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How Does Target Lesion Selection Affect RECIST? A Computer Simulation Study.

Teresa M Tareco Bucho1, Renaud L M Tissier, Kevin B W Groot Lipman

  • 1From the Radiology Department (T.T.B., K.G.L., Z.B., T.D.L.N.-K., R.B.-T., S.T.), Biostatistics Unit (R.T.), and Thoracic Oncology (K.G.L.), Netherlands Cancer Institute, Amsterdam, the Netherlands; GROW School for Oncology and Reproduction, Maastricht University, Maastricht, the Netherlands (T.T.B., K.G.L., Z.B., R.B.-T., S.T.); Institute for Advanced Biomedical Technologies, Gabriele d'Annunzio University of Chieti-Pescara, Italy (A.D.P.); Department of Innovative Technologies in Medicine and Dentistry, Gabriele d'Annunzio University of Chieti-Pescara, Italy (A.D.P.); Institute of Diagnostic and Interventional Radiology, University Hospital of Zurich, Zurich, Switzerland (T.D.L.N.-K.); Institute of Radiology and Nuclear Medicine, Stadtspital Zürich, Zurich, Switzerland (T.D.L.N.-K.); and Faculty of Health Sciences, University of Southern Denmark, Odense, Denmark (R.B.-T.).

Investigative Radiology
|November 3, 2023
PubMed
Summary
This summary is machine-generated.

The Response Evaluation Criteria in Solid Tumors (RECIST) may inaccurately estimate total tumor burden (TTB) due to subjective target lesion selection, especially with widespread or multiple lesions. Including more lesions in analysis could improve accuracy.

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Area of Science:

  • Oncology
  • Radiology
  • Medical Imaging Analysis

Background:

  • Response Evaluation Criteria in Solid Tumors (RECIST) assumes objective target lesion selection for estimating total tumor burden (TTB).
  • Subjectivity in target lesion selection may compromise the representativeness of RECIST assessments.

Purpose of the Study:

  • To challenge the assumption of objective target lesion selection in RECIST using computer simulations.
  • To analyze the impact of lesion number, organ distribution, and growth on RECIST accuracy.

Main Methods:

  • A computer simulation model was developed to assess target lesion selection subjectivity.
  • Reader disagreement and measurement vs. TTB disagreement were analyzed based on lesion characteristics.

Main Results:

  • Disagreement increases with more lesions, concentrated organ involvement, and growth near response thresholds.
  • RECIST 1.1 has intrinsic errors in TTB estimation, with error rates of 7.8% (5 lesions) and 17.3% (15 lesions).

Conclusions:

  • RECIST accurately estimates TTB in localized disease but fails with distal metastases and multiple organ involvement.
  • Selection bias from "largest lesions" hinders accurate TTB estimation; including more lesions is recommended.