Time to Rethink RECIST 1.1?

Colin G. Miller

The standard criteria for managing the use of medical imaging in clinical oncology trials—RECIST (Response Evaluation Criteria in Solid Tumors) guidelines – have been in place for more than 20 years, with the original criteria published in 2000 and RECIST 1.1 appearing in 2009. In all that time, RECIST has been instrumental in helping to evaluate treatment response in solid tumors and identifying new lesions in progressive disease. Now, a recent paper suggests that it may be time for an upgrade from RECIST 1.1.

The paper, published in Clinical Cancer Research in December 2020, reports on the work of researchers who re-measured original CT images and datasets from two previous phase 3 clinical trials involving 988 patients with colorectal cancer. Discussion points and findings are outlined below:


Purpose of the study:

  • Mathematical models combined with new imaging technologies may help improve clinical oncology studies by more accurately detecting the therapeutic effect in patients with cancer



  • Newer metrics based on methods of modeling the longitudinal growth of solid tumors have yet to be shown superior to RECIST metrics
  • Digital imaging techniques, such as volumetric measurement of target lesions, have been suggested but not adopted to improve sensitivity for changes in tumor burden due to treatment

Study assessments and findings:

  • Volumetric measurement of target lesions was assessed to estimate the rates of exponential tumor growth and treatment regression
  • Potentially important advantages were found when combining a model-based metric with volumetric assessment of tumor burden
  • Comparing treatments based on calculation of the tumor growth rate, g, using volume measures of tumor directly on CT images, achieved greater statistical power than using conventional unidimensional measurements


The findings in this study suggest that to accelerate improvements in the clinical study of cancer therapies, combining direct measurement of tumor lesions from images with growth modeling could be a valuable advancement over modeling of RECIST-based unidimensional target lesions alone.

An older paper, published in Clinical Cancer Research in April 2018, had previously suggested that the end of RECIST was near.

As medical imaging products and practices evolve and advance, we will continue to monitor potential changes to RECIST 1.1 guidelines—as well as the possibility of their replacement.


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