A Reproducible Computerized Method for Quantitation of Capillary Density using Nailfold Capillaroscopy

Summary

Capillaroscopy is a non-invasive, efficient, relatively inexpensive and easy-to-learn methodology for directly visualizing capillaries in the microcirculation. However, only one publication to date describes the reliability of a complex software program available for quantitating capillaroscopy data. Here, we present a simple, reliable protocol for quantitating capillaries using a standardized algorithm.

Abstract

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.

Introduction

Microvascular imaging is a rapidly growing field with many potential clinical applications.² For example, oncologists are using microvessel imaging to determine the extent of tumor angiogenesis, yielding valuable information concerning the state of the tumor and insight into possible treatment options. ³⁴ However, nailfold capillaroscopy is perhaps the most cost efficient and widely applicable form of microvascular imaging. Researchers are using video nailfold capillaroscopy to study blood flow rates and investigate capillary morphology.^{5 6} Both video and still-picture nailfold capillaroscopy are adjuncts to care for diagnosing and treating Raynaud’s phenomenon and various connective tissue diseases such as systemic sclerosis.²

Nailfold capillaroscopy has various potential cardiovascular applications as well. Current research using nailfold capillaroscopy suggests that diabetes mellitus Type 1 and Type 2 patients exhibit a high prevalence of abnormal capillary morphology, yet have unchanged capillary densities compared to non-diabetic individuals.^7-8 Capillaroscopy has also been studied experimentally in hypertension. Structural capillary rarefaction leading to a reduced capillary density has been demonstrated in hypertensive individuals compared to non-hypertensive individuals.^9-10 In contrast to these older hypertensive patients (mean age 40 and above) who exhibit structural rarefaction, more recent research has demonstrated that younger hypertensive patients (mean age under 40 years old) have functional rarefaction without structural rarefaction.¹¹ This suggests that functional rarefaction occurs before and may progress over time to structural rarefaction.

Interestingly, hypertensive patients treated with specific antihypertensive drugs such as Perindopril/Indapamide displayed normal capillary density and endothelial function after treatment, while those treated with ACE (angiotensin-converting-enzyme) inhibitors or diuretics maintained a low capillary density despite comparable blood pressure control.¹² This suggests that some antihypertensive medications may normalize capillary density by reversing the capillary rarefaction caused by hypertension. In addition, other researchers have shown that a reduction in salt intake leads to reversal of both functional and structural capillary rarefaction in hypertensive individuals.¹³

Despite the various potential clinical applications of this technology, there is little standardization in technique for quantitating capillary density images.² To date, researchers have found that capillary density results are reproducible from both an intra-observer and inter-observer perspective only if the exact same area is being counted each time. ^{1,14 15} Of note, previous researchers have largely performed capillary counts manually using the naked eye, ^{9 16 17 18} which is a slow and subjective process.

Standardized, computer based algorithms for quantitation of capillary images theoretically provide more efficient and reproducible data analysis with less subjectivity, facilitating clinical applications of capillaroscopy. Some researchers have indeed used computer-based programs to quantitate the data from nailfold capillaroscopic pictures. ^{1,6 19 20} However, only one publication to date describes reliability of a complex software program available for quantitating capillaroscopy data,¹ and this program is complicated as previously noted above by the requirement to count the exact same visual field. Here, we present a simpler, reliable protocol for quantitating capillaries using a standardized algorithm which allows for the use of multiple visual fields. The use of multiple visual fields not only simplifies the procedure, but also permits the assessment of normal biological variation in capillary count.

The aim of this study is to describe a reproducible and efficient computer based algorithm which standardizes the capillary quantitation process. While these methods are not fully automated they require very little user input, and provide rapid and reliable quantitation of the pictures.

Protocol

Note: The acquisition process for obtaining capillary images has previously been published and is accomplished using a still digital camera with a corresponding image acquisition and analysis computer program. ¹¹²¹ This lab utilizes still images for analysis, not videos, simplifying image acquisition for analysis. The following describes the new technique for quantitating the capillaries from the images.

1. Image Enhancement Process

1. Obtain digital images with a monochrome digital camera. Calibrate the images to an object of known size by taking a picture of an object of known length such as a ruler with the camera. This process allows the computer program to measure and count capillaries accurately after processing. Ideally for the highest precision, a reticule (scientifically manufactured piece of glass with a ruler etched into it) should be used. Measure the number of pixels in a 1 mm square box using a computer program.
   Note: The key to the reproducibility and standardization of this protocol depends largely upon proper placement of the 1 mm² box that is counted.
2. Use contrast enhancement tools to darken the capillaries and lighten the background, which will maximize visualization of the capillaries. Initial differentiation of capillaries from background is important for proper cropping of the image in later steps. Do this by adjusting the image using a “best fit histogram.” To do this click on: capture, intensity, image histogram, best fit.
3. Crop a region of interest (ROI) for capillary counting as a new image (select, regions of interest). Use a 1 mm² box, which was determined by calibrating the images at 530 pixels equaling 1 mm. check that the cropped image places the apex of the capillary loops at the very top of the image.
4. Flatten the image so all future image adjustments will be evenly applied to the image. To do this click on: process tab, 2D filters, flatten, BG intensity of “bright,” object width to “75,” apply.
5. Raise the contrast of the image so capillaries are maximally visualized. To do this click on: adjust tab, display, raise contrast to 75.
6. Despeckle the image to smooth the edges of the capillaries by clicking on process tab, 2D filters, despeckle, kernel size 7 x 7, apply.
7. Finalize the image contrast so capillaries are black and the background is white. Perform this step by adjusting the histogram to the “best fit” model.
   Note: Please refer to Figure 2 in Representative Results for an example of what the processed image should look like following these steps.

2. Performing Capillary Counts / Quantitating Capillary Density

1. On each image, manually select one part of a well-defined capillary using the “target object” feature to be recognized as objects to be counted by the program. Then, select a small part of background, using the “background” feature, as a reference to areas that need to be disregarded by the counting algorithm.
   Note: The combination of these highlights causes all capillaries to be highlighted while disregarding the background noise. The quantitation (counting) protocol utilizes computer functions to differentiate parts of the image based on color and morphology.
2. Use the count function to instantly count all capillaries in the image with the imaging equipment. Set the minimum diameter of counted objects to 5 pixels in order to avoid counting background noise as capillaries.
3. For each individual, count the average of 3 - 4 images in order to obtain a more reliable assessment.
   Note: Please refer to Figure 3 in Representative Results for an example of what the image should look like during the counting procedure.

3. Creating and Using Macros to Automate Image Processing

Note: To save time, macros can be created in order to automatically perform a specific sequence of processes on one or many images. These sequences can be customized in order to make the image modifications quicker. In essence, these macros remember how the images are processed, and perform all the steps quickly and with no user input. Performing counts on 12 capillary images takes this lab between 20 to 30 min with the macros (2 to 3 min per picture), as opposed to about 8 min per picture without the macros. Therefore using the macros is 3 to 5 times more efficient than manually processing each individual image.

1. In order to create a macro, select “record macro” and on one image perform the steps and processes desired, as described in steps 1 and 2 above. Name the macro based on which image processing steps were performed for future reference. When using the macro on future pictures, simply click “run macro” and the program will automatically apply the recorded enhancements to the image(s) desired.
   Note: This lab uses a macro to perform all but one of the steps in Section 1 of the methods in a few seconds. The only step that requires user input is choosing where to crop the image, Step 1.2.

Results

The goal of this image processing procedure is to differentiate the capillaries from the background image so they can be accurately quantified. Both incomplete image processing and excessive image processing are detrimental to the program's ability to quantify the capillaries. As seen in Figure 3, incomplete image processing makes the capillaries difficult to distinguish from the background. It is critical that the user be able to readily distinguish the border of a capillary since the counting method de...

Discussion

Nailfold capillaroscopy shows promise as a clinically useful tool in the future for various oncology, cardiovascular, and rheumatologic disease applications. The image acquisition process is fairly consistent among researchers, yet there are currently multiple methods for image processing and analysis. Methods currently include computerized and manual capillary counts. Manual counts are problematic as they are time-consuming, and subject to user subjectivity and fatigue. Current computer based methods require a high leve...

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
Image-Pro Premier	Media Cybernetics, Inc	9.1	Image processing software