Literature DB >> 33479392

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

A K Jha1,2,3, S Mithun4,5,6, V Jaiswar4, U B Sherkhane4,6, N C Purandare4,5, K Prabhash7,5, V Rangarajan4,5, A Dekker6, L Wee6, A Traverso6.   

Abstract

The repeatability and reproducibility of radiomic features extracted from CT scans need to be investigated to evaluate the temporal stability of imaging features with respect to a controlled scenario (test-retest), as well as their dependence on acquisition parameters such as slice thickness, or tube current. Only robust and stable features should be used in prognostication/prediction models to improve generalizability across multiple institutions. In this study, we investigated the repeatability and reproducibility of radiomic features with respect to three different scanners, variable slice thickness, tube current, and use of intravenous (IV) contrast medium, combining phantom studies and human subjects with non-small cell lung cancer. In all, half of the radiomic features showed good repeatability (ICC > 0.9) independent of scanner model. Within acquisition protocols, changes in slice thickness was associated with poorer reproducibility compared to the use of IV contrast. Broad feature classes exhibit different behaviors, with only few features appearing to be the most stable. 108 features presented both good repeatability and reproducibility in all the experiments, most of them being wavelet and Laplacian of Gaussian features.

Entities:  

Year:  2021        PMID: 33479392      PMCID: PMC7820018          DOI: 10.1038/s41598-021-81526-8

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  26 in total

1.  3D Slicer as an image computing platform for the Quantitative Imaging Network.

Authors:  Andriy Fedorov; Reinhard Beichel; Jayashree Kalpathy-Cramer; Julien Finet; Jean-Christophe Fillion-Robin; Sonia Pujol; Christian Bauer; Dominique Jennings; Fiona Fennessy; Milan Sonka; John Buatti; Stephen Aylward; James V Miller; Steve Pieper; Ron Kikinis
Journal:  Magn Reson Imaging       Date:  2012-07-06       Impact factor: 2.546

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

Authors:  Alberto Traverso; Michal Kazmierski; Zhenwei Shi; Petros Kalendralis; Mattea Welch; Henrik Dahl Nissen; David Jaffray; Andre Dekker; Leonard Wee
Journal:  Phys Med       Date:  2019-04-28       Impact factor: 2.685

3.  The intraclass correlation coefficient as a measure of reliability.

Authors:  J J Bartko
Journal:  Psychol Rep       Date:  1966-08

4.  Computational Radiomics System to Decode the Radiographic Phenotype.

Authors:  Joost J M van Griethuysen; Andriy Fedorov; Chintan Parmar; Ahmed Hosny; Nicole Aucoin; Vivek Narayan; Regina G H Beets-Tan; Jean-Christophe Fillion-Robin; Steve Pieper; Hugo J W L Aerts
Journal:  Cancer Res       Date:  2017-11-01       Impact factor: 12.701

5.  The Design of SimpleITK.

Authors:  Bradley C Lowekamp; David T Chen; Luis Ibáñez; Daniel Blezek
Journal:  Front Neuroinform       Date:  2013-12-30       Impact factor: 4.081

Review 6.  Imaging biomarker roadmap for cancer studies.

Authors:  James P B O'Connor; Eric O Aboagye; Judith E Adams; Hugo J W L Aerts; Sally F Barrington; Ambros J Beer; Ronald Boellaard; Sarah E Bohndiek; Michael Brady; Gina Brown; David L Buckley; Thomas L Chenevert; Laurence P Clarke; Sandra Collette; Gary J Cook; Nandita M deSouza; John C Dickson; Caroline Dive; Jeffrey L Evelhoch; Corinne Faivre-Finn; Ferdia A Gallagher; Fiona J Gilbert; Robert J Gillies; Vicky Goh; John R Griffiths; Ashley M Groves; Steve Halligan; Adrian L Harris; David J Hawkes; Otto S Hoekstra; Erich P Huang; Brian F Hutton; Edward F Jackson; Gordon C Jayson; Andrew Jones; Dow-Mu Koh; Denis Lacombe; Philippe Lambin; Nathalie Lassau; Martin O Leach; Ting-Yim Lee; Edward L Leen; Jason S Lewis; Yan Liu; Mark F Lythgoe; Prakash Manoharan; Ross J Maxwell; Kenneth A Miles; Bruno Morgan; Steve Morris; Tony Ng; Anwar R Padhani; Geoff J M Parker; Mike Partridge; Arvind P Pathak; Andrew C Peet; Shonit Punwani; Andrew R Reynolds; Simon P Robinson; Lalitha K Shankar; Ricky A Sharma; Dmitry Soloviev; Sigrid Stroobants; Daniel C Sullivan; Stuart A Taylor; Paul S Tofts; Gillian M Tozer; Marcel van Herk; Simon Walker-Samuel; James Wason; Kaye J Williams; Paul Workman; Thomas E Yankeelov; Kevin M Brindle; Lisa M McShane; Alan Jackson; John C Waterton
Journal:  Nat Rev Clin Oncol       Date:  2016-10-11       Impact factor: 66.675

Review 7.  Quantitative radiomics studies for tissue characterization: a review of technology and methodological procedures.

Authors:  Ruben T H M Larue; Gilles Defraene; Dirk De Ruysscher; Philippe Lambin; Wouter van Elmpt
Journal:  Br J Radiol       Date:  2016-12-12       Impact factor: 3.039

Review 8.  How rapid advances in imaging are defining the future of precision radiation oncology.

Authors:  Laura Beaton; Steve Bandula; Mark N Gaze; Ricky A Sharma
Journal:  Br J Cancer       Date:  2019-03-26       Impact factor: 7.640

9.  Radiomics: Images Are More than Pictures, They Are Data.

Authors:  Robert J Gillies; Paul E Kinahan; Hedvig Hricak
Journal:  Radiology       Date:  2015-11-18       Impact factor: 11.105

10.  Test-Retest Data for Radiomics Feature Stability Analysis: Generalizable or Study-Specific?

Authors:  Janna E van Timmeren; Ralph T H Leijenaar; Wouter van Elmpt; Jiazhou Wang; Zhen Zhang; André Dekker; Philippe Lambin
Journal:  Tomography       Date:  2016-12
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  14 in total

Review 1.  A primer on texture analysis in abdominal radiology.

Authors:  Natally Horvat; Joao Miranda; Maria El Homsi; Jacob J Peoples; Niamh M Long; Amber L Simpson; Richard K G Do
Journal:  Abdom Radiol (NY)       Date:  2021-11-26

Review 2.  Rectal MRI radiomics inter- and intra-reader reliability: should we worry about that?

Authors:  Henry C Kwok; Charlotte Charbel; Jayasree Chakraborty; Natally Horvat; Sofia Danilova; Joao Miranda; Natalie Gangai; Iva Petkovska
Journal:  Abdom Radiol (NY)       Date:  2022-04-02

3.  Data harmonisation for information fusion in digital healthcare: A state-of-the-art systematic review, meta-analysis and future research directions.

Authors:  Yang Nan; Javier Del Ser; Simon Walsh; Carola Schönlieb; Michael Roberts; Ian Selby; Kit Howard; John Owen; Jon Neville; Julien Guiot; Benoit Ernst; Ana Pastor; Angel Alberich-Bayarri; Marion I Menzel; Sean Walsh; Wim Vos; Nina Flerin; Jean-Paul Charbonnier; Eva van Rikxoort; Avishek Chatterjee; Henry Woodruff; Philippe Lambin; Leonor Cerdá-Alberich; Luis Martí-Bonmatí; Francisco Herrera; Guang Yang
Journal:  Inf Fusion       Date:  2022-06       Impact factor: 17.564

4.  Radiomic Features of 18F-FDG PET in Hodgkin Lymphoma Are Predictive of Outcomes.

Authors:  Yeye Zhou; Yuchun Zhu; Zhiqiang Chen; Jihui Li; Shibiao Sang; Shengming Deng
Journal:  Contrast Media Mol Imaging       Date:  2021-11-22       Impact factor: 3.161

5.  Prognostic Value of Radiomic Features of 18F-FDG PET/CT in Patients With B-Cell Lymphoma Treated With CD19/CD22 Dual-Targeted Chimeric Antigen Receptor T Cells.

Authors:  Yeye Zhou; Jihui Li; Xiaoyi Zhang; Tongtong Jia; Bin Zhang; Na Dai; Shibiao Sang; Shengming Deng
Journal:  Front Oncol       Date:  2022-02-07       Impact factor: 6.244

6.  Radiomics of Patients with Locally Advanced Rectal Cancer: Effect of Preprocessing on Features Estimation from Computed Tomography Imaging.

Authors:  Stefania Linsalata; Rita Borgheresi; Daniela Marfisi; Patrizio Barca; Aldo Sainato; Fabiola Paiar; Emanuele Neri; Antonio Claudio Traino; Marco Giannelli
Journal:  Biomed Res Int       Date:  2022-03-20       Impact factor: 3.411

7.  MaasPenn Radiomics Reproducibility Score: A Novel Quantitative Measure for Evaluating the Reproducibility of CT-Based Handcrafted Radiomic Features.

Authors:  Abdalla Ibrahim; Bruno Barufaldi; Turkey Refaee; Telmo M Silva Filho; Raymond J Acciavatti; Zohaib Salahuddin; Roland Hustinx; Felix M Mottaghy; Andrew D A Maidment; Philippe Lambin
Journal:  Cancers (Basel)       Date:  2022-03-22       Impact factor: 6.639

8.  Combatting the effect of image reconstruction settings on lymphoma [18F]FDG PET metabolic tumor volume assessment using various segmentation methods.

Authors:  Maria C Ferrández; Jakoba J Eertink; Sandeep S V Golla; Sanne E Wiegers; Gerben J C Zwezerijnen; Simone Pieplenbosch; Josée M Zijlstra; Ronald Boellaard
Journal:  EJNMMI Res       Date:  2022-07-29       Impact factor: 3.434

Review 9.  The International Collaboration for Research methods Development in Oncology (CReDO) workshops: shaping the future of global oncology research.

Authors:  Priya Ranganathan; Girish Chinnaswamy; Manju Sengar; Durga Gadgil; Shivakumar Thiagarajan; Balram Bhargava; Christopher M Booth; Marc Buyse; Sanjiv Chopra; Chris Frampton; Satish Gopal; Nick Grant; Mark Krailo; Ruth Langley; Prashant Mathur; Xavier Paoletti; Mahesh Parmar; Arnie Purushotham; Douglas Pyle; Preetha Rajaraman; Martin R Stockler; Richard Sullivan; Soumya Swaminathan; Ian Tannock; Edward Trimble; Rajendra A Badwe; C S Pramesh
Journal:  Lancet Oncol       Date:  2021-06-30       Impact factor: 54.433

10.  The Role of Histogram-Based Textural Analysis of 18F-FDG PET/CT in Evaluating Tumor Heterogeneity and Predicting the Prognosis of Invasive Lung Adenocarcinoma.

Authors:  Hasan Önner; Nazım Coşkun; Mustafa Erol; Meryem İlkay Eren Karanis
Journal:  Mol Imaging Radionucl Ther       Date:  2022-02-02
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