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University of Denver

Computational Methodology for Generating Patient-Specific Soft Tissue Representations

Abstract

dc:description.abstract

<p>This dissertation focused on modeling specimen-specific soft tissue structures in the context of joint replacement surgery. The research addressed four key aspects. The first study involved developing a workflow for creating finite element models of the hip capsule to replicate its torque-rotational response. Experimental data from ten cadaveric hips were used to calibrate the models, resulting in improved accuracy and relevance for surgical planning and implant design. The second study tackled the challenge of expediting the calibration of mechanical properties of the hip capsule to match patient-specific laxities. A statistical shape function model was proposed to generate patient-specific finite element models, demonstrating potential for instant modeling and potential use in improving outcomes in hip arthroplasty. The third study involved developing a computational model of an experimental knee simulator for simultaneous evaluation of tibiofemoral and patellofemoral mechanics. The model's predictions were verified against experimental measurements, providing a reliable computational tool for further studies. The fourth study investigated the influence of soft tissue balance and implant congruency on knee stability during daily activities. Finite element models were calibrated based on experimental data, perturbed for varying soft-tissue imbalance levels, evaluated for stability during the activities of daily living, thereby highlighting the impact of implant design on stability. The dissertation's findings contribute to the knowledge of surgical planning, implant design, and potentially enhancing outcomes in joint replacement surgeries.</p>

Degree

thesis:*
Name thesis:degree_name
Ph.D.
Level thesis:degree_level
Dissertation
Year
2023

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Anantha Krishnan, Ahilan
Contributors dc:contributor
  • Chadd Clary
  • Daniel Linseman
  • Paul Rullkoetter
  • Peter Laz

Subjects

dc:subject × 11

Rights

dc:rights
Statement dc:rights
  • <p>Copyright is held by the author. User is responsible for all copyright compliance.</p>
Language dc:language
English (eng)

Identifiers

dc:identifier.*
Repository record dc:identifier
https://digitalcommons.du.edu/etd/2341
OAI identifier oai:identifier
oai:digitalcommons.du.edu:etd-3327

Chain of custody

source
Harvested from
University of Denver
Base URL
digitalcommons.du.edu/do/oai/
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Anantha Krishnan, Ahilan. Computational Methodology for Generating Patient-Specific Soft Tissue Representations. Dissertation thesis, 2023. https://digitalcommons.du.edu/etd/2341