深度学习重建技术在乳腺MRI图像质量优化中的应用研究  

Application of deep learning reconstruction techniques in optimizing breast MRI image quality

作　　者：范文文 冯倩倩 李二妮 刘侃 权光南 王鹏 卢铜锁 胡思洁 郎宇 张红梅 FAN Wenwen;FENG Qianqian;LI Erni;LIU Kan;QUAN Guangnan;WANG Peng;LU Tongsuo;HU Sijie;LANG Yu;ZHANG Hongmei(Department of Radiology,National Cancer Center,National Clinical Research Center for Cancer,Cancer Hospital,Chinese Academy of Medical Sciences and Peking Union Medical College,Beijing 100021,China;GE Healthcare,Beijing 100176,China)

机构地区：[1]国家癌症中心/国家肿瘤临床医学研究中心/中国医学科学院北京协和医学院肿瘤医院影像诊断科,北京100021 [2]通用电气医疗(中国)有限公司,北京100176

出　　处：《磁共振成像》2024年第10期43-49,共7页Chinese Journal of Magnetic Resonance Imaging

摘　　要：目的评估深度学习重建技术(deep learning reconstruction,DLR)在提升乳腺多序列、多参数MRI图像质量中的应用价值。材料与方法前瞻性纳入60例病理诊断为乳腺癌的初诊患者(60个病灶),分别行乳腺MRI常规快速恢复快速自旋回波序列(fast recovery fast spin echo T2-weighted imaging,FRFSE)-T2WI、短时间反转恢复序列-扩散加权成像(short tau inversion recovery-diffusion weighted imaging,STIR-DWI)、应用DLR快速FRFSE-T2WI和STIR-DWI扫描。两名具有多年乳腺MRI诊断经验的医师分别按5分标准对常规FRFSE-T2WI、应用DLR快速FRFSE-T2WI和常规STIR、DLR快速STIR-DWI的整体图像质量、图像伪影和病变清晰度进行主观评价。由一位资深的乳腺诊断医师对病变区域进行了图像信噪比(signal-to-noise ratio,SNR)和对比噪声比(contrast-to-noise ratio,CNR)的测定。采用Shapiro-Wilk检验评价定量数值和主观评分的正态分布,不符合正态性分布的数据采用了Wilcoxon符号秩检验评价其统计学差异。对比分析常规、DLR快速扫描的FRFSE-T2WI和常规STIR-DWI、DLR快速扫描STIR-DWI图像的主观评分和客观指标的差异。研究者对乳腺病变图像的评分一致性通过Weighted-Kappa检验比较组间主观评分一致性,确保评分的可靠性。结果本研究共纳入60例受试者,年龄25~68(49.8±8.2)岁。DLR快速FRFSE-T2W较常规FRFSE-T2WI扫描时间缩短47.8%,DLR快速STIR-DWI较常规STIR-DWI扫描时间缩短47.6%,两位高年资医师的主观评分结果表明,DLR快速FRFSE-T2WI、DLR快速STIR-DWI在整体图像质量、伪影程度和乳腺病变可视化清晰度方面均优异于传统的FRFSE-T2WI及STIR-DWI序列(P<0.05)。常规的FRFSE-T2WI与DLR快速FRFSE-T2WI的SNR分别为102.37(63.24,141.85)、132.37(77.25,218.62),差异具有统计学意义(P<0.001);两者病灶的CNR分别为2.87(6.35,57.01)、3.10(8.94,22.34),差异具有统计学意义(P<0.001)。常规b值为1000 s/mm^(2)的STIR-DWI与DLR快速STIR-DWI的SNR�Objective:To investigate the impact of deep learning reconstruction(DLR)technology on the quality of breast MRI images and scan time.Materials and Methods:A total of 60 patients with a pathological diagnosis of breast cancer at first diagnosis were prospectively enrolled in this study.Conventional fast recovery fast spin echo T2-Weighted imaging,DLR fast fast recovery fast spin echo(FRFSE)-T2WI and conventional short tau inversion recovery-diffusion weighted imaging(STIR-DWI),DLR fast STIR-DWI scanning were performed,respectively.The overall image quality score and artifacts score of two T2WI and DWI(conventional FRFSE-T2WI,DLR fast FRSE-T2WI,and STIR-DWI,DLR fast STIR-DWI)were evaluated subjectively(5-point scale)by two radiologists.One senior radiologist measured the signal-to-noise ratio(SNR)and contrast-to-noise ratio(CNR).Shapiro-Wilk test was used to evaluate the normal distribution of quantitative values and subjective scores.Wilcoxon signed rank test was used to evaluate the statistical difference of data that did not conform to the normal distribution.The study compared the differences in subjective scores and objective metrics between conventional and DLR-accelerated FRFSE-T2WI scans,as well as conventional STIR-DWI and DLR-accelerated STIR-DWI images.The consistency of researchers'ratings of breast lesion images was quantified using Weighted-Kappa to ensure the reliability of the evaluations.Results:A total of 60 patients[25-68(49.8±8.2)years old]with breast tumors were enrolled in this study.The FRFSE-T2WI scan time was reduced by 47.8%compared to conventional FRFSE-T2WI,and the STIR-DWI scan time was reduced by 47.6%compared to conventional STIR-DWI.The subjective evaluations by two senior physicians reveal that both FRFSE-T2WI and DLR-accelerated FRFSE-T2WI,as well as standard STIR-DWI and DLR-accelerated STIR-DWI,demonstrate significantly superior overall image quality,reduced artifact levels,and enhanced clarity in breast lesion visualization compared to conventional FRFSE-T2-weighted imaging and

关 键 词：乳腺癌 深度学习重建 磁共振成像 信噪比 对比噪声比 

分 类 号：R445.2[医药卫生—影像医学与核医学] R737.9[医药卫生—诊断学]