Literature DB >> 31151578

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

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.
Copyright © 2019 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

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


  15 in total

1.  Repeatability and reproducibility of magnetic resonance imaging-based radiomic features in rectal cancer.

Authors:  Robba Rai; Michael B Barton; Phillip Chlap; Gary Liney; Carsten Brink; Shalini Vinod; Monique Heinke; Yuvnik Trada; Lois C Holloway
Journal:  J Med Imaging (Bellingham)       Date:  2022-08-18

2.  Image resampling and discretization effect on the estimate of myocardial radiomic features from T1 and T2 mapping in hypertrophic cardiomyopathy.

Authors:  Daniela Marfisi; Carlo Tessa; Chiara Marzi; Jacopo Del Meglio; Stefania Linsalata; Rita Borgheresi; Alessio Lilli; Riccardo Lazzarini; Luca Salvatori; Claudio Vignali; Andrea Barucci; Mario Mascalchi; Giancarlo Casolo; Stefano Diciotti; Antonio Claudio Traino; Marco Giannelli
Journal:  Sci Rep       Date:  2022-06-17       Impact factor: 4.996

3.  Whole lesion histogram analysis of apparent diffusion coefficient predicts therapy response in locally advanced rectal cancer.

Authors:  Mayra Evelia Jiménez de Los Santos; Juan Armando Reyes-Pérez; Victor Domínguez Osorio; Yolanda Villaseñor-Navarro; Liliana Moreno-Astudillo; Itzel Vela-Sarmiento; Isabel Sollozo-Dupont
Journal:  World J Gastroenterol       Date:  2022-06-21       Impact factor: 5.374

4.  Ability of Delta Radiomics to Predict a Complete Pathological Response in Patients with Loco-Regional Rectal Cancer Addressed to Neoadjuvant Chemo-Radiation and Surgery.

Authors:  Valerio Nardone; Alfonso Reginelli; Roberta Grassi; Giovanna Vacca; Giuliana Giacobbe; Antonio Angrisani; Alfredo Clemente; Ginevra Danti; Pierpaolo Correale; Salvatore Francesco Carbone; Luigi Pirtoli; Lorenzo Bianchi; Angelo Vanzulli; Cesare Guida; Roberto Grassi; Salvatore Cappabianca
Journal:  Cancers (Basel)       Date:  2022-06-18       Impact factor: 6.575

5.  Repeatability of Quantitative Imaging Features in Prostate Magnetic Resonance Imaging.

Authors:  Hong Lu; Nestor A Parra; Jin Qi; Kenneth Gage; Qian Li; Shuxuan Fan; Sebastian Feuerlein; Julio Pow-Sang; Robert Gillies; Jung W Choi; Yoganand Balagurunathan
Journal:  Front Oncol       Date:  2020-05-07       Impact factor: 6.244

6.  Repeatability and reproducibility study of radiomic features on a phantom and human cohort.

Authors:  A K Jha; S Mithun; V Jaiswar; U B Sherkhane; N C Purandare; K Prabhash; V Rangarajan; A Dekker; L Wee; A Traverso
Journal:  Sci Rep       Date:  2021-01-21       Impact factor: 4.379

Review 7.  A systematic review and quality of reporting checklist for repeatability and reproducibility of radiomic features.

Authors:  Elisabeth Pfaehler; Ivan Zhovannik; Lise Wei; Ronald Boellaard; Andre Dekker; René Monshouwer; Issam El Naqa; Jan Bussink; Robert Gillies; Leonard Wee; Alberto Traverso
Journal:  Phys Imaging Radiat Oncol       Date:  2021-11-09

8.  MRI-based radiomics in breast cancer: feature robustness with respect to inter-observer segmentation variability.

Authors:  N M H Verbakel; A Ibrahim; M L Smidt; H C Woodruff; R W Y Granzier; J E van Timmeren; T J A van Nijnatten; R T H Leijenaar; M B I Lobbes
Journal:  Sci Rep       Date:  2020-08-25       Impact factor: 4.379

9.  Robustness of radiomic features in magnetic resonance imaging: review and a phantom study.

Authors:  Renee Cattell; Shenglan Chen; Chuan Huang
Journal:  Vis Comput Ind Biomed Art       Date:  2019-11-20

10.  Stability of Liver Radiomics across Different 3D ROI Sizes-An MRI In Vivo Study.

Authors:  Laura J Jensen; Damon Kim; Thomas Elgeti; Ingo G Steffen; Bernd Hamm; Sebastian N Nagel
Journal:  Tomography       Date:  2021-12-03
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