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Assessing bone mineral density in non-weight bearing regions of the body: a texture analysis approach using abdomen and pelvis computed tomography Hounsfield units—a cross-sectional study
BACKGROUND: Highlighting a gap in comprehending bone microarchitecture’s intricacies using dual-energy X-ray absorptiometry (DXA), this study aims to bridge this chasm by analyzing texture in non-weight bearing regions on axial computed tomography (CT) scans. Our goal is to enrich osteoporosis patie...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AME Publishing Company
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10644143/ https://www.ncbi.nlm.nih.gov/pubmed/37969628 http://dx.doi.org/10.21037/qims-23-512 |
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author | Kim, Min Woo Huh, Jung Wook Noh, Young Min Seo, Han Eol Lee, Dong Ha |
author_facet | Kim, Min Woo Huh, Jung Wook Noh, Young Min Seo, Han Eol Lee, Dong Ha |
author_sort | Kim, Min Woo |
collection | PubMed |
description | BACKGROUND: Highlighting a gap in comprehending bone microarchitecture’s intricacies using dual-energy X-ray absorptiometry (DXA), this study aims to bridge this chasm by analyzing texture in non-weight bearing regions on axial computed tomography (CT) scans. Our goal is to enrich osteoporosis patient management by enhancing bone quality and microarchitecture insights. METHODS: Conducted at Busan Medical Center from March 1, 2013, to August 30, 2022, 1,320 cases (782 patients) were screened. After applying exclusion criteria, 458 samples (296 patients) underwent bone mineral density (BMD) assessment with both CT and DXA. Regions of interest (ROIs) included spine pedicle’s maximum trabecular area, sacrum Zone 1, superior/inferior pubic ramus, and femur’s greater/lesser trochanters. Texture features (n=45) were extracted from ROIs using gray-level co-occurrence matrices. A regression model predicted BMD, spotlighting the top five influential texture features. RESULTS: Correlation coefficients ranged from 0.709 (lowest for total femur BMD) to 0.804 (highest for femur intertrochanter BMD). Mean squared error (MSE) values were also provided for lumbar and femur BMD/bone mineral content (BMC) metrics. The most influential texture features included contrast_32, correlation_32_v, and three other metrics. CONCLUSIONS: By melding traditional DXA and CT texture analysis, our approach presents a comprehensive bone health perspective, potentially revolutionizing osteoporosis diagnostics. |
format | Online Article Text |
id | pubmed-10644143 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | AME Publishing Company |
record_format | MEDLINE/PubMed |
spelling | pubmed-106441432023-11-15 Assessing bone mineral density in non-weight bearing regions of the body: a texture analysis approach using abdomen and pelvis computed tomography Hounsfield units—a cross-sectional study Kim, Min Woo Huh, Jung Wook Noh, Young Min Seo, Han Eol Lee, Dong Ha Quant Imaging Med Surg Original Article BACKGROUND: Highlighting a gap in comprehending bone microarchitecture’s intricacies using dual-energy X-ray absorptiometry (DXA), this study aims to bridge this chasm by analyzing texture in non-weight bearing regions on axial computed tomography (CT) scans. Our goal is to enrich osteoporosis patient management by enhancing bone quality and microarchitecture insights. METHODS: Conducted at Busan Medical Center from March 1, 2013, to August 30, 2022, 1,320 cases (782 patients) were screened. After applying exclusion criteria, 458 samples (296 patients) underwent bone mineral density (BMD) assessment with both CT and DXA. Regions of interest (ROIs) included spine pedicle’s maximum trabecular area, sacrum Zone 1, superior/inferior pubic ramus, and femur’s greater/lesser trochanters. Texture features (n=45) were extracted from ROIs using gray-level co-occurrence matrices. A regression model predicted BMD, spotlighting the top five influential texture features. RESULTS: Correlation coefficients ranged from 0.709 (lowest for total femur BMD) to 0.804 (highest for femur intertrochanter BMD). Mean squared error (MSE) values were also provided for lumbar and femur BMD/bone mineral content (BMC) metrics. The most influential texture features included contrast_32, correlation_32_v, and three other metrics. CONCLUSIONS: By melding traditional DXA and CT texture analysis, our approach presents a comprehensive bone health perspective, potentially revolutionizing osteoporosis diagnostics. AME Publishing Company 2023-09-14 2023-11-01 /pmc/articles/PMC10644143/ /pubmed/37969628 http://dx.doi.org/10.21037/qims-23-512 Text en 2023 Quantitative Imaging in Medicine and Surgery. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) . |
spellingShingle | Original Article Kim, Min Woo Huh, Jung Wook Noh, Young Min Seo, Han Eol Lee, Dong Ha Assessing bone mineral density in non-weight bearing regions of the body: a texture analysis approach using abdomen and pelvis computed tomography Hounsfield units—a cross-sectional study |
title | Assessing bone mineral density in non-weight bearing regions of the body: a texture analysis approach using abdomen and pelvis computed tomography Hounsfield units—a cross-sectional study |
title_full | Assessing bone mineral density in non-weight bearing regions of the body: a texture analysis approach using abdomen and pelvis computed tomography Hounsfield units—a cross-sectional study |
title_fullStr | Assessing bone mineral density in non-weight bearing regions of the body: a texture analysis approach using abdomen and pelvis computed tomography Hounsfield units—a cross-sectional study |
title_full_unstemmed | Assessing bone mineral density in non-weight bearing regions of the body: a texture analysis approach using abdomen and pelvis computed tomography Hounsfield units—a cross-sectional study |
title_short | Assessing bone mineral density in non-weight bearing regions of the body: a texture analysis approach using abdomen and pelvis computed tomography Hounsfield units—a cross-sectional study |
title_sort | assessing bone mineral density in non-weight bearing regions of the body: a texture analysis approach using abdomen and pelvis computed tomography hounsfield units—a cross-sectional study |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10644143/ https://www.ncbi.nlm.nih.gov/pubmed/37969628 http://dx.doi.org/10.21037/qims-23-512 |
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