Abstract

BackgroundPlatelet-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.MethodsThirty-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).ResultsThe 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.ConclusionsHere, 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 registrationProtocol no. CAAE 56164316.6.0000.5411.

Highlights

  • The technological advance of regenerative medicine capacitated the integration of tissue engineering with orthopedics daily practice, allowing prosperous results in the treatment of lesions and diseases [1, 2]

  • Texture and machine learning analyses regions of interest (RoI) were positioned on the sagittal plane along the largest diameter of the anterior cruciate ligament (ACL) by two experienced radiologists

  • In conclusion, texture analysis (TA) associated with machine learning (ML) classifiers proved to be a feasible tool in the differentiation of patients after ACL reconstruction surgery with and without the use of Platelet-rich plasma (PRP)

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Summary

Introduction

The technological advance of regenerative medicine capacitated the integration of tissue engineering with orthopedics daily practice, allowing prosperous results in the treatment of lesions and diseases [1, 2]. The anterior cruciate ligament (ACL) reconstruction surgery, frequently performed in sportive medicine, is an example of such integration [1, 3]. ACL is important since it maintains the movement and normal stability of knee articulation. ACL is usually injured due to high tension forces of traction and knee torsion. Over 400,000 reconstruction surgeries are performed annually worldwide [4]. Treatments choices consider factors such as patients’ age, knee instability, and the type and sports practiced. Platelet-rich plasma (PRP) has been used to favor anterior cruciate ligament (ACL) healing after reconstruction surgeries. We propose a quantitative method to demonstrate that PRP produced morphological structure changes

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