Improved image quality through deep learning acceleration of gradient-echo acquisitions in uterine MRI: first application with the female pelvis
Rationale and Objectives - The aim of this study was to compare the image quality of a deep learning (DL)-accelerated volumetric interpolated breath-hold examination (VIBE) sequence with a standard (ST) VIBE sequence in assessing the uterus. - Materials and methods - Between April and December 2023,...
Gespeichert in:
| Hauptverfasser: | , , , , , , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
May 2025
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| In: |
Academic radiology
Year: 2025, Jahrgang: 32, Heft: 5, Pages: 2776-2786 |
| ISSN: | 1878-4046 |
| DOI: | 10.1016/j.acra.2024.12.021 |
| Online-Zugang: | Verlag, kostenfrei, Volltext: https://doi.org/10.1016/j.acra.2024.12.021 Verlag, kostenfrei, Volltext: https://www.sciencedirect.com/science/article/pii/S1076633224009905 
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| Verfasserangaben: | Daniel Hausmann, MD, Antonio Marketin, MD, Roman Rotzinger, MD, Jakob Heimer, MD, Dominik Nickel, PhD, Elisabeth Weiland, PhD, Rahel A. Kubik-Huch, MD |
MARC
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| 245 | 1 | 0 | |a Improved image quality through deep learning acceleration of gradient-echo acquisitions in uterine MRI |b first application with the female pelvis |c Daniel Hausmann, MD, Antonio Marketin, MD, Roman Rotzinger, MD, Jakob Heimer, MD, Dominik Nickel, PhD, Elisabeth Weiland, PhD, Rahel A. Kubik-Huch, MD |
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| 520 | |a Rationale and Objectives - The aim of this study was to compare the image quality of a deep learning (DL)-accelerated volumetric interpolated breath-hold examination (VIBE) sequence with a standard (ST) VIBE sequence in assessing the uterus. - Materials and methods - Between April and December 2023, a total of 61 female patients (aged 41 ± 14 years) who were referred for an magnetic resonance imaging (MRI) of the pelvis were included in this prospective study, after providing informed consent. All examinations were performed with a 1.5 T MRI scanner. The DL VIBE and ST VIBE were acquired before (noncontrast [NC]) and after (contrast-enhanced [CE]) contrast administration in the sagittal orientation. Three readers independently evaluated the following aspects of the images’ quality using 4-point Likert scales (1 = nondiagnostic; 4 = excellent): global image quality, anatomy delineation, and lesion detection/demarcation. Motion artifacts and noise were also assessed (1 = no artifacts; 4 = severe artifacts). In addition, all three readers selected their preferred sequence and the sequence in which they had the highest diagnostic confidence. - Results - After exclusions, the data for 54 patients were analyzed. The DL VIBE was preferred by all three readers in almost all cases (NC: 99%; CE: 96%) and rated highest for diagnostic confidence (NC: 98%; CE: 90%). The image quality of the DL VIBE was rated statistically significantly better than that of the ST VIBE, with simultaneously reduced noise and motion artifacts (p < 0.01). The image quality of the DL VIBE was predominantly rated with a score of 4 (NC: 54%; CE: 78%), while the image quality of the ST VIBE was mostly rated with a score of 3 (NC: 53%; CE: 80%). The anatomy of the female pelvis was significantly better delineated by the DL VIBE (p < 0.01; log[OR] = 5.3; 95% CI: 3.7-6.8), and lesions were more clearly demarcated (p < 0.01; log[OR] = 6.7; 95% CI: 4.5-8.8). - Conclusion - The DL VIBE sequence showed a significant overall improvement in all image quality characteristics for all readers and was preferred in most cases. The clinical implementation of DL VIBE in MRI of the female pelvis could improve the diagnostic value of the examination. | ||
| 650 | 4 | |a Artificial intelligence | |
| 650 | 4 | |a Deep learning | |
| 650 | 4 | |a Magnetic resonance imaging | |
| 650 | 4 | |a Uterus | |
| 700 | 1 | |a Marketin, Antonio |e VerfasserIn |4 aut | |
| 700 | 1 | |a Rotzinger, Roman |e VerfasserIn |4 aut | |
| 700 | 1 | |a Heimer, Jakob |e VerfasserIn |4 aut | |
| 700 | 1 | |a Nickel, Dominik |e VerfasserIn |4 aut | |
| 700 | 1 | |a Weiland, Elisabeth |e VerfasserIn |4 aut | |
| 700 | 1 | |a Kubik-Huch, Rahel A. |e VerfasserIn |4 aut | |
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