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Preoperative prediction of residual back pain after vertebral augmentation for osteoporotic vertebral compression fractures: Initial application of a radiomics score based nomogram
BACKGROUND: Most patients with osteoporotic vertebral compression fracture (OVCF) obtain pain relief after vertebral augmentation, but some will experience residual back pain (RBP) after surgery. Although several risk factors of RBP have been reported, it is still difficult to estimate the risk of R...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9816386/ https://www.ncbi.nlm.nih.gov/pubmed/36619583 http://dx.doi.org/10.3389/fendo.2022.1093508 |
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author | Ge, Chen Chen, Zhe Lin, Yazhou Zheng, Yuehuan Cao, Peng Chen, Xiaoyong |
author_facet | Ge, Chen Chen, Zhe Lin, Yazhou Zheng, Yuehuan Cao, Peng Chen, Xiaoyong |
author_sort | Ge, Chen |
collection | PubMed |
description | BACKGROUND: Most patients with osteoporotic vertebral compression fracture (OVCF) obtain pain relief after vertebral augmentation, but some will experience residual back pain (RBP) after surgery. Although several risk factors of RBP have been reported, it is still difficult to estimate the risk of RBP preoperatively. Radiomics is helpful for disease diagnosis and outcome prediction by establishing complementary relationships between human-recognizable and computer-extracted features. However, musculoskeletal radiomics investigations are less frequently reported. OBJECTIVE: This study aims to establish a radiomics score (rad-score) based nomogram for the preoperative prediction of RBP in OVCF patients. METHODS: The training cohort of 731 OVCF patients was used for nomogram development, and the validation cohort was utilized for performance test. RBP was determined as the score of visual analogue scale ≥ 4 at both 3 and 30 days following surgery. After normalization, the RBP-related radiomics features were selected to create rad-scores. These rad-scores, along with the RBP predictors initially identified by univariate analyses, were included in the multivariate analysis to establish a nomogram for the assessment of the RBP risk in OVCF patients preoperatively. RESULTS: A total of 81 patients (11.2%) developed RBP postoperatively. We finally selected 8 radiomics features from 1316 features extracted from each segmented image to determine the rad-score. Multivariate analysis revealed that the rad-score plus bone mineral density, intravertebral cleft, and thoracolumbar fascia injury were independent factors of RBP. Our nomograms based on these factors demonstrated good discrimination, calibration, and clinical utility in both training and validation cohorts. Furthermore, it achieved better performance than the rad-score itself, as well as the nomogram only incorporating regular features. CONCLUSION: We developed and validated a nomogram incorporating the rad-score and regular features for preoperative prediction of the RBP risk in OVCF patients, which contributed to improved surgical outcomes and patient satisfaction. |
format | Online Article Text |
id | pubmed-9816386 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-98163862023-01-07 Preoperative prediction of residual back pain after vertebral augmentation for osteoporotic vertebral compression fractures: Initial application of a radiomics score based nomogram Ge, Chen Chen, Zhe Lin, Yazhou Zheng, Yuehuan Cao, Peng Chen, Xiaoyong Front Endocrinol (Lausanne) Endocrinology BACKGROUND: Most patients with osteoporotic vertebral compression fracture (OVCF) obtain pain relief after vertebral augmentation, but some will experience residual back pain (RBP) after surgery. Although several risk factors of RBP have been reported, it is still difficult to estimate the risk of RBP preoperatively. Radiomics is helpful for disease diagnosis and outcome prediction by establishing complementary relationships between human-recognizable and computer-extracted features. However, musculoskeletal radiomics investigations are less frequently reported. OBJECTIVE: This study aims to establish a radiomics score (rad-score) based nomogram for the preoperative prediction of RBP in OVCF patients. METHODS: The training cohort of 731 OVCF patients was used for nomogram development, and the validation cohort was utilized for performance test. RBP was determined as the score of visual analogue scale ≥ 4 at both 3 and 30 days following surgery. After normalization, the RBP-related radiomics features were selected to create rad-scores. These rad-scores, along with the RBP predictors initially identified by univariate analyses, were included in the multivariate analysis to establish a nomogram for the assessment of the RBP risk in OVCF patients preoperatively. RESULTS: A total of 81 patients (11.2%) developed RBP postoperatively. We finally selected 8 radiomics features from 1316 features extracted from each segmented image to determine the rad-score. Multivariate analysis revealed that the rad-score plus bone mineral density, intravertebral cleft, and thoracolumbar fascia injury were independent factors of RBP. Our nomograms based on these factors demonstrated good discrimination, calibration, and clinical utility in both training and validation cohorts. Furthermore, it achieved better performance than the rad-score itself, as well as the nomogram only incorporating regular features. CONCLUSION: We developed and validated a nomogram incorporating the rad-score and regular features for preoperative prediction of the RBP risk in OVCF patients, which contributed to improved surgical outcomes and patient satisfaction. Frontiers Media S.A. 2022-12-23 /pmc/articles/PMC9816386/ /pubmed/36619583 http://dx.doi.org/10.3389/fendo.2022.1093508 Text en Copyright © 2022 Ge, Chen, Lin, Zheng, Cao and Chen https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Endocrinology Ge, Chen Chen, Zhe Lin, Yazhou Zheng, Yuehuan Cao, Peng Chen, Xiaoyong Preoperative prediction of residual back pain after vertebral augmentation for osteoporotic vertebral compression fractures: Initial application of a radiomics score based nomogram |
title | Preoperative prediction of residual back pain after vertebral augmentation for osteoporotic vertebral compression fractures: Initial application of a radiomics score based nomogram |
title_full | Preoperative prediction of residual back pain after vertebral augmentation for osteoporotic vertebral compression fractures: Initial application of a radiomics score based nomogram |
title_fullStr | Preoperative prediction of residual back pain after vertebral augmentation for osteoporotic vertebral compression fractures: Initial application of a radiomics score based nomogram |
title_full_unstemmed | Preoperative prediction of residual back pain after vertebral augmentation for osteoporotic vertebral compression fractures: Initial application of a radiomics score based nomogram |
title_short | Preoperative prediction of residual back pain after vertebral augmentation for osteoporotic vertebral compression fractures: Initial application of a radiomics score based nomogram |
title_sort | preoperative prediction of residual back pain after vertebral augmentation for osteoporotic vertebral compression fractures: initial application of a radiomics score based nomogram |
topic | Endocrinology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9816386/ https://www.ncbi.nlm.nih.gov/pubmed/36619583 http://dx.doi.org/10.3389/fendo.2022.1093508 |
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