Gabriella Schreiner, Stephen Fucaloro, Mark Ward, Laura Krivicich, Jack Bragg, Matthew Harkey, Matthew Salzler
{"title":"超声诊断前交叉韧带撕裂的准确性：一项系统回顾和荟萃分析。","authors":"Gabriella Schreiner, Stephen Fucaloro, Mark Ward, Laura Krivicich, Jack Bragg, Matthew Harkey, Matthew Salzler","doi":"10.1007/s00256-025-04866-w","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Advances in technology and affordability of ultrasound (US) have expanded its use in the evaluation of musculoskeletal injuries. However, US accuracy for diagnosing anterior cruciate ligament (ACL) injuries remains inconsistently reported in the literature.</p><p><strong>Hypothesis/purpose: </strong>Systematically review the literature and perform a meta-analysis to statistically evaluate the accuracy of US in diagnosing ACL tears.</p><p><strong>Methods: </strong>PubMed, Embase, and Web of Science databases were queried for studies comparing US to MRI or arthroscopy for diagnosing ACL tears. Studies evaluating US techniques including anterior tibial translation relative to the femur, hematoma at the ACL insertion (\"notch sign\"), or direct ACL visualization were pooled using random-effects models to generate sensitivity, specificity, positive predictive values (PPV), and negative predictive values (NPV). A p-value less than 0.05 was used to indicate statistical significance.</p><p><strong>Results: </strong>Across 12 studies, US correctly identified 419/518 (81%) of confirmed ACL injuries and 425/465 (91%) of uninjured ACLs. Meta-analysis showed high overall specificity (92%, I<sup>2</sup> = 24%), but variable sensitivity (84%, I<sup>2</sup> = 86%). PPVs were high for notch sign (96%, I<sup>2</sup> = 0%) and anterior translation (97%, I<sup>2</sup> = 0%) but low for visualization (77%, I<sup>2</sup> = 70%). NPVs were heterogeneous across techniques (notch sign 73%, I<sup>2</sup> = 90%; visualization 87%, I<sup>2</sup> = 0%; anterior translation 83%, I<sup>2</sup> = 88%).</p><p><strong>Conclusion: </strong>Ultrasound demonstrates high specificity (92%) and PPV (92%) for diagnosis of ACL tears compared to confirmed tears but is limited by fair sensitivity (84%) and NPV (83%).</p>","PeriodicalId":21783,"journal":{"name":"Skeletal Radiology","volume":" ","pages":""},"PeriodicalIF":1.9000,"publicationDate":"2025-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The diagnostic accuracy of ultrasound in assessing anterior cruciate ligament tears: a systematic review and meta-analysis.\",\"authors\":\"Gabriella Schreiner, Stephen Fucaloro, Mark Ward, Laura Krivicich, Jack Bragg, Matthew Harkey, Matthew Salzler\",\"doi\":\"10.1007/s00256-025-04866-w\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Advances in technology and affordability of ultrasound (US) have expanded its use in the evaluation of musculoskeletal injuries. However, US accuracy for diagnosing anterior cruciate ligament (ACL) injuries remains inconsistently reported in the literature.</p><p><strong>Hypothesis/purpose: </strong>Systematically review the literature and perform a meta-analysis to statistically evaluate the accuracy of US in diagnosing ACL tears.</p><p><strong>Methods: </strong>PubMed, Embase, and Web of Science databases were queried for studies comparing US to MRI or arthroscopy for diagnosing ACL tears. Studies evaluating US techniques including anterior tibial translation relative to the femur, hematoma at the ACL insertion (\\\"notch sign\\\"), or direct ACL visualization were pooled using random-effects models to generate sensitivity, specificity, positive predictive values (PPV), and negative predictive values (NPV). A p-value less than 0.05 was used to indicate statistical significance.</p><p><strong>Results: </strong>Across 12 studies, US correctly identified 419/518 (81%) of confirmed ACL injuries and 425/465 (91%) of uninjured ACLs. Meta-analysis showed high overall specificity (92%, I<sup>2</sup> = 24%), but variable sensitivity (84%, I<sup>2</sup> = 86%). PPVs were high for notch sign (96%, I<sup>2</sup> = 0%) and anterior translation (97%, I<sup>2</sup> = 0%) but low for visualization (77%, I<sup>2</sup> = 70%). NPVs were heterogeneous across techniques (notch sign 73%, I<sup>2</sup> = 90%; visualization 87%, I<sup>2</sup> = 0%; anterior translation 83%, I<sup>2</sup> = 88%).</p><p><strong>Conclusion: </strong>Ultrasound demonstrates high specificity (92%) and PPV (92%) for diagnosis of ACL tears compared to confirmed tears but is limited by fair sensitivity (84%) and NPV (83%).</p>\",\"PeriodicalId\":21783,\"journal\":{\"name\":\"Skeletal Radiology\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2025-01-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Skeletal Radiology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1007/s00256-025-04866-w\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ORTHOPEDICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Skeletal Radiology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s00256-025-04866-w","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ORTHOPEDICS","Score":null,"Total":0}
The diagnostic accuracy of ultrasound in assessing anterior cruciate ligament tears: a systematic review and meta-analysis.
Background: Advances in technology and affordability of ultrasound (US) have expanded its use in the evaluation of musculoskeletal injuries. However, US accuracy for diagnosing anterior cruciate ligament (ACL) injuries remains inconsistently reported in the literature.
Hypothesis/purpose: Systematically review the literature and perform a meta-analysis to statistically evaluate the accuracy of US in diagnosing ACL tears.
Methods: PubMed, Embase, and Web of Science databases were queried for studies comparing US to MRI or arthroscopy for diagnosing ACL tears. Studies evaluating US techniques including anterior tibial translation relative to the femur, hematoma at the ACL insertion ("notch sign"), or direct ACL visualization were pooled using random-effects models to generate sensitivity, specificity, positive predictive values (PPV), and negative predictive values (NPV). A p-value less than 0.05 was used to indicate statistical significance.
Results: Across 12 studies, US correctly identified 419/518 (81%) of confirmed ACL injuries and 425/465 (91%) of uninjured ACLs. Meta-analysis showed high overall specificity (92%, I2 = 24%), but variable sensitivity (84%, I2 = 86%). PPVs were high for notch sign (96%, I2 = 0%) and anterior translation (97%, I2 = 0%) but low for visualization (77%, I2 = 70%). NPVs were heterogeneous across techniques (notch sign 73%, I2 = 90%; visualization 87%, I2 = 0%; anterior translation 83%, I2 = 88%).
Conclusion: Ultrasound demonstrates high specificity (92%) and PPV (92%) for diagnosis of ACL tears compared to confirmed tears but is limited by fair sensitivity (84%) and NPV (83%).
期刊介绍：
Skeletal Radiology provides a forum for the dissemination of current knowledge and information dealing with disorders of the musculoskeletal system including the spine. While emphasizing the radiological aspects of the many varied skeletal abnormalities, the journal also adopts an interdisciplinary approach, reflecting the membership of the International Skeletal Society. Thus, the anatomical, pathological, physiological, clinical, metabolic and epidemiological aspects of the many entities affecting the skeleton receive appropriate consideration.
This is the Journal of the International Skeletal Society and the Official Journal of the Society of Skeletal Radiology and the Australasian Musculoskelelal Imaging Group.
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