Brunozzi Denise, Shakur Sophia F, Ismail Rahim, Linninger Andreas, Hsu Chih-Yang, Charbel Fady T, Alaraj Ali
Department of Neurosurgery, University of Illinois at Chicago, Chicago, Illinois, USA.
Department of Bioengineering, University of Illinois at Chicago, Chicago, Illinois, USA.
World Neurosurg. 2018 Feb;110:e315-e320. doi: 10.1016/j.wneu.2017.10.178. Epub 2017 Nov 10.
Digital subtraction angiography (DSA) provides an excellent anatomic characterization of cerebral vasculature, but hemodynamic assessment is often qualitative and subjective. Various clinical algorithms have been produced to semiquantify flow from the data obtained from DSA, but few have tested them against reliable flow values.
An arched flow model was created and injected with contrast material. Seventeen injections were acquired in anterior-posterior and lateral DSA projections, and 4 injections were acquired in oblique projection. Image intensity change over the angiogram cycle of each DSA run was analyzed through a custom MATLAB code. Time-density plots obtained were divided into 3 components (time-density times, TDTs): TDT (time needed for contrast material to change image intensity from 10% to 100%), TDT (time needed for contrast material to change image intensity from 100% to 10%), and TDT (time needed for contrast material to change from 25% image intensity to 25%). Time-density index (TDI) was defined as model cross-sectional area to TDT ratio, and it was measured against different flow rates.
TDI, TDI, and TDI all correlated significantly with flow (P < 0.001). TDI, TDI, and TDI showed, respectively, a correlation coefficient of 0.91, 0.91, and 0.97 in the anterior-posterior DSA projections (P < 0.001). In the lateral DSA projection, TDI showed a weaker correlation (r = 0.57; P = 0.03). Also in the oblique DSA projection, TDIs correlated significantly with flow.
TDI on DSA correlates significantly with flow. Although in vitro studies might overlook conditions that occur in patients, this method appears to correlate with the flow and could offer a semiquantitative method to evaluate the cerebral blood flow.
数字减影血管造影（DSA）能对脑血管系统进行出色的解剖学特征描述，但血流动力学评估往往是定性且主观的。已经产生了各种临床算法，用于从DSA获得的数据中对血流进行半定量分析，但很少有研究将它们与可靠的血流值进行对比测试。
构建一个弓形血流模型并注入造影剂。在前后位和侧位DSA投影下进行了17次注射，在斜位投影下进行了4次注射。通过自定义的MATLAB代码分析每次DSA运行的血管造影周期内的图像强度变化。获得的时间-密度图被分为3个成分（时间-密度时间，TDTs）：TDT（造影剂将图像强度从10%改变到100%所需的时间），TDT（造影剂将图像强度从100%改变到10%所需的时间），以及TDT（造影剂从25%图像强度改变到25%所需的时间）。时间-密度指数（TDI）被定义为模型横截面积与TDT的比值，并针对不同的流速进行测量。
TDI、TDI和TDI均与血流显著相关（P < 0.001）。在前后位DSA投影中，TDI、TDI和TDI的相关系数分别为0.91、0.91和0.97（P < 0.001）。在侧位DSA投影中，TDI的相关性较弱（r = 0.57；P = 0.03）。同样在斜位DSA投影中，TDIs与血流显著相关。
DSA上的TDI与血流显著相关。尽管体外研究可能会忽略患者体内发生的情况，但这种方法似乎与血流相关，并且可以提供一种半定量方法来评估脑血流量。
