Automated assessment of renal cortical surface roughness from computerized tomography images and its association with age.

Academic Radiology(2014)

引用 11|浏览7
暂无评分
摘要
Nephrosclerosis occurs with aging and is characterized by increased kidney subcapsular surface irregularities at autopsy. Assessments of cortical roughness in vivo could provide an important measure of nephrosclerosis. The purpose of this study was to develop and validate an image-processing algorithm for quantifying renal cortical surface roughness in vivo and determine its association with age.Renal cortical surface roughness was measured on contrast-enhanced abdominal computed tomography (CT) images of potential living kidney donors. A roughness index was calculated based on geometric curvature of each kidney from three-dimensional images and compared to visual observation scores. Cortical roughness was compared between the oldest and youngest donors, and its interaction with cortical volume and age assessed.The developed quantitative roughness index identified significant differences in kidneys with visual surface roughness scores of 0 (minimal), 1 (mild), and 2 (moderate; P < .001) in a random sample of 200 potential kidney donors. Cortical roughness was significantly higher in the 94 oldest (64-75 years) versus 91 youngest (18-25 years) potential kidney donors (P < .001). Lower cortical volume was associated with older age but not with roughness (r = -0.03, P = .75). The association of oldest age group with roughness (odds ratio [OR] = 1.8 per standard deviation [SD] of roughness index) remained significant after adjustment for total cortex volume (OR = 2.0 per SD of roughness index).A new algorithm to measure renal cortical surface roughness from CT scans detected rougher surface in older compared to younger kidneys, independent of cortical volume loss. This novel index may allow quantitative evaluation of nephrosclerosis in vivo using contrast-enhanced CT.
更多
查看译文
关键词
Nephrosclerosis,surface roughness,computerized tomography,kidney aging
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要