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Automatic full field analysis of perfusion images gained by scanning laser Doppler flowmetry

机译:通过扫描激光多普勒血流仪获得的灌注图像的自动全场分析

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摘要

BACKGROUND—Scanning laser Doppler flowmetry (SLDF) enables the measurement of the laser Doppler frequency shift in retinal tissue. This process allows the quantification of retinal and optic nerve head perfusion in an area of 2.7 mm × 0.7 mm within 2 seconds and with a spatial resolution of 10 µm × 10 µm. Owing to the local heterogeneity of the retinal microcirculation itself and to heart associated pulsation the capillary retinal blood flow depends on location and time. Because of technical limitations measurements of flow are only valid in retinal points with adequate brightness and focus, and away from big vessels. To include the heart beat associated pulsation and the spatial heterogeneity of retinal blood flow into the evaluation of blood flow an algorithm was developed examining automatically the whole SLDF perfusion image.
AIM—To report intraobserver reliability and interobserver reliability of a new method for analysing automatically full field perfusion images.
METHOD—The base of blood flow calculation by the automatic full field perfusion image analyser (AFFPIA) was 16 384 intensity time curves of all pixels of the whole perfusion image gained by the SLDF. AFFPIA calculates the Doppler frequency shift and the haemodynamic variables flow, volume, and velocity of each pixel. The resulting perfusion image was processed with respect to (1) underexposed and overexposed pixels, (2) saccades, and (3) the retinal vessel tree. The rim area and the saccades were marked interactively by the operator. The capillaries and vessels of the retinal vessel tree were identified automatically by pattern analysis. Retinal vessels with a diameter greater than 30 µm, underexposed or overexposed areas, and saccades were excluded automatically. Based on the whole perfusion image total mean flow, total mean volume, total mean velocity, standard deviation, cumulative distribution curve of flow, and the capillary pulsation index were calculated automatically. Heart beat associated pulsation of capillary blood flow was estimated by plotting the mean capillary flow of each horizontal line against time. Intraobserver reliability was estimated by measuring 10 eyes of 10 subjects on five different days by one observer. Interobserver reliability of AFFPIA was evaluated by analysing 10 perfusion maps by five different operators. To find a baseline of retinal blood flow, perfusion maps of 67 eyes of normal subjects with a mean age of 40.4 (SD 15) years were evaluated by AFFPIA.
RESULTS—The coefficient of reliability of the intraobserver reproducibility of flow was 0.74. The coefficient of reliability of the interobserver reproducibility was 0.95. The juxtapapillary retinal capillary flow was temporally 484 (SD 125), nasally 450 (117); the rim area capillary flow was 443 (110). The mean capillary pulsation index of retinal flow was 0.56 (0.14).
CONCLUSION—Retinal blood flow evaluation by the AFFPIA increases significantly the interobserver reliability compared with conventional evaluation of 100 µm × 100 µm areas in SLDF images with the original Heidelberg retina flowmeter software. The intraobserver reliability of AFFPIA was in the same range as conventional evaluation.

 Keywords: retinal blood flow; optic nerve head blood flow; scanning laser Doppler flowmetry
机译:背景技术扫描激光多普勒血流仪(SLDF)能够测量视网膜组织中的激光多普勒频移。这个过程可以在2秒内以2.7 mm×0.7 mm的面积对视网膜和视神经头的灌注进行定量,其空间分辨率为10 µm×10 µm。由于视网膜微循环本身的局部异质性以及与心脏相关的搏动,毛细管视网膜血流取决于位置和时间。由于技术限制,流量的测量仅在具有足够亮度和焦点的视网膜点有效,并且远离大血管。为了将心跳相关的搏动和视网膜血流的空间异质性纳入血流评估中,开发了一种算法来自动检查整个SLDF灌注图像。目的:报告观察者内部和观察者之间的可靠性,这是一种自动分析全视野灌注图像的新方法。方法-自动全视野灌注图像分析仪(AFFPIA)计算血流的基础是SLDF获得的整个灌注图像的所有像素的16384条强度时间曲线。 AFFPIA计算多普勒频移和血流动力学变量的每个像素的流量,体积和速度。针对(1)曝光不足和曝光过度的像素,(2)扫视镜和(3)视网膜血管树对所得的灌注图像进行处理。边缘区域和扫视由操作员交互式标记。通过模式分析自动识别视网膜血管树的毛细血管。直径大于30 µm的视网膜血管,曝光不足或曝光过度的区域以及扫视镜将被自动排除。根据整个灌注图像,自动计算总平均流量,总平均体积,总平均速度,标准偏差,流量累积分布曲线和毛细管脉动指数。通过绘制每条水平线的平均毛细血管流量与时间的关系来估计与心搏相关的毛细血管血流的脉动。一位观察员在五个不同日期测量10个对象的10眼来评估观察者内部的可靠性。 AFFPIA的观察者间可靠性是通过五位不同的运营商分析10次灌注图来评估的。为了找到视网膜血流的基线,通过AFFPIA对平均年龄为40.4(SD 15)岁的正常受试者的67眼灌注图进行了评估。结果—观察者内流动的可靠性系数为0.74。观察者间再现性的可靠性系数为0.95。颞乳头状视网膜毛细血管流量为484(SD 125),鼻为450(117);边缘区域毛细流量为443(110)。视网膜血流的平均毛细血管搏动指数为0.56(0.14)。结论-与使用原始海德堡视网膜流量计软件对SLDF图像中100 µm×100 µm区域进行常规评估相比,AFFPIA进行的视网膜血流评估显着提高了观察者之间的可靠性。 AFFPIA的观察者内部可靠性与常规评估处于同一范围内。关键词:视网膜血流视神经头血流;扫描激光多普勒血流仪

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