Computational Design, Fabrication, and Evaluation of Optimized Patient-Specific Transtibial Prosthetic Sockets

Amputation Stump Clinical Trial

Official title: Computational Design, Fabrication, and Evaluation of Optimized Patient-Specific Transtibial Prosthetic Sockets

Status Completed

Clinical Trial Summary

The overall goal of this study is to further develop and clinically assess a computational and data-driven design and manufacturing framework for mechanical interfaces that quantitatively produces transtibial prosthetic sockets in a faster and more cost-effective way than conventional processes. The main hypothesis of this proposal is that the novel quantitative interface is equivalent to, or better than, a conventional interface in terms of: 1) gait symmetry, 2) skin contact pressures, 3) skin surface temperature, and 4) comfort as evaluated from a questionnaire.

Clinical Trial Description

Title: Computational Design, Fabrication, and Evaluation of Optimized Patient-Specific Transtibial Prosthetic Sockets

Principle Investigator: Dr. Hugh Herr

Background: The overall goal of this application is to further develop and clinically assess a computational and data-driven design and manufacturing framework for mechanical interfaces that quantitatively produces transtibial prosthetic sockets in a faster and more cost-effective way than conventional processes. Traditionally, prosthetic socket production has been a craft activity, based primarily on the experience of the prosthetist. Even with advances in computer-aided design and computer-aided manufacturing (CAD/CAM), the design process remains manual. The manual nature of the process means it is non-repeatable and currently largely non-data-driven, and quantitative data is either not obtained or insufficiently employed. Furthermore, discomfort, skin problems and pressure ulcer formation remain prevalent. Through the proposed computational modeling framework, a repeatable, data-driven and patient-specific design process is made available which is based on scientific rationale.

Objective/hypothesis: The main hypothesis of this proposal is that a socket, designed using the novel computational design framework, is equivalent to, or better than, a conventional socket (designed by a prosthetist) in terms of: 1) gait symmetry, 2) skin contact pressures, 3) skin surface temperature, and 4) comfort as evaluated from a questionnaire. Our hypothesis is supported by the presented pilot data which shows reduced or equivalent skin contact pressures and subject reported comfort levels for several critical anatomical regions.

Specific Aims: 1) Subject-specific biomechanical modeling for N=18 subjects, 2) Computational design and fabrication of sockets for N=18 subjects, and 3) Clinical evaluation of novel sockets for N=18 subjects.

Study Design: A cohort of 18 subjects will be recruited for this study. MRI or CT data will be recorded for all subjects. Through image segmentation geometrically accurate 3D finite element analysis (FEA) models will be constructed. The resulting predictive FEA models will then be used in a novel, data-driven, and automated computational design framework for prosthetic sockets, to design prosthetic sockets for all subjects. The framework optimizes the socket designs, as assessed by skin contact pressures and internal tissue strain, through iterative adjustment of the virtual tests sockets. Final designs are subsequently 3D printed. To evaluate the prosthetic sockets with each of the subjects each subject will do a standing and walking exercise using their conventional sockets or the novel sockets. Meanwhile skin contact pressures and temperatures are recorded, gait symmetry data is collecetd, and socket comfort is assessed using a questionnaire. Together this data provides a quantitative and qualitative evaluation and comparison of the novel and conventional sockets. ;

Related Conditions & MeSH terms

• Amputation Stump

• NCT number: NCT03544853
• Study type: Interventional
• Source: Massachusetts Institute of Technology
• Status: Completed
• Phase: N/A
• Start date: September 15, 2017
• Completion date: August 31, 2022