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利用人工智能进行胸部 CT 机会性骨质疏松症筛查。

Opportunistic osteoporosis screening using chest CT with artificial intelligence.

机构信息

Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1277, Jiefang Avenue, Wuhan, Hubei Province, China.

Department of Geriatrics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1277, Jiefang Avenue, Wuhan, Hubei Province, China.

出版信息

Osteoporos Int. 2022 Dec;33(12):2547-2561. doi: 10.1007/s00198-022-06491-y. Epub 2022 Aug 6.

Abstract

UNLABELLED

Osteoporosis has a high incidence and a low detection rate. If it is not detected in time, it will cause osteoporotic fracture and other serious consequences. This study showed that the attenuation values of vertebrae on chest CT could be used for opportunistic screening of osteoporosis. This will be beneficial to improve the detection rate of osteoporosis and reduce the incidence of adverse events caused by osteoporosis.

INTRODUCTION

To explore the value of the attenuation values of all thoracic vertebrae and the first lumbar vertebra measured by artificial intelligence on non-enhanced chest CT to do osteoporosis screening.

METHODS

On base of images of chest CT, using artificial intelligence (AI) to measure the attenuation values (HU) of all thoracic and the first vertebrae of patients who underwent CT examination for lung cancer screening and dual-energy X-ray absorptiometry (DXA) examination during the same period. The patients were divided into three groups: normal group, osteopenia group, and osteoporosis group according to the results of DXA. Clinical baseline data and attenuation values were compared among the three groups. The correlation between attenuation values and BMD values was analyzed, and the predictive ability and diagnostic efficacy of attenuation values of thoracic and first lumbar vertebrae on osteopenia or osteoporosis risk were further evaluated.

RESULTS

CT values of each thoracic vertebrae and the first lumbar vertebrae decreased with age, especially in menopausal women and presented high predictive ability and diagnostic efficacy for osteopenia or osteoporosis. After clinical data correction, with every 10 HU increase of CT values, the risk of osteopenia or osteoporosis decreased by 32 ~ 44% and 61 ~ 80%, respectively. And the combined diagnostic efficacy of all thoracic vertebrae was higher than that of a single vertebra. The AUC of recognizing osteopenia or osteoporosis from normal group was 0.831and 0.972, respectively.

CONCLUSIONS

The routine chest CT with AI is of great value in opportunistic screening for osteopenia or osteoporosis, which can quickly screen the population at high risk of osteoporosis without increasing radiation dose, thus reducing the incidence of osteoporotic fracture.

摘要

目的

探讨人工智能测量非增强胸部 CT 上所有胸椎和第 1 腰椎的衰减值(HU)在骨质疏松症筛查中的价值。

方法

基于胸部 CT 图像,使用人工智能(AI)测量同期行肺癌筛查 CT 检查和双能 X 线吸收法(DXA)检查患者的所有胸椎和第 1 腰椎的衰减值(HU)。根据 DXA 结果将患者分为正常组、骨量减少组和骨质疏松组。比较三组间临床基线资料和衰减值。分析衰减值与 BMD 值的相关性,并进一步评价胸椎和第 1 腰椎衰减值对骨量减少或骨质疏松风险的预测能力和诊断效能。

结果

各胸椎和第 1 腰椎 CT 值随年龄增长而降低,在绝经后女性中尤为明显,对骨量减少或骨质疏松症具有较高的预测能力和诊断效能。校正临床数据后,CT 值每增加 10 HU,骨量减少或骨质疏松症的风险分别降低 32%44%和 61%80%。且所有胸椎联合诊断效能均高于单一椎体。识别骨量减少或骨质疏松症的正常组 AUC 分别为 0.831 和 0.972。

结论

人工智能常规胸部 CT 对骨量减少或骨质疏松症的机会性筛查具有重要价值,它可以快速筛查骨质疏松症高危人群,而不会增加辐射剂量,从而降低骨质疏松性骨折的发生率。

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