Methodology for Robotic In Vitro Testing of the Knee.

The 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.

Age is superior to aortopathy phenotype as a predictor of aortic mechanics in patients with bicuspid valve.

OBJECTIVES: Bicuspid aortic valve (BAV) aortopathy is defined by 3 phenotypes-root, ascending, and diffuse-based on region of maximal aortic dilation. We sought to determine the association between aortic mechanical behavior and aortopathy phenotype versus other clinical variables. METHODS: From August 1, 2016, to March 1, 2023, 375 aortic specimens were collected from 105 patients undergoing elective ascending aortic aneurysm repair for BAV aortopathy. Planar biaxial data (191 specimens) informed constitutive descriptors of the arterial wall that were combined with in vivo geometry and hemodynamics to predict stiffness, stress, and energy density under physiologic loads. Uniaxial testing (184 specimens) evaluated failure stretch and failure Cauchy stress. Boosting regression was implemented to model the association between clinical variables and mechanical metrics. RESULTS: There were no significant differences in mechanical metrics between the root phenotype (N = 33, 31%) and ascending/diffuse phenotypes (N = 72, 69%). Biaxial testing demonstrated older age was associated with increased circumferential stiffness, decreased stress, and decreased energy density. On uniaxial testing, longitudinally versus circumferentially oriented specimens failed at significantly lower Cauchy stress (50th [15th, 85th percentiles]: 1.0 [0.7, 1.6] MPa vs 1.9 [1.3, 3.1] MPa; P < .001). Age was associated with decreased failure stretch and stress. Elongated ascending aortas were also associated with decreased failure stress. CONCLUSIONS: Aortic mechanical function under physiologic and failure conditions in BAV aortopathy is robustly associated with age and poorly associated with aortopathy phenotype. Data suggesting that the root phenotype of BAV aortopathy portends worse outcomes are unlikely to be related to aberrant, phenotype-specific tissue mechanics.

Longitudinal versus circumferential biomechanical behavior of the aneurysmal ascending aorta.

OBJECTIVES: We evaluate the independent effects of patient and aortic tissue characteristics on biaxial physiologic mechanical metrics in aneurysmal and nonaneurysmal tissues, and uniaxial failure metrics in aneurysmal tissue, comparing longitudinal and circumferential behavior. METHODS: From February 2017 to October 2022, 382 aortic specimens were collected from 134 patients; 268 specimens underwent biaxial testing, and 114 specimens underwent uniaxial testing. Biaxial testing evaluated Green-Lagrange transition strain and low and high tangent moduli. Uniaxial testing evaluated failure stretch, Cauchy stress, and low and high tangent moduli. Longitudinal gradient boosting models were implemented to estimate mechanical metrics and covariates of importance. RESULTS: On biaxial testing, nonaneurysmal tissue was less deformable and exhibited a lower transition strain than aneurysmal tissue in the longitudinal (0.18 vs 0.30, P < .001) and circumferential (0.25 vs 0.30, P = .01) directions. Older age and increasing ascending aortic length contributed most to predicting transition strain. On uniaxial testing, longitudinal specimens failed at lower stretch (1.4 vs 1.5, P = .003) and Cauchy stress (1.0 vs 1.9 kPa, P < .001) than circumferential specimens. Failure stretch and Cauchy stress were most strongly associated with tissue orientation and decreased sharply with older age. Age, ascending aortic length, and tissue thickness were the most frequent covariates predicting mechanical metrics across 10 prediction models. CONCLUSIONS: Age was the strongest predictor of mechanical behavior. After adjusting for age, nonaneurysmal tissue was less deformable than aneurysmal tissue. Differences in longitudinal and circumferential mechanics contribute to tissue dysfunction and failure in ascending aneurysms. This highlights the need to better understand the effects of age, ascending aortic length, and thickness on clinical aortic behavior.

Ex vivo biaxial load testing analysis of aortic biomechanics demonstrates variation in elastic energy distribution across the aortic zone zero.

OBJECTIVES: We hypothesized that tissue characteristics vary significantly along zone zero, which may be reflected by regional differences in stored elastic energy. Our objectives were to (1) characterize the regional variation in stored elastic energy within tissues of the aortic zone zero and (2) identify the association between this variation and patient characteristics. METHODS: From February 2018 to January 2021, 123 aortic tissue samples were obtained from the aortic root and proximal and distal ascending aortas of 65 adults undergoing elective ascending aorta replacement. Biaxial biomechanics testing was performed to obtain tissue elastic energy at the inflection point and compared with patient demographics and preoperative computed tomography imaging. Coefficient models were fit using B-spline to interrogate the relationship among elastic energy, region, and patient characteristics. RESULTS: Mean elastic energy at inflection point was 24.3 ± 15.6 kJ/m3. Elastic energy increased significantly between the root and proximal, and root and distal ascending aorta and decreased with increasing age. Differences due to history of connective tissue disorder and bicuspid aortic valve were significant but diminished when controlled for other patient characteristics. Among covariates, age and region were found to be the most important predictors for elastic energy. CONCLUSIONS: Aortic tissue biomechanical metrics varied across regions and with patient characteristics within the aortic zone zero. Assessment of endovascular outcomes in the ascending aorta must closely consider the region of deployment and variable tissue qualities along the length of the landing zone. Regional variation in tissue characteristics should be incorporated into existing patient-specific models of aortic mechanics.

Aortic diameter is a poor predictor of aortic tissue failure metrics in patients with ascending aneurysms.

OBJECTIVES: There is growing consensus that aortic diameter is a flawed predictor of aortic dissection risk. We hypothesized that aortic tissue metrics would be better predicted by clinical metrics other than aortic diameter. Our objectives were to (1) characterize circumferential aortic failure stress and stretch as a result of aortic size and patient demographics, and (2) identify the influence of bicuspid aortic valve on failure metrics. METHODS: From February 2018 to January 2021, 136 aortic tissue samples were obtained from 86 adults undergoing elective ascending aorta repair. Uniaxial biomechanical testing to failure, defined as a full-thickness central tear, was performed to obtain tissue failure stress and failure stretch and compared with clinical data and preoperative computed tomography imaging. The relationships among aortic diameter, patient demographics, and failure metrics were assessed using random forest regression models. RESULTS: Median failure stress was 1.46 (1.02-1.94) megapascals, and failure stretch was 1.36 (1.27-1.54). Regression models correlated moderately with failure stress (R2 = 0.557) and highly with failure stretch (R2 = 0.806). Failure stress decreased with increasing age, lower body mass index, thicker tissue, and tricuspid aortic valves, whereas failure stretch was most highly correlated with age. Aortic area-to-height index outperformed aortic diameter in all models. CONCLUSIONS: Aneurysmal ascending aortic tissue failure metrics correlated with available clinical metrics. Greater tissue thickness, older age, and tricuspid aortic valve morphology outperformed aortic diameter, warranting further investigation into the role of a patient-specific multifactorial dissection risk assessment over aortic diameter as a sole marker of aortic tissue integrity.