Detection and measurement of rotator cuff tears with sonography: analysis of diagnostic errors
- PMID: 15908528
- DOI: 10.2214/ajr.184.6.01841768
Detection and measurement of rotator cuff tears with sonography: analysis of diagnostic errors
Abstract
Objective: The purpose of this study was to analyze the causes of errors in the detection and measurement of rotator cuff tears in our patient population.
Subjects and methods: Seventy-one consecutive patients with shoulder pain who were prospectively studied with sonography had subsequent arthroscopy that showed a full-thickness or partial-thickness tear or intact cuff. For sonography and arthroscopy, the length or degree of retraction and width of a tear, when present, was recorded. When there were discrepant findings, representative images were jointly evaluated by the radiologist and orthopedic surgeon to determine the cause of the error.
Results: Fifteen detection errors were found, including five misses (three < 5-mm subscapularis and two small partial-thickness tears), four errors inherent with the test (distinguishing large bursal side or extensive partial-thickness from full-thickness tears and tendinopathy from partial-thickness tears), three errors of an unknown cause, two due to misinterpretation, and one error inherent with the patient. Seventeen measurement errors occurred with full-thickness tears, 15 of those in patients with large or massive tears. Bursal thickening (n = 4), non-visualization of the torn tendon end (n = 2), nonretracted tear (n = 2), and complex tear (n = 1) contributed to the errors. Eight measurement errors occurred with partial-thickness tears. Difficulty distinguishing tendinopathy from partial-thickness tears (n = 3) and complex tears (n = 3) accounted for six errors.
Conclusion: Although infrequent, detection errors were due to limitations inherent with the test or misses. Limitations inherent with the patient and misinterpretation of the findings were rare. Most measurement errors occurred in patients with large or massive cuff tears.
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