Tumor metrics imaging core labs: primer for radiologists

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Authors: Rachana Gurudu, Dhruv Bansal, Anil Chauhan, Sree Harsha Tirumani
Cited by: 0
References: 49

Abstract

Imaging biomarkers have emerged as increasingly important endpoints in cancer clinical trials. Incorporating tumor metric reads as part of routine clinical reads by on-site radiologists for cancer clinical trials has several challenges which can be addressed by tumor metrics imaging core lab. Despite the operational and financial challenges inherent in establishing and maintaining tumor metrics imaging core labs, including workflow complexities, infrastructure demands, and data security considerations, these facilities confer significant advantages including accelerated trial timelines, improved regulatory compliance, and the creation of interdisciplinary research environments. Moreover, the integration of artificial intelligence within tumor metrics imaging core labs offers enhanced image analysis, predictive modeling, and improved trial efficiency. This article provides a comprehensive review of the role of tumor metrics imaging core labs in clinical trials and provides an overview of the key components involved in setting up a core lab. We will also briefly present the challenges in the successful operation of a tumor metrics imaging core lab and delve into the potential solutions, including the integration of AI tools for clinical trials.

Fields of Study & Subjects

Medical Imaging Techniques and Applications Radiomics and Machine Learning in Medical Imaging Radiology practices and education

Publication details

Journal / source
Abdominal Radiology
Volume
51
Issue
9
Pages
4725–4734
Publication date
3 March 2026
Language
EN