Value of Strain Elastography in Evaluation of Supraspinatus Tendinopathy in Patients with Chronic Shoulder Pain, A Comparative Study to MRI

Abstract Background Rotator cuff disorders are one of the most important causes of chronic shoulder pain and the clinical differentiation between the different rotator cuff disorders is difficult and imaging is mandatory for diagnosis and proper assessment of rotator cuff abnormalities. The most commonly used imaging modalities are ultrasonography (US) and magnetic resonance imaging (MRI) with MRI is the reference standard for imaging of rotator cuff disorders yet its use is hindered by high cost and MRI contraindications. Aim of the Work to assess role of SEL in the evaluation of supraspinatus tendon abnormalities and to evaluate the relationship between the measured strain ratio and the MRI grade of tendinopathy. Patients and Methods Our study included 40 patients with chronic shoulder pain including 11 patients with no evident tendinopathy on MRI (grade 0) (27.5%) 9 patients with grade I tendinopathy (22.5 %), 10 patients with grade II tendinopathy (25 %) and 10 patients (25 %) with supraspinatus tendon tear (grade III). Results Our study showed that normal supraspinatus tendons appear homogenous and stiff with high strain ratios, whereas pathological ones showed a more heterogenous and reduced stiffness pattern with intratendinous color alterations and lower strain ratios. This is explained by the fact that tendinopathy leads to collagen fiber degeneration and breaking down, resulting into tendon softening and weakness. Our study also showed strong linear association between the MRI grade and the stiffness indicated by the strain ratios (p < 0.05). There was a perfect negative correlation grade of tendinopathy and SEL strain ratio. As tendinopathy increased, tendons became softer which was indicated by the reduced strain ratio values. These findings were in agreement with many previously published studies. Conclusion The application of SEL in musculoskeletal system is not well established, but this study showed that SEL can detect differences between the normal and diseased rotator cuff tendons with good correlation to MRI with other studies showed improved sensitivity, specificity and accuracy in detection of tendon abnormalities. It can also add further important information to conventional shoulder imaging such as tendon quality which considered as a prognostic factor for rotator cuff repair.

Authors

Institutions

Publication Details

Journal
QJM
Published
2024-10-01
DOI
https://doi.org/10.1093/qjmed/hcae175.894
Primary Topic
Shoulder Injury and Treatment
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Value of Strain Elastography in Evaluation of Supraspinatus Tendinopathy in Patients with Chronic Shoulder Pain, A Comparative Study to MRI

Ahmed Ashraf Okba, Ahmed Mohamed Samir Abdelmohsen, Marwa Ibrahim Fahmy
QJM
Shoulder Injury and Treatment
article

Value of Strain Elastography in Evaluation of Supraspinatus Tendinopathy in Patients with Chronic Shoulder Pain, A Comparative Study to MRI

Ahmed Ashraf Okba, Ahmed Mohamed Samir Abdelmohsen, Marwa Ibrahim Fahmy
article en

Abstract

Abstract Background Rotator cuff disorders are one of the most important causes of chronic shoulder pain and the clinical differentiation between the different rotator cuff disorders is difficult and imaging is mandatory for diagnosis and proper assessment of rotator cuff abnormalities. The most commonly used imaging modalities are ultrasonography (US) and magnetic resonance imaging (MRI) with MRI is the reference standard for imaging of rotator cuff disorders yet its use is hindered by high cost and MRI contraindications. Aim of the Work to assess role of SEL in the evaluation of supraspinatus tendon abnormalities and to evaluate the relationship between the measured strain ratio and the MRI grade of tendinopathy. Patients and Methods Our study included 40 patients with chronic shoulder pain including 11 patients with no evident tendinopathy on MRI (grade 0) (27.5%) 9 patients with grade I tendinopathy (22.5 %), 10 patients with grade II tendinopathy (25 %) and 10 patients (25 %) with supraspinatus tendon tear (grade III). Results Our study showed that normal supraspinatus tendons appear homogenous and stiff with high strain ratios, whereas pathological ones showed a more heterogenous and reduced stiffness pattern with intratendinous color alterations and lower strain ratios. This is explained by the fact that tendinopathy leads to collagen fiber degeneration and breaking down, resulting into tendon softening and weakness. Our study also showed strong linear association between the MRI grade and the stiffness indicated by the strain ratios (p < 0.05). There was a perfect negative correlation grade of tendinopathy and SEL strain ratio. As tendinopathy increased, tendons became softer which was indicated by the reduced strain ratio values. These findings were in agreement with many previously published studies. Conclusion The application of SEL in musculoskeletal system is not well established, but this study showed that SEL can detect differences between the normal and diseased rotator cuff tendons with good correlation to MRI with other studies showed improved sensitivity, specificity and accuracy in detection of tendon abnormalities. It can also add further important information to conventional shoulder imaging such as tendon quality which considered as a prognostic factor for rotator cuff repair.

QJMVol. 117(Supplement_2)
Ain Shams University (EG)
Openalex Percentile: Top 60%
Shoulder Injury and Treatment
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.