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Abstract #4938

A Combined Radiomics and Anatomical Features Model Enhances MRI-Based Recognition of Symptomatic Nerves in Primary Trigeminal Neuralgia

hongjian Li1,2, Shaojie Li3, Yuxin Yang4, Shipei He4, Xiaoxue Xu5, and hanfeng Yang5
1College of Medical Imaging, North Sichuan Medical College, Nanchong, China, 2radiology department, Affiliated Hospital of North Sichuan Medical College, Nanchong, China, 3The Second Affiliated Hospital of Fujian Medical University Quanzhou, Fujian, China, 4United Imaging Research Institute of Intelligent Imaging, Beijing, China, 5Affiliated Hospital of North Sichuan Medical College, Nanchong, China

Synopsis

Keywords: Peripheral Nerves, Radiomics

Motivation: This study addresses radiologists' limited accuracy in diagnosing primary trigeminal neuralgia (PTN) and explores its pathology through radiomics.

Goal(s): To create a PTN diagnostic model combining radiomic and clinical features, demonstrating that neurovascular compression (NVC) isn’t the primary cause of PTN.

Approach: Data from 279 trigeminal nerves in 140 PTN patients were retrospectively analyzed. Regions of interest (ROI) in the trigeminal cisternal segment and Meckel cavity (MC) provided 2632 radiomics features; 13 clinical features were included. Lasso regression and other methods were used.

Results: The model with two ROIs and clinical features achieved an AUC of 0.91/0.90, surpassing radiologists in identifying symptomatic nerves.

Impact: This study has greatly improved the accuracy of radiologists in diagnosing the disease, which is conducive to the early detection and treatment of the disease; It also provides the basis for the study of the pathophysiological mechanism of PTN.

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