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Annals of Biomedical Engineering

, Volume 47, Issue 1, pp 154–161 | Cite as

Effects of Tendon Degeneration on Predictions of Supraspinatus Tear Propagation

  • R. Matthew Miller
  • James Thunes
  • Spandan Maiti
  • Volker Musahl
  • Richard E. Debski
Article
  • 90 Downloads

Abstract

Rotator cuff tendons undergo degeneration with age, which could have an impact on tear propagation. The objective of this study was to predict tear propagation for different levels of tissue degeneration using an experimentally validated finite element model of a supraspinatus tendon. It was hypothesized that greater amounts of degeneration will result in tear propagation at lower loads than tendons with less degeneration. Using a previously-validated computational model of supraspinatus tendon, 1-cm tears were introduced in the anterior, middle, and posterior thirds of the tendon. Cohesive elements were assigned subject-specific failure properties to model tear propagation, and tendon degeneration ranging from “minimal” to “severe” was modeled by modifying its mechanical properties. Tears in tendons with severe degeneration required the smallest loads to propagate (122–207 N). Posterior tears required greater loads compared to middle and anterior tears at all levels of degeneration. Stress and strain required for tear propagation decreased substantially with degeneration, ranging from 8.5 MPa and 32.6% strain for minimal degeneration and 0.6 MPa and 4.5% strain for severe degeneration. Overall, this work indicates that greater amounts of tendon degeneration lead to greater risk of tear propagation, supporting the need for early detection and treatment of rotator cuff tears.

Keywords

Rotator cuff tendon Finite element model Subject-specific 

Notes

Acknowledgments

Support from The Albert B. Ferguson, Jr., M.D. Orthopaedic Fund (AD2015-1765-23), the Department of Orthopaedic Surgery, and Pittsburgh Chapter of the ARCS Foundation is gratefully acknowledged.

Conflict of interest

No benefits in any form have been or will be received from a commercial party related directly or indirectly to the subject of this manuscript.

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Copyright information

© Biomedical Engineering Society 2018

Authors and Affiliations

  1. 1.Department of BioengineeringUniversity of PittsburghPittsburghUSA
  2. 2.Orthopaedic Robotics LaboratoryUniversity of PittsburghPittsburghUSA
  3. 3.Department of Orthopaedic SurgeryUniversity of PittsburghPittsburghUSA

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