The rotator cuff (RC) is the primary dynamic stabilizer of the glenohumeral joint and dysfunction can lead to abnormal joint kinematics through loss of force couples, deterioration of shoulder function, and ultimately cartilage degeneration and cuff arthropathy. Full-thickness RC tendon tears are common, occurring in >20% of the adult population, and when non-operative management fails, surgical repair is often performed. Although muscle fibrosis and tendon degeneration are important variables that can increase surgical complexity and lead to lower patient outcome scores, they are difficult to evaluate non-invasively, including with conventional magnetic resonance imaging (MRI) and ultrasound (US), the two most widely used imaging modalities. Recently the novel ultrashort echo time magnetization transfer (UTE-MT) MRI technique has been developed to assess tendon quality, and preliminary results showed insensitivity to the magic angle effect, a strong correlation with collagen loss, and the capability to distinguish between tendinopathy groups. However, the variable presence of fat diminishes the accuracy of the technique when applied to degenerated muscle, for which several new fat-suppression methods have been proposed. Ultrasound quantification of muscle fat and fibrosis has also been attempted using routine B-mode images with limited success. The goal of this proposal is to develop, optimize, validate, and translate novel MRI and US techniques for comprehensive quantitative evaluation of RC muscle and tendon collagen abnormalities and fibrosis. In the first technical development aim, novel UTE-MT with various fat-suppression methods will be optimized and implemented, and the superior version with optimized parameters will be determined. In addition, quantitative US based on raw radiofrequency data will be implemented and novel tissue-specific scattering models will be created. The first hypothesis is that novel quantitative UTE-MT with fat-suppression and quantitative US incorporating tissue-specific models for tendon and muscle can be developed and optimized. In the second aim, a controlled rat model with unilateral massive RC tendon tear is used to induce muscle and tendon degeneration. The novel quantitative MRI and US techniques will be validated and compared alongside existing quantitative techniques. The second hypothesis is that these novel techniques can be implemented longitudinally, are reproducible, and will better correlate with reference standard histological measurements. The third human translational aim brings these new techniques to the clinic. Two age- and gender-matched cohorts of patients will be imaged, including individuals without full-thickness RC tears and individuals with full-thickness RC tears who will undergo surgical repair with acquisition of small biopsy samples. The third hypothesis is that the novel quantitative MRI and US techniques can be translated to the clinic for comprehensive, non-invasive assessment of RC muscle and tendon.

Public Health Relevance

The rotator cuff (RC) of the shoulder is a common source of pain and disability. Full-thickness RC tendon tears occur in >20% of the adult population and Veterans are particularly affected, due to the presence of injuries incurred during active duty and greater average age. Conventional magnetic resonance imaging (MRI) and ultrasound (US) can be used to assess tendon tear size, muscle atrophy, and fatty infiltration, but are less well- suited for evaluation of tendon degeneration and muscle fibrosis. Both of these important variables can increase surgical complexity and lead to lower patient outcome scores. We propose to develop, optimize, validate and translate novel quantitative MRI and US techniques for comprehensive assessment of RC collagen abnormalities and fibrosis. These techniques may guide treatment decisions, operative planning, and yield prognostic information. In addition, these techniques may be useful for many applications that are highly relevant to the VA population, such as muscle wasting due to aging, cachexia, chronic bed rest, and nervous system injury.

Agency
National Institute of Health (NIH)
Institute
Veterans Affairs (VA)
Type
Non-HHS Research Projects (I01)
Project #
2I01CX001388-05
Application #
10004383
Study Section
Special Emphasis Panel (ZRD1)
Project Start
2016-07-01
Project End
2024-06-30
Budget Start
2020-07-01
Budget End
2021-06-30
Support Year
5
Fiscal Year
2020
Total Cost
Indirect Cost
Name
VA San Diego Healthcare System
Department
Type
DUNS #
073358855
City
San Diego
State
CA
Country
United States
Zip Code
92161
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