title: Tumor volume measurement errors of RECIST studied with ellipsoids.
abstract: OBJECTIVE
  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 modem 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.
authors.affiliation: Optical Technology Division, National Institute of Standards and Technology, Gaithersburg, Maryland 20899-8441, USA. zlevine@nist.gov
authors.forename: Zachary H
authors.initials: ZH
authors.lastname: Levine
authors.forename: Benjamin R
authors.initials: BR
authors.lastname: Galloway
authors.forename: Adele P
authors.initials: AP
authors.lastname: Peskin
authors.forename: Claus P
authors.initials: CP
authors.lastname: Heussel
authors.forename: Joseph J
authors.initials: JJ
authors.lastname: Chen
mesh_terms: D000465:Algorithms; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D009369:Neoplasms / Q000000981:diagnostic imaging*; D011856:Radiographic Image Enhancement / Q000379:methods*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed / Q000379:methods*