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      Reproducibility of radiomics quality score: an intra- and inter-rater reliability study

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          Abstract

          Objectives

          To investigate the intra- and inter-rater reliability of the total radiomics quality score (RQS) and the reproducibility of individual RQS items’ score in a large multireader study.

          Methods

          Nine raters with different backgrounds were randomly assigned to three groups based on their proficiency with RQS utilization: Groups 1 and 2 represented the inter-rater reliability groups with or without prior training in RQS, respectively; group 3 represented the intra-rater reliability group. Thirty-three original research papers on radiomics were evaluated by raters of groups 1 and 2. Of the 33 papers, 17 were evaluated twice with an interval of 1 month by raters of group 3. Intraclass coefficient (ICC) for continuous variables, and Fleiss’ and Cohen’s kappa ( k) statistics for categorical variables were used.

          Results

          The inter-rater reliability was poor to moderate for total RQS (ICC 0.30–055, p < 0.001) and very low to good for item’s reproducibility ( k − 0.12 to 0.75) within groups 1 and 2 for both inexperienced and experienced raters. The intra-rater reliability for total RQS was moderate for the less experienced rater (ICC 0.522, p = 0.009), whereas experienced raters showed excellent intra-rater reliability (ICC 0.91–0.99, p < 0.001) between the first and second read. Intra-rater reliability on RQS items’ score reproducibility was higher and most of the items had moderate to good intra-rater reliability ( k − 0.40 to 1).

          Conclusions

          Reproducibility of the total RQS and the score of individual RQS items is low. There is a need for a robust and reproducible assessment method to assess the quality of radiomics research.

          Clinical relevance statement

          There is a need for reproducible scoring systems to improve quality of radiomics research and consecutively close the translational gap between research and clinical implementation.

          Key Points

          • Radiomics quality score has been widely used for the evaluation of radiomics studies.

          • Although the intra-rater reliability was moderate to excellent, intra- and inter-rater reliability of total score and point-by-point scores were low with radiomics quality score.

          • A robust, easy-to-use scoring system is needed for the evaluation of radiomics research.

          Supplementary Information

          The online version contains supplementary material available at 10.1007/s00330-023-10217-x.

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          Most cited references58

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          A Guideline of Selecting and Reporting Intraclass Correlation Coefficients for Reliability Research.

          Intraclass correlation coefficient (ICC) is a widely used reliability index in test-retest, intrarater, and interrater reliability analyses. This article introduces the basic concept of ICC in the content of reliability analysis.
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            Interrater reliability: the kappa statistic

            The kappa statistic is frequently used to test interrater reliability. The importance of rater reliability lies in the fact that it represents the extent to which the data collected in the study are correct representations of the variables measured. Measurement of the extent to which data collectors (raters) assign the same score to the same variable is called interrater reliability. While there have been a variety of methods to measure interrater reliability, traditionally it was measured as percent agreement, calculated as the number of agreement scores divided by the total number of scores. In 1960, Jacob Cohen critiqued use of percent agreement due to its inability to account for chance agreement. He introduced the Cohen’s kappa, developed to account for the possibility that raters actually guess on at least some variables due to uncertainty. Like most correlation statistics, the kappa can range from −1 to +1. While the kappa is one of the most commonly used statistics to test interrater reliability, it has limitations. Judgments about what level of kappa should be acceptable for health research are questioned. Cohen’s suggested interpretation may be too lenient for health related studies because it implies that a score as low as 0.41 might be acceptable. Kappa and percent agreement are compared, and levels for both kappa and percent agreement that should be demanded in healthcare studies are suggested.
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              • Record: found
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              • Article: not found

              Radiomics: Images Are More than Pictures, They Are Data

              This report describes the process of radiomics, its challenges, and its potential power to facilitate better clinical decision making, particularly in the care of patients with cancer.
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                Author and article information

                Contributors
                tugba.akincidantonoli@unibas.ch
                Journal
                Eur Radiol
                Eur Radiol
                European Radiology
                Springer Berlin Heidelberg (Berlin/Heidelberg )
                0938-7994
                1432-1084
                21 September 2023
                21 September 2023
                2024
                : 34
                : 4
                : 2791-2804
                Affiliations
                [1 ]GRID grid.440128.b, ISNI 0000 0004 0457 2129, Institute of Radiology and Nuclear Medicine, , Cantonal Hospital Baselland, ; Liestal, Switzerland
                [2 ]GRID grid.419457.a, ISNI 0000 0004 1758 0179, Division of Radiology, , Istituto Dermopatico dell’Immacolata (IDI) IRCCS, ; Rome, Italy
                [3 ]Institute of Radiology, University Hospital of Padova, ( https://ror.org/05xrcj819) Padua, Italy
                [4 ]Department of Advanced Biomedical Sciences, University of Naples “Federico II”, ( https://ror.org/05290cv24) Naples, Italy
                [5 ]Department of Medical Imaging, University Hospital of Heraklion, ( https://ror.org/0312m2266) Crete, Greece
                [6 ]Department of Radiology, School of Medicine, University of Crete, ( https://ror.org/00dr28g20) Heraklion, Crete Greece
                [7 ]Section of Radiology, Department of Biomedicine, Neuroscience and Advanced Diagnostics (BiND), University of Palermo, ( https://ror.org/044k9ta02) Palermo, Italy
                [8 ]MVZ Diagnostikum Berlin Gmbh, Diagnostisches Zentrum, Berlin, Germany
                [9 ]Department of Translational Research, Academic Radiology, University of Pisa, ( https://ror.org/03ad39j10) Pisa, Italy
                [10 ]GRID grid.415738.c, ISNI 0000 0000 9216 2496, Radiology Department, Research Institute of Children Oncology and Haematology of National Medical Research Center of Oncology n.a.N.N. Blokhin of Ministry of Health of RF, ; Moscow, Russia
                [11 ]Department of Biomedical Sciences, Humanitas University, ( https://ror.org/020dggs04) Pieve Emanuele, Milan, Italy
                [12 ]GRID grid.4494.d, ISNI 0000 0000 9558 4598, Department of Radiation Oncology, , University of Groningen, University Medical Center Groningen, ; Groningen, The Netherlands
                [13 ]Department of Radiology, University Medical Center Freiburg, ( https://ror.org/03vzbgh69) Freiburg, Germany
                [14 ]GRID grid.411097.a, ISNI 0000 0000 8852 305X, Department of Radiology, , University Hospital of Cologne, ; Cologne, Germany
                [15 ]Department of Radiology, University Hospital of Frankfurt, ( https://ror.org/03f6n9m15) Frankfurt, Germany
                [16 ]Department of Medicine, Surgery and Dentistry, University of Salerno, ( https://ror.org/0192m2k53) Baronissi, Italy
                Author information
                http://orcid.org/0000-0002-7237-711X
                Article
                10217
                10.1007/s00330-023-10217-x
                10957586
                37733025
                a624a44a-0b27-445a-ac49-5867407a8c1b
                © The Author(s) 2023

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 17 May 2023
                : 3 July 2023
                : 30 July 2023
                Funding
                Funded by: University of Basel
                Categories
                Imaging Informatics and Artificial Intelligence
                Custom metadata
                © European Society of Radiology 2024

                Radiology & Imaging
                reproducibility of results,artificial intelligence,radiomics,inter-observer variability,intra-observer variability

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