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通过B型超声预测大型至巨大型肩袖撕裂的手术可修复性:一项横断面研究

Predicting the surgical reparability of large-to-massive rotator cuff tears by B-mode ultrasonography: a cross-sectional study.

作者信息

Chen Po-Cheng, Wu Kuan-Ting, Chen Yi-Cun, Huang Yu-Chi, Chang Ching-Di, Lin Wei-Che, Chou Wen-Yi

机构信息

Department of Physical Medicine and Rehabilitation, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung, Taiwan.

Department of Public Health, College of Medicine, National Cheng Kung University, Tainan, Taiwan.

出版信息

Ultrasonography. 2022 Jan;41(1):177-188. doi: 10.14366/usg.20192. Epub 2021 Jun 6.

DOI:10.14366/usg.20192
PMID:34551499
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8696139/
Abstract

PURPOSE

This study aimed to compare the ability of B-mode ultrasonography and magnetic resonance imaging (MRI) to predict the repairability of large-to-massive rotator cuff tears (RCTs).

METHODS

This cross-sectional study included participants with large-to-massive RCTs who underwent arthroscopic repair. B-mode ultrasonography and MRI were conducted prior to arthroscopic repair. B-mode ultrasonography was used to evaluate the echogenicity of the rotator cuff muscle using the Heckmatt scale. Intra-rater and inter-rater reliabilities were examined for two independent physicians. MRI was used to evaluate the degrees of tendon retraction, fatty infiltration of rotator cuff muscles, and muscle atrophy. Finally, two experienced orthopedic surgeons performed surgery and decided whether the torn stump could be completely repaired intraoperatively.

RESULTS

Fifty participants were included, and 32 complete repairs and 18 partial repairs were performed. B-mode ultrasonography showed good intra-rater reliability and inter-rater reliability for assessment of the muscle echogenicity of the supraspinatus and infraspinatus muscles. The correlation coefficients between B-mode ultrasound findings and MRI findings showed medium to large effect sizes (r=0.4-0.8). The Goutallier classification of the infraspinatus muscles was the MRI predictor with the best discriminative power for surgical reparability (area under the curve [AUC], 0.89; 95% confidence interval [CI], 0.81 to 0.98), while the Heckmatt scale for infraspinatus muscles was the most accurate ultrasound predictor (AUC, 0.85; 95% CI, 0.74 to 0.96). No significant differences in AUCs among the MRI and ultrasound predictors were found.

CONCLUSION

B-mode ultrasonography was a reliable examination tool and had a similar ability to predict surgical reparability to that of MRI among patients with large-to-massive RCTs.

摘要

目的

本研究旨在比较B型超声和磁共振成像(MRI)预测大型至巨大型肩袖撕裂(RCT)可修复性的能力。

方法

本横断面研究纳入了接受关节镜修复的大型至巨大型RCT患者。在关节镜修复前进行B型超声和MRI检查。使用Heckmatt量表通过B型超声评估肩袖肌肉的回声性。对两名独立的医生进行了评估者内和评估者间信度检查。MRI用于评估肌腱回缩程度、肩袖肌肉脂肪浸润和肌肉萎缩情况。最后,两名经验丰富的骨科医生进行手术,并决定术中撕裂残端是否能完全修复。

结果

纳入50名参与者,进行了32例完全修复和18例部分修复。B型超声在评估冈上肌和冈下肌肌肉回声性方面显示出良好的评估者内信度和评估者间信度。B型超声检查结果与MRI检查结果之间的相关系数显示出中等至较大的效应量(r = 0.4 - 0.8)。冈下肌的Goutallier分级是对手术可修复性具有最佳判别力的MRI预测指标(曲线下面积[AUC],0.89;95%置信区间[CI],0.81至0.98),而冈下肌的Heckmatt量表是最准确的超声预测指标(AUC,0.85;95%CI,0.74至0.96)。在MRI和超声预测指标之间未发现AUC有显著差异。

结论

在大型至巨大型RCT患者中,B型超声是一种可靠的检查工具,在预测手术可修复性方面与MRI具有相似的能力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f410/8696139/c9e4d44d2616/usg-20192f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f410/8696139/8ee35b764858/usg-20192f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f410/8696139/c91fc50367df/usg-20192f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f410/8696139/4b927c6882fc/usg-20192f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f410/8696139/64d1323dbe8c/usg-20192f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f410/8696139/26a1cc3e01f2/usg-20192f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f410/8696139/c9e4d44d2616/usg-20192f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f410/8696139/8ee35b764858/usg-20192f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f410/8696139/c91fc50367df/usg-20192f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f410/8696139/4b927c6882fc/usg-20192f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f410/8696139/64d1323dbe8c/usg-20192f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f410/8696139/26a1cc3e01f2/usg-20192f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f410/8696139/c9e4d44d2616/usg-20192f6.jpg

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