Radiology Commons^™

Blunt Cerebrovascular Injury (Bcvi): Universal Cta Neck Screening At Level 2 Trauma Center, Tamine Gogel

Doctor of Nursing Practice Projects

Blunt Cerebrovascular Injury (BCVI) refers to injuries to the vessels supplying blood to the brain, primarily carotid and vertebral arteries, and can result from trauma, resulting in stroke by vessel dissection, thrombus formation, embolization, and hemorrhage. Timely identification is crucial for effective intervention and improved outcomes. This doctoral project proposes the implementation of universal screening using Computed Tomography Angiography (CTA) of the neck during initial workup for blunt force trauma at a Level II ACS-verified trauma center. The primary objective is to mitigate potential delays in diagnosing and treating BCVI, thereby reducing the likelihood of complications. Patients ≥ 15 years …

Applications Of Deep Learning With Detecting Intracranial Aneurysms On Ct Angiograms: A Literature Review, Christian Fang, Emily Wang

Rowan-Virtua Research Day

INTRODUCTION

Deep learning is a method of artificial intelligence involving progressively layered neural networks to extrapolate patterns from data to provide predictions. Moreover, given the arduous nature required for examining CT scans for intracranial aneurysms, discovering ways to expedite this process is beneficial. The use of deep learning to evaluate CT angiograms for intracranial aneurysms has been sparsely studied. This literature review aims to determine the accuracy and reliability of deep learning to analyze CT angiograms in patients suspected to have intracranial aneurysms.

METHODS

A qualitative review of literature using PubMed, SCOPUS, and EMBASE was conducted. Inclusion criteria comprised articles …

Unveiling The Potential: The Role Of Ai-Enhanced Ecg In Cardiovascular Disease Detection, Alisha Vincent

Rowan-Virtua Research Day

Background: The Electrocardiogram (ECG) is a widely utilized, non-invasive, cost-effective cardiac test. Its integration with Artificial Intelligence (AI) has empowered it to become a potent screening tool and a predictor for various cardiovascular diseases, especially in asymptomatic individuals. Objective: This review investigates the utility of AI-powered ECG in early detection of cardiac conditions, focusing on conditions such as low ejection fraction (LEF), atrial fibrillation (AF), aortic valve stenosis (AVS), and cardiac amyloidosis (CA). Methods: A literature review spanning 2018 to 2024 was conducted, analyzing 10 articles - 3 on AF, 3 on AVS, 3 on LEF, and …

Ultrasound Versus Radiography For Evaluating Surgical Necrotizing Enterocolitis, Sayed H. Aftab, Santiago Martinez-Correa, Minh-Huy Huynh, Wondwossen T. Lerebo, Jorge Delgado, Rebecca Denis, Misun Hwang

Rowan-Virtua Research Day

Purpose:

Necrotizing enterocolitis (NEC) is an abdominal inflammatory condition that is common in premature neonates. Although abdominal radiograph (AR) remains the imaging standard for NEC, it may miss up to 50% of early signs of NEC and has been described to have a sensitivity as low as 15.4% for detecting pneumoperitoneum. Abdominal ultrasound (US) is portable, non-invasive, and allows real-time bowel integrity, movement, and perfusion assessment. We aim to evaluate the concordance between US and AR in detecting NEC features and the diagnostic performance of both modalities in detecting pneumoperitoneum.

Methods and materials:

We conducted an IRB-approved retrospective, cross-sectional, single-center …

Promises And Risks Of Applying Ai Medical Imaging To Early Detection Of Cancers, And Regulation For Ai Medical Imaging, Yiyao Zhang

The Journal of Purdue Undergraduate Research

No abstract provided.

The Impact Of Simulated Image Acquisition Time Reduction On Image Quality And Parameters Of Myocardial Perfusion Imaging Using A Dedicated Cardiac Camera, Alireza Khatami

Electronic Thesis and Dissertation Repository

Heart disease is the second leading cause of death in Canada, highlighting the crucial role of early diagnosis in disease management. Myocardial perfusion imaging (MPI), is widely employed for this purpose, involves injecting a radiopharmaceutical into the body, imaging its distribution with a gamma camera, and revealing cardiac blood flow patterns. A significant challenge in MPI is the lengthy 8 to 10 minutes required for stress and rest imaging, potentially causing patient discomfort and compromising image quality due to movement. In a clinical study with 26 patients, post-processed data manipulation simulated a reduction in MPI imaging time. The findings indicated …