Methodology for Robotic In Vitro Testing of the Knee

Author:

Colbrunn Robb William1,Loss Jeremy Granieri1,Gillespie Callan Michael1,Pace Elizabeth Bailey1,Nagle Tara Francesca1

Affiliation:

1. Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, Ohio

Abstract

AbstractThe knee joint plays a pivotal role in mobility and stability during ambulatory and standing activities of daily living (ADL). Increased incidence of knee joint pathologies and resulting surgeries has led to a growing need to understand the kinematics and kinetics of the knee. In vivo, in silico, and in vitro testing domains provide researchers different avenues to explore the effects of surgical interactions on the knee. Recent hardware and software advancements have increased the flexibility of in vitro testing, opening further opportunities to answer clinical questions. This paper describes best practices for conducting in vitro knee biomechanical testing by providing guidelines for future research. Prior to beginning an in vitro knee study, the clinical question must be identified by the research and clinical teams to determine if in vitro testing is necessary to answer the question and serve as the gold standard for problem resolution. After determining the clinical question, a series of questions (What surgical or experimental conditions should be varied to answer the clinical question, what measurements are needed for each surgical or experimental condition, what loading conditions will generate the desired measurements, and do the loading conditions require muscle actuation?) must be discussed to help dictate the type of hardware and software necessary to adequately answer the clinical question. Hardware (type of robot, load cell, actuators, fixtures, motion capture, ancillary sensors) and software (type of coordinate systems used for kinematics and kinetics, type of control) can then be acquired to create a testing system tailored to the desired testing conditions. Study design and verification steps should be decided upon prior to testing to maintain the accuracy of the collected data. Collected data should be reported with any supplementary metrics (RMS error, dynamic statistics) that help illuminate the reported results. An example study comparing two different anterior cruciate ligament reconstruction techniques is provided to demonstrate the application of these guidelines. Adoption of these guidelines may allow for better interlaboratory result comparison to improve clinical outcomes.

Funder

Cleveland Clinic Research Program Committees

Publisher

Georg Thieme Verlag KG

Reference58 articles.

1. Understanding the human knee and its relationship to total knee replacement;E Vaienti;Acta Biomed,2017

2. Normal anatomy and biomechanics of the knee;F Flandry;Sports Med Arthrosc Rev,2011

3. Highlights of the 2022 American Joint Replacement Registry Annual Report;V Hegde;Arthroplast Today,2023

4. Anterior cruciate ligament tear;V Musahl;N Engl J Med,2019

5. Knee osteoarthritis has doubled in prevalence since the mid-20th century;I J Wallace;Proc Natl Acad Sci U S A,2017

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