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双层光谱探测器计算机断层扫描(SDCT)测定的肝脏多参数定量指标与冠状动脉斑块评分的相关性

Association of liver multi-parameter quantitative metrics determined by dual-layer spectral detector computed tomography (SDCT) with coronary plaque scores.

作者信息

Wang Min, Ma Yue, Lan Yu, Bai Ruobing, Yang Linlin, Hou Yang

机构信息

Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, China.

出版信息

Quant Imaging Med Surg. 2024 Oct 1;14(10):7392-7405. doi: 10.21037/qims-24-53. Epub 2024 Sep 21.

DOI:10.21037/qims-24-53
PMID:39429605
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11485365/
Abstract

BACKGROUND

Hepatic steatosis is closely related to the occurrence and development of coronary plaques. Spectral detector computed tomography (SDCT) can provide more precise multiparameter quantitative parameters for hepatic steatosis. Hence, the purpose of this cross-sectional study was to explore the effect of quantitative liver metrics measured using SDCT on the extent and severity of coronary plaques.

METHODS

In patients who underwent upper abdomen unenhanced SDCT and coronary computed tomography angiography, plaque extent and severity were assessed using segmental involvement score (SIS) and segmental stenosis score (SSS). Liver fat quantification was evaluated by polychromatic and virtual mono-energetic images at 40 and 70 kev, spectral attenuation curve slope, and effective atomic number (CT40 keV, CT70 kev, λHU, and Zeff, respectively). A logistic regression model evaluated the factors influencing high SIS and SSS.

RESULTS

Enrolled patients (n=644) were divided into groups: low SIS (<5) (n=451), high SIS (≥5) (n=193), low SSS (<5) (n=461), and high SSS (≥5) (n=183). Zeff was more closely correlated with SIS (standard partial regression coefficient =-0.422, P<0.001) and SSS (standard partial regression coefficient =-0.346, P<0.001). Zeff was divided into four groups using interquartile intervals. Compared with the patients in the lowest quartile, those in the second [odds ratio (OR) =2.116, 95% confidence interval (CI): 1.134-3.949, P=0.018], third (OR =2.832, 95% CI: 1.461-5.491, P=0.002), and fourth (OR =3.584, 95% CI: 1.857-6.918, P<0.001) quartiles showed higher risk for high SIS. And correspondingly, the second (OR =1.933, 95% CI: 1.040-3.592, P=0.037), third (OR =2.900, 95% CI: 1.499-5.609, P=0.002), and fourth (OR =3.368, 95% CI: 1.743-6.510, P<0.001) quartiles showed higher risk for high SSS, especially in those who were <60 years old, male and had visceral adipose tissue/subcutaneous adipose tissue <1.18.

CONCLUSIONS

The SDCT-Zeff was an independent factor associated with high SIS and SSS. The quantification of liver fat may be useful for evaluating the risk and prognosis of coronary atherosclerosis.

摘要

背景

肝脂肪变性与冠状动脉斑块的发生发展密切相关。光谱探测器计算机断层扫描(SDCT)可为肝脂肪变性提供更精确的多参数定量指标。因此,本横断面研究的目的是探讨使用SDCT测量的肝脏定量指标对冠状动脉斑块范围和严重程度的影响。

方法

对接受上腹部非增强SDCT和冠状动脉计算机断层血管造影的患者,使用节段累及评分(SIS)和节段狭窄评分(SSS)评估斑块范围和严重程度。通过40keV和70keV的多色和虚拟单能图像、光谱衰减曲线斜率和有效原子序数(分别为CT40keV、CT70keV、λHU和Zeff)评估肝脏脂肪定量。采用逻辑回归模型评估影响高SIS和SSS的因素。

结果

纳入患者(n=644)分为以下几组:低SIS(<5)(n=451)、高SIS(≥5)(n=193)、低SSS(<5)(n=461)和高SSS(≥5)(n=183)。Zeff与SIS(标准偏回归系数=-0.422,P<0.001)和SSS(标准偏回归系数=-0.346,P<0.001)的相关性更强。使用四分位数间距将Zeff分为四组。与最低四分位数的患者相比,第二四分位数[比值比(OR)=2.116,95%置信区间(CI):1.134-3.949,P=0.018]、第三四分位数(OR =2.832,95%CI:1.461-5.491,P=0.002)和第四四分位数(OR =3.584,95%CI:1.857-6.918,P<0.001)的患者发生高SIS的风险更高。相应地,第二四分位数(OR =1.933,95%CI:1.040-3.592,P=0.037)、第三四分位数(OR =2.900,95%CI:1.499-5.609,P=0.002)和第四四分位数(OR =3.368,95%CI:1.743-6.510,P<0.001)的患者发生高SSS的风险更高,尤其是年龄<60岁、男性且内脏脂肪组织/皮下脂肪组织<1.18的患者。

结论

SDCT-Zeff是与高SIS和SSS相关的独立因素。肝脏脂肪定量可能有助于评估冠状动脉粥样硬化的风险和预后。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9410/11485365/b7dc79818cab/qims-14-10-7392-f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9410/11485365/8221a9989fed/qims-14-10-7392-f1.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9410/11485365/fdc3cb1bcab2/qims-14-10-7392-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9410/11485365/b7dc79818cab/qims-14-10-7392-f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9410/11485365/8221a9989fed/qims-14-10-7392-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9410/11485365/abba307e4c22/qims-14-10-7392-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9410/11485365/645b01dbfb1b/qims-14-10-7392-f3.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9410/11485365/b7dc79818cab/qims-14-10-7392-f6.jpg

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