Texture analysis to differentiate anterior cruciate ligament in patients after surgery with platelet-rich plasma

Abstract Background Platelet-rich plasma (PRP) has been used to favor anterior cruciate ligament (ACL) healing after reconstruction surgeries. However, clinical data are still inconclusive and subjective about PRP. Thus, we propose a quantitative method to demonstrate that PRP produced morphological...

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Main Authors: Allan Felipe Fattori Alves, José Ricardo de Arruda Miranda, Sérgio Augusto Santana de Souza, Ricardo Violante Pereira, Paulo Roberto de Almeida Silvares, Seizo Yamashita, Elenice Deffune, Diana Rodrigues de Pina
Format: Article
Language:English
Published: BMC 2021-04-01
Series:Journal of Orthopaedic Surgery and Research
Subjects:
Online Access:https://doi.org/10.1186/s13018-021-02437-y
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spelling doaj-5d6506556d3045c29628c942fdfb5e202021-05-02T11:28:37ZengBMCJournal of Orthopaedic Surgery and Research1749-799X2021-04-011611810.1186/s13018-021-02437-yTexture analysis to differentiate anterior cruciate ligament in patients after surgery with platelet-rich plasmaAllan Felipe Fattori Alves0José Ricardo de Arruda Miranda1Sérgio Augusto Santana de Souza2Ricardo Violante Pereira3Paulo Roberto de Almeida Silvares4Seizo Yamashita5Elenice Deffune6Diana Rodrigues de Pina7Medical School, Sao Paulo State University Julio de Mesquita FilhoInstitute of Bioscience, Sao Paulo State University Julio de Mesquita FilhoInstitute of Bioscience, Sao Paulo State University Julio de Mesquita FilhoMedical School, Sao Paulo State University Julio de Mesquita FilhoMedical School, Sao Paulo State University Julio de Mesquita FilhoMedical School, Sao Paulo State University Julio de Mesquita FilhoMedical School, Sao Paulo State University Julio de Mesquita FilhoMedical School, Sao Paulo State University Julio de Mesquita FilhoAbstract Background Platelet-rich plasma (PRP) has been used to favor anterior cruciate ligament (ACL) healing after reconstruction surgeries. However, clinical data are still inconclusive and subjective about PRP. Thus, we propose a quantitative method to demonstrate that PRP produced morphological structure changes. Methods Thirty-four patients undergoing ACL reconstruction surgery were evaluated and divided into control group (sixteen patients) without PRP application and experiment group (eighteen patients) with intraoperative application of PRP. Magnetic resonance imaging (MRI) scans were performed 3 months after surgery. We used Matlab® and machine learning (ML) in Orange Canvas® to texture analysis (TA) features extraction. Experienced radiologists delimited the regions of interest (RoIs) in the T2-weighted images. Sixty-two texture parameters were extracted, including gray-level co-occurrence matrix and gray level run length. We used the algorithms logistic regression (LR), naive Bayes (NB), and stochastic gradient descent (SGD). Results The accuracy of the classification with NB, LR, and SGD was 83.3%, 75%, 75%, respectively. For the area under the curve, NB, LR, and SGD presented values of 91.7%, 94.4%, 75%, respectively. In clinical evaluations, the groups show similar responses in terms of improvement in pain and increase in the IKDC index (International Knee Documentation Committee) and Lysholm score indices differing only in the assessment of flexion, which presents a significant difference for the group treated with PRP. Conclusions Here, we demonstrated quantitatively that patients who received PRP presented texture changes when compared to the control group. Thus, our findings suggest that PRP interferes with morphological parameters of the ACL. Trial registration Protocol no. CAAE 56164316.6.0000.5411.https://doi.org/10.1186/s13018-021-02437-yKnee jointClassificationMagnetic resonance imagingTexture analysisMachine learningPlatelet-rich plasma
collection DOAJ
language English
format Article
sources DOAJ
author Allan Felipe Fattori Alves
José Ricardo de Arruda Miranda
Sérgio Augusto Santana de Souza
Ricardo Violante Pereira
Paulo Roberto de Almeida Silvares
Seizo Yamashita
Elenice Deffune
Diana Rodrigues de Pina
spellingShingle Allan Felipe Fattori Alves
José Ricardo de Arruda Miranda
Sérgio Augusto Santana de Souza
Ricardo Violante Pereira
Paulo Roberto de Almeida Silvares
Seizo Yamashita
Elenice Deffune
Diana Rodrigues de Pina
Texture analysis to differentiate anterior cruciate ligament in patients after surgery with platelet-rich plasma
Journal of Orthopaedic Surgery and Research
Knee joint
Classification
Magnetic resonance imaging
Texture analysis
Machine learning
Platelet-rich plasma
author_facet Allan Felipe Fattori Alves
José Ricardo de Arruda Miranda
Sérgio Augusto Santana de Souza
Ricardo Violante Pereira
Paulo Roberto de Almeida Silvares
Seizo Yamashita
Elenice Deffune
Diana Rodrigues de Pina
author_sort Allan Felipe Fattori Alves
title Texture analysis to differentiate anterior cruciate ligament in patients after surgery with platelet-rich plasma
title_short Texture analysis to differentiate anterior cruciate ligament in patients after surgery with platelet-rich plasma
title_full Texture analysis to differentiate anterior cruciate ligament in patients after surgery with platelet-rich plasma
title_fullStr Texture analysis to differentiate anterior cruciate ligament in patients after surgery with platelet-rich plasma
title_full_unstemmed Texture analysis to differentiate anterior cruciate ligament in patients after surgery with platelet-rich plasma
title_sort texture analysis to differentiate anterior cruciate ligament in patients after surgery with platelet-rich plasma
publisher BMC
series Journal of Orthopaedic Surgery and Research
issn 1749-799X
publishDate 2021-04-01
description Abstract Background Platelet-rich plasma (PRP) has been used to favor anterior cruciate ligament (ACL) healing after reconstruction surgeries. However, clinical data are still inconclusive and subjective about PRP. Thus, we propose a quantitative method to demonstrate that PRP produced morphological structure changes. Methods Thirty-four patients undergoing ACL reconstruction surgery were evaluated and divided into control group (sixteen patients) without PRP application and experiment group (eighteen patients) with intraoperative application of PRP. Magnetic resonance imaging (MRI) scans were performed 3 months after surgery. We used Matlab® and machine learning (ML) in Orange Canvas® to texture analysis (TA) features extraction. Experienced radiologists delimited the regions of interest (RoIs) in the T2-weighted images. Sixty-two texture parameters were extracted, including gray-level co-occurrence matrix and gray level run length. We used the algorithms logistic regression (LR), naive Bayes (NB), and stochastic gradient descent (SGD). Results The accuracy of the classification with NB, LR, and SGD was 83.3%, 75%, 75%, respectively. For the area under the curve, NB, LR, and SGD presented values of 91.7%, 94.4%, 75%, respectively. In clinical evaluations, the groups show similar responses in terms of improvement in pain and increase in the IKDC index (International Knee Documentation Committee) and Lysholm score indices differing only in the assessment of flexion, which presents a significant difference for the group treated with PRP. Conclusions Here, we demonstrated quantitatively that patients who received PRP presented texture changes when compared to the control group. Thus, our findings suggest that PRP interferes with morphological parameters of the ACL. Trial registration Protocol no. CAAE 56164316.6.0000.5411.
topic Knee joint
Classification
Magnetic resonance imaging
Texture analysis
Machine learning
Platelet-rich plasma
url https://doi.org/10.1186/s13018-021-02437-y
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