Helmholtz Gemeinschaft

Search
Browse
Statistics
Feeds

Whole-body magnetic resonance imaging in the large population-based German National Cohort study: predictive capability of automated image quality assessment for protocol repetitions

[img]
Preview
PDF (Accepted Manuscript (final draft) incl. Suppl. Information) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
1MB

Item Type:Article
Title:Whole-body magnetic resonance imaging in the large population-based German National Cohort study: predictive capability of automated image quality assessment for protocol repetitions
Creators Name:Schuppert, C. and von Krüchten, R. and Hirsch, J.G. and Rospleszcz, S. and Hoinkiss, D.C. and Selder, S. and Köhn, A. and von Stackelberg, O. and Peters, A. and Völzke, H. and Kröncke, T. and Niendorf, T. and Forsting, M. and Hosten, N. and Hendel, T. and Pischon, T. and Jöckel, K.H. and Kaaks, R. and Bamberg, F. and Kauczor, H.U. and Günther, M. and Schlett, C.L.
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.
Keywords:Cohort Studies, Magnetic Resonance Imaging, Multicenter Studies as Topic, Prospective Studies, Reproducibility of Results, Retrospective Studies, Whole Body Imaging
Source:Investigative Radiology
ISSN:0020-9996
Publisher:Lippincott Williams & Wilkins
Volume:57
Number:7
Page Range:478-487
Date:1 July 2022
Additional Information:Copyright © 2022 Wolters Kluwer Health, Inc. All rights reserved.
Official Publication:https://doi.org/10.1097/RLI.0000000000000861
PubMed:View item in PubMed

Repository Staff Only: item control page

Downloads

Downloads per month over past year

Open Access
MDC Library