Cargando…

Diagnostics of Articular Cartilage Damage Based on Generated Acoustic Signals Using ANN—Part II: Patellofemoral Joint

Cartilage loss due to osteoarthritis (OA) in the patellofemoral joint provokes pain, stiffness, and restriction of joint motion, which strongly reduces quality of life. Early diagnosis is essential for prolonging painless joint function. Vibroarthrography (VAG) has been proposed in the literature as...

Descripción completa

Detalles Bibliográficos
Autores principales: Karpiński, Robert, Krakowski, Przemysław, Jonak, Józef, Machrowska, Anna, Maciejewski, Marcin, Nogalski, Adam
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9146478/
https://www.ncbi.nlm.nih.gov/pubmed/35632174
http://dx.doi.org/10.3390/s22103765
_version_ 1784716573417668608
author Karpiński, Robert
Krakowski, Przemysław
Jonak, Józef
Machrowska, Anna
Maciejewski, Marcin
Nogalski, Adam
author_facet Karpiński, Robert
Krakowski, Przemysław
Jonak, Józef
Machrowska, Anna
Maciejewski, Marcin
Nogalski, Adam
author_sort Karpiński, Robert
collection PubMed
description Cartilage loss due to osteoarthritis (OA) in the patellofemoral joint provokes pain, stiffness, and restriction of joint motion, which strongly reduces quality of life. Early diagnosis is essential for prolonging painless joint function. Vibroarthrography (VAG) has been proposed in the literature as a safe, noninvasive, and reproducible tool for cartilage evaluation. Until now, however, there have been no strict protocols for VAG acquisition especially in regard to differences between the patellofemoral and tibiofemoral joints. The purpose of this study was to evaluate the proposed examination and acquisition protocol for the patellofemoral joint, as well as to determine the optimal examination protocol to obtain the best diagnostic results. Thirty-four patients scheduled for knee surgery due to cartilage lesions were enrolled in the study and compared with 33 healthy individuals in the control group. VAG acquisition was performed prior to surgery, and cartilage status was evaluated during the surgery as a reference point. Both closed (CKC) and open (OKC) kinetic chains were assessed during VAG. The selection of the optimal signal measures was performed using a neighborhood component analysis (NCA) algorithm. The classification was performed using multilayer perceptron (MLP) and radial basis function (RBF) neural networks. The classification using artificial neural networks was performed for three variants: I. open kinetic chain, II. closed kinetic chain, and III. open and closed kinetic chain. The highest diagnostic accuracy was obtained for variants I and II for the RBF 9-35-2 and MLP 10-16-2 networks, respectively, achieving a classification accuracy of 98.53, a sensitivity of 0.958, and a specificity of 1. For variant III, a diagnostic accuracy of 97.79 was obtained with a sensitivity and specificity of 0.978 for MLP 8-3-2. This indicates a possible simplification of the examination protocol to single kinetic chain analyses.
format Online
Article
Text
id pubmed-9146478
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-91464782022-05-29 Diagnostics of Articular Cartilage Damage Based on Generated Acoustic Signals Using ANN—Part II: Patellofemoral Joint Karpiński, Robert Krakowski, Przemysław Jonak, Józef Machrowska, Anna Maciejewski, Marcin Nogalski, Adam Sensors (Basel) Article Cartilage loss due to osteoarthritis (OA) in the patellofemoral joint provokes pain, stiffness, and restriction of joint motion, which strongly reduces quality of life. Early diagnosis is essential for prolonging painless joint function. Vibroarthrography (VAG) has been proposed in the literature as a safe, noninvasive, and reproducible tool for cartilage evaluation. Until now, however, there have been no strict protocols for VAG acquisition especially in regard to differences between the patellofemoral and tibiofemoral joints. The purpose of this study was to evaluate the proposed examination and acquisition protocol for the patellofemoral joint, as well as to determine the optimal examination protocol to obtain the best diagnostic results. Thirty-four patients scheduled for knee surgery due to cartilage lesions were enrolled in the study and compared with 33 healthy individuals in the control group. VAG acquisition was performed prior to surgery, and cartilage status was evaluated during the surgery as a reference point. Both closed (CKC) and open (OKC) kinetic chains were assessed during VAG. The selection of the optimal signal measures was performed using a neighborhood component analysis (NCA) algorithm. The classification was performed using multilayer perceptron (MLP) and radial basis function (RBF) neural networks. The classification using artificial neural networks was performed for three variants: I. open kinetic chain, II. closed kinetic chain, and III. open and closed kinetic chain. The highest diagnostic accuracy was obtained for variants I and II for the RBF 9-35-2 and MLP 10-16-2 networks, respectively, achieving a classification accuracy of 98.53, a sensitivity of 0.958, and a specificity of 1. For variant III, a diagnostic accuracy of 97.79 was obtained with a sensitivity and specificity of 0.978 for MLP 8-3-2. This indicates a possible simplification of the examination protocol to single kinetic chain analyses. MDPI 2022-05-15 /pmc/articles/PMC9146478/ /pubmed/35632174 http://dx.doi.org/10.3390/s22103765 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Karpiński, Robert
Krakowski, Przemysław
Jonak, Józef
Machrowska, Anna
Maciejewski, Marcin
Nogalski, Adam
Diagnostics of Articular Cartilage Damage Based on Generated Acoustic Signals Using ANN—Part II: Patellofemoral Joint
title Diagnostics of Articular Cartilage Damage Based on Generated Acoustic Signals Using ANN—Part II: Patellofemoral Joint
title_full Diagnostics of Articular Cartilage Damage Based on Generated Acoustic Signals Using ANN—Part II: Patellofemoral Joint
title_fullStr Diagnostics of Articular Cartilage Damage Based on Generated Acoustic Signals Using ANN—Part II: Patellofemoral Joint
title_full_unstemmed Diagnostics of Articular Cartilage Damage Based on Generated Acoustic Signals Using ANN—Part II: Patellofemoral Joint
title_short Diagnostics of Articular Cartilage Damage Based on Generated Acoustic Signals Using ANN—Part II: Patellofemoral Joint
title_sort diagnostics of articular cartilage damage based on generated acoustic signals using ann—part ii: patellofemoral joint
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9146478/
https://www.ncbi.nlm.nih.gov/pubmed/35632174
http://dx.doi.org/10.3390/s22103765
work_keys_str_mv AT karpinskirobert diagnosticsofarticularcartilagedamagebasedongeneratedacousticsignalsusingannpartiipatellofemoraljoint
AT krakowskiprzemysław diagnosticsofarticularcartilagedamagebasedongeneratedacousticsignalsusingannpartiipatellofemoraljoint
AT jonakjozef diagnosticsofarticularcartilagedamagebasedongeneratedacousticsignalsusingannpartiipatellofemoraljoint
AT machrowskaanna diagnosticsofarticularcartilagedamagebasedongeneratedacousticsignalsusingannpartiipatellofemoraljoint
AT maciejewskimarcin diagnosticsofarticularcartilagedamagebasedongeneratedacousticsignalsusingannpartiipatellofemoraljoint
AT nogalskiadam diagnosticsofarticularcartilagedamagebasedongeneratedacousticsignalsusingannpartiipatellofemoraljoint