Title

Volumetric Wear Analysis of Meniscus Degeneration

Document Type

Student Presentation

Presentation Date

4-15-2019

College

College of Engineering

Department

Department of Mechanical & Biomedical Engineering

Faculty Sponsor

Dr. Trevor Lujan

Abstract

Meniscus degeneration is highly prevalent with over 56% of individuals above the age of 70 years impacted [1]. This degeneration is a pathological breakdown or wearing of meniscal fibrous tissue which can result in knee pain and lead to osteoarthritis [2,3]. In order to develop effective treatments and preventative strategies for meniscus degeneration, researchers need an accurate method to quantify meniscal wear, yet, no method currently exists. The objective of this research was to develop and validate a process for characterizing meniscus volumetric wear using a surrogate model of known dimensions. The surrogate model was scanned via a 3D optical scanner to generate a volumetric rendering of the model before and after wear occurred. An open-source software, CloudCompare, was then used to computationally evaluate volume loss of the surrogate model. The process was repeated at varying wear depths, and the percentage error between real-life measured volumes and CloudCompare calculated volumes was determined to be <2% when measuring 1086 mm3 of wear. This study has developed and validated a novel methodology that can be used to help identify the physical and biochemical factors that lead to meniscus degeneration and thereby help advance treatment and prevention strategies of this prevalent disease.

References

[1] Englund, M. et. al. Incidental Meniscal Findings on Knee MRI in Middle-Aged and Elderly Persons, N Engl J Med. 359 (2008) 1108-1115.

[2] Fischenich, Kristine M. et. al. Effects of degeneration on the compressive and tensile properties of human meniscus, Journal of Biomechanics. 48 (2015) 1407-1411.

[3] Howell R, Kumar NS, Patel N, Tom J. Degenerative meniscus: Pathogenesis, diagnosis, and treatment options. World J Orthop. 5 (2015) 597-602.

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