Jiang Jing, Haacke E Mark, Dong Ming
Radiology Department, Wayne State University, 440 E. Ferry Street, Detroit, MI 48202, USA.
J Magn Reson Imaging. 2007 Jun;25(6):1226-34. doi: 10.1002/jmri.20918.
To determine the appropriate image acquisition parameters for an accurate measurement of vessel cross-sectional area from MR angiography (MRA) images.
A series of images with different vessel cross-sectional areas, resolutions, and signal-to-noise ratios (SNRs) were simulated and validated experimentally. Dynamic programming (DP) was employed to determine the accuracy and precision of the vessel cross-sectional area as a function of vessel size, sampling matrix, acquisition time, and postprocessing parameters such as zooming and bias correction.
We show that there is an optimal value of lambda (the ratio of vessel diameter to resolution) for a given intrinsic SNR that yields the most accurate and precise area measurement. Specifically, when the SNR is > or =10:1, this value of lambda is 8 and yields a cross-sectional area error of <5% with a zoom factor of > or =2.
The predicted ideal result of lambda = 8 is within reach with current technology to image vessels such as the carotid artery or aorta. It is possible to determine the ideal resolution that minimizes errors in the measurement of the vessel cross-sectional area for a given SNR, processing algorithm, and vessel of interest.
确定从磁共振血管造影（MRA）图像准确测量血管横截面积的合适图像采集参数。
模拟并通过实验验证了一系列具有不同血管横截面积、分辨率和信噪比（SNR）的图像。采用动态规划（DP）来确定作为血管大小、采样矩阵、采集时间以及诸如缩放和偏差校正等后处理参数函数的血管横截面积的准确性和精确性。
我们表明，对于给定的固有SNR，存在一个λ（血管直径与分辨率的比值）的最佳值，可实现最准确和精确的面积测量。具体而言，当SNR≥10:1时，该λ值为8，缩放因子≥2时横截面积误差<5%。
利用当前技术对诸如颈动脉或主动脉等血管进行成像，预测的λ = 8的理想结果是可以实现的。对于给定的SNR、处理算法和感兴趣的血管，有可能确定使血管横截面积测量误差最小化的理想分辨率。
