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用于关节镜验证的同时多层并行成像加速膝关节MRI的深度学习超分辨率

Deep Learning Superresolution for Simultaneous Multislice Parallel Imaging-Accelerated Knee MRI Using Arthroscopy Validation.

作者信息

Walter Sven S, Vosshenrich Jan, Cantarelli Rodrigues Tatiane, Dalili Danoob, Fritz Benjamin, Kijowski Richard, Park Eun Hae, Serfaty Aline, Stern Steven E, Brinkmann Inge, Koerzdoerfer Gregor, Fritz Jan

机构信息

From the Department of Radiology, Division of Musculoskeletal Radiology, NYU Grossman School of Medicine, 660 1st Ave, 3rd Fl, Rm 313, New York, NY 10016 (S.S.W., J.V., R.K., E.H.P., J.F.); Department for Diagnostic and Interventional Radiology, Eberhard Karls University Tübingen, University Hospital Tübingen, Tübingen, Germany (S.S.W.); Department of Radiology, University Hospital Basel, Basel, Switzerland (J.V.); Department of Radiology, Hospital do Coraçao, São Paulo, Brazil (T.C.R.); Academic Surgical Unit, South West London Elective Orthopaedic Centre (SWLEOC), London, United Kingdom (D.D.); Department of Radiology, Balgrist University Hospital, Zurich, Switzerland (B.F.); Department of Radiology, Jeonbuk National University Hospital, Jeonju, Republic of Korea (E.H.P.); Research Institute of Clinical Medicine of Jeonbuk National University, Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, Republic of Korea (E.H.P.); Medscanlagos Radiology, Cabo Frio, Brazil (A.S.); Centre for Data Analytics, Bond University, Gold Coast, Australia (S.E.S.); Siemens Healthineers AG, Erlangen, Germany (I.B.); and Siemens Medical Solutions USA, Malvern, Pa (G.K.).

出版信息

Radiology. 2025 Jan;314(1):e241249. doi: 10.1148/radiol.241249.

Abstract

Background Deep learning (DL) methods can improve accelerated MRI but require validation against an independent reference standard to ensure robustness and accuracy. Purpose To validate the diagnostic performance of twofold-simultaneous-multislice (SMSx2) twofold-parallel-imaging (PIx2)-accelerated DL superresolution MRI in the knee against conventional SMSx2-PIx2-accelerated MRI using arthroscopy as the reference standard. Materials and Methods Adults with painful knee conditions were prospectively enrolled from December 2021 to October 2022. Participants underwent fourfold SMSx2-PIx2-accelerated standard-of-care and investigational DL superresolution MRI at 3 T. Seven radiologists independently evaluated the MRI examinations for overall image quality (using Likert scale scores: 1, very bad, to 5, very good) and the presence or absence of meniscus and ligament tears. Articular cartilage was categorized as intact, or partial or full-thickness defects. Statistical analyses included interreader agreements (Cohen κ and Gwet AC2) and diagnostic performance testing used area under the receiver operating characteristic curve (AUC) values. Results A total of 116 adults (mean age, 45 years ± 15 [SD]; 74 men) who underwent arthroscopic surgery within 38 days ± 22 were evaluated. Overall image quality was better for DL superresolution MRI (median Likert score, 5; range, 3-5) than conventional MRI (median Likert score, 4; range, 3-5) ( < .001). Diagnostic performances of conventional versus DL superresolution MRI were similar for medial meniscus tears (AUC, 0.94 [95% CI: 0.89, 0.97] vs 0.94 [95% CI: 0.90, 0.98], respectively; > .99), lateral meniscus tears (AUC, 0.85 [95% CI: 0.78, 0.91] vs 0.87 [95% CI: 0.81, 0.94], respectively; = .96), and anterior cruciate ligament tears (AUC, 0.98 [95% CI: 0.93, >0.99] vs 0.98 [95% CI: 0.93, >0.99], respectively; > .99). DL superresolution MRI (AUC, 0.78; 95% CI: 0.75, 0.81) had higher diagnostic performance than conventional MRI (AUC, 0.71; 95% CI: 0.67, 0.74; = .002) for articular cartilage lesions. DL superresolution MRI did not introduce hallucinations or erroneously omit abnormalities. Conclusion Compared with conventional SMSx2-PIx2-accelerated MRI, fourfold SMSx2-PIx2-accelerated DL superresolution MRI in the knee provided better image quality, similar performance for detecting meniscus and ligament tears, and improved performance for depicting articular cartilage lesions. © RSNA, 2025 See also the editorial by Nevalainen in this issue.

摘要

背景 深度学习(DL)方法可改善加速磁共振成像(MRI),但需要对照独立的参考标准进行验证,以确保其稳健性和准确性。目的 以关节镜检查为参考标准,验证膝关节双重同时多层(SMSx2)双重并行成像(PIx2)加速的DL超分辨率MRI相对于传统SMSx2-PIx2加速MRI的诊断性能。材料与方法 2021年12月至2022年10月前瞻性纳入患有膝关节疼痛疾病的成年人。参与者在3T下接受了四倍SMSx2-PIx2加速的标准护理和研究性DL超分辨率MRI检查。七名放射科医生独立评估MRI检查的整体图像质量(使用李克特量表评分:1为非常差,至5为非常好)以及半月板和韧带撕裂的有无。关节软骨分为完整、部分或全层缺损。统计分析包括阅片者间一致性(Cohen κ和Gwet AC2)以及使用受试者操作特征曲线(AUC)值进行的诊断性能测试。结果 共评估了116名成年人(平均年龄45岁±15[标准差];74名男性),他们在38天±22天内接受了关节镜手术。DL超分辨率MRI的整体图像质量(中位数李克特评分,5;范围,3-5)优于传统MRI(中位数李克特评分,4;范围,3-5)(P<0.001)。对于内侧半月板撕裂,传统MRI与DL超分辨率MRI的诊断性能相似(AUC分别为0.94[95%CI:0.89,0.97]和0.94[95%CI:0.90,0.98];P>.99),外侧半月板撕裂(AUC分别为0.85[95%CI:0.78,0.91]和0.87[95%CI:0.81,0.94];P=.96),以及前交叉韧带撕裂(AUC分别为0.98[95%CI:0.93,>0.99]和0.98[95%CI:0.93,>0.99];P>.99)。对于关节软骨病变,DL超分辨率MRI(AUC为0.78;95%CI:0.75,0.81)的诊断性能高于传统MRI(AUC为0.71;95%CI:0.67,0.74;P=.002)。DL超分辨率MRI未产生幻觉或错误遗漏异常情况。结论 与传统的SMSx2-PIx2加速MRI相比,膝关节四倍SMSx2-PIx2加速的DL超分辨率MRI提供了更好的图像质量,在检测半月板和韧带撕裂方面性能相似,在描绘关节软骨病变方面性能有所改善。©RSNA,2025 另见本期Nevalainen的社论。

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