FORUMS

(November 21, 2025) Joseph Lo, PhD from Duke presented the latest advances from CVIT, featuring AI benchmark models and virtual readers for lung cancer screening in chest CT. He will highlight AI frameworks that generate synthetic CT data to improve nodule detection/classification, showing how integrated virtual readers can emulate radiologists’ workflows and advance clinical adoption.

(October 31, 2025) Justin Solomon, PhD, from Duke University, discusses a recent NEJM paper (https://www.nejm.org/doi/full/10.1056/NEJMoa2502098) linking radiation from medical imaging to an increased risk of hematologic cancer in children and adolescents. The journal-club–style session will explore the study’s findings, evidence strengths and limitations, and how virtual clinical trials could help assess and reduce imaging-related risks.

(October 17, 2025) Maryellen Giger, PhD from the University of Chicago discusses AI in medical imaging, including radiomic “virtual biopsies”, deep learning across imaging modalities, and the importance of curated, diverse data. She will highlight MIDRC’s role in providing validated, representative datasets and resources for trustworthy AI.

(September 19, 2025) Jessica Sieren, PhD from the University of Iowa presents two experimental lung imaging studies highlighting the role of physiology and technology in quantitative imaging. One examines menstrual cycle effects on lung biomarkers in women using CT and hyperpolarized gas MRI. The other evaluates ultra-high-resolution photon-counting CT with a phantom, showing accurate, dose-efficient ...

(September 9, 2025) Prof. Giorgio De Nunzio and Dr. Luana Conte show that radiomics and AI, combined with standardized imaging and federated architectures, can refine preoperative breast cancer diagnosis, supporting precision oncology and multicenter collaborations.