Cargando…
Three-Dimensional Reconstruction of a CT Image under Deep Learning Algorithm to Evaluate the Application of Percutaneous Kyphoplasty in Osteoporotic Thoracolumbar Compression Fractures
In order to investigate the therapeutic evaluation of percutaneous kyphoplasty (PKP) for the treatment of osteoporotic thoracolumbar compression fractures by three-dimensional (3D) reconstruction of computed tomography (CT) based on the deep learning V-Net network, the traditional V-Net was optimize...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9290755/ https://www.ncbi.nlm.nih.gov/pubmed/35919502 http://dx.doi.org/10.1155/2022/9107021 |
_version_ | 1784748983698063360 |
---|---|
author | Li, Jiameng Xiang, Zhong Zhou, Jiaqing Zhang, Meng |
author_facet | Li, Jiameng Xiang, Zhong Zhou, Jiaqing Zhang, Meng |
author_sort | Li, Jiameng |
collection | PubMed |
description | In order to investigate the therapeutic evaluation of percutaneous kyphoplasty (PKP) for the treatment of osteoporotic thoracolumbar compression fractures by three-dimensional (3D) reconstruction of computed tomography (CT) based on the deep learning V-Net network, the traditional V-Net was optimized first and a new and improved V-Net was proposed. The introduced U-Net, V-Net, and convolutional neural network (CNN) were compared in this study. Then, 106 patients with osteoporotic thoracolumbar compression fractures were enrolled, and 128 centrums were divided into the test group with 53 cases of PKP and the control group with 53 cases of percutaneous vertebroplasty (PVP) according to different surgical protocols. All patients underwent CT scan based on the improved V-Net, and data of centrum measurement indicators, pain score, and therapeutic evaluation results of the modified Macnab were collected. The Dice coefficient of the improved V-Net was observably higher than that of U-Net, V-Net, and CNN, while the Hausdorff distance was lower than that of U-Net, V-Net, and CNN (P < 0.05). The anterior height, central height, and posterior height of the centrum were significantly higher than those in the control group after operation (3, 5, and 7 days), while the Cobb angle of vertebral kyphosis was significantly lower than that in the control group (P < 0.05). The score of visual analog scale (VAS) and analgesic use score of patients in the test group were markedly lower than those in the control group (3, 5, and 7 days after operation), P < 0.05. Besides, the excellent and good rate of the test group was remarkably higher than that of the control group, P < 0.05. Hence, the improved V-Net had better quality of segmentation and reconstruction than the traditional deep learning network. Compared with PVP, PKP was helpful in restoring the height of the centrum in patients with osteoporotic thoracolumbar compression fractures and correct kyphosis, with better analgesic effect safety. |
format | Online Article Text |
id | pubmed-9290755 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-92907552022-08-01 Three-Dimensional Reconstruction of a CT Image under Deep Learning Algorithm to Evaluate the Application of Percutaneous Kyphoplasty in Osteoporotic Thoracolumbar Compression Fractures Li, Jiameng Xiang, Zhong Zhou, Jiaqing Zhang, Meng Contrast Media Mol Imaging Research Article In order to investigate the therapeutic evaluation of percutaneous kyphoplasty (PKP) for the treatment of osteoporotic thoracolumbar compression fractures by three-dimensional (3D) reconstruction of computed tomography (CT) based on the deep learning V-Net network, the traditional V-Net was optimized first and a new and improved V-Net was proposed. The introduced U-Net, V-Net, and convolutional neural network (CNN) were compared in this study. Then, 106 patients with osteoporotic thoracolumbar compression fractures were enrolled, and 128 centrums were divided into the test group with 53 cases of PKP and the control group with 53 cases of percutaneous vertebroplasty (PVP) according to different surgical protocols. All patients underwent CT scan based on the improved V-Net, and data of centrum measurement indicators, pain score, and therapeutic evaluation results of the modified Macnab were collected. The Dice coefficient of the improved V-Net was observably higher than that of U-Net, V-Net, and CNN, while the Hausdorff distance was lower than that of U-Net, V-Net, and CNN (P < 0.05). The anterior height, central height, and posterior height of the centrum were significantly higher than those in the control group after operation (3, 5, and 7 days), while the Cobb angle of vertebral kyphosis was significantly lower than that in the control group (P < 0.05). The score of visual analog scale (VAS) and analgesic use score of patients in the test group were markedly lower than those in the control group (3, 5, and 7 days after operation), P < 0.05. Besides, the excellent and good rate of the test group was remarkably higher than that of the control group, P < 0.05. Hence, the improved V-Net had better quality of segmentation and reconstruction than the traditional deep learning network. Compared with PVP, PKP was helpful in restoring the height of the centrum in patients with osteoporotic thoracolumbar compression fractures and correct kyphosis, with better analgesic effect safety. Hindawi 2022-04-28 /pmc/articles/PMC9290755/ /pubmed/35919502 http://dx.doi.org/10.1155/2022/9107021 Text en Copyright © 2022 Jiameng Li 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 Li, Jiameng Xiang, Zhong Zhou, Jiaqing Zhang, Meng Three-Dimensional Reconstruction of a CT Image under Deep Learning Algorithm to Evaluate the Application of Percutaneous Kyphoplasty in Osteoporotic Thoracolumbar Compression Fractures |
title | Three-Dimensional Reconstruction of a CT Image under Deep Learning Algorithm
to Evaluate the Application of Percutaneous Kyphoplasty in Osteoporotic Thoracolumbar
Compression Fractures |
title_full | Three-Dimensional Reconstruction of a CT Image under Deep Learning Algorithm
to Evaluate the Application of Percutaneous Kyphoplasty in Osteoporotic Thoracolumbar
Compression Fractures |
title_fullStr | Three-Dimensional Reconstruction of a CT Image under Deep Learning Algorithm
to Evaluate the Application of Percutaneous Kyphoplasty in Osteoporotic Thoracolumbar
Compression Fractures |
title_full_unstemmed | Three-Dimensional Reconstruction of a CT Image under Deep Learning Algorithm
to Evaluate the Application of Percutaneous Kyphoplasty in Osteoporotic Thoracolumbar
Compression Fractures |
title_short | Three-Dimensional Reconstruction of a CT Image under Deep Learning Algorithm
to Evaluate the Application of Percutaneous Kyphoplasty in Osteoporotic Thoracolumbar
Compression Fractures |
title_sort | three-dimensional reconstruction of a ct image under deep learning algorithm
to evaluate the application of percutaneous kyphoplasty in osteoporotic thoracolumbar
compression fractures |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9290755/ https://www.ncbi.nlm.nih.gov/pubmed/35919502 http://dx.doi.org/10.1155/2022/9107021 |
work_keys_str_mv | AT lijiameng threedimensionalreconstructionofactimageunderdeeplearningalgorithmtoevaluatetheapplicationofpercutaneouskyphoplastyinosteoporoticthoracolumbarcompressionfractures AT xiangzhong threedimensionalreconstructionofactimageunderdeeplearningalgorithmtoevaluatetheapplicationofpercutaneouskyphoplastyinosteoporoticthoracolumbarcompressionfractures AT zhoujiaqing threedimensionalreconstructionofactimageunderdeeplearningalgorithmtoevaluatetheapplicationofpercutaneouskyphoplastyinosteoporoticthoracolumbarcompressionfractures AT zhangmeng threedimensionalreconstructionofactimageunderdeeplearningalgorithmtoevaluatetheapplicationofpercutaneouskyphoplastyinosteoporoticthoracolumbarcompressionfractures |