Identifying sinus invasion in meningioma patients before surgery with deep learning

Qi Qiu; Kai Sun; Jing Zhang; Panpan Liu; Liang Wang; Junting Zhang; Junlin Zhou; Zhenyu Liu; Jie Tian

doi:10.1117/12.2611054

4 April 2022 Identifying sinus invasion in meningioma patients before surgery with deep learning

Qi Qiu, Kai Sun, Jing Zhang, Panpan Liu, Liang Wang, Junting Zhang, Junlin Zhou, Zhenyu Liu, Jie Tian

Proceedings Volume 12033, Medical Imaging 2022: Computer-Aided Diagnosis; 120332B (2022) https://doi.org/10.1117/12.2611054
Event: SPIE Medical Imaging, 2022, San Diego, California, United States

Conference Poster

Abstract

Meningioma is the most common intracranial non-malignant tumor but is usually closely associated with the major venous sinuses. It has been recognized by neurosurgeons that meningioma should be treated with different surgical options depending on the status of sinus invasion. Therefore, it is necessary to accurately identify the venous sinus invasion status of meningioma patients before surgery; however, appropriate techniques are still lacking. Our study aimed to construct a deep learning model for accurate determination of sinus invasion before surgery. In this study, we collected multi-modal imaging data and clinical information for a total of 1048 meningioma patients from two hospitals. ResNet-50 with a dual attention mechanism was used on the preprocessed T1c and T2WI data respectively, and the final model was generated by combining the two unimodal models. The classification performance was evaluated by the area under receiver operating characteristic (ROC) curve (AUC). The results implied that the multimodal fusion classification model showed good performance in predicting meningioma sinus invasion. Further analysis on the patients with different WHO gradings indicated that our model has the best classification ability under WHO grading 1 in an independent validation cohort (0.84 AUC). This study shows that deep learning is a reliable method for predicting sinus invasion in patients with meningioma before surgery.

Conference Presentation

Citation Download Citation

Qi Qiu, Kai Sun, Jing Zhang, Panpan Liu, Liang Wang, Junting Zhang, Junlin Zhou, Zhenyu Liu, and Jie Tian "Identifying sinus invasion in meningioma patients before surgery with deep learning", Proc. SPIE 12033, Medical Imaging 2022: Computer-Aided Diagnosis, 120332B (4 April 2022); https://doi.org/10.1117/12.2611054

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available