Literature DB >> 32575082

Standardization of CT radiomics features for multi-center analysis: impact of software settings and parameters.

Arianna Defeudis1, Cristina De Mattia2, Francesco Rizzetto3, Francesca Calderoni3, Simone Mazzetti1, Alberto Torresin3, Angelo Vanzulli3, Daniele Regge1, Valentina Giannini4.   

Abstract

The aim of this multicentric study is an inter-center benchmarking, to assess how different set tools applied to the same radiomics workflow affected the radiomics features (RFs) values. This topic is of key importance to start collaboration between different centers and to bring radiomic studies from benchmark to bedside. A per-lesion analysis was performed on 56 metastases (mts) selected from 14 patients. A single radiologist performed the segmentation of all mts and RFs were extracted from the same segmentation, but using different software and file format. Potential sources of discrepancies were evaluated. The intraclass correlation coefficient was used to describe how strongly the same radiomic measurements calculated in the two different centers resemble each other. Moreover, means of the relative differences of each RF were calculated, compared and gradually reduced. We showed that, after matching all formulas, discrepancies in RFs calculation between two centers ranged from 1% to 277%. Therefore, we evaluated other sources of variability using a stepwise approach, which led us to reduce the inter-center discrepancies to 0% for 22/25 RFs and below 2% for 3 RFs out of 25. In this study we demonstrated that different radiomic applications and masks formats might strongly impact the computation of some RFs. Therefore, when dealing with multi-center studies it is mandatory to adopt all strategies that can help in limiting the differences, thus keeping in mind the feasibility of these strategies in large cohort studies.
© 2020 Institute of Physics and Engineering in Medicine.

Entities:  

Keywords:  CT images; multi-center study; radiomics; standardization

Year:  2020        PMID: 32575082     DOI: 10.1088/1361-6560/ab9f61

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  4 in total

1.  Impact of inter-reader contouring variability on textural radiomics of colorectal liver metastases.

Authors:  Francesco Rizzetto; Francesca Calderoni; Cristina De Mattia; Arianna Defeudis; Valentina Giannini; Simone Mazzetti; Lorenzo Vassallo; Silvia Ghezzi; Andrea Sartore-Bianchi; Silvia Marsoni; Salvatore Siena; Daniele Regge; Alberto Torresin; Angelo Vanzulli
Journal:  Eur Radiol Exp       Date:  2020-11-10

Review 2.  Radiomics and Magnetic Resonance Imaging of Rectal Cancer: From Engineering to Clinical Practice.

Authors:  Francesca Coppola; Valentina Giannini; Michela Gabelloni; Jovana Panic; Arianna Defeudis; Silvia Lo Monaco; Arrigo Cattabriga; Maria Adriana Cocozza; Luigi Vincenzo Pastore; Michela Polici; Damiano Caruso; Andrea Laghi; Daniele Regge; Emanuele Neri; Rita Golfieri; Lorenzo Faggioni
Journal:  Diagnostics (Basel)       Date:  2021-04-23

3.  Delta-Radiomics Predicts Response to First-Line Oxaliplatin-Based Chemotherapy in Colorectal Cancer Patients with Liver Metastases.

Authors:  Valentina Giannini; Laura Pusceddu; Arianna Defeudis; Giulia Nicoletti; Giovanni Cappello; Simone Mazzetti; Andrea Sartore-Bianchi; Salvatore Siena; Angelo Vanzulli; Francesco Rizzetto; Elisabetta Fenocchio; Luca Lazzari; Alberto Bardelli; Silvia Marsoni; Daniele Regge
Journal:  Cancers (Basel)       Date:  2022-01-04       Impact factor: 6.639

Review 4.  Radiomics in Oncology, Part 2: Thoracic, Genito-Urinary, Breast, Neurological, Hematologic and Musculoskeletal Applications.

Authors:  Damiano Caruso; Michela Polici; Marta Zerunian; Francesco Pucciarelli; Gisella Guido; Tiziano Polidori; Federica Landolfi; Matteo Nicolai; Elena Lucertini; Mariarita Tarallo; Benedetta Bracci; Ilaria Nacci; Carlotta Rucci; Marwen Eid; Elsa Iannicelli; Andrea Laghi
Journal:  Cancers (Basel)       Date:  2021-05-29       Impact factor: 6.639

  4 in total

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