A novel concept of an acoustic ultrasound wearable for early detection of implant failure

Abstract Mechanical failure of medical implants, especially in orthopedic poses a significant burden to the patients and healthcare system. The majority of the implant failures are diagnosed at very late stages and are of mechanical causes. This makes the diagnosis and screening of implant failure v...

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Main Authors: Amirhossein Yazdkhasti, Elizabeth Hughes, Joshua S Norton, Gage L. Olson, Casey Lam, Sophie Lloyd, Miao Yu, Joseph H. Schwab, Hamid Ghaednia
Format: Article
Language:English
Published: Nature Portfolio 2024-12-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-024-82743-7
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author Amirhossein Yazdkhasti
Elizabeth Hughes
Joshua S Norton
Gage L. Olson
Casey Lam
Sophie Lloyd
Miao Yu
Joseph H. Schwab
Hamid Ghaednia
author_facet Amirhossein Yazdkhasti
Elizabeth Hughes
Joshua S Norton
Gage L. Olson
Casey Lam
Sophie Lloyd
Miao Yu
Joseph H. Schwab
Hamid Ghaednia
author_sort Amirhossein Yazdkhasti
collection DOAJ
description Abstract Mechanical failure of medical implants, especially in orthopedic poses a significant burden to the patients and healthcare system. The majority of the implant failures are diagnosed at very late stages and are of mechanical causes. This makes the diagnosis and screening of implant failure very challenging. There have been several attempts for development of new implants and screening methods to address this issue; however, the majority of these methods focus on development of new implants or material and cannot satisfy the needs of the patients that have already been operated on. In this work we are introducing a novel screening method and investigate the feasibility of using low-intensity, low-frequency ultrasound acoustic waves for understanding of interfacial implant defects through computational simulation. In this method, we simultaneously apply and sense acoustic waves. COMSOL simulations proved the correlation between implant health condition, severity, and location of defects with measured acoustic signal. Moreover, we show that machine learning not only can detect and classify failure types, it can also assess the severity of the defects. We believe that this work can be used as a proof of concept to rationalize the development of non-invasive screening acoustic wearables for early detection of implant failure in patients with orthopedic implants.
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issn 2045-2322
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publishDate 2024-12-01
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spelling doaj-art-e32a6cc4a5b840359e340859ba54f79b2024-12-29T12:17:00ZengNature PortfolioScientific Reports2045-23222024-12-0114111210.1038/s41598-024-82743-7A novel concept of an acoustic ultrasound wearable for early detection of implant failureAmirhossein Yazdkhasti0Elizabeth Hughes1Joshua S Norton2Gage L. Olson3Casey Lam4Sophie Lloyd5Miao Yu6Joseph H. Schwab7Hamid Ghaednia8Center for Surgical Innovation and Engineering, Cedars Sinai Health SystemCalifornia Institute of TechnologyPurdue UniversityCenter for Surgical Innovation and Engineering, Cedars Sinai Health SystemTufts UniversityDartmouth UniversityDepartment of Mechanical Engineering and Institute for Systems Research, University of MarylandCenter for Surgical Innovation and Engineering, Cedars Sinai Health SystemCenter for Surgical Innovation and Engineering, Cedars Sinai Health SystemAbstract Mechanical failure of medical implants, especially in orthopedic poses a significant burden to the patients and healthcare system. The majority of the implant failures are diagnosed at very late stages and are of mechanical causes. This makes the diagnosis and screening of implant failure very challenging. There have been several attempts for development of new implants and screening methods to address this issue; however, the majority of these methods focus on development of new implants or material and cannot satisfy the needs of the patients that have already been operated on. In this work we are introducing a novel screening method and investigate the feasibility of using low-intensity, low-frequency ultrasound acoustic waves for understanding of interfacial implant defects through computational simulation. In this method, we simultaneously apply and sense acoustic waves. COMSOL simulations proved the correlation between implant health condition, severity, and location of defects with measured acoustic signal. Moreover, we show that machine learning not only can detect and classify failure types, it can also assess the severity of the defects. We believe that this work can be used as a proof of concept to rationalize the development of non-invasive screening acoustic wearables for early detection of implant failure in patients with orthopedic implants.https://doi.org/10.1038/s41598-024-82743-7
spellingShingle Amirhossein Yazdkhasti
Elizabeth Hughes
Joshua S Norton
Gage L. Olson
Casey Lam
Sophie Lloyd
Miao Yu
Joseph H. Schwab
Hamid Ghaednia
A novel concept of an acoustic ultrasound wearable for early detection of implant failure
Scientific Reports
title A novel concept of an acoustic ultrasound wearable for early detection of implant failure
title_full A novel concept of an acoustic ultrasound wearable for early detection of implant failure
title_fullStr A novel concept of an acoustic ultrasound wearable for early detection of implant failure
title_full_unstemmed A novel concept of an acoustic ultrasound wearable for early detection of implant failure
title_short A novel concept of an acoustic ultrasound wearable for early detection of implant failure
title_sort novel concept of an acoustic ultrasound wearable for early detection of implant failure
url https://doi.org/10.1038/s41598-024-82743-7
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