Repeatability and Reproducibility of Radiomic Features: A Systematic Review.
Purpose: An ever-growing number of predictive models used to inform clinical decision making have included quantitative, computer-extracted imaging biomarkers, or "radiomic features." Broadly generalizable validity of radiomics-assisted models may be impeded by concerns about reproducibility. We off...
| Publicado en: | International Journal of Radiation Oncology, Biology, Physics Vol. 102; no. 4; pp. 1143 - 1159 |
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| Autores principales: | , , , |
| Formato: | research systematic review tables/charts Journal Article |
| Publicado: |
Pergamon Press - An Imprint of Elsevier Science
Nov2018
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=132486453&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 132486453 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 03603016 1ZQ jtl: International Journal of Radiation Oncology, Biology, Physics issn: 03603016 maglogo: N pubinfo: dt: Nov2018 vid: 102 iid: 4 pid: 2410 pub: Pergamon Press - An Imprint of Elsevier Science artinfo: ui: 132486453 132486453 NLM30170872 132486453 10.1016/j.ijrobp.2018.05.053 NLM30170872 132486453 ppf: 1143 ppct: 16 formats: tig: atl: Repeatability and Reproducibility of Radiomic Features: A Systematic Review. aug: au: Traverso, Alberto Wee, Leonard Dekker, Andre Gillies, Robert affil: Department of Radiation Oncology, MAASTRO Clinic, Maastricht, The Netherlands sug: subj: Image Processing, Computer Assisted Methods Phantoms, Imaging Reproducibility of Results Neoplasms Human Funding Source Systematic Review ab: Purpose: An ever-growing number of predictive models used to inform clinical decision making have included quantitative, computer-extracted imaging biomarkers, or "radiomic features." Broadly generalizable validity of radiomics-assisted models may be impeded by concerns about reproducibility. We offer a qualitative synthesis of 41 studies that specifically investigated the repeatability and reproducibility of radiomic features, derived from a systematic review of published peer-reviewed literature.Methods and Materials: The PubMed electronic database was searched using combinations of the broad Haynes and Ingui filters along with a set of text words specific to cancer, radiomics (including texture analyses), reproducibility, and repeatability. This review has been reported in compliance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. From each full-text article, information was extracted regarding cancer type, class of radiomic feature examined, reporting quality of key processing steps, and statistical metric used to segregate stable features.Results: Among 624 unique records, 41 full-text articles were subjected to review. The studies primarily addressed non-small cell lung cancer and oropharyngeal cancer. Only 7 studies addressed in detail every methodologic aspect related to image acquisition, preprocessing, and feature extraction. The repeatability and reproducibility of radiomic features are sensitive at various degrees to processing details such as image acquisition settings, image reconstruction algorithm, digital image preprocessing, and software used to extract radiomic features. First-order features were overall more reproducible than shape metrics and textural features. Entropy was consistently reported as one of the most stable first-order features. There was no emergent consensus regarding either shape metrics or textural features; however, coarseness and contrast appeared among the least reproducible.Conclusions: Investigations of feature repeatability and reproducibility are currently limited to a small number of cancer types. Reporting quality could be improved regarding details of feature extraction software, digital image manipulation (preprocessing), and the cutoff value used to distinguish stable features. pubtype: Academic Journal doctype: research systematic review tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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