title: Target lesion selection: an important factor causing variability of response classification in the Response Evaluation Criteria for Solid Tumors 1.1.
abstract: OBJECTIVE
  We conducted a systematic analysis of factors (manual vs automated and unidimensional vs 3-dimensional size assessment, and impact of different target lesion selection) contributing to variability of response categorization in the Response Evaluation Criteria for Solid Tumors 1.1.
  
  
  METHODS
  A total of 41 female patients (58.1 ± 13.2 years old) with metastatic breast cancer underwent contrast-enhanced thoracoabdominal computed tomography for initial staging and first follow-up after systemic chemotherapy. Data were independently interpreted by 3 radiologists with 5 to 9 years of experience. In addition, response was evaluated by a computer-assisted diagnosis system that allowed automated unidimensional and 3-dimensional assessment of target lesions.
  
  
  RESULTS
  Overall, between-reader agreement was moderate (κ = 0.53), with diverging response classification observed in 19 of 41 patients (46%). In 25 patients, readers had chosen the same, and in 16, readers had chosen different target lesions. Selection of the same target lesions was associated with a 76% rate of agreement (19/25) with regard to response classification; selection of different target lesions was associated with an 81% rate of disagreement (13/16) (P < 0.001). After dichotomizing response classes according to their therapeutic implication in progressive versus nonprogressive, disagreement was observed in 11 of 41 patients (27%) (κ = 0.57). In 9 of these 11 patients, readers had chosen different target lesions. Disagreement rates due to manual versus automated or unidimensional versus volumetric size measurements were less important (11/41 and 6/41; 27% and 15%, respectively).
  
  
  CONCLUSIONS
  A major source of variability is not the manual or unidimensional measurement, but the variable choice of target lesions between readers. Computer-assisted diagnosis-based analysis or tumor volumetry can help avoid variability due to manual or unidimensional measurements only but will not solve the problem of target lesion selection.
authors.affiliation: From the Departments of *Diagnostic and Interventional Radiology and †Haematology, Oncology, and Stem Cell Transplantation, University of Aachen, Aachen, Germany.
authors.forename: Sebastian
authors.initials: S
authors.lastname: Keil
authors.forename: Alexandra
authors.initials: A
authors.lastname: Barabasch
authors.forename: Timm
authors.initials: T
authors.lastname: Dirrichs
authors.forename: Philipp
authors.initials: P
authors.lastname: Bruners
authors.forename: Nienke Lynn
authors.initials: NL
authors.lastname: Hansen
authors.forename: Heribert B
authors.initials: HB
authors.lastname: Bieling
authors.forename: Tim H
authors.initials: TH
authors.lastname: Brümmendorf
authors.forename: Christiane K
authors.initials: CK
authors.lastname: Kuhl
mesh_terms: D000465:Algorithms; D016477:Artifacts; D001943:Breast Neoplasms / Q000000981:diagnostic imaging*; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods / Q000592:standards; D007090:Image Interpretation, Computer-Assisted / Q000379:methods* / Q000592:standards; D021621:Imaging, Three-Dimensional / Q000379:methods* / Q000592:standards; D038622:Internationality; D008207:Lymphatic Metastasis; D008327:Mammography / Q000379:methods* / Q000592:standards; D008875:Middle Aged; D015588:Observer Variation; D015203:Reproducibility of Results; D066066:Response Evaluation Criteria in Solid Tumors; D012189:Retrospective Studies; D018401:Sample Size; D012680:Sensitivity and Specificity; D012984:Software; D014057:Tomography, X-Ray Computed / Q000379:methods* / Q000592:standards; D016896:Treatment Outcome