title: Volumetric response classification in metastatic solid tumors on MSCT: initial results in a whole-body setting.
abstract: OBJECTIVE
  To examine technical parameters of measurement accuracy and differences in tumor response classification using RECIST 1.1 and volumetric assessment in three common metastasis types (lung nodules, liver lesions, lymph node metastasis) simultaneously.
  
  
  METHODS
  56 consecutive patients (32 female) aged 41-82 years with a wide range of metastatic solid tumors were examined with MSCT for baseline and follow up. Images were evaluated by three experienced radiologists using manual measurements and semi-automatic lesion segmentation. Institutional ethics review was obtained and all patients gave written informed consent. Data analysis comprised interobserver variability operationalized as coefficient of variation and categorical response classification according to RECIST 1.1 for both manual and volumetric measures. Continuous data were assessed for statistical significance with Wilcoxon signed-rank test and categorical data with Fleiss kappa.
  
  
  RESULTS
  Interobserver variability was 6.3% (IQR 4.6%) for manual and 4.1% (IQR 4.4%) for volumetrically obtained sum of relevant diameters (p<0.05, corrected). 4-8 patients' response to therapy was classified differently across observers by using volumetry compared to standard manual measurements. Fleiss kappa revealed no significant difference in categorical agreement of response classification between manual (0.7558) and volumetric (0.7623) measurements.
  
  
  CONCLUSIONS
  Under standard RECIST thresholds there was no advantage of volumetric compared to manual response evaluation. However volumetric assessment yielded significantly lower interobserver variability. This may allow narrower thresholds for volumetric response classification in the future.
authors.affiliation: Klinik für Diagnostische Radiologie, Arnold-Heller-Straße 3, Haus 23, 24105 Kiel, Germany. a.wulff@rad.uni-kiel.de
authors.forename: A M
authors.initials: AM
authors.lastname: Wulff
authors.forename: M
authors.initials: M
authors.lastname: Fabel
authors.forename: S
authors.initials: S
authors.lastname: Freitag-Wolf
authors.forename: M
authors.initials: M
authors.lastname: Tepper
authors.forename: H M
authors.initials: HM
authors.lastname: Knabe
authors.forename: J P
authors.initials: JP
authors.lastname: Schäfer
authors.forename: O
authors.initials: O
authors.lastname: Jansen
authors.forename: H
authors.initials: H
authors.lastname: Bolte
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008297:Male; D008875:Middle Aged; D009362:Neoplasm Metastasis / Q000000981:diagnostic imaging*; D015588:Observer Variation; D010363:Pattern Recognition, Automated / Q000379:methods*; D010865:Pilot Projects; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed / Q000379:methods*; D051598:Whole Body Imaging / Q000379:methods*
keywords: Computed tomography; Liver metastasis; Lung metastasis; Lymph node metastasis; Segmentation