Sources of variation in multicenter rectal MRI data and their effect on radiomics feature reproducibility

N.W. Schurink, S.R. van Kranen, S. Roberti, J.J.M. van Griethuysen, N. Bogveradze, F. Castagnoli, N. El Khababi, F.C.H. Bakers, S.H. de Bie, G.P.T. Bosma, V.C. Cappendijk, R.W.F. Geenen, P.A. Neijenhuis, G.M. Peterson, C.J. Veeken, R.F.A. Vliegen, R.G.H. Beets-Tan*, D.M.J. Lambregts*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

3 Citations (Web of Science)

Abstract

Objectives To investigate sources of variation in a multicenter rectal cancer MRI dataset focusing on hardware and image acquisition, segmentation methodology, and radiomics feature extraction software. Methods T2W and DWI/ADC MRIs from 649 rectal cancer patients were retrospectively acquired in 9 centers. Fifty-two imaging features (14 first-order/6 shape/32 higher-order) were extracted from each scan using whole-volume (expert/non-expert) and single-slice segmentations using two different software packages (PyRadiomics/CapTk). Influence of hardware, acquisition, and patient-intrinsic factors (age/gender/cTN-stage) on ADC was assessed using linear regression. Feature reproducibility was assessed between segmentation methods and software packages using the intraclass correlation coefficient. Results Image features differed significantly (p < 0.001) between centers with more substantial variations in ADC compared to T2W-MRI. In total, 64.3% of the variation in mean ADC was explained by differences in hardware and acquisition, compared to 0.4% by patient-intrinsic factors. Feature reproducibility between expert and non-expert segmentations was good to excellent (median ICC 0.89-0.90). Reproducibility for single-slice versus whole-volume segmentations was substantially poorer (median ICC 0.40-0.58). Between software packages, reproducibility was good to excellent (median ICC 0.99) for most features (first-order/shape/GLCM/GLRLM) but poor for higher-order (GLSZM/NGTDM) features (median ICC 0.00-0.41). Conclusions Significant variations are present in multicenter MRI data, particularly related to differences in hardware and acquisition, which will likely negatively influence subsequent analysis if not corrected for. Segmentation variations had a minor impact when using whole volume segmentations. Between software packages, higher-order features were less reproducible and caution is warranted when implementing these in prediction models.
Original languageEnglish
Pages (from-to)1506-1516
Number of pages11
JournalEuropean Radiology
Volume32
Issue number3
Early online date16 Oct 2021
DOIs
Publication statusPublished - Mar 2022

Keywords

  • Multicenter study
  • Rectal neoplasms
  • Reproducibility of results
  • Magnetic resonance imaging
  • Image processing
  • Computer-assisted
  • CANCER
  • PREDICTION
  • REPEATABILITY

Cite this