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基于深度学习重建技术改善前列腺T2WI图像质量的研究 被引量:7

Novel deep learning-based T2-weighted imaging of the prostate provides superior image quality
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摘要 目的 探讨基于深度学习重建(deep learning-based reconstruction, DLR)技术对前列腺T2WI图像质量及诊断置信度的影响。材料与方法 回顾性分析78例行前列腺磁共振检查患者的影像资料,扫描序列包括传统T2WI(conventional T2WI, T2WI_C)及基于DLR技术的T2WI(T2WI_(DL)),二者扫描参数及时间相同。对所有患者的T2WI_C及T2WI_(DL)图像进行主观评价、客观评价及诊断置信度评价。主观评价及诊断置信度评价由两名具有不同影像诊断经验(3年、7年)的医师(阅片者1、阅片者2)依据Likert Scale评分法进行双盲评价(5分:优,1分:极差),并采用Wilcoxon秩和检验及Kappa统计法评估两位阅片者间评分的差异性及一致性;T2WI图像质量评价指标包括:前列腺包膜清晰度、病灶对比度及边缘锐利度、解剖细节的显示、盆腔肌肉及骨骼的清晰度及整体图像质量;T2WI诊断置信度评价指标包括:病灶位置及形态识别、病灶良恶性的初步判断。分别记录两位阅片者浏览每一组图像及作出初步诊断的用时,采用配对t检验进行统计学分析。客观评价包括测量T2WI_C及T2WI_(DL)图像前列腺病灶的信噪比(signal-to-noise ratio, SNR)及对比噪声比(contrast-to-noise ratio, CNR),使用配对t检验和Mann-Whitney U检验进行统计学分析。结果 本研究78例患者年龄(67.1±9.9)岁。基于主观评分标准,两名阅片者T2WI_C图像的总评分分别为(3.4±0.7)、(3.0±0.8)分,T2WI_(DL)图像的总评分分别为(4.6±0.6)、(4.3±0.7)分;两名阅片者对T2WI_(DL)图像评分一致性为0.6~0.8,在解剖细节及整体图像质量方面,两名阅片者间评分差异有统计学意义(P<0.05)。诊断置信度评价方面,两名阅片者总评分和用时分别为T2WI_C图像:(3.8±0.4)分、(3.7±0.5)分和(36.6±12.6)s、(25.0±5.7) s;T2WI_(DL)图像:(4.8±0.3)分、(4.8±0.4)分和(28.6±11.0) s、(20.6±5.4) s;差异均具有统计学意义(P<0.01)。基于客观评价,T2WI_(DL)图像的SNR及CNR均高于T2WI_C图像,差异具有统计学意义(P<0.05);其中良、恶性病灶T2WI_C和T2WI_(DL)的SNR分别为(12.4±2.4)、(10.1±1.8)和(28.7±8.1)、(27.7±5.4),差异均有统计学意义(P<0.01);良、恶性病灶有无DL的CNR差异均无统计学意义(P>0.05)。结论 T2WI_(DL)图像主观评分高、病灶对比度明显、SNR及CNR均高于传统T2WI_C图像,且诊断医师对T2WI_(DL)图像诊断信心更足、诊断用时更少。故相同扫描时间内,基于DLR技术有助于提高前列腺T2WI图像质量,为临床诊疗提供了更为精准的影像学依据。 Objective:To introduce a novel deep learning-based reconstruction(DLR,which is now commercially available as AIRTM Recon DL,GE Healthcare)T2-weighted imaging(T2WIDL)sequence in prostate MRI and investigate its image quality and diagnostic confidence compared to conventional T2-weighted imaging(T2WIC).Materials and Methods:Seventy-eight patients who underwent prostate MRI examinations(T2WIC and T2WIDLwith the same parameters)were included in this retrospective study.For the qualitative and diagnostic confidence evaluation,double-blinded evaluation was performed by both three-and seven-year experienced radiologists according to the Likert Scale(5=excellent,1=very poor),and then the difference among the scores were evaluated using Wilcoxon test and the intra-/inter-observer agreement were evaluated usingκstatistics.The evaluation indicators of T2WI image quality and diagnostic confidence including:prostate capsule,lesion contrast and edge sharpness,anatomical details(urethra,zone of prostate,seminal vesicle),skeleton and muscle clarity,overall image quality,lesion location and morphology,lesion is benign or malignant.In addition,the time spent by two radiologists browsing each set of images was recorded respectively,and the paired t test was used for statistical analysis.As for quantitative evaluation,the signal-to-noise ratio(SNR)and contrast-to-noise ratio(CNR)measured between each prostate lesion on the MR images acquired with different sequences were analyzed,paired t test and Mann-Whitney U test were used for statistical analysis.Results:Seventy-eight patients at the mean age of(67.1±9.9)years were included in this retrospective study.Based on the subjective scoring criteria,overall image quality scores were rated significantly superior by both readers with(4.6±0.6)and(4.3±0.7)on T2WIDL compared to(3.4±0.7)and(3.0±0.8)on T2WIC(P<0.05).For T2WIDL,the score consistency ranged from 0.6 to 0.8;there were significant differences in the scores between the two readers only for anatomical details and overall image quality(P<0.05).Besides,overall diagnostic confidence scores also were rated significantly superior by both readers with(4.8±0.3)and(4.8±0.4)on T2WIDL compared to(3.8±0.4)and(3.7±0.5)on T2WIC(P<0.05),with fewer time to spend.Based on objective evaluation,SNR and CNR of T2WIDL were higher than those of T2WIC,and the differences were statistically significant(P<0.05).The SNR of T2WIC and T2WIDL in benign and malignant lesions were(12.4±2.4),(28.7±8.1)and(10.1±1.8),(27.7±5.4),respectively,with significant differences(P<0.01).There was no significant difference in CNR between benign and malignant lesions with and without DL(P>0.05).Conclusions:The prostate T2WIDLimages have high subjective rating scores,clearer lesion contrast,high SNR and CNR.In addition,the radiologists had more diagnostic confidence in T2WIDL image with less diagnostic time.Therefore,the novel DLR technique is helpful to improve the image quality of prostate T2WI within the same scanning time,which provides a more accurate imaging basis for clinical diagnosis and treatment.
作者 可赞 李亮 宋鑫洋 文之 高宇凡 刘薇音 权光南 查云飞 KE Zan;LI Liang;SONG Xinyang;WEN Zhi;GAO Yufan;LIU Weiyin;QUAN Guangnan;ZHA Yunfei(Department of Radiology,Renmin Hospital of Wuhan University,Wuhan 430060,China;Department of Radiology,Xiangyang No.1 People's Hospital,Hubei University of Medicine,Xiangyang 441000,China;GE Healthcare(China)Co.,Ltd.,Beijing 100176,China)
出处 《磁共振成像》 CAS CSCD 北大核心 2023年第5期41-47,共7页 Chinese Journal of Magnetic Resonance Imaging
基金 国家自然科学基金(编号:81601461)。
关键词 前列腺 前列腺癌 深度学习 磁共振成像 图像质量 信噪比 对比噪声比 prostate prostate cancer deep learning magnetic resonance imaging image quality signal-to-noise ratio contrast-to-noise ratio
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