Premium
Tumor volume measurement errors of RECIST studied with ellipsoids
Author(s) -
Levine Zachary H.,
Galloway Benjamin R.,
Peskin Adele P.,
Heussel Claus P.,
Chen Joseph J.
Publication year - 2011
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.3577602
Subject(s) - ellipsoid , response evaluation criteria in solid tumors , confidence interval , medicine , nuclear medicine , statistics , mathematics , medical physics , computer science , radiology , clinical trial , physics , astronomy , phases of clinical research
Purpose: The authors investigate the extent to which Response Evaluation Criteria in Solid Tumors (RECIST) can predict tumor volumes in ideal geometric settings and using clinical data.Methods: The authors consider a hierarchy of models including uniaxial ellipsoids, general ellipsoids, and composites of ellipsoids, using both analytical and numerical techniques to show how well RECIST can predict tumor volumes in each case. The models have certain features that are compared to clinical data.Results: The principal conclusion is that a change in the reported RECIST value needs to be a factor of at least 1.2 to achieve a 95% confidence that one ellipsoid is larger than another assuming the ratio of maximum to minimum diameters is no more than 2, an assumption that is reasonable for some classes of tumors. There is a significant probability that RECIST will select a tumor other than the largest due to orientation effects of nonspherical tumors: in previously reported malignoma data, RECIST would have selected a tumor other than the largest in 9% of the cases. Also, the widely used spherical model connecting RECIST values for a single tumor to volumes overestimates these volumes.Conclusions: RECIST imposes a limit on the ability to determine tumor volumes, which is greater than the limit imposed by modern medical computed tomography machines. It is also likely the RECIST limit is above natural biological variability of stable lesions. The authors recommend the study of such natural variability as a fruitful avenue for further study.