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Repeatability of Multiparametric Prostate MRI Radiomics Features

Institution:
Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Publication Date:
Jul-2019
Journal:
Sci Rep
Volume Number:
9
Issue Number:
1
Pages:
9441
Citation:
Sci Rep. 2019 Jul 1;9(1):9441.
PubMed ID:
31263116
PMCID:
PMC6602944
Appears in Collections:
NCIGT, SPL
Sponsors:
U24 CA180918/U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI)/
U01 CA151261/U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI)/
U24 CA194354/U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI)/
U01 CA190234/U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI)/
P41 EB015898/U.S. Department of Health & Human Services | NIH | National Institute of Biomedical Imaging and Bioengineering (NIBIB)/
Generated Citation:
Schwier M., van Griethuysen J., Vangel M.G., Pieper S., Peled S., Tempany C., Aerts H.J.W.L., Kikinis R., Fennessy F.M., Fedorov A. Repeatability of Multiparametric Prostate MRI Radiomics Features. Sci Rep. 2019 Jul 1;9(1):9441. PMID: 31263116. PMCID: PMC6602944.
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In this study we assessed the repeatability of radiomics features on small prostate tumors using test-retest Multiparametric Magnetic Resonance Imaging (mpMRI). The premise of radiomics is that quantitative image-based features can serve as biomarkers for detecting and characterizing disease. For such biomarkers to be useful, repeatability is a basic requirement, meaning its value must remain stable between two scans, if the conditions remain stable. We investigated repeatability of radiomics features under various preprocessing and extraction configurations including various image normalization schemes, different image pre-filtering, and different bin widths for image discretization. Although we found many radiomics features and preprocessing combinations with high repeatability (Intraclass Correlation Coefficient > 0.85), our results indicate that overall the repeatability is highly sensitive to the processing parameters. Neither image normalization, using a variety of approaches, nor the use of pre-filtering options resulted in consistent improvements in repeatability. We urge caution when interpreting radiomics features and advise paying close attention to the processing configuration details of reported results. Furthermore, we advocate reporting all processing details in radiomics studies and strongly recommend the use of open source implementations.