基于深度学习重建的快速T2加权成像：前列腺癌根治术患者的图像质量和诊断性能评估
Fast T2-Weighted Imaging With Deep Learning-Based Reconstruction: Evaluation of Image Quality and Diagnostic Performance in Patients Undergoing Radical Prostatectomy.
作者信息
Park Jae Chun, Park Kye Jin, Park Mi Yeon, Kim Mi-Hyun, Kim Jeong Kon
机构信息
Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea.
出版信息
J Magn Reson Imaging. 2022 Jun;55(6):1735-1744. doi: 10.1002/jmri.27992. Epub 2021 Nov 13.
BACKGROUND
Deep learning-based reconstruction (DLR) can potentially improve image quality by reduction of noise, thereby enabling fast acquisition of magnetic resonance imaging (MRI). However, a systematic evaluation of image quality and diagnostic performance of MRI using short acquisition time with DLR has rarely been investigated in men with prostate cancer.
PURPOSE
To assess the image quality and diagnostic performance of MRI using short acquisition time with DLR for the evaluation of extraprostatic extension (EPE).
STUDY TYPE
Retrospective.
POPULATION
One hundred and nine men.
FIELD STRENGTH/SEQUENCE: 3 T; turbo spin echo T2-weighted images (T2WI), echo-planar diffusion-weighted, and spoiled gradient echo dynamic contrast-enhanced images.
ASSESSMENT
To compare image quality, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) and subjective analysis using Likert scales on three T2WIs (MRI using conventional acquisition time, MRI using short acquisition time [fast MRI], and fast MRI with DLR) were performed. The diagnostic performance for EPE was evaluated by three independent readers.
STATISTICAL TESTS
SNR, CNR, and image quality scores across the three imaging protocols were compared using Friedman tests. The diagnostic performance for EPE was assessed using the area under receiver operating characteristic curves (AUCs). P < 0.05 was considered statistically significant.
RESULTS
Fast MRI with DLR demonstrated significantly higher SNR (mean ± SD, 14.7 ± 6.8 vs. 8.8 ± 4.9) and CNR (mean ± SD, 6.5 ± 6.3 vs. 3.4 ± 3.6) values and higher image quality scores (median, 4.0 vs. 3.0 for three readers) than fast MRI. The AUCs for EPE were significantly higher with the use of DLR (0.86 vs. 0.75 for reader 2 and 0.82 vs. 0.73 for reader 3) compared with fast MRI, whereas differences were not significant for reader 1 (0.81 vs. 0.74; P = 0.09).
DATA CONCLUSION
DLR may be useful in reducing the acquisition time of prostate MRI without compromising image quality or diagnostic performance.
LEVEL OF EVIDENCE
4 TECHNICAL EFFICACY: Stage 3.
背景
基于深度学习的重建（DLR）可通过降低噪声潜在地提高图像质量，从而实现磁共振成像（MRI）的快速采集。然而，在前列腺癌男性患者中，很少有人对使用DLR进行短采集时间的MRI图像质量和诊断性能进行系统评估。
目的
评估使用DLR进行短采集时间的MRI对前列腺外侵犯（EPE）评估的图像质量和诊断性能。
研究类型
回顾性研究。
研究对象
109名男性。
场强/序列：3T；涡轮自旋回波T2加权图像（T2WI）、回波平面扩散加权图像以及扰相梯度回波动态对比增强图像。
评估
为比较图像质量、信噪比（SNR）和对比噪声比（CNR），并使用李克特量表对三张T2WI图像（使用传统采集时间的MRI、使用短采集时间的MRI [快速MRI]以及使用DLR的快速MRI）进行主观分析。由三位独立阅片者评估EPE诊断性能。
统计检验
使用Friedman检验比较三种成像方案的SNR、CNR和图像质量得分。使用受试者操作特征曲线下面积（AUC）评估EPE的诊断性能。P < 0.05被认为具有统计学意义。
结果
与快速MRI相比，使用DLR的快速MRI显示出显著更高的SNR值（均值±标准差，14.7±6.8 vs. 8.8±4.9）和CNR值（均值±标准差，6.5±6.3 vs. 3.4±3.6），以及更高的图像质量得分（三位阅片者的中位数分别为4.0 vs. 3.0）。与快速MRI相比，使用DLR时EPE的AUC显著更高（阅片者2为0.86 vs. 0.75，阅片者3为0.82 vs. 0.73），而阅片者1的差异不显著（0.81 vs. 0.74；P = 0.09）。
数据结论
DLR在不影响图像质量或诊断性能的情况下，可能有助于缩短前列腺MRI的采集时间。
证据水平
4级 技术效能：3级
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