Postgraduate Fellow Zhen Li received a Robert F. Wagner All-Conference Best Student Paper Finalist Award at SPIE Medical Imaging 2025. She presented her paper entitled “Contrast-enhanced image-guided learning for nasopharyngeal carcinoma diagnosis using non-contrast MRI” in the Computer-Aided Diagnosis track on the 17th February.

Abstract:

Contrast-enhanced T1-weighted magnetic resonance imaging (MRI) with gadolinium-based contrast agents (GBCAs) offers superior discrimination between nasopharyngeal carcinoma (NPC) tissue and non-malignant tissue, making it crucial for NPC diagnosis. However, due to concerns about gadolinium accumulation, there is a global interest in developing contrast agent-free alternatives to replace GBCA-enhanced MRI. In this study, we developed an NPC diagnosis model using non-contrast images under the guidance of contrast-enhanced T1-weighted images. Our model was trained on a dataset of 694 cases and validated on 160 cases, with an equal split of 50% NPC and 50% non-NPC for both training and validation. It was then tested on an additional dataset comprising 263 cases (43% NPC and 57% non-NPC). The proposed model demonstrated high accuracy in detecting NPC using only non-contrast images, achieving performance comparable to predictions based on both contrast and non-contrast images.

The Robert F. Wagner All Conference Best Student Paper Award is an acknowledgement of his many significant contributions to the Medical Imaging meeting and his advances in medical imaging. The award is open to all SPIE Medical Imaging student presentaters.

Zhen Li, Yuxuan Shi, Xueli Liu, Li Wang, Jonghye Woo, Jinsong Ouyang, Georges El Fakhri, Hongmeng Yu, Xiaofeng Liu. Contrast-enhanced image-guided learning for nasopharyngeal carcinoma diagnosis using non-contrast MRI. SPIE Medical Imaging 2025: Computer-Aided Diagnosis.