Deep learning-based integration of histology, radiology, and genomics for improved survival prediction in glioma patients

Luoting Zhuang; Jana Lipkova; Richard Chen; Faisal Mahmood

doi:10.1117/12.2626318

4 April 2022 Deep learning-based integration of histology, radiology, and genomics for improved survival prediction in glioma patients

Luoting Zhuang, Jana Lipkova, Richard Chen, Faisal Mahmood

Author Affiliations +

Proceedings Volume 12039, Medical Imaging 2022: Digital and Computational Pathology; 120390Z (2022) https://doi.org/10.1117/12.2626318
Event: SPIE Medical Imaging, 2022, San Diego, California, United States

Abstract

Management of aggressive malignancies, such as glioma, is complicated by a lack of predictive biomarkers that could reliably stratify patients based on treatment outcome. The complex mechanisms driving glioma recurrence and treatment resistance cannot be fully understood without the integration of multiscale factors such as cellular morphology, tissue microenvironment, and macroscopic features of the tumor and the host tissue. We present a weakly-supervised, interpretable, multimodal deep learning-based model fusing histology, radiology, and genomics features for glioma survival predictions. The proposed framework demonstrates the feasibility of multimodal integration for improved survival prediction in glioma patients.

Conference Presentation

Citation Download Citation

Luoting Zhuang, Jana Lipkova, Richard Chen, and Faisal Mahmood "Deep learning-based integration of histology, radiology, and genomics for improved survival prediction in glioma patients", Proc. SPIE 12039, Medical Imaging 2022: Digital and Computational Pathology, 120390Z (4 April 2022); https://doi.org/10.1117/12.2626318

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