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从骨质疏松评估的临床 CT 图像中提取 3D 股骨颈小梁骨结构:一种新框架。

Extraction of 3D Femur Neck Trabecular Bone Architecture from Clinical CT Images in Osteoporotic Evaluation: a Novel Framework.

机构信息

Department of Biomedical Engineering, SRM University, Kattankalathur, Tamil Nadu, Chennai, 603203, India,

出版信息

J Med Syst. 2015 Aug;39(8):81. doi: 10.1007/s10916-015-0266-7. Epub 2015 Jul 3.

Abstract

The early detection of osteoporosis risk enhances the lifespan and quality of life of an individual. A reasonable in-vivo assessment of trabecular bone strength at the proximal femur helps to evaluate the fracture risk and henceforth, to understand the associated structural dynamics on occurrence of osteoporosis. The main aim of our study was to develop a framework to automatically determine the trabecular bone strength from clinical femur CT images and thereby to estimate its correlation with BMD. All the 50 studied south Indian female subjects aged 30 to 80 years underwent CT and DXA measurements at right femur region. Initially, the original CT slices were intensified and active contour model was utilised for the extraction of the neck region. After processing through a novel process called trabecular enrichment approach (TEA), the three dimensional (3D) trabecular features were extracted. The extracted 3D trabecular features, such as volume fraction (VF), solidity of delta points (SDP) and boundness, demonstrated a significant correlation with femoral neck bone mineral density (r = 0.551, r = 0.432, r = 0.552 respectively) at p < 0.001. The higher area under the curve values of the extracted features (VF: 85.3 %; 95CI: 68.2-100 %, SDP: 82.1 %; 95CI: 65.1-98.9 % and boundness: 90.4 %; 95CI: 78.7-100 %) were observed. The findings suggest that the proposed framework with TEA method would be useful for spotting women vulnerable to osteoporotic risk.

摘要

骨质疏松风险的早期检测可以提高个体的寿命和生活质量。对股骨近端小梁骨强度进行合理的体内评估有助于评估骨折风险,从而了解骨质疏松发生时的相关结构动态。我们研究的主要目的是开发一种从临床股骨 CT 图像中自动确定小梁骨强度的框架,并评估其与 BMD 的相关性。所有 50 名研究对象均为年龄在 30 岁至 80 岁的南印度女性,均在右股骨区域接受 CT 和 DXA 测量。首先,对原始 CT 切片进行增强处理,并利用主动轮廓模型提取颈部区域。经过一种称为小梁富集方法(TEA)的新处理后,提取了三维(3D)小梁特征。提取的 3D 小梁特征,如体积分数(VF)、三角点的坚固性(SDP)和束缚性,与股骨颈骨密度(r = 0.551、r = 0.432、r = 0.552)呈显著相关,p < 0.001。提取特征的曲线下面积(VF:85.3%;95CI:68.2-100%,SDP:82.1%;95CI:65.1-98.9%和束缚性:90.4%;95CI:78.7-100%)更高。研究结果表明,该方法结合 TEA 方法的框架有助于发现处于骨质疏松风险的女性。

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