Active
NIH R01AR077636 7/1/2020 – 6/30/2025
PI = Andrew Anderson, co-I = Jeff Weiss, Steve Aoki, Bo Foreman, Neal Bangerter, Megan Mills, Chris Peters
Morphological and Biomechanical Insights into the Pathophysiology of Femoroacetabular Impingement Syndrome
Goals: The objective of this study is to advance understanding of femoroacetabular impingement syndrome pathophysiology through rigorous evaluation of hip biomechanics and morphometrics. We will employ innovative and accurate measurement technologies including dual fluoroscopy, patient-specific finite element analysis, and statistical shape modeling (SSM). Three cohorts will be examined: femoroacetabular impingement syndrome patients, asymptomatic subjects without radiographic deformities (i.e., negative controls), and asymptomatic subjects with deformities (i.e., positive controls). Study data should improve clinical understanding of femoroacetabular impingement syndrome and inform development of new treatment approaches.
NIH 2R01EB016701-05 8/1/2020 – 7/31/2024
Computational and Statistical Framework to Model Tissue Shape and Mechanics
PI = Andrew Anderson, co-I: Jeff Weiss, Ross Whitaker, Shireen Elhabian, Chris Peters
Goals: Develop a framework to improve the efficiency in which computer models of tissue biomechanics and shape are developed and analyzed. Notably, we will apply techniques to visualize modeling data in aggregate form and will implement advanced statistical tests to evaluate group-differences in model predictions as well as findings from volumetric imaging.
NIH U24EB029011 9/30/2019 – 8/31/2024
ShapeWorksStudio: An Integrative, User-Friendly, and Scalable Suite for Shape Representation and Analysis
PI = Shireen Elhabian, Co-I: Andrew Anderson
Goals: Develop general-purpose, scalable, and open-source statistical shape modeling (SSM) tools, which will present unique capabilities for automated anatomy modeling with less user input. The proposed technology will introduce several improvements to current SSM approaches and tools, including the support for challenging modeling problems, inferring shapes directly from images (and hence bypass the segmentation step), parallel optimizations for speed, and new user interfaces that will be easier and scalable.
NIH R01AR076120 7/1/2019 – 5/31/2023
Anatomy Directly from Imagery: General-purpose, Scalable, and Open-source Machine Learning Approaches
PI = Shireen Elhabian, Co-I: Andrew Anderson
Goals: This project will develop general-purpose, scalable, and open-source statistical shape modeling (SSM) tools, which will present unique capabilities for automated anatomy modeling with less user input. The proposed technology will introduce several improvements to current SSM approaches and tools, including the support for challenging modeling problems, inferring shapes directly from images (and hence bypass the segmentation step), parallel optimizations for speed, and new user interfaces that will be easier and scalable.
Recently Completed
NIH R21AR069773 4/1/2017 – 3/31/2020
In Vivo Arthrokinematics of Total Ankle Replacement and Ankle Arthrodesis
PI = Andrew Anderson, co-I = Alexej Barg, Charles Saltzman
Goals: The major goal of this project was to develop dual fluoroscopy imaging research methodologies to quantify in vivo motion of the tibiotalar and subtalar joint in patients who had undergone surgery for advanced ankle osteoarthritis. Results improved understanding of the biomechanical tradeoffs of ankle fusion and total ankle replacement.
NIH R56AR074416 9/1/2019 – 8/31/2021
Quantifying the Pathophysiology of Femoroacetabular Impingement Syndrome
PI = Andrew Anderson, co-I = Jeff Weiss, Steve Aoki, Bo Foreman, Neal Bangerter, Megan Mills, Chris Peters, Travis Maak
Goals: The major goal of this project was to apply quantitative magnetic resonance imaging to study hip cartilage in patients with FAIS. Preliminary data obtained from this study supported a successful project funded by the NIH.
NIH R01 AR067196 5/1/2016 – 4/30/2022
Biomechanics of reverse total shoulder arthroplasty
PI = Heath Henninger, Co-I: Andrew Anderson
The goals of this study were to quantify the transient changes in scapulohumeral kinematics in reverse total shoulder patients during short term (<1 yr) recovery and test the relationships between shoulder kinematics and implant hardware configuration in the laboratory using a dynamic shoulder simulator.
PAC12 Research Grant 5/1/2018 – 4/30/2021
Developing a Comprehensive, Quantitative Understanding of Hip Morphometrics and Biomechanics in Collegiate Athletes at Risk for Developing Femoroacetabular Impingement Syndrome
PI = Andrew Anderson, co-I = Bo Foreman, Steve Aoki, Travis Maak
Goals: Determine if collegiate athletes are at a higher risk of developing femoroacetabular impingement syndrome based on the 3D shape of their hip. Develop predictive relationships between hip shape and kinematics, kinetics, and muscle activations measured in collegiate athletes.