Deep learning-based non-contrast MRI model for nasopharyngeal carcinoma diagnosis: an end-to-end gadolinium-free solution.

ABSTRACT: Nasopharyngeal carcinoma (NPC) diagnosis and routine follow-up for recurrence typically rely on contrast-enhanced MRI. This study introduces a deep learning model for diagnosing NPC using only non-contrast MRI, reducing the need for gadolinium-based contrast agents (GBCA). This approach helps avoid safety concerns related to GBCA deposition, while also shortening scan times and reducing costs. In this study, we propose an innovative deep learning model for NPC diagnosis using only non-contrast MRI, reducing the need for gadolinium-based contrast agents (GBCA). This approach not only mitigates potential safety concerns associated with residual GBCA deposition but also reduces scan time and examination costs. The study consisted of three phases. Firstly, a novel knowledge distilled modality

SUBMITTER: Li Z 

PROVIDER: S-EPMC12748797 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature