• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

在韩国人群中,对接受肺癌筛查的个体使用低剂量胸部CT进行自动化机会性骨质疏松症筛查。

Automated Opportunistic Osteoporosis Screening Using Low-Dose Chest CT among Individuals Undergoing Lung Cancer Screening in a Korean Population.

作者信息

Kang Woo Young, Yang Zepa, Park Heejun, Lee Jemyoung, Hong Suk-Joo, Shim Euddeum, Woo Ok Hee

机构信息

Department of Radiology, Korea University Guro Hospital, Seoul 08308, Republic of Korea.

Department of Applied Bioengineering, Seoul National University, Seoul 08826, Republic of Korea.

出版信息

Diagnostics (Basel). 2024 Aug 16;14(16):1789. doi: 10.3390/diagnostics14161789.

DOI:10.3390/diagnostics14161789
PMID:39202277
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11354205/
Abstract

Opportunistic osteoporosis screening using deep learning (DL) analysis of low-dose chest CT (LDCT) scans is a potentially promising approach for the early diagnosis of this condition. We explored bone mineral density (BMD) profiles across all adult ages and prevalence of osteoporosis using LDCT with DL in a Korean population. This retrospective study included 1915 participants from two hospitals who underwent LDCT during general health checkups between 2018 and 2021. Trabecular volumetric BMD of L1-2 was automatically calculated using DL and categorized according to the American College of Radiology quantitative computed tomography diagnostic criteria. BMD decreased with age in both men and women. Women had a higher peak BMD in their twenties, but lower BMD than men after 50. Among adults aged 50 and older, the prevalence of osteoporosis and osteopenia was 26.3% and 42.0%, respectively. Osteoporosis prevalence was 18.0% in men and 34.9% in women, increasing with age. Compared to previous data obtained using dual-energy X-ray absorptiometry, the prevalence of osteoporosis, particularly in men, was more than double. The automated opportunistic BMD measurements using LDCT can effectively predict osteoporosis for opportunistic screening and identify high-risk patients. Patients undergoing lung cancer screening may especially profit from this procedure requiring no additional imaging or radiation exposure.

摘要

利用低剂量胸部CT(LDCT)扫描的深度学习(DL)分析进行机会性骨质疏松筛查,是早期诊断这种疾病的一种潜在的有前景的方法。我们在韩国人群中使用LDCT结合DL探索了所有成年人年龄组的骨密度(BMD)情况和骨质疏松患病率。这项回顾性研究纳入了来自两家医院的1915名参与者,他们在2018年至2021年的一般健康检查期间接受了LDCT检查。使用DL自动计算L1-2的小梁体积骨密度,并根据美国放射学会定量计算机断层扫描诊断标准进行分类。男性和女性的骨密度均随年龄下降。女性在二十多岁时骨密度峰值较高,但50岁后低于男性。在50岁及以上的成年人中,骨质疏松症和骨质减少的患病率分别为26.3%和42.0%。男性骨质疏松症患病率为18.0%,女性为34.9%,且随年龄增加。与之前使用双能X线吸收法获得的数据相比,骨质疏松症的患病率,尤其是男性的患病率增加了一倍多。使用LDCT进行自动机会性骨密度测量可以有效地预测机会性筛查中的骨质疏松症,并识别高危患者。接受肺癌筛查的患者可能尤其受益于这种无需额外成像或辐射暴露的检查程序。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c24f/11354205/5d143f325f1e/diagnostics-14-01789-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c24f/11354205/571eb424ad06/diagnostics-14-01789-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c24f/11354205/b436bf486be4/diagnostics-14-01789-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c24f/11354205/fec367a2c9ed/diagnostics-14-01789-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c24f/11354205/5d143f325f1e/diagnostics-14-01789-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c24f/11354205/571eb424ad06/diagnostics-14-01789-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c24f/11354205/b436bf486be4/diagnostics-14-01789-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c24f/11354205/fec367a2c9ed/diagnostics-14-01789-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c24f/11354205/5d143f325f1e/diagnostics-14-01789-g004.jpg

相似文献

1
Automated Opportunistic Osteoporosis Screening Using Low-Dose Chest CT among Individuals Undergoing Lung Cancer Screening in a Korean Population.在韩国人群中,对接受肺癌筛查的个体使用低剂量胸部CT进行自动化机会性骨质疏松症筛查。
Diagnostics (Basel). 2024 Aug 16;14(16):1789. doi: 10.3390/diagnostics14161789.
2
Opportunistic Screening Using Low-Dose CT and the Prevalence of Osteoporosis in China: A Nationwide, Multicenter Study.利用低剂量 CT 进行机会性筛查与中国骨质疏松症的患病率:一项全国性、多中心研究。
J Bone Miner Res. 2021 Mar;36(3):427-435. doi: 10.1002/jbmr.4187. Epub 2020 Nov 4.
3
Opportunistic use of chest low-dose computed tomography (LDCT) imaging for low bone mineral density and osteoporosis screening: cutoff thresholds for the attenuation values of the lower thoracic and upper lumbar vertebrae.胸部低剂量计算机断层扫描(LDCT)成像在低骨密度和骨质疏松症筛查中的机会性应用:下胸椎和上腰椎衰减值的截断阈值
Quant Imaging Med Surg. 2024 Jul 1;14(7):4792-4803. doi: 10.21037/qims-24-59. Epub 2024 Jun 24.
4
Automatic opportunistic osteoporosis screening using low-dose chest computed tomography scans obtained for lung cancer screening.利用低剂量胸部 CT 扫描进行肺癌筛查,实现骨质疏松症自动机会性筛查。
Eur Radiol. 2020 Jul;30(7):4107-4116. doi: 10.1007/s00330-020-06679-y. Epub 2020 Feb 19.
5
Vertebral bone attenuation on low-dose chest CT: quantitative volumetric analysis for bone fragility assessment.低剂量胸部CT上的椎体骨质衰减:用于评估骨脆性的定量容积分析
Osteoporos Int. 2017 Jan;28(1):329-338. doi: 10.1007/s00198-016-3724-2. Epub 2016 Aug 1.
6
Utilization of DXA Bone Mineral Densitometry in Ontario: An Evidence-Based Analysis.安大略省双能X线吸收法骨密度测定的应用:基于证据的分析。
Ont Health Technol Assess Ser. 2006;6(20):1-180. Epub 2006 Nov 1.
7
Evaluation of deep learning-based quantitative computed tomography for opportunistic osteoporosis screening.基于深度学习的定量计算机断层扫描在机会性骨质疏松症筛查中的评价。
Sci Rep. 2024 Jan 5;14(1):363. doi: 10.1038/s41598-023-45824-7.
8
Prevalence of osteoporosis and osteopenia diagnosed using quantitative CT in 296 consecutive lumbar fusion patients.296 例连续腰椎融合患者定量 CT 诊断骨质疏松症和骨量减少症的患病率。
Neurosurg Focus. 2020 Aug;49(2):E5. doi: 10.3171/2020.5.FOCUS20241.
9
Automatic opportunistic osteoporosis screening in routine CT: improved prediction of patients with prevalent vertebral fractures compared to DXA.常规 CT 自动机会性骨质疏松症筛查:与 DXA 相比,提高了对现患椎体骨折患者的预测能力。
Eur Radiol. 2021 Aug;31(8):6069-6077. doi: 10.1007/s00330-020-07655-2. Epub 2021 Jan 28.
10
Artificial intelligence assisted automatic screening of opportunistic osteoporosis in computed tomography images from different scanners.人工智能辅助自动筛查不同扫描仪的计算机断层扫描图像中的机会性骨质疏松症。
Eur Radiol. 2025 Apr;35(4):2287-2295. doi: 10.1007/s00330-024-11046-2. Epub 2024 Sep 4.

本文引用的文献

1
Fully automated deep learning system for osteoporosis screening using chest computed tomography images.使用胸部计算机断层扫描图像的全自动深度学习骨质疏松筛查系统。
Quant Imaging Med Surg. 2024 Apr 3;14(4):2816-2827. doi: 10.21037/qims-23-1617. Epub 2024 Mar 21.
2
AntiHalluciNet: A Potential Auditing Tool of the Behavior of Deep Learning Denoising Models in Low-Dose Computed Tomography.AntiHalluciNet:一种低剂量计算机断层扫描中深度学习去噪模型行为的潜在审计工具。
Diagnostics (Basel). 2023 Dec 31;14(1):96. doi: 10.3390/diagnostics14010096.
3
Evaluation of deep learning-based quantitative computed tomography for opportunistic osteoporosis screening.
基于深度学习的定量计算机断层扫描在机会性骨质疏松症筛查中的评价。
Sci Rep. 2024 Jan 5;14(1):363. doi: 10.1038/s41598-023-45824-7.
4
Automated vertebral bone mineral density measurement with phantomless internal calibration in chest LDCT scans using deep learning.基于深度学习的胸部 LDCT 扫描中无模体自动椎骨骨密度内校准测量。
Br J Radiol. 2023 Dec;96(1152):20230047. doi: 10.1259/bjr.20230047. Epub 2023 Oct 24.
5
Revolutionizing healthcare: the role of artificial intelligence in clinical practice.人工智能在临床实践中的应用:医疗保健的革命。
BMC Med Educ. 2023 Sep 22;23(1):689. doi: 10.1186/s12909-023-04698-z.
6
Development and validation of a fully automated system using deep learning for opportunistic osteoporosis screening using low-dose computed tomography scans.利用深度学习开发并验证一种基于低剂量计算机断层扫描进行机会性骨质疏松症筛查的全自动系统。
Quant Imaging Med Surg. 2023 Aug 1;13(8):5294-5305. doi: 10.21037/qims-22-1438. Epub 2023 Jul 20.
7
Opportunistic Screening Techniques for Analysis of CT Scans.机会性筛查技术在 CT 扫描分析中的应用。
Curr Osteoporos Rep. 2023 Feb;21(1):65-76. doi: 10.1007/s11914-022-00764-5. Epub 2022 Nov 26.
8
Value-added Opportunistic CT Screening: State of the Art.增值性机会性 CT 筛查:现状。
Radiology. 2022 May;303(2):241-254. doi: 10.1148/radiol.211561. Epub 2022 Mar 15.
9
Deep Learning Algorithm for Simultaneous Noise Reduction and Edge Sharpening in Low-Dose CT Images: A Pilot Study Using Lumbar Spine CT.深度学习算法在低剂量 CT 图像降噪和边缘锐化中的应用:一项基于腰椎 CT 的初步研究
Korean J Radiol. 2021 Nov;22(11):1850-1857. doi: 10.3348/kjr.2021.0140. Epub 2021 Aug 19.
10
Advancements in Osteoporosis Imaging, Screening, and Study of Disease Etiology.骨质疏松症影像学、筛查和疾病病因研究的进展。
Curr Osteoporos Rep. 2021 Oct;19(5):532-541. doi: 10.1007/s11914-021-00699-3. Epub 2021 Jul 22.