Cheng Cynthia, Lee Chadd W, Daskalakis Constantine
Department of Family and Community Medicine, Thomas Jefferson University;
Sidney Kimmel Medical College, Thomas Jefferson University.
J Vis Exp. 2015 Oct 27(105):e53088. doi: 10.3791/53088.
Capillaroscopy is a non-invasive, efficient, relatively inexpensive and easy to learn methodology for directly visualizing the microcirculation. The capillaroscopy technique can provide insight into a patient's microvascular health, leading to a variety of potentially valuable dermatologic, ophthalmologic, rheumatologic and cardiovascular clinical applications. In addition, tumor growth may be dependent on angiogenesis, which can be quantitated by measuring microvessel density within the tumor. However, there is currently little to no standardization of techniques, and only one publication to date reports the reliability of a currently available, complex computer based algorithms for quantitating capillaroscopy data.(1) This paper describes a new, simpler, reliable, standardized capillary counting algorithm for quantitating nailfold capillaroscopy data. A simple, reproducible computerized capillaroscopy algorithm such as this would facilitate more widespread use of the technique among researchers and clinicians. Many researchers currently analyze capillaroscopy images by hand, promoting user fatigue and subjectivity of the results. This paper describes a novel, easy-to-use automated image processing algorithm in addition to a reproducible, semi-automated counting algorithm. This algorithm enables analysis of images in minutes while reducing subjectivity; only a minimal amount of training time (in our experience, less than 1 hr) is needed to learn the technique.
毛细血管显微镜检查是一种用于直接观察微循环的非侵入性、高效、相对廉价且易于掌握的方法。毛细血管显微镜检查技术能够深入了解患者的微血管健康状况,从而在皮肤科、眼科、风湿病学和心血管病学等领域产生多种具有潜在价值的临床应用。此外,肿瘤生长可能依赖于血管生成,而血管生成可通过测量肿瘤内微血管密度来定量。然而,目前该技术几乎没有标准化,迄今为止仅有一篇出版物报道了一种现有复杂计算机算法用于定量毛细血管显微镜检查数据的可靠性。(1) 本文描述了一种用于定量甲襞毛细血管显微镜检查数据的新的、更简单、可靠且标准化的毛细血管计数算法。这样一种简单、可重复的计算机化毛细血管显微镜检查算法将有助于该技术在研究人员和临床医生中更广泛地应用。目前许多研究人员通过手工分析毛细血管显微镜检查图像,这会导致使用者疲劳且结果具有主观性。除了一种可重复的半自动计数算法外,本文还描述了一种新颖、易于使用的自动图像处理算法。该算法能够在数分钟内分析图像,同时减少主观性;学习该技术仅需极少量的培训时间(根据我们的经验,少于1小时)。