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Artificial Intelligence Algorithm-Based Magnetic Resonance Imaging to Evaluate the Effect of Radiation Synovectomy for Hemophilic Arthropathy

This study aimed to discuss magnetic resonance imaging (MRI) based on artificial intelligence (AI) algorithm to evaluate the effect of radiation synovectomy for hemophilic arthropathy (HA). MRI based on the Canny algorithm was applied and compared with conventional MRI to evaluate its application ef...

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Autores principales: Zhang, Heng, Duan, Shukai, Xiao, Wei, Yang, Xinyue, Li, Shenglin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8957465/
https://www.ncbi.nlm.nih.gov/pubmed/35360269
http://dx.doi.org/10.1155/2022/5694163
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author Zhang, Heng
Duan, Shukai
Xiao, Wei
Yang, Xinyue
Li, Shenglin
author_facet Zhang, Heng
Duan, Shukai
Xiao, Wei
Yang, Xinyue
Li, Shenglin
author_sort Zhang, Heng
collection PubMed
description This study aimed to discuss magnetic resonance imaging (MRI) based on artificial intelligence (AI) algorithm to evaluate the effect of radiation synovectomy for hemophilic arthropathy (HA). MRI based on the Canny algorithm was applied and compared with conventional MRI to evaluate its application effects according to the PSNR and SSIM. Sixty patients diagnosed with HA were selected as the research subjects. According to the detection method, the patients were divided into group A (pathological detection after radiation synovectomy), group B (conventional MRI detection), and group C (MRI detection based on the Canny algorithm). The application value of MRI based on the Canny algorithm was judged by comparing the differences between the two detection methods and pathological results. The results displayed that the reconstruction effect of the Canny algorithm was remarkably better than that of the traditional algorithm regarding the peak signal-to-noise ratio (PSNR) and structural similarity (SSIM), which showed a clearer synovial contour. The results of the IPSG score of joint effusion and hemorrhage showed that there was a difference in the detection rate of joints between conventional MRI and pathological results on the score of 1 and 2 (P < 0.05); and there was no significant difference between the MRI and pathological results based on the Canny algorithm (P > 0.05). The results of the IPSG score of synovial hyperplasia showed that the detection rate of conventional MRI was different from pathological results on the score of 1 and 2 (P < 0.05); and there was no significant difference between the MRI and pathological results based on the Canny algorithm (P > 0.05). The results of the IPSG score of hemosiderin deposition showed that the detection rate of conventional MRI was different from the pathological results on the score of 1 and 2 (P < 0.05); and there was no significant difference between the MRI and pathological results based on the Canny algorithm (P > 0.05). The synovial volume of patients after surgery was reduced compared with that before surgery. One-factor variance was used to analyze the clinical hemorrhage frequency before and after surgery, and the results showed that the differences were statistically significant (P < 0.05). Therefore, MRI on account of AI algorithm made it easier to detect synovial contour, which was helpful to evaluate the efficacy of polygenic risk scores (PRS) surgery in HA patients. MRI based on the Canny algorithm had less differences between the score of hemophilic arthropathy and pathological results, which could replace conventional MRI examination and have clinical application value.
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spelling pubmed-89574652022-03-30 Artificial Intelligence Algorithm-Based Magnetic Resonance Imaging to Evaluate the Effect of Radiation Synovectomy for Hemophilic Arthropathy Zhang, Heng Duan, Shukai Xiao, Wei Yang, Xinyue Li, Shenglin Contrast Media Mol Imaging Research Article This study aimed to discuss magnetic resonance imaging (MRI) based on artificial intelligence (AI) algorithm to evaluate the effect of radiation synovectomy for hemophilic arthropathy (HA). MRI based on the Canny algorithm was applied and compared with conventional MRI to evaluate its application effects according to the PSNR and SSIM. Sixty patients diagnosed with HA were selected as the research subjects. According to the detection method, the patients were divided into group A (pathological detection after radiation synovectomy), group B (conventional MRI detection), and group C (MRI detection based on the Canny algorithm). The application value of MRI based on the Canny algorithm was judged by comparing the differences between the two detection methods and pathological results. The results displayed that the reconstruction effect of the Canny algorithm was remarkably better than that of the traditional algorithm regarding the peak signal-to-noise ratio (PSNR) and structural similarity (SSIM), which showed a clearer synovial contour. The results of the IPSG score of joint effusion and hemorrhage showed that there was a difference in the detection rate of joints between conventional MRI and pathological results on the score of 1 and 2 (P < 0.05); and there was no significant difference between the MRI and pathological results based on the Canny algorithm (P > 0.05). The results of the IPSG score of synovial hyperplasia showed that the detection rate of conventional MRI was different from pathological results on the score of 1 and 2 (P < 0.05); and there was no significant difference between the MRI and pathological results based on the Canny algorithm (P > 0.05). The results of the IPSG score of hemosiderin deposition showed that the detection rate of conventional MRI was different from the pathological results on the score of 1 and 2 (P < 0.05); and there was no significant difference between the MRI and pathological results based on the Canny algorithm (P > 0.05). The synovial volume of patients after surgery was reduced compared with that before surgery. One-factor variance was used to analyze the clinical hemorrhage frequency before and after surgery, and the results showed that the differences were statistically significant (P < 0.05). Therefore, MRI on account of AI algorithm made it easier to detect synovial contour, which was helpful to evaluate the efficacy of polygenic risk scores (PRS) surgery in HA patients. MRI based on the Canny algorithm had less differences between the score of hemophilic arthropathy and pathological results, which could replace conventional MRI examination and have clinical application value. Hindawi 2022-03-19 /pmc/articles/PMC8957465/ /pubmed/35360269 http://dx.doi.org/10.1155/2022/5694163 Text en Copyright © 2022 Heng Zhang et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Zhang, Heng
Duan, Shukai
Xiao, Wei
Yang, Xinyue
Li, Shenglin
Artificial Intelligence Algorithm-Based Magnetic Resonance Imaging to Evaluate the Effect of Radiation Synovectomy for Hemophilic Arthropathy
title Artificial Intelligence Algorithm-Based Magnetic Resonance Imaging to Evaluate the Effect of Radiation Synovectomy for Hemophilic Arthropathy
title_full Artificial Intelligence Algorithm-Based Magnetic Resonance Imaging to Evaluate the Effect of Radiation Synovectomy for Hemophilic Arthropathy
title_fullStr Artificial Intelligence Algorithm-Based Magnetic Resonance Imaging to Evaluate the Effect of Radiation Synovectomy for Hemophilic Arthropathy
title_full_unstemmed Artificial Intelligence Algorithm-Based Magnetic Resonance Imaging to Evaluate the Effect of Radiation Synovectomy for Hemophilic Arthropathy
title_short Artificial Intelligence Algorithm-Based Magnetic Resonance Imaging to Evaluate the Effect of Radiation Synovectomy for Hemophilic Arthropathy
title_sort artificial intelligence algorithm-based magnetic resonance imaging to evaluate the effect of radiation synovectomy for hemophilic arthropathy
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8957465/
https://www.ncbi.nlm.nih.gov/pubmed/35360269
http://dx.doi.org/10.1155/2022/5694163
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