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Applying Radiomics to Predict Outcomes in Patients with High-Grade Retroperitoneal Sarcoma Treated with Preoperative

Adel Shahnam¹, Nicholas Hardcastle², David E Gyorki^3,4

¹Department of Medical Oncology, Peter MacCallum Cancer Center, Melbourne 3000, Australia.

Journal of Imaging

|December 24, 2025

Summary

This summary is machine-generated.

Radiomic features from CT scans can improve predictions for overall survival and distant metastasis in patients with high-risk retroperitoneal sarcoma (RPS). These imaging biomarkers offer additional prognostic value beyond traditional clinical factors for personalized RPS treatment.

Keywords:

predictive model radiomics retroperitoneal sarcomas

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Area of Science:

Oncology
Radiology
Medical Imaging

Background:

Retroperitoneal sarcomas (RPS) are rare and often recur after surgery.
Current treatment relies on surgical resection, but improved prognostication is needed.
Combining clinical data with radiomic features may enhance treatment stratification for RPS.

Purpose of the Study:

To evaluate if radiomic features from CT scans provide additional prognostic value for high-risk RPS.
To assess the predictive capability of radiomic features beyond established clinicopathological factors.
To improve treatment personalization for patients with high-risk RPS.

Main Methods:

Retrospective analysis of 72 patients with high-risk RPS treated with preoperative radiotherapy.
Cox proportional hazards regression used to analyze clinical and radiomic features for time-to-event outcomes.
C-statistics assessed predictive accuracy for overall survival (OS) and time to distant metastasis (TDM).

Main Results:

Older age, grade 3 tumors, and larger tumor size predicted worse OS.
Radiomic features kurtosis and NGTDM busyness significantly improved OS prediction (c-statistics 0.69 and 0.73).
Kurtosis also improved TDM prediction (c-statistic 0.72).

Conclusions:

Radiomic features show promise in complementing clinicopathological factors for predicting outcomes in high-risk RPS.
These imaging biomarkers may aid in personalizing treatment strategies for RPS patients.
Further validation in larger, multi-institutional studies is warranted.