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阐明骨密度与多裂肌特征之间的相关性:一项采用双能X线吸收法和脊柱计算机断层扫描纹理分析的跨模态研究。

Elucidating the Correlation between Bone Mineral Density and Multifidus Muscle Characteristics: A Cross-Modal Study with Dual-Energy X-ray Absorptiometry and Spinal Computed Tomography Texture Analysis.

作者信息

Kim Min-Woo, Noh Young-Min, Jung Yun-Sung, Jeon Se-Yeong, Lee Dong-Ha

机构信息

Department of Orthopedic Surgery, Busan Medical Center, 62, Yangjeong-ro, Busanjin-gu, Busan 47227, Republic of Korea.

Ulsan National Institute of Science and Technology, Ulsan 44919, Republic of Korea.

出版信息

Diagnostics (Basel). 2023 Nov 17;13(22):3466. doi: 10.3390/diagnostics13223466.

DOI:10.3390/diagnostics13223466
PMID:37998602
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10670274/
Abstract

BACKGROUND

Recent research underscores the clinical relevance of muscle conditions such as sarcopenia and their links to bone mineral density (BMD), yet notable gaps persist in the understanding of their interconnections. Our study addresses this by introducing a novel approach to decipher the correlation between BMD and the texture of the multifidus muscle, utilizing spinal computed tomography (CT) and dual-energy X-ray absorptiometry (DXA) to evaluate muscle texture, BMD, and bone mineral content (BMC) at the total lumbar vertebra and total hip.

METHODS

Our single-institution study examined 395 cases collected from 6 May 2012 to 30 November 2021. Each patient underwent a spinal CT scan and a DXA scan within a one-month interval. BMD and BMC at the total lumbar vertebra and total hip were measured. The texture features of the multifidus muscle from the axial cuts of T12 to S1 vertebrae were assessed via gray-level co-occurrence matrices. CT texture analysis values at angles of 45 + 45 and 90 degrees were calculated and correlated with BMD and BMC. A regression model was then constructed to predict BMD values, and the precision of these correlations was evaluated using mean square error (MSE) analysis.

RESULTS

Total lumbar BMC showed a correlation of 0.583-0.721 (MSE 1.568-1.842) and lumbar BMD of 0.632-0.756 (MSE 0.068-0.097). Total hip BMC had a correlation of 0.556-0.690 (MSE 0.448-0.495), while hip BMD ranged from 0.585 to 0.746 (MSE 0.072-0.092).

CONCLUSIONS

The analysis of spinal CT texture alongside BMD and BMC measures provides a new approach to understanding the relationship between bone and muscle health. The strong correlations expected from our research affirm the importance of integrating bone and muscle measures in the prevention, diagnosis, and management of conditions such as sarcopenia and osteoporosis.

摘要

背景

近期研究强调了肌肉减少症等肌肉状况的临床相关性及其与骨密度(BMD)的联系,但在理解它们之间的相互关系方面仍存在显著差距。我们的研究通过引入一种新方法来解决这一问题,该方法利用脊柱计算机断层扫描(CT)和双能X线吸收法(DXA)来评估多裂肌的纹理、BMD以及全腰椎和全髋关节的骨矿物质含量(BMC),从而解读BMD与多裂肌纹理之间的相关性。

方法

我们在单一机构开展的研究纳入了2012年5月6日至2021年11月30日期间收集的395例病例。每位患者在1个月内先后接受了脊柱CT扫描和DXA扫描。测量全腰椎和全髋关节的BMD和BMC。通过灰度共生矩阵评估T12至S1椎体轴位切片上多裂肌的纹理特征。计算45°+45°和90°角度下的CT纹理分析值,并将其与BMD和BMC进行关联。然后构建回归模型来预测BMD值,并使用均方误差(MSE)分析评估这些相关性的精度。

结果

全腰椎BMC的相关性为0.583 - 0.721(MSE为1.568 - 1.842),腰椎BMD的相关性为0.632 - 0.756(MSE为0.068 - 0.097)。全髋关节BMC的相关性为0.556 - 0.690(MSE为0.448 - 0.495),而髋关节BMD范围为0.585至0.746(MSE为0.072 - 0.092)。

结论

结合BMD和BMC测量对脊柱CT纹理进行分析,为理解骨骼与肌肉健康之间的关系提供了一种新方法。我们研究中预期的强相关性证实了在肌肉减少症和骨质疏松症等疾病的预防、诊断和管理中整合骨骼和肌肉测量的重要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a96/10670274/08b9edc83857/diagnostics-13-03466-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a96/10670274/35ddcfa00949/diagnostics-13-03466-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a96/10670274/0fab46ba3cf7/diagnostics-13-03466-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a96/10670274/741ff5569608/diagnostics-13-03466-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a96/10670274/90d4ac99b228/diagnostics-13-03466-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a96/10670274/fda86088aee8/diagnostics-13-03466-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a96/10670274/08b9edc83857/diagnostics-13-03466-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a96/10670274/35ddcfa00949/diagnostics-13-03466-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a96/10670274/0fab46ba3cf7/diagnostics-13-03466-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a96/10670274/741ff5569608/diagnostics-13-03466-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a96/10670274/90d4ac99b228/diagnostics-13-03466-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a96/10670274/fda86088aee8/diagnostics-13-03466-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a96/10670274/08b9edc83857/diagnostics-13-03466-g006.jpg

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