| Literature DB >> 31151578 |
Alberto Traverso1, Michal Kazmierski2, Zhenwei Shi2, Petros Kalendralis2, Mattea Welch3, Henrik Dahl Nissen4, David Jaffray3, Andre Dekker2, Leonard Wee2.
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.Entities:
Keywords: Apparent diffusion coefficient; Diffusion weighted imaging; Locally advanced rectal carcinoma; Magnetic resonance imaging; Radiomic feature reproducibility
Mesh:
Year: 2019 PMID: 31151578 DOI: 10.1016/j.ejmp.2019.04.009
Source DB: PubMed Journal: Phys Med ISSN: 1120-1797 Impact factor: 2.685