As a medical physicist, Samuel Brady, PhD's, primary experience lies in developing and maintaining protocols for imaging efficacy and safety. His particular interest lies in dose-minimization for CT imaging techniques. This is a particularly important concept in pediatric radiology, where tissues are still developing and are thus especially susceptible to radiation damage.
BS: Physics, Utah Valley University, Orem, UT.
MS: Medical Physics, Duke University, Durham, NC.
PhD: Medical Physics, Duke University, Durham, NC.
Radiology
Radiology
Impact of upgrading from a 25-cm to a 30-cm z-axis field of view digital PET/CT in a pediatric hospital. Pediatric Radiology: roentgenology, nuclear medicine, ultrasonics, CT, MRI. 2024; 54:1896-1905.
Deep Learning Models for Abdominal CT Organ Segmentation in Children: Development and Validation in Internal and Heterogeneous Public Datasets. American Journal of Roentgenology. 2024; 223:e2430931.
An adult and pediatric size-based contrast administration reduction phantom study for single and dual-energy CT through preservation of contrast-to-noise ratio. Journal of applied clinical medical physics / American College of Medical Physics. 2024; 25:e14340.
Real‐World Accuracy of a Continuous Glucose Monitoring System after Radiologic Exposure. Pediatric Diabetes. 2024; 2024.
Reduced count pediatric whole-body 18F-FDG PET imaging reconstruction with a Bayesian penalized likelihood algorithm. Pediatric Radiology: roentgenology, nuclear medicine, ultrasonics, CT, MRI. 2024; 54:170-180.
Biologic Effects of Ionizing Radiation on Children. Nelson Textbook of Pediatrics: Volume 1-2. 2024.
Implementation of AI image reconstruction in CT-how is it validated and what dose reductions can be achieved. British Journal of Radiology. 2023; 96:20220915.
Computed tomography-based measurements of normative liver and spleen volumes in children. Pediatric Radiology: roentgenology, nuclear medicine, ultrasonics, CT, MRI. 2023; 53:378-386.
Simulated Reduced-Count Whole-Body FDG PET: Evaluation in Children and Young Adults Imaged on a Digital PET Scanner. American Journal of Roentgenology. 2022; 219:952-961.
Current and emerging artificial intelligence applications for pediatric abdominal imaging. Pediatric Radiology: roentgenology, nuclear medicine, ultrasonics, CT, MRI. 2022; 52:2139-2148.