AI-Supported Autonomous Uterus Reconstructions: First Application in MRI Using 3D SPACE with Iterative Denoising.

Autor:	Hausmann D; Department of Radiology, Kantonsspital Baden, Im Ergel 1, Baden, 5404, Switzerland (D.H., A.L., M.F., M.G., K.H.); Department of Radiology and Nuclear Medicine, University Medical Center Mannheim, Heidelberg University, Mannheim, Germany (D.H.). Electronic address: daniel.hausmann@ksb.ch., Lerch A; Department of Radiology, Kantonsspital Baden, Im Ergel 1, Baden, 5404, Switzerland (D.H., A.L., M.F., M.G., K.H.); Institute for Translational Medicine, ETH Zurich, Zurich, Switzerland (A.L); ETH, Department of Health Sciences and Technology (A.L.)., Hitziger S; Mediaire GmbH, Berlin, Germany (S.H., A.L.)., Farkas M; Department of Radiology, Kantonsspital Baden, Im Ergel 1, Baden, 5404, Switzerland (D.H., A.L., M.F., M.G., K.H.)., Weiland E; MR Application Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany (E.W.)., Lemke A; Mediaire GmbH, Berlin, Germany (S.H., A.L.)., Grimm M; Department of Radiology, Kantonsspital Baden, Im Ergel 1, Baden, 5404, Switzerland (D.H., A.L., M.F., M.G., K.H.)., Kubik-Huch RA; Department of Radiology, Kantonsspital Baden, Im Ergel 1, Baden, 5404, Switzerland (D.H., A.L., M.F., M.G., K.H.).
Jazyk:	angličtina
Zdroj:	Academic radiology [Acad Radiol] 2024 Apr; Vol. 31 (4), pp. 1400-1409. Date of Electronic Publication: 2023 Nov 03.
DOI:	10.1016/j.acra.2023.09.035
Abstrakt:	Rationale and Objectives: T2-weighted imaging in at least two orthogonal planes is recommended for assessment of the uterus. To determine whether a convolutional neural network-based algorithm could be used for the re-constructions of uterus axes derived from a 3D SPACE with iterative denoising. Materials and Methods: 50 patients aged 18-81 (mean: 42) years who underwent an MRI examination of the uterus participated voluntarily in this prospective study after informed consent. In addition to a standard MRI pelvis protocol, a 3D SPACE research application sequence was acquired in sagittal orientation. Reconstructions for both the cervix and the cavum in the short and long axes were performed by a research trainee (T), an experienced radiologist (E), and the prototype software (P). In the next step, the reconstructions were evaluated anonymously by two experienced readers according to 5-point-Likert-Scales. In addition, the length of the cervical canal, the length of the cavum and the distance between the tube angles were measured on all reconstructions. Interobserver agreement was assessed for all ratings. Results: For all axes, significant differences were found between the scores of the reconstructions by research T, E and P. P received higher scores and was preferred significantly more often with the exception of the comparison of the reconstruction Cervix short of E (Cervix short: P vs. T: p = 0.02; P vs. E: p = 0.26; Cervix long: P vs. T: p = 0.01; P vs. E: p < 0.01; Cavum short: P vs. T: p = 0.01; P vs. E: p = 0.02; Cavum long: P vs. T: p < 0.01; P vs. E: p < 0.01). Regarding the measured diameters, (length of cervical canal/cavum/distance between tube angles) significantly larger diameters were recorded for P compared to E and T (Cervix long (mm): T: 25.43; E: 25.65; P: 26.65; Cavum short (mm): T: 26.24; E: 25.04; P: 27.33; Cavum long (mm): T: 31.98; E: 32.91; P: 34.41; P vs. T: p < 0.01); P vs. E: p = 0.04). Moderate to substantial agreement was found between Reader 1 and Reader 2 (range: 0.39-0.67). Conclusion: P was able to reconstruct the axes at least as well as or better than E and T. P could thereby lead to workflow facilitation and enable more efficient reporting of uterine MRI. Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Rahel Kubik reports financial support was provided by Gebauer Foundation. The Institute of Clinical Radiology and Nuclear Medicine Mannheim and the Institute of Radiology, Kantonsspital Baden, have research agreements with Siemens Healthcare (Erlangen) and author Dr. Weiland is a Siemens Healthcare employee. The authors Andreas Lemke and Sebastian Hitziger work at a medical start-up (Mediaire GmbH) and co-developed the algorithm. The study was partially funded by a competitive grant from the Gebauer Foundation (50.289 CHF). The study nurse involved in the study, Silke Callies, was partially supported by a non-restricted grant of Bayer (Schweiz) AG. (Copyright © 2024 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.)
Databáze:	MEDLINE
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