Rotator cuff tears are common, affecting up to 40% of individuals over age 60 and accounting for an economic burden of $3-5 billion per year. Surgical repair is a satisfactory solution for many patients, but clinical outcomes and healing of the repair tissue after rotator cuff surgery can be unpredictable. Tear chronicity (i.e., the extent to which the muscle/tendon unit has degenerated over time) is a critical factor in determining healing and clinical outcomes. However, conventional approaches for assessing tear chronicity use only qualitative descriptions (mild, moderate, severe) or grades (0 to 4) without any explicit assessment of the quality of the muscle and tendon tissues. Consequently, it is perhaps not entirely surprising that these conventional assessments are only weak predictors of healing and clinical outcome after surgery. This is important, because without a reliable measure of tear chronicity it is difficult for surgeons to know prior to surgery how challenging the repair may be, what alternatives may need to be considered during surgery, what post-operative rehabilitation activities should be prescribed, and how best to counsel patients on expected outcomes. Ultrasound shear wave elastography has emerged as a promising technique for non-invasively assessing the in-vivo stiffness of soft tissues. Given that the pathologic processes associated with rotator cuff tears are characterized by changes in tissue stiffness, shear wave elastography may have clinical utility in assessing the chronicity of rotator cuff disease. However, even though this advanced technique has been used extensively for breast and liver imaging, it has seen only limited use in musculoskeletal tissues. Consequently, the objective of this study is to determine the extent to which rotator cuff shear wave speed (SWS) predicts healing and clinical outcomes after rotator cuff repair. Our approach will be to use shear wave elastography to measure SWS in patients who are having surgical rotator cuff repair. These data will be acquired prior to surgery and then related to conventional tear characteristics (tear size, tear retraction, muscle atrophy, fatty degeneration), healing, and conventional clinical outcomes (strength, ROM, patient- reported outcomes) collected at 12 months post-surgery. Our central hypothesis is that SWS will be a significant predictor of healing and clinical outcomes and superior to conventional predictors of healing and clinical outcome. The proposed research is innovative because it will use an emerging technology to assess the quality of the rotator cuff tissues, which cannot currently be obtained in any other way. This contribution of the proposed research will be significant because we believe it will establish the clinical utility of shear wave elastography by identifying SWS as a superior predictor of clinical outcome and repair tissue healing. In turn, clinical use of shear wave elastography will provide physicians with the information necessary to improve care for patients suffering with rotator cuff tears.

Public Health Relevance

A rotator cuff tear is a common and painful shoulder condition that is often treated with surgery, but it?s difficult to predict to what extent a patient?s shoulder function will be restored after surgery. This project will use advanced ultrasound imaging to assess the quality of patients? rotator cuff muscles and tendons before surgery, and relate that information to the patients? functional outcomes after surgery. The proposed research is relevant to public health because it will advance our understanding of the treatment of rotator cuff tears and will ultimately lead to improved patient care and lower medical costs.

Agency
National Institute of Health (NIH)
Institute
National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)
Type
Exploratory/Developmental Grants (R21)
Project #
5R21AR072785-02
Application #
9744556
Study Section
Skeletal Biology Structure and Regeneration Study Section (SBSR)
Program Officer
Washabaugh, Charles H
Project Start
2018-07-15
Project End
2020-06-30
Budget Start
2019-07-01
Budget End
2020-06-30
Support Year
2
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Henry Ford Health System
Department
Type
DUNS #
073134603
City
Detroit
State
MI
Country
United States
Zip Code
48202