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Updated: Jun 19, 2026
Using Micro-computed Tomography for the Assessment of Tumor Development and Follow-up of Response to Treatment in a Mouse Model of Lung Cancer
Published on: May 20, 2016
Semiquantitative visual approach to scoring lung cancer treatment response using computed tomography: a pilot study
Ronald H Gottlieb1, Prasanna Kumar, Peter Loud
1Roswell Park Cancer Institute, Elm and Carlton Streets, Buffalo, NY 14263, USA. ronald.gottlieb@roswellpark.org
Objective:
Our objective was to compare a newly developed semiquantitative visual scoring (SVS) method with the current standard, the Response Evaluation Criteria in Solid Tumors (RECIST) method, in the categorization of treatment response and reader agreement for patients with metastatic lung cancer followed by computed tomography.
Materials And Methods:
The 18 subjects (5 women and 13 men; mean age, 62.8 years) were from an institutional review board-approved phase 2 study that evaluated a second-line chemotherapy regimen for metastatic (stages III and IV) non-small cell lung cancer. Four radiologists, blinded to the patient outcome and each other's reads, evaluated the change in the patients' tumor burden from the baseline to the first restaging computed tomographic scan using either the RECIST or the SVS method. We compared the numbers of patients placed into the partial response, the stable disease (SD), and the progressive disease (PD) categories (Fisher exact test) and observer agreement (kappa statistic).
Results:
Requiring the concordance of 3 of the 4 readers resulted in the RECIST placing 17 (100%) of 17 patients in the SD category compared with the SVS placing 9 (60%) of 15 patients in the partial response, 5 (33%) of the 15 patients in the SD, and 1 (6.7%) of the 15 patients in the PD categories (P < 0.0001). Interobserver agreement was higher among the readers using the SVS method (kappa, 0.54; P < 0.0001) compared with that of the readers using the RECIST method (kappa, -0.01; P = 0.5378).
Conclusions:
Using the SVS method, the readers more finely discriminated between the patient response categories with superior agreement compared with the RECIST method, which could potentially result in large differences in early treatment decisions for advanced lung cancer.
