Faster Elbow MRI with Deep Learning Reconstruction—Assessment of Image Quality, Diagnostic Confidence, and Anatomy Visualization Compared to Standard Imaging

Author:

Herrmann Judith1ORCID,Afat Saif1ORCID,Gassenmaier Sebastian1ORCID,Grunz Jan-Peter2ORCID,Koerzdoerfer Gregor3ORCID,Lingg Andreas1ORCID,Almansour Haidara1,Nickel Dominik3ORCID,Patzer Theresa Sophie2ORCID,Werner Sebastian1

Affiliation:

1. Department of Diagnostic and Interventional Radiology, University Hospital Tübingen, 72076 Tübingen, Germany

2. Department of Diagnostic and Interventional Radiology, University Hospital Würzburg, 97080 Würzburg, Germany

3. MR Application Predevelopment, Siemens Healthcare GmbH, 91052 Erlangen, Germany

Abstract

Objective: The objective of this study was to evaluate a deep learning (DL) reconstruction for turbo spin echo (TSE) sequences of the elbow regarding image quality and visualization of anatomy. Materials and Methods: Between October 2020 and June 2021, seventeen participants (eight patients, nine healthy subjects; mean age: 43 ± 16 (20–70) years, eight men) were prospectively included in this study. Each patient underwent two examinations: standard MRI, including TSE sequences reconstructed with a generalized autocalibrating partial parallel acquisition reconstruction (TSESTD), and prospectively undersampled TSE sequences reconstructed with a DL reconstruction (TSEDL). Two radiologists evaluated the images concerning image quality, noise, edge sharpness, artifacts, diagnostic confidence, and delineation of anatomical structures using a 5-point Likert scale, and rated the images concerning the detection of common pathologies. Results: Image quality was significantly improved in TSEDL (mean 4.35, IQR 4–5) compared to TSESTD (mean 3.76, IQR 3–4, p = 0.008). Moreover, TSEDL showed decreased noise (mean 4.29, IQR 3.5–5) compared to TSESTD (mean 3.35, IQR 3–4, p = 0.004). Ratings for delineation of anatomical structures, artifacts, edge sharpness, and diagnostic confidence did not differ significantly between TSEDL and TSESTD (p > 0.05). Inter-reader agreement was substantial to almost perfect (κ = 0.628–0.904). No difference was found concerning the detection of pathologies between the readers and between TSEDL and TSESTD. Using DL, the acquisition time could be reduced by more than 35% compared to TSESTD. Conclusion: TSEDL provided improved image quality and decreased noise while receiving equal ratings for edge sharpness, artifacts, delineation of anatomical structures, diagnostic confidence, and detection of pathologies compared to TSESTD. Providing more than a 35% reduction of acquisition time, TSEDL may be clinically relevant for elbow imaging due to increased patient comfort and higher patient throughput.

Publisher

MDPI AG

Subject

Clinical Biochemistry

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