Name: evaluation of capillary and other vessel contribution to macular perfusion density measured with optical coherence tomography angiography
Uploaded: 2022-02-18T13:15:00
Description: Watch this Scientific Journal Video about Evaluation of Capillary and Other Vessel Contribution to Macular Perfusion Density Measured with Optical Coherence Tomography Angiography at JoVE.com

The authors would like to thank Zeiss Mexico for the unrestricted support to use the Cirrus 6000 with AngioPlex equipment.

This protocol was approved by Sala Uno&#39;s human research ethics committee. See Video 1 for sections 1 and 2 and the Table of Materials for details about the equipment used in this study.
1. Retinal analysis in the OCTA device
<ol>
	<li>Select the menu for retinal analysis in the OCTA device.</li>
	<li>Select a 3 x 3 mm retinal map; select superficial if the OCTA device measures different capillary plexuses.</li>
	<li>Sele...

<ol>
	<li>Ong, J. X., Fawzi, A. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Perspectives+on+diabetic+retinopathy+from+advanced+retinal+vascular+imaging.">Perspectives on diabetic retinopathy from advanced retinal vascular imaging.</a> Eye. , (2022).</li><li>Tan, A. C. S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=An+overview+of+the+clinical+applications+of+optical+coherence+tomography+angiography.">An overview of the clinical applications of optical coherence tomography angiography.</a> Eye. 32 (2), 262-286 (2018).</li><li>Elnahry, A. G., Ramsey, D. 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Report 1: Diabetic Retinopathy.</a> Translational Vision Science and Technology. 9, 34 (2020).</li><li>Xu, Q., Sun, H., Huang, X., Qu, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Retinal+microvascular+metrics+in+untreated+essential+hypertensives+using+optical+coherence+tomography+angiography.">Retinal microvascular metrics in untreated essential hypertensives using optical coherence tomography angiography.</a> Graefe's Archive for Clinical and Experimental Ophthalmology. 259 (2), 395-403 (2021).</li><li>Yeh, R. Y., Nischal, K. K., LeDuc, P., Cagan, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Written+in+blood:+applying+grammars+to+retinal+vasculatures.">Written in blood: applying grammars to retinal vasculatures.</a> Translational Vision Science &amp; Technology. 9, 36 (2020).</li><li>Corvi, F., Sadda, S. R., Staurenghi, G., Pellegrini, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Thresholding+strategies+to+measure+vessel+density+by+optical+coherence+tomography+angiography.">Thresholding strategies to measure vessel density by optical coherence tomography angiography.</a> Canadian Journal of Ophthalmology. 55 (4), 317-322 (2020).</li><li>Pathak, P., Panday, S. B., Ahn, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Artificial+neural+network+model+effectively+estimates+muscle+and+fat+mass+using+simple+demographic+and+anthropometric+measures.">Artificial neural network model effectively estimates muscle and fat mass using simple demographic and anthropometric measures.</a> Clinical Nutrition. 41 (1), 144-152 (2022).</li><li>OFee, K., Deych, E., Ciani, O., Brown, D. 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The contribution of vessels larger than capillaries to perfusion density changes in retinal vascular diseases before the development of retinopathy. It decreased in the inner region of patients with arterial hypertension and varied between fields in patients with diabetes. There are direct methods for measuring vascular reactivity in the retina, which depend on the exposure to a stimulus14,15. The measurement proposed in this paper uses two metrics, automatically...

Retinal circulation is the combination of arteriolar, capillary, and venular flow, whose contribution can vary to meet the oxygen needs of the different retinal layers. This circulation does not depend on the autonomous nervous system regulation and has been traditionally evaluated with fluorescein angiography, an invasive method that uses intravenous contrast to delineate retinal vessels. Sequential photographs allow the evaluation of arterial, arteriolar, venular, and venous circulation, as well as sites of capillary damage in retinal vascular diseases1.
A current method to measure the macular circulation is optical coherence tomography angiography (OCTA), which uses interferometry to obtain retinal images and can outline capillaries and larger retinal vessels2. Unlike fluorescein angiography, OCTA imaging is not influenced by macular xanthophyll pigment shadowing, allowing superior imaging of macular capillaries3. Other advantages of OCTA over fluorescein angiography are its noninvasiveness and higher resolution4.
OCTA devices measure the superficial capillary plexus at the parafovea in a 3 x 3 mm map, concentric to the foveal center (Figure 1). The equipment automatically measures vessel length density (the length of capillaries with circulation in the measured area) and perfusion density (the percentage of the measured area with circulation), which includes that of vessels larger than capillaries (Figure 2)5. Vessel density has a substantial contribution to perfusion density under physiological conditions. Some devices measure vessel density as a &#34;skeletonized vascular density&#34; and perfusion density as &#34;vessel/vascular density.&#34; Regardless of the device, there is usually a measurement for length (measured in mm/mm2 or mm-1) and another for the area with circulation (measured in %), which are generated automatically.
Vessel density can change in healthy people when exposed to darkness, flicker light6, or caffeinated drinks7 because of the neurovascular coupling that redistributes blood flow between the superficial, middle, and deep capillary plexuses according to the retinal layer with the highest activity. Any decrease in vessel density caused by this redistribution returns to baseline values after the stimulus ceases and does not represent capillary loss, a pathological change reported before retinopathy appears in vascular diseases such as diabetes8 or arterial hypertension9.
The decrease in capillaries could be compensated partially by arteriolar vasodilatation. Measuring only a percentage or perfused area does not provide any insight into whether there is vasodilatation, which can appear when capillaries reach a minimum threshold. Measuring vessel density would not help detect an increased circulation area resulting from vasodilatation. The contribution of arteriolar circulation to perfusion density can be estimated indirectly using a coefficient of determination between vessel density and perfusion density, and defining the percentage of the area with circulation that corresponds to capillaries or other vessels.
The rationale behind this technique is that regression analysis can identify the extent to which the changes of an independent numeric value result in changes of a dependent numeric value. In macular vessel imaging using OCTA, capillary circulation is an independent variable that influences the area with circulation because there are few larger vessels in the evaluated region. However, the parafovea has larger vessels that can dilate and change the percentage of the area with circulation, which cannot be identified directly by the current automated OCTA metrics. The advantage of using a coefficient of determination is that it measures a relationship between two existing metrics to produce two more: the percentage of the area with circulation that corresponds to capillaries, and the percentage that corresponds to other vessels. Both percentages can be measured directly using a pixel count with imaging software. However, the coefficient of determination can be calculated for a sample with the numbers that the OCTA devices generate automatically10,11.
Pathak et al. used a coefficient of determination to estimate lean muscle and fat mass from demographic and anthropometric measures using an artificial neural network. Their study found that their model had an R2 value of 0.92, which explained the variability of a large portion of their dependent variables12. O&#39;Fee and colleagues used a coefficient of determination to rule out nonfatal myocardial infarction as a surrogate for all-cause and cardiovascular mortality because they found an R2 of 0.01 to 0.21. Those results showed that the independent variable explained less than 80% of the changes of the dependent variables, set as a criterion of surrogacy (R2= 0.8)13.
The coefficient of determination is used to assess the effect of changes of a variable, a group of variables, or a model over the changes of an outcome variable. The difference between 1 and the R2 value represents the contribution of other variables to the changes of the outcome variable. It is uncommon to attribute the difference to a single variable because there are usually more than two contributing to the outcome. However, the proportion of the macular area that has circulation can only originate from the area covered by capillaries and from that covered by larger vessels, as larger vessels dilate more than capillaries. Moreover, reactive vasodilation is considered to most probably originate from retinal arterioles, because a reduced capillary circulation could decrease oxygen supply.
Only two sources contribute to a percentage of area with circulation in the macula: capillaries and vessels larger than them. The coefficient of determination between vessel density and perfusion density determines the contribution of capillaries to the area with circulation, and the remaining changes (the difference between 1 and the R2 value) represent the contribution of the only other variable that represents an area with circulation (that within larger retinal vessels). This paper describes the method of measuring this contribution in healthy people (group 1) and how it changes in patients with retinal vascular diseases: arterial hypertension without hypertensive retinopathy (group 2) and diabetes mellitus without diabetic retinopathy (group 3).

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Cirrus 6000 with Angioplex</td>
			<td>Carl Zeiss Meditec Inc., Dublin CA</td>
			<td>N/A</td>
			<td>3 x 3 vessel and perfusion density maps</td>
		</tr>
		<tr>
			<td>Excel</td>
			<td>Microsoft</td>
			<td>N/A</td>
			<td>spreadsheet</td>
		</tr>
		<tr>
			<td>Personal computer</td>
			<td>Generic</td>
			<td>N/A</td>
			<td>for running the calculations on the spreadsheet</td>
		</tr>
	</tbody>
</table>

evaluation of capillary and other vessel contribution to macular perfusion density measured with optical coherence tomography angiography

Parafoveal circulation of the superficial retinal capillary plexus is usually measured with vessel density, which determines the length of capillaries with circulation, and perfusion density, which calculates the percentage of the evaluated area that has circulation. Perfusion density also considers the circulation of vessels larger than capillaries, although the contribution of these vessels to the first is not usually evaluated. As both measurements are automatically generated by optical coherence tomography angiography devices, this paper proposes a method for estimating the contribution of vessels larger than capillaries by using a coefficient of determination between vessel and perfusion densities. This method can reveal a change in the proportion of perfusion density from vessels larger than capillaries, even when mean values do not differ. This change could reflect compensatory arterial vasodilatation as a response to capillary dropout in the initial stages of retinal vascular diseases before clinical retinopathy appears. The proposed method would allow the estimation of the changes in the composition of perfusion density without the need for other devices.

There were 45 subjects in group 1, 18 in group 2, and 36 in group 3. Table 1 shows the distribution of age and densities by group; only vessel and perfusion densities in group 1 were lower than in group 2. The coefficients of determination of center vessel and perfusion densities are shown in Figure 5. There was no significant difference between the groups.
The coefficient of determination between the inner vessel and perfusion densities was 0.818...

Watch this Scientific Journal Video about Evaluation of Capillary and Other Vessel Contribution to Macular Perfusion Density Measured with Optical Coherence Tomography Angiography at JoVE.com

Evaluation of Capillary and Other Vessel Contribution to Macular Perfusion Density Measured with Optical Coherence Tomography Angiography

We describe the evaluation of a coefficient of determination between vessel and perfusion density of the parafoveal superficial capillary plexus to identify the contribution of vessels larger than capillaries to perfusion density.

Parafoveal circulation of the superficial retinal capillary plexus is usually measured with vessel density, which determines the length of capillaries ...

The protocol allows the identification of the proportion of an area with the circulation from dilated vessels. This dilation can be a response of clinical pathologic condition. This technique can indirectly outline vasodilation using an usual optical coherence tomography metrics to evaluate a group of patients.Finding vasodilation could indirectly reveal low oxygenation in the stages of retinal vascular diseases before clinical signs appear. Demonstrating the procedure will be Jatziri Perez-Aragon a retinal surgeon from our lab. To begin, select the menu for retinal analysis in the OCTA device.Select a three by three millimeter retinal map and select superficial if the OCTA device measures different capillary plexuses. Select vessel length density or its equivalent, like skeletonized vascular density. Measure vessel length density per millimeter in a three by three millimeter retinal map.Return to the menu for retinal analysis. Select a three by three millimeter retinal map and select superficial if the OCTA device measures different capillary plexuses. Select perfusion density or its equivalent like vessel density.Measure perfusion density in percent in a three by three millimeter retinal map. Verify that the density maps have a signal strength of more than seven, and then verify that the maps have no measurement errors resulting from artifacts or eye movements. Register the values of center vessel length density, center perfusion density, inner vessel length density, inner perfusion density, superior vessel length density, superior perfusion density, inferior vessel length density, inferior perfusion density temporal vessel length density, temporal perfusion density, nasal vessel length density and nasal perfusion density in the spreadsheet.Select the variables to be evaluated. For example, center vessel length density and center perfusion density and select the values of both variables for a defined group. In the toolbar click on insert.Click on the recommended charts button in the graph section and wait for a scatter chart to appear as a suggestion in a window. Click the okay button to accept the suggestion. Inspect the scatter chart of the data and right click on the series to display an options menu.Select the Add Trendline option, and wait for a linear trend line to be added to the chart and for a menu on the right side of the screen. Displace the menu downwards to find the display R squared value on the chart option. Select this option to display the R squared value on the chart.Select home on the toolbar, and then click on the copy button. Prepare a chart of coefficients of determination on a new page. Select a destination cell and click on the right mouse button.Select paste with keeping source formatting. Prepare a new chart to show the percentage of perfusion density changes explained by changes in vessel density. Select the cell with the coefficient of determination in the previous chart.Click on the right mouse button and select copy. Select a destination cell in the new chart. Click on the right mouse button and select paste.Select the cell with the pasted value and then select a home in the toolbar, followed by a selection of percent style in the number menu. Select increased decimal in the number menu and click once. Prepare another table to show the percentage of perfusion density explained by the changes in vessels larger than capillaries.Select a destination cell and subtract the last results from one. Select this cell and then select home in the toolbar. Select percent style in the number menu.Click once on increased decimals in the number menu. Format the charts to display the contribution of capillaries and vessels larger than capillaries in the changes in perfusion density. Repeat the procedure to obtain the values of the inner vessel or perfusion densities and superior, inferior, temporal and nasal vessel or perfusion densities in group three.Compare the coefficients of determination in three groups. One, healthy people, two, patients with arterial hypertension without hypertensive retinopathy, and three, patients with type two diabetes melitis without diabetic retinopathy. In group three, also compare the coefficients of determination between fields superior, inferior, temporal and nasal.Compare the percentage differences in the contribution of capillaries and vessels larger than capillaries to perfusion density between groups and between fields in group three. The vessel and perfusion densities in group one were lower than in group two. The comparison between the coefficients of determination of center vessel and perfusion densities in the three groups showed that there was no significant difference between the groups.The contribution of vessels larger than capillaries accounted for 18.2%in healthy subjects, 2.6%in patients with arterial hypertension and 16.4%in patients with diabetes. Although the inner region had a contribution of vessels larger than capillaries that accounted for 16.4%of perfusion density this contribution was 27.8%in the superior field, 20.7%in the inferior field, 33.4%in the temporal field and 13.8%in the nasal field. It's important to obtain the R square value as it is essential to calculate the percentage of perfusion density of dilated vessels.

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