Oyama Kazuki, Ichinohe Fumihito, Adachi Yasuo, Kito Yoshihiro, Maruyama Katsuya, Mitsuda Minoru, Benkert Thomas, Darwish Omar, Fujinaga Yasunari
Department of Radiology, Shinshu University School of Medicine, 3-1-1 Asahi, Matsumoto, Nagano, 390-8621, Japan.
Radiology Division, Shinshu University Hospital, 3-1-1 Asahi, Matsumoto, Nagano, 390-8621, Japan.
Jpn J Radiol. 2025 Apr 26. doi: 10.1007/s11604-025-01790-w.
This study aimed to evaluate the efficacy of deep learning-based reconstruction (DLR) in improving pancreatic diffusion-weighted imaging (DWI) quality.
In total, 117 patients (mean age of 68.0 ± 12.9 years) suspected of pancreatic diseases underwent magnetic resonance imaging (MRI) between July and December 2023. MRI sequences included respiratory-gated conventional diffusion-weighted images (RGC-DWIs), respiratory-gated diffusion-weighted images with deep learning-based reconstruction (DLR) (RGDLR-DWIs), and breath-hold diffusion-weighted images with DLR (BHDLR-DWIs) (short TE and long TE equal to other DWIs) at a 3 T MR system. Among these patients, 27 had solid lesions. Two radiologists qualitatively assessed pancreatic shape, main pancreatic duct (MPD) visualization, and solid lesion conspicuity using a 5-point scale. Quantitative analysis included apparent diffusion coefficient (ADC) values for pancreatic parenchyma and solid lesions, signal-to-noise ratio (SNR), pancreas-to-muscle signal-intensity ratio (PM-SIR) and lesion-to-pancreas signal-intensity ratio (LP-SIR). Differences among DWI sequences were analyzed using Friedman's and Bonferroni's tests.
Qualitatively, BHDLR-DWIs (short TE) had the highest scores for pancreatic shape and MPD but lowest for solid lesions visibility, whereas RGDLR-DWIs had the highest score for solid lesions. Quantitatively, BHDLR-DWIs (short TE) had the lowest ADC values for pancreatic parenchyma and solid lesions, with the highest PM-SIR. There was no significant difference between BHDLR-DWIs (short TE) and RGDLR-DWIs for solid lesion ADC values. RGC-DWIs had the highest SNR, though differences from RGDLR-DWIs and BHDLR-DWIs (short TE) were not significant. Although LP-SIR in RGDLR-DWIs were the lowest, the difference was not significant.
BHDLR-DWIs (short TE) provided the best pancreatic morphology image quality, whereas RGDLR-DWIs were superior for solid lesion detection.
本研究旨在评估基于深度学习的重建（DLR）对提高胰腺扩散加权成像（DWI）质量的效果。
2023年7月至12月期间，共有117例疑似胰腺疾病的患者（平均年龄68.0±12.9岁）接受了磁共振成像（MRI）检查。MRI序列包括在3T磁共振系统上的呼吸门控常规扩散加权图像（RGC-DWI）、基于深度学习重建的呼吸门控扩散加权图像（RGDLR-DWI）以及屏气扩散加权图像（BHDLR-DWI）（短TE和长TE与其他DWI相同）。在这些患者中，27例有实性病变。两名放射科医生使用5分制对胰腺形态、主胰管（MPD）显示情况以及实性病变的清晰度进行了定性评估。定量分析包括胰腺实质和实性病变的表观扩散系数（ADC）值、信噪比（SNR）、胰腺与肌肉信号强度比（PM-SIR）以及病变与胰腺信号强度比（LP-SIR）。使用Friedman检验和Bonferroni检验分析DWI序列之间的差异。
定性方面，BHDLR-DWI（短TE）在胰腺形态和MPD方面得分最高，但在实性病变可见性方面得分最低，而RGDLR-DWI在实性病变方面得分最高。定量方面，BHDLR-DWI（短TE）的胰腺实质和实性病变ADC值最低，PM-SIR最高。BHDLR-DWI（短TE）与RGDLR-DWI在实性病变ADC值方面无显著差异。RGC-DWI的SNR最高，尽管与RGDLR-DWI和BHDLR-DWI（短TE）的差异不显著。尽管RGDLR-DWI中的LP-SIR最低，但差异不显著。
BHDLR-DWI（短TE）提供了最佳的胰腺形态图像质量，而RGDLR-DWI在实性病变检测方面更具优势。
