Christopher Schuppert1, Ricarda von Krüchten2, Jochen G Hirsch3, Susanne Rospleszcz, Daniel C Hoinkiss3, Sonja Selder4, Alexander Köhn3, Oyunbileg von Stackelberg1, Annette Peters, Henry Völzke, Thomas Kröncke5, Thoralf Niendorf6, Michael Forsting7, Norbert Hosten8, Thomas Hendel9, Tobias Pischon10, Karl-Heinz Jöckel11, Rudolf Kaaks12, Fabian Bamberg2, Hans-Ulrich Kauczor1, Matthias Günther3, Christopher L Schlett2. 1. From the Department of Diagnostic and Interventional Radiology, Heidelberg University Hospital, Heidelberg. 2. Department of Diagnostic and Interventional Radiology, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg. 3. Fraunhofer Institute for Digital Medicine MEVIS, Bremen. 4. Department of Radiology, Ludwig Maximilian University Hospital, Munich. 5. Department of Diagnostic and Interventional Radiology, University Hospital Augsburg, University of Augsburg, Augsburg. 6. Berlin Ultrahigh Field Facility, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin. 7. Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, University Duisburg-Essen, Essen. 8. Department of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald. 9. Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg. 10. Molecular Epidemiology Research Group, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin. 11. Institute for Medical Informatics, Biometry and Epidemiology, University Hospital Essen, University Duisburg-Essen, Essen. 12. Division of Cancer Epidemiology, German Cancer Research Center, Heidelberg, Germany.
Abstract
BACKGROUND: Reproducible image quality is of high relevance for large cohort studies and can be challenging for magnetic resonance imaging (MRI). Automated image quality assessment may contribute to conducting radiologic studies effectively. PURPOSE: The aims of this study were to assess protocol repetition frequency in population-based whole-body MRI along with its effect on examination time and to examine the applicability of automated image quality assessment for predicting decision-making regarding repeated acquisitions. MATERIALS AND METHODS: All participants enrolled in the prospective, multicenter German National Cohort (NAKO) study who underwent whole-body MRI at 1 of 5 sites from 2014 to 2016 were included in this analysis (n = 11,347). A standardized examination program of 12 protocols was used. Acquisitions were carried out by certified radiologic technologists, who were authorized to repeat protocols based on their visual perception of image quality. Eleven image quality parameters were derived fully automatically from the acquired images, and their discrimination ability regarding baseline acquisitions and repetitions was tested. RESULTS: At least 1 protocol was repeated in 12% (n = 1359) of participants, and more than 1 protocol in 1.6% (n = 181). The repetition frequency differed across protocols (P < 0.001), imaging sites (P < 0.001), and over the study period (P < 0.001). The mean total scan time was 62.6 minutes in participants without and 67.4 minutes in participants with protocol repetitions (mean difference, 4.8 minutes; 95% confidence interval, 4.5-5.2 minutes). Ten of the automatically derived image quality parameters were individually retrospectively predictive for the repetition of particular protocols; for instance, "signal-to-noise ratio" alone provided an area under the curve of 0.65 (P < 0.001) for repetition of the Cardio Cine SSFP SAX protocol. Combinations generally improved prediction ability, as exemplified by "image sharpness" plus "foreground ratio" yielding an area under the curve of 0.89 (P < 0.001) for repetition of the Neuro T1w 3D MPRAGE protocol, versus 0.85 (P < 0.001) and 0.68 (P < 0.001) as individual parameters. CONCLUSIONS: Magnetic resonance imaging protocol repetitions were necessary in approximately 12% of scans even in the highly standardized setting of a large cohort study. Automated image quality assessment shows predictive value for the technologists' decision to perform protocol repetitions and has the potential to improve imaging efficiency.
BACKGROUND: Reproducible image quality is of high relevance for large cohort studies and can be challenging for magnetic resonance imaging (MRI). Automated image quality assessment may contribute to conducting radiologic studies effectively. PURPOSE: The aims of this study were to assess protocol repetition frequency in population-based whole-body MRI along with its effect on examination time and to examine the applicability of automated image quality assessment for predicting decision-making regarding repeated acquisitions. MATERIALS AND METHODS: All participants enrolled in the prospective, multicenter German National Cohort (NAKO) study who underwent whole-body MRI at 1 of 5 sites from 2014 to 2016 were included in this analysis (n = 11,347). A standardized examination program of 12 protocols was used. Acquisitions were carried out by certified radiologic technologists, who were authorized to repeat protocols based on their visual perception of image quality. Eleven image quality parameters were derived fully automatically from the acquired images, and their discrimination ability regarding baseline acquisitions and repetitions was tested. RESULTS: At least 1 protocol was repeated in 12% (n = 1359) of participants, and more than 1 protocol in 1.6% (n = 181). The repetition frequency differed across protocols (P < 0.001), imaging sites (P < 0.001), and over the study period (P < 0.001). The mean total scan time was 62.6 minutes in participants without and 67.4 minutes in participants with protocol repetitions (mean difference, 4.8 minutes; 95% confidence interval, 4.5-5.2 minutes). Ten of the automatically derived image quality parameters were individually retrospectively predictive for the repetition of particular protocols; for instance, "signal-to-noise ratio" alone provided an area under the curve of 0.65 (P < 0.001) for repetition of the Cardio Cine SSFP SAX protocol. Combinations generally improved prediction ability, as exemplified by "image sharpness" plus "foreground ratio" yielding an area under the curve of 0.89 (P < 0.001) for repetition of the Neuro T1w 3D MPRAGE protocol, versus 0.85 (P < 0.001) and 0.68 (P < 0.001) as individual parameters. CONCLUSIONS: Magnetic resonance imaging protocol repetitions were necessary in approximately 12% of scans even in the highly standardized setting of a large cohort study. Automated image quality assessment shows predictive value for the technologists' decision to perform protocol repetitions and has the potential to improve imaging efficiency.
Authors: Alexander Rau; Martin Soschynski; Jana Taron; Philipp Ruile; Christopher L Schlett; Fabian Bamberg; Tobias Krauss Journal: Radiologie (Heidelb) Date: 2022-08-25