room (ER) with complaints of vertigo, vomiting, and a headache.

Bacterial Contamination Of Platelet Products, Michael R Jacobs, Bowen Zhou, Aditi Tayal, Robert W Maitta

Faculty, Staff and Student Publications

Transfusion of bacterially contaminated platelets, although rare, is still a major cause of mortality and morbidity despite the introduction of many methods to limit this over the past 20 years. The methods used include improved donor skin disinfection, diversion of the first part of donations, use of apheresis platelet units rather than whole-blood derived pools, primary and secondary testing by culture or rapid test, and use of pathogen reduction. Primary culture has been in use the US since 2004, using culture 24 h after collection of volumes of 4-8 mL from apheresis collections and whole-blood derived pools inoculated into aerobic …

Ai-Enhanced Detection Of Clinically Relevant Structural And Functional Anomalies In Mri: Traversing The Landscape Of Conventional To Explainable Approaches, Pegah Khosravi, Saber Mohammadi, Fatemeh Zahiri, Masoud Khodarahmi, Javad Zahiri

Publications and Research

Anomaly detection in medical imaging, particularly within the realm of magnetic resonance imaging (MRI), stands as a vital area of research with far-reaching implications across various medical fields. This review meticulously examines the integration of artificial intelligence (AI) in anomaly detection for MR images, spotlighting its transformative impact on medical diagnostics. We delve into the forefront of AI applications in MRI, exploring advanced machine learning (ML) and deep learning (DL) methodologies that are pivotal in enhancing the precision of diagnostic processes. The review provides a detailed analysis of preprocessing, feature extraction, classification, and segmentation techniques, alongside a comprehensive evaluation of …

Predicting Radiotherapy Patient Outcomes With Real-Time Clinical Data Using Mathematical Modelling, Alexander P Browning, Thomas D Lewin, Ruth E Baker, Philip K Maini, Eduardo G Moros, Jimmy Caudell, Helen M Byrne, Heiko Enderling

Faculty, Staff and Student Publications

Longitudinal tumour volume data from head-and-neck cancer patients show that tumours of comparable pre-treatment size and stage may respond very differently to the same radiotherapy fractionation protocol. Mathematical models are often proposed to predict treatment outcome in this context, and have the potential to guide clinical decision-making and inform personalised fractionation protocols. Hindering effective use of models in this context is the sparsity of clinical measurements juxtaposed with the model complexity required to produce the full range of possible patient responses. In this work, we present a compartment model of tumour volume and tumour composition, which, despite relative simplicity, is …

Deep Learning-Based Multimodality Classification Of Chronic Mild Traumatic Brain Injury Using Resting-State Functional Mri And Pet Imaging, Faezeh Vedaei, Najmeh Mashhadi, Mahdi Alizadeh, George Zabrecky, Daniel A. Monti, Md, Nancy Wintering, Emily Navarreto, Chloe Hriso, Andrew B. Newberg, Feroze B. Mohamed

Department of Radiology Faculty Papers

Mild traumatic brain injury (mTBI) is a public health concern. The present study aimed to develop an automatic classifier to distinguish between patients with chronic mTBI (n = 83) and healthy controls (HCs) (n = 40). Resting-state functional MRI (rs-fMRI) and positron emission tomography (PET) imaging were acquired from the subjects. We proposed a novel deep-learning-based framework, including an autoencoder (AE), to extract high-level latent and rectified linear unit (ReLU) and sigmoid activation functions. Single and multimodality algorithms integrating multiple rs-fMRI metrics and PET data were developed. We hypothesized that combining different imaging modalities provides complementary information and …

Non-Ketotic Hyperglycemia Unmasks Hemichorea - A Reply, Ezhilkugan Ganessane, Sasikumar Mahalingam, Selva Ganesan

Journal of Community Hospital Internal Medicine Perspectives

No abstract for this article type

Correlation Between Melphalan Chemotherapy With Longitudinal Global Strain Indices Of The Left Ventricle In Multiple Myeloma Patients: A Velocity Vector Imaging (Vvi) Echocardiography Study, Liaosadat Mirsafaee, Mohammad Dehghani Firouzabadi, Sayeh Parkhideh, Hassan Vahidnezhad, Fatemeh Dehghani Firouzabadi, Maryam Arab, David M. Yousem, Mersedeh Karvandi

Jefferson Institute of Molecular Medicine Papers and Presentations

Multiple myeloma (MM) is characterized by the neoplastic proliferation of plasma cells, leading to the production of monoclonal immunoglobulins. High-dose chemotherapy with autologous stem cell transplant has been used in the treatment of patients with MM (1). Melphalan (L-phenylalanine nitrogen mustard) is one of the most effective chemotherapeutic drugs in the treatment of MM (2). The side effects of melphalan include anemia, nausea, vomiting, allergic reactions, oral ulcers, nephrotoxicity, and arrhythmia at high doses (3). The effect of this drug on cardiac mechanics and heart damage is not well established, as previous studies have only focused on the electrocardiographic and …

Quantifying 3d Mr Fingerprinting (3d-Mrf) Reproducibility Across Subjects, Sessions, And Scanners Automatically Using Mni Atlases, Andrew Dupuis, Yong Chen, Jessie E.P. Sun, Chaitra Badve, Dan Ma, Mark A. Griswold, Rasim Boyacioglu

Researchers, Instructors, & Staff Scholarship

Purpose: Quantitative MRI techniques such as MR fingerprinting (MRF) promise more objective and comparable measurements of tissue properties at the point-of-care than weighted imaging. However, few direct cross-modal comparisons of MRF's repeatability and reproducibility versus weighted acquisitions have been performed. This work proposes a novel fully automated pipeline for quantitatively comparing cross-modal imaging performance in vivo via atlas-based sampling. Methods: We acquire whole-brain 3D-MRF, turbo spin echo, and MPRAGE sequences three times each on two scanners across 10 subjects, for a total of 60 multimodal datasets. The proposed automated registration and analysis pipeline uses linear and nonlinear registration to align …

Overcoming Resolution Attenuation During Tilted Cryo-Em Data Collection, Sriram Aiyer, Philip R Baldwin, Shi Min Tan, Zelin Shan, Juntaek Oh, Atousa Mehrani, Marianne E Bowman, Gordon Louie, Dario Oliveira Passos, Selena Đorđević-Marquardt, Mario Mietzsch, Joshua A Hull, Shuichi Hoshika, Benjamin A Barad, Danielle A Grotjahn, Robert Mckenna, Mavis Agbandje-Mckenna, Steven A Benner, Joseph A P Noel, Dong Wang, Yong Zi Tan, Dmitry Lyumkis

Faculty, Staff and Students Publications

Structural biology efforts using cryogenic electron microscopy are frequently stifled by specimens adopting "preferred orientations" on grids, leading to anisotropic map resolution and impeding structure determination. Tilting the specimen stage during data collection is a generalizable solution but has historically led to substantial resolution attenuation. Here, we develop updated data collection and image processing workflows and demonstrate, using multiple specimens, that resolution attenuation is negligible or significantly reduced across tilt angles. Reconstructions with and without the stage tilted as high as 60° are virtually indistinguishable. These strategies allowed the reconstruction to 3 Å resolution of a bacterial RNA polymerase with …

Can Vpac-Targeted Cu-67-Tp3805 Play A Theranostic Role For Prostate Cancer?: A Quest, Mathew L. Thakur

Department of Radiology Faculty Papers

Early and accurate detection of prostate cancer (PCa) together with effective treatment can save lives. Despite the recent advances in its treatment, the mortality trends due to PCa, in the USA, continue to be alarming with annual increase of 3%. In this brief communication, we propose a novel approach to treat PCa, its metastasis and recurrence. This is guided by a large quantity of preliminary data driven by targeting an endogenous genetic product, VPAC, expressed in high density on the cell surface at the onset of genetic mutation that ignites the cancerous transformation. A large body of preclinical and clinical …

Treatment And Diagnosis Of Pulmonary Emboli In Ct, Jacob Gardner

Student Research Poster Presentations 2024

This research project elaborates on the diagnosis and treatment of pulmonary emboli, and how computed tomography can provide a quick and accurate diagnosis. Statistics, symptoms, computed tomography pulmonary angiography protocol, and pulmonary emboli radiographic appearance are also discussed to provide information on how a diagnosis is achieved and which treatment is used. Pulmonary emboli are a life-threatening condition that, if untreated, can potentially be fatal. Pulmonary emboli are the third most frequently occurring cause of cardiovascular death behind a stroke and myocardial infarction. Deaths in the United States from pulmonary emboli are approximately 300,000 deaths per year. In addition, 5-10% …

The Measure Of Efficiency And Effectiveness When Using Artificial Intelligence (Ai) In Radiology, Jordan Watts

Theses, Dissertations and Capstones

Introduction: The use of artificial intelligence in radiology has helped radiologists identify patterns and abnormalities in medical images to diagnose and treat patients. Deep learning and machine learning algorithms have been used to assist physicians in detecting features that are not noticeable to the human eye. The FDA has approved almost 400 AI algorithms for radiology and estimated that the market for AI in medical imaging would grow from $21.48 billion in 2018 to $264.85 billion in 2028.

Purpose of the Study: The purpose of this research was to evaluate the use of artificial intelligence in radiology to determine its …

Different Spectrum Of Space Radiation Induced Cognitive Impairments In Radiation-Naïve And Adapted Rats, Richard A. Britten, Arriyam S. Fesshaye, Alyssa Tidmore, Ella N. Tamgue, Paola A. Alvarado-Arriaga

Center for Integrative Neuroscience and Inflammatory Diseases (CINID) Faculty Publications

NASA's decision to resume manned deep space mission, first to the Moon and then Mars, necessitated a detailed assessment of the potential health effects that astronauts may experience on long-duration missions. Multiple studies suggest that there may be significant space radiation (SR)-induced impairment of neurocognitive processes, including advanced executive functions. However, given the multitude of SR-induced changes in the CNS, it is possible that completely different SR-induced sequelae will be induced in previously exposed individuals. Thus, current risk estimates are likely to be pertinent only for the early stages of a deep space mission, and even then only for astronauts …

Role Of Computed Tomography In Traumatic Brain Injuries, Rebekah Spott

Medical Imaging Senior Posters

This project explains the role of computed tomography (CT) in assessing traumatic brain injuries (TBI). The major components of the research include various intracranial traumas, penetrating vs. non-penetrating TBIs, symptoms, grades of injury, and treatment options. CT is essential in diagnosing a TBI because it can quickly produce hundreds of images of the brain and skull in slices. CT allows radiologists, physicians, and surgeons to plan a course of action for the best possible patient recovery outcome. Images can identify various lesions and fractures as well as their severity. A TBI can present itself as penetrating or non-penetrating, ultimately determining …

Cryptococcus Gattii: Disseminated Disease In An Immunocompetent Patient, Conner Dalton, Jani Smit

South Atlantic Division GME Research Day 2024

No abstract provided.

Hyperthermic Encephalopathy In A Healthy Young Adult, Timothy Kocher, Dhruvkumar Patel

South Atlantic Division GME Research Day 2024

No abstract provided.

A Case Of Neurosarcoidosis And Its Radiographic Findings, Chase Tenewitz, Brantley Grimball, Druv Patel

South Atlantic Division GME Research Day 2024

No abstract provided.

A Case Of Bullet Embolization And Its Management, Emily Clifton, William Clifton, Chase Tenewitz, David Kupshik, Michael Jones

South Atlantic Division GME Research Day 2024

No abstract provided.

Flexible Attenuation Fields: Tomographic Reconstruction From Heterogeneous Datasets, Clifford S. Parker

Theses and Dissertations--Computer Science

Traditional reconstruction methods for X-ray computed tomography (CT) are highly constrained in the variety of input datasets they admit. Many of the imaging settings -- the incident energy, field-of-view, effective resolution -- remain fixed across projection images, and the only real variance is in the detector's position and orientation with respect to the scene. In contrast, methods for 3D reconstruction of natural scenes are extremely flexible to the geometric and photometric properties of the input datasets, readily accepting and benefiting from images captured under varying lighting conditions, with different cameras, and at disparate points in time and space. Extending CT …

Fibromatous Desmoid Tumor Presenting As A Left Supraclavicular Mass In A 21-Year-Old Female, Robson De Macedo Filho, Christopher Hulsey

South Atlantic Division GME Research Day 2024

No abstract provided.