Radiopathological System for Quantifying the Tumor Microenvironment and Predicting Prognosis in Osteosarcoma: A Multicenter Study

Motivation: Current quantification methods for osteosarcoma tumors and their tumor microenvironment (TME) are often ineffective, resulting in treatment failures and poor patient prognosis. Goal(s): To develop an automated system integrating MRI and WSI data for precise, quantitative assessment of tumors and TME to improve prognostic predictions. Approach: We developed a system utilizing MRI and WSI data from a 185-patient, multisite cohort, enabling independent assessment of tumors and TME. Results: Combined radiopathomic features significantly improve patient outcome predictions. Impact: This model provides a comprehensive prognostic assessment, essential for advancing predictive tools and extensive validation before clinical application.

Authors

Publication Details

Journal
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Published
2025-09-16
DOI
https://doi.org/10.58530/2025/0228
Primary Topic
Sarcoma Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
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article

Radiopathological System for Quantifying the Tumor Microenvironment and Predicting Prognosis in Osteosarcoma: A Multicenter Study

Shisi Li, Rui-ling She, Yinghua Zhao, Xiaoping Chen et al.
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Sarcoma Diagnosis and Treatment
article

Radiopathological System for Quantifying the Tumor Microenvironment and Predicting Prognosis in Osteosarcoma: A Multicenter Study

Shisi Li, Rui-ling She, Yinghua Zhao, Xiaoping Chen, Xiaoxuan Zhang, Qianjin Feng
article en

Abstract

Motivation: Current quantification methods for osteosarcoma tumors and their tumor microenvironment (TME) are often ineffective, resulting in treatment failures and poor patient prognosis. Goal(s): To develop an automated system integrating MRI and WSI data for precise, quantitative assessment of tumors and TME to improve prognostic predictions. Approach: We developed a system utilizing MRI and WSI data from a 185-patient, multisite cohort, enabling independent assessment of tumors and TME. Results: Combined radiopathomic features significantly improve patient outcome predictions. Impact: This model provides a comprehensive prognostic assessment, essential for advancing predictive tools and extensive validation before clinical application.

Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Openalex Percentile: Top 64%
Sarcoma Diagnosis and Treatment
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