ArticleAbdominal radiology (New York)2025
Deep learning reconstruction of diffusion-weighted imaging with single-shot echo-planar imaging in endometrial cancer: a comparison with multi-shot echo-planar imaging.
Article in Abdominal radiology (New York), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Intravoxel incoherent motion imaging with improved image quality by deep learning reconstruction for prediction of lymph-vascular space invasion in patients with cervical cancer.Abdominal radiology (New York) · 2026Article
- Deep learning reconstruction-applied PROPELLER diffusion-weighted imaging in uterine malignancies: a comparison study with MUSE.Japanese journal of radiology · 2026Article
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Abstract
purposeTo evaluate the efficacy of deep learning reconstruction (DLR) in diffusion-weighted imaging (DWI) with single-shot echo-planar imaging (SSEPI) for endometrial cancer, compared to multiplexed sensitivity-encoding (MUSE) DWI.
methodsWe retrospectively reviewed 31 women with surgically confirmed endometrial cancer who underwent preoperative pelvic magnetic resonance imaging (MRI) including DWI. Qualitative analysis including overall image quality, susceptibility artifacts, sharpness of the uterine edge, and lesion conspicuity were compared among conventional SSEPI (SSEPI-C), SSEPI with DLR (SSEPI-DL), and MUSE using the Friedman's test. Quantitative analysis including the apparent diffusion coefficient (ADC) values, noise, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were also compared among three DWI sequences using the Friedman's test. In addition, the diagnostic accuracy for deep myometrial invasion was compared to three DWI sequences using Cochran's Q test.
resultsThe scores of overall image quality, sharpness of the uterine edge, and lesion conspicuity in SSEPI-DL were higher than SSEPI-C (p < 0.001) with no significant difference compared to MUSE (p > 0.05). Noise in SSEPI-DL was lower than SSEPI-C (p < 0.001), with no significant difference compared to MUSE (p > 0.05). SNR and CNR in SSEPI-DL were also superior to SSEPI-C (p < 0.001), and comparable to MUSE (p > 0.05). The diagnostic accuracy for detecting deep myometrial invasion showed no significant difference among SSEPI-C, SSEPI-DL and MUSE (p > 0.05).
conclusionDLR improves the image quality of DWI in endometrial cancer, demonstrating image quality equivalent to that of SSEPI-DL and MUSE. SSEPI-DL can be an alternative to MUSE in female pelvic MRI, with the benefit of significantly shortened scan time.
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