If you have any questions about uploading your poster or signing the agreement, contact the Research Medical Library.
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A Comparison Between Single-Isocenter and Multi-Isocenter Plan Quality for Multi-Target Abdominal Radiation Treatments
Victoria Vira, Karen Bui, Caitlin Tran, Nhi Pham, Temiloluwa Oluwanifemi Esho, and Rachael M. Martin-Paulpeter
Comparison of single- versus multi-isocenter SBRT VMAT plans for abdominal oligometastases showed both are clinically acceptable. Multi-isocenter offered slight improvements but greater complexity.
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Artificial Intelligence in MRI: A dual Approach to Quality Enhancement and Time Reduction
Angelica Maria Baquedano, Marissa Elizabeth Cardoza, Jonathon H. Dajao, Maricela Garcia, Talore Lanice Jones, and Saleha Zafar
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Artificial Intelligence in Radiology: A Comparative Study of Accuracy and Efficiency Across X-ray, CT, and Nuclear Medicine
Courtney J. Mello, Sophia D. Galvan, Britney R. Williams, Tuyen T. Thai, Phuong P. Mor, and Saleha Zafar
Artificial intelligence (AI) is increasingly used in radiology to improve diagnostic accuracy and workflow efficiency; however, there is limited standardized research comparing its performance across imaging modalities. This study aimed to evaluate the accuracy and efficiency of AI in X-ray, computed tomography (CT), and nuclear medicine. A systematic review was conducted following PRISMA guidelines, analyzing peer-reviewed studies published between 2015 and 2025. Data were extracted on key performance metrics, including sensitivity, specificity, interpretation time, and error rates, to enable cross-modality comparison. Results demonstrated that AI achieved high diagnostic accuracy in X-ray imaging, with average sensitivity and specificity near 91% and 90%, respectively, though it still had limitations in detecting subtle findings. In CT imaging, AI showed comparable specificity and slightly lower sensitivity while improving the detection of volumetric data and lesions. Nuclear medicine applications primarily demonstrated qualitative benefits, including improved image reconstruction and noise reduction, but lacked standardized quantitative metrics for direct comparison. Across modalities, AI consistently reduced interpretation time and improved workflow efficiency, although variability in study design limited full comparability. Overall, AI serves as an effective clinical decision-support tool that enhances radiologist performance rather than replacing it, highlighting the need for standardized evaluation frameworks and expanded research in nuclear medicine.
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Assessment of Diagnostic Image Quality in Mobile vs Conventional Departmental Head CT scans
Anjelica De Los Reyes, Austin Messer, Brianna Fowler, Tristan Flores, Lindzee Lemonn, and Saleha Zafar
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Comparative Evaluation of Conventional CT and Dual-Energy CT in the Detection and Characterization of Intracerebral Stroke
Aidan Rosado, Shakiba Jalili, Hap Tain, and Saleha Zafar
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Exploring the Drivers of Excessive CT Ordering in the Emergency Department. A Mixed Methods Study of Provider Decision Making, Workflow Pressures, and System-Level Factors Contributing to Unnecessary Imaging
Anabel Battenfield, Sandra Escobar, Enrique Salazar, and Saleha Zafar
CT overutilization emergency department
