Advancing Treatment Response Assessment of Hepatic Metastases Using AI-Driven Volumetric Analysis

Abstract

Response Evaluation Criteria in Solid Tumors (RECIST) remains the cornerstone for treatment response assessment in oncology. However, its traditional 2D approach faces challenges including measurement variability and time-intensive workflow. This study presents a comparative analysis between conventional human-performed RECIST1.1 measurements and a volumetric approach driven by artificial in-telligence (AI). Through the analysis of 23 patients with colorectal liver metastases (CRLM) treated with chemother-apy, we demonstrate that AI-based volumetric assessment achieves enhanced tumor response assessment while potentially offering improved reproducibility and efficiency. This work provides evidence supporting the clinical validity of AI-based volumetric tumor assessment as a complementary or alternative approach to the traditional RECIST evaluation.

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