Stability of radiomic features of apparent diffusion coefficient (ADC) maps for locally advanced rectal cancer in response to image pre-processing

Alberto Traverso*, Michal Kazmierski, Zhenwei Shi, Petros Kalendralis, Mattea Welch, Henrik Dahl Nissen, David Jaffray, Andre Dekker, Leonard Wee

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

25 Citations (Web of Science)

Abstract

Quantitative imaging features (radiomics) extracted from apparent diffusion coefficient (ADC) maps of rectal cancer patients can provide additional information to support treatment decision. Most available radiomic computational packages allow extraction of hundreds to thousands of features. However, two major factors can influence the reproducibility of radiomic features: interobserver variability, and imaging filtering applied prior to features extraction. In this exploratory study we seek to determine to what extent various commonly-used features are reproducible with regards to the mentioned factors using ADC maps from two different clinics (56 patients). Features derived from intensity distribution histograms are less sensitive to manual tumour delineation differences, noise in ADC images, pixel size resampling and intensity discretization. Shape features appear to be strongly affected by delineation quality. On the whole, textural features appear to be poorly or moderately reproducible with respect to the image pre-processing perturbations we reproduced.

Original languageEnglish
Pages (from-to)44-51
Number of pages8
JournalPhysica Medica: European journal of medical physics
Volume61
DOIs
Publication statusPublished - May 2019
Event2nd European Congress of Medical Physics - Copenhagen, Denmark
Duration: 23 Aug 201825 Aug 2018
Conference number: 2

Keywords

  • Magnetic resonance imaging
  • Diffusion weighted imaging
  • Apparent diffusion coefficient
  • Radiomic feature reproducibility
  • Locally advanced rectal carcinoma
  • PREOPERATIVE RADIOTHERAPY
  • PREDICTING RESPONSE
  • TUMOR VOLUME
  • CHEMORADIOTHERAPY

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