title: Evaluating the agreement between tumour volumetry and the estimated volumes of tumour lesions using an algorithm.
abstract: OBJECTIVE
  To evaluate the agreement between tumour volume derived from semiautomated volumetry (SaV) and tumor volume defined by spherical volume using longest lesion diameter (LD) according to Response Evaluation Criteria In Solid Tumors (RECIST) or ellipsoid volume using LD and longest orthogonal diameter (LOD) according to World Health Organization (WHO) criteria.
  
  
  METHODS
  Twenty patients with metastatic colorectal cancer from the CIOX trial were included. A total of 151 target lesions were defined by baseline computed tomography and followed until disease progression. All assessments were performed by a single reader. A variance component model was used to compare the three volume versions.
  
  
  RESULTS
  There was a significant difference between the SaV and RECIST-based tumour volumes. The same model showed no significant difference between the SaV and WHO-based volumes. Scatter plots showed that the RECIST-based volumes overestimate lesion volume. The agreement between the SaV and WHO-based relative changes in tumour volume, evaluated by intraclass correlation, showed nearly perfect agreement.
  
  
  CONCLUSIONS
  Estimating the volume of metastatic lesions using both the LD and LOD (WHO) is more accurate than those based on LD only (RECIST), which overestimates lesion volume. The good agreement between the SaV and WHO-based relative changes in tumour volume enables a reasonable approximation of three-dimensional tumour burden.
  
  
  CONCLUSIONS
  • Tumour response in patients undergoing chemotherapy is assessed using CT images • Measurements are based on RECIST (unidimensional)-based or WHO (bidimensional)-based criteria • We calculated tumour volume from bidimensional target lesion measurements • This formula provides good tumour volume approximation, based on semiautomated volumetry.
authors.affiliation: German Cancer Consortium (DKTK), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany.
authors.forename: Ruediger P
authors.initials: RP
authors.lastname: Laubender
authors.forename: Julia
authors.initials: J
authors.lastname: Lynghjem
authors.forename: Melvin
authors.initials: M
authors.lastname: D'Anastasi
authors.forename: Volker
authors.initials: V
authors.lastname: Heinemann
authors.forename: Dominik P
authors.initials: DP
authors.lastname: Modest
authors.forename: Ulrich R
authors.initials: UR
authors.lastname: Mansmann
authors.forename: Ute
authors.initials: U
authors.lastname: Sartorius
authors.forename: Michael
authors.initials: M
authors.lastname: Schlichting
authors.forename: Anno
authors.initials: A
authors.lastname: Graser
mesh_terms: D000328:Adult; D000368:Aged; D000465:Algorithms; D000970:Antineoplastic Agents / Q000627:therapeutic use*; D015179:Colorectal Neoplasms / Q000175:diagnosis* / Q000188:drug therapy / Q000556:secondary; D018450:Disease Progression; D004359:Drug Therapy, Combination; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D008297:Male; D008875:Middle Aged; D015588:Observer Variation; D015203:Reproducibility of Results; D012189:Retrospective Studies; D014057:Tomography, X-Ray Computed / Q000379:methods*; D047368:Tumor Burden / Q000187:drug effects
chemical_list: D000970:Antineoplastic Agents