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      Reproducibility of Aorta Segmentation on 4D Flow MRI in Healthy Volunteers

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          Abstract

          Background

          Hemodynamic aorta parameters can be derived from 4D flow MRI, but this requires lumen segmentation. In both commercially available and research 4D flow MRI software tools, lumen segmentation is mostly (semi‐)automatically performed and subsequently manually improved by an observer. Since the segmentation variability, together with 4D flow MRI data and image processing algorithms, will contribute to the reproducibility of patient‐specific flow properties, the observer's lumen segmentation reproducibility and repeatability needs to be assessed.

          Purpose

          To determine the interexamination, interobserver reproducibility, and intraobserver repeatability of aortic lumen segmentation on 4D flow MRI.

          Study Type

          Prospective and retrospective.

          Population

          A healthy volunteer cohort of 10 subjects who underwent 4D flow MRI twice. Also, a clinical cohort of six subjects who underwent 4D flow MRI once.

          Field Strength/Sequence

          3T; time‐resolved three‐directional and 3D velocity‐encoded sequence (4D flow MRI).

          Assessment

          The thoracic aorta was segmented on the 4D flow MRI in five systolic phases. By positioning six planes perpendicular to a segmentation's centerline, the aorta was divided into five segments. The volume, surface area, centerline length, maximal diameter, and curvature radius were determined for each segment.

          Statistical Tests

          To assess the reproducibility, the coefficient of variation (COV), Pearson correlation coefficient ( r), and intraclass correlation coefficient (ICC) were calculated.

          Results

          The interexamination and interobserver reproducibility and intraobserver repeatability were comparable for each parameter. For both cohorts there was very good reproducibility and repeatability for volume, surface area, and centerline length (COV = 10–32%, r = 0.54–0.95 and ICC = 0.65–0.99), excellent reproducibility and repeatability for maximal diameter (COV = 3–11%, r = 0.94–0.99, ICC = 0.94–0.99), and good reproducibility and repeatability for curvature radius (COV = 25–62%, r = 0.73–0.95, ICC = 0.84–0.97).

          Data Conclusion

          This study demonstrated no major reproducibility and repeatability limitations for 4D flow MRI aortic lumen segmentation.

          Level of Evidence

          3

          Technical Efficacy Stage

          2

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          Most cited references32

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          SciPy 1.0: fundamental algorithms for scientific computing in Python

          SciPy is an open-source scientific computing library for the Python programming language. Since its initial release in 2001, SciPy has become a de facto standard for leveraging scientific algorithms in Python, with over 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories and millions of downloads per year. In this work, we provide an overview of the capabilities and development practices of SciPy 1.0 and highlight some recent technical developments.
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            STATISTICAL METHODS FOR ASSESSING AGREEMENT BETWEEN TWO METHODS OF CLINICAL MEASUREMENT

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              The NumPy Array: A Structure for Efficient Numerical Computation

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                Author and article information

                Contributors
                j.f.juffermans@lumc.nl
                Journal
                J Magn Reson Imaging
                J Magn Reson Imaging
                10.1002/(ISSN)1522-2586
                JMRI
                Journal of Magnetic Resonance Imaging
                John Wiley & Sons, Inc. (Hoboken, USA )
                1053-1807
                1522-2586
                11 November 2020
                April 2021
                : 53
                : 4 ( doiID: 10.1002/jmri.v53.4 )
                : 1268-1279
                Affiliations
                [ 1 ] Department of Radiology Leiden University Medical Center Leiden The Netherlands
                [ 2 ] Department of Paediatric Cardiology Leiden University Medical Center Leiden The Netherlands
                Author notes
                [*] [* ] Address reprint requests to: J.F.J., Albinusdreef 2, 2333 ZA Leiden, The Netherlands. E‐mail: j.f.juffermans@ 123456lumc.nl

                Author information
                https://orcid.org/0000-0001-8914-8279
                https://orcid.org/0000-0003-1946-1715
                Article
                JMRI27431
                10.1002/jmri.27431
                7984392
                33179389
                7b3d3bd0-5d68-44d3-87bf-9e0b8cb92235
                © 2020 The Authors. Journal of Magnetic Resonance Imaging published by Wiley Periodicals LLC. on behalf of International Society for Magnetic Resonance in Medicine.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 20 October 2020
                : 16 June 2020
                : 20 October 2020
                Page count
                Figures: 6, Tables: 5, Pages: 12, Words: 5895
                Funding
                Funded by: Hartstichting , open-funder-registry 10.13039/501100002996;
                Award ID: CVON2017‐08‐RADAR
                Categories
                Original Research
                Original Research
                Cardiac
                Custom metadata
                2.0
                April 2021
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.0.0 mode:remove_FC converted:22.03.2021

                Radiology & Imaging
                aorta,segmentation,aortic diameter,4d flow mri,reproducibility,repeatability
                Radiology & Imaging
                aorta, segmentation, aortic diameter, 4d flow mri, reproducibility, repeatability

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