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半自动评估皮肤毛细血管密度:原理验证。

Semi-automatic assessment of skin capillary density: proof of principle and validation.

机构信息

Department of Psychiatry and Neuropsychology and School for Mental Health and Neuroscience (MeHNs), Maastricht University Medical Centre (MUMC), Maastricht, The Netherlands.

出版信息

Microvasc Res. 2013 Nov;90:192-8. doi: 10.1016/j.mvr.2013.08.003. Epub 2013 Aug 26.

Abstract

BACKGROUND

Skin capillary density and recruitment have been proven to be relevant measures of microvascular function. Unfortunately, the assessment of skin capillary density from movie files is very time-consuming, since this is done manually. This impedes the use of this technique in large-scale studies. We aimed to develop a (semi-) automated assessment of skin capillary density.

METHODS

CapiAna (Capillary Analysis) is a newly developed semi-automatic image analysis application. The technique involves four steps: 1) movement correction, 2) selection of the frame range and positioning of the region of interest (ROI), 3) automatic detection of capillaries, and 4) manual correction of detected capillaries. To gain insight into the performance of the technique, skin capillary density was measured in twenty participants (ten women; mean age 56.2 [42-72] years). To investigate the agreement between CapiAna and the classic manual counting procedure, we used weighted Deming regression and Bland-Altman analyses. In addition, intra- and inter-observer coefficients of variation (CVs), and differences in analysis time were assessed.

RESULTS

We found a good agreement between CapiAna and the classic manual method, with a Pearson's correlation coefficient (r) of 0.95 (P<0.001) and a Deming regression coefficient of 1.01 (95%CI: 0.91; 1.10). In addition, we found no significant differences between the two methods, with an intercept of the Deming regression of 1.75 (-6.04; 9.54), while the Bland-Altman analysis showed a mean difference (bias) of 2.0 (-13.5; 18.4) capillaries/mm(2). The intra- and inter-observer CVs of CapiAna were 2.5% and 5.6% respectively, while for the classic manual counting procedure these were 3.2% and 7.2%, respectively. Finally, the analysis time for CapiAna ranged between 25 and 35min versus 80 and 95min for the manual counting procedure.

CONCLUSION

We have developed a semi-automatic image analysis application (CapiAna) for the assessment of skin capillary density, which agrees well with the classic manual counting procedure, is time-saving, and has a better reproducibility as compared to the classic manual counting procedure. As a result, the use of skin capillaroscopy is feasible in large-scale studies, which importantly extends the possibilities to perform microcirculation research in humans.

摘要

背景

皮肤毛细血管密度和募集已被证明是微血管功能的相关指标。不幸的是,从电影文件中评估皮肤毛细血管密度非常耗时,因为这是手动完成的。这阻碍了该技术在大规模研究中的应用。我们旨在开发一种(半自动)皮肤毛细血管密度评估方法。

方法

CapiAna(毛细血管分析)是一种新开发的半自动图像分析应用程序。该技术涉及四个步骤:1)运动校正,2)选择帧范围和定位感兴趣区域(ROI),3)自动检测毛细血管,以及 4)手动校正检测到的毛细血管。为了深入了解该技术的性能,我们在二十名参与者(十名女性;平均年龄 56.2[42-72]岁)中测量了皮肤毛细血管密度。为了研究 CapiAna 与经典手动计数方法之间的一致性,我们使用加权 Deming 回归和 Bland-Altman 分析。此外,还评估了内-间观察者变异系数(CV)和分析时间差异。

结果

我们发现 CapiAna 与经典手动方法之间具有良好的一致性,Pearson 相关系数(r)为 0.95(P<0.001),Deming 回归系数为 1.01(95%CI:0.91;1.10)。此外,两种方法之间没有显著差异,Deming 回归的截距为 1.75(-6.04;9.54),而 Bland-Altman 分析显示平均差异(偏差)为 2.0(-13.5;18.4)个毛细血管/mm(2)。CapiAna 的内-间观察者 CV 分别为 2.5%和 5.6%,而经典手动计数程序的 CV 分别为 3.2%和 7.2%。最后,CapiAna 的分析时间范围在 25 到 35 分钟之间,而经典手动计数程序的分析时间范围在 80 到 95 分钟之间。

结论

我们开发了一种半自动图像分析应用程序(CapiAna),用于评估皮肤毛细血管密度,该程序与经典手动计数程序一致,节省时间,并且与经典手动计数程序相比具有更好的可重复性。因此,皮肤毛细血管镜检查在大规模研究中是可行的,这重要地扩展了在人类中进行微循环研究的可能性。

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