应用团注追踪参数和心率预测冠状动脉 CT 血管造影升主动脉衰减。

Prediction of the attenuation of the ascending aorta using bolus-tracking parameters and heart rate in coronary computed tomography angiography.

机构信息

Department of Radiology, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan.

出版信息

Eur J Radiol. 2012 Nov;81(11):3250-3. doi: 10.1016/j.ejrad.2012.02.001. Epub 2012 Feb 26.

DOI:10.1016/j.ejrad.2012.02.001

PMID:22370097

Abstract

OBJECTIVE

The purpose of this study was to evaluate the correlation between bolus-tracking parameters and heart rate (HR) with attenuation of the ascending aorta and create a linear regression model for predicting coronary attenuation in coronary computed tomography angiography (CCTA).

METHODS

A total of 50 patients (31 men, 19 women; mean age, 67.2±10.8 y) underwent CCTA using a 320-detector CT scanner. A bolus-tracking scan was performed to optimize the scan timing. The average HR under normal breathing for 10s was recorded just before the bolus-tracking scan started. Attenuation values of the pulmonary artery at 7s (PA7) and 10s (PA10) after the beginning of the injection were recorded during the bolus-tracking scan and the ascending aortic attenuation (CEAAo) was measured during the diagnostic scan.

RESULTS

A positive correlation was observed between PA7 and CEAAo (r=0.41, P=0.003) and PA10 and CEAAo (r=0.66, P<0.0001), and weak negative correlation was observed between HR and CEAAo (r=-0.46, P=0.15). A multivariable linear regression model for predicting CEAAo was evaluated, and the residual error between the predicted and the measured CEAAo was within approximately ±100 HU.

CONCLUSIONS

Coronary attenuation could be predicted using HR and pulmonary artery attenuation during the bolus-tracking method.

摘要

目的

本研究旨在评估升主动脉衰减与团注追踪参数和心率（HR）之间的相关性，并建立用于预测冠状动脉 CT 血管造影（CCTA）中冠状动脉衰减的线性回归模型。

方法

共 50 例患者（男 31 例，女 19 例；平均年龄 67.2±10.8 岁）接受了使用 320 探测器 CT 扫描仪进行的 CCTA。进行了团注追踪扫描以优化扫描时间。在开始团注追踪扫描之前，记录正常呼吸 10 秒时的平均 HR。在团注追踪扫描期间记录注射开始后 7s（PA7）和 10s（PA10）时肺动脉的衰减值，并在诊断扫描期间测量升主动脉衰减（CEAAo）。

结果

PA7 与 CEAAo 之间存在正相关（r=0.41，P=0.003），PA10 与 CEAAo 之间存在强正相关（r=0.66，P<0.0001），HR 与 CEAAo 之间存在弱负相关（r=-0.46，P=0.15）。评估了用于预测 CEAAo 的多变量线性回归模型，预测的和实测的 CEAAo 之间的残差约为±100 HU。