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W tym Artykule

  • Podsumowanie
  • Streszczenie
  • Wprowadzenie
  • Protokół
  • Wyniki
  • Dyskusje
  • Ujawnienia
  • Podziękowania
  • Materiały
  • Odniesienia
  • Przedruki i uprawnienia

Podsumowanie

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.

Streszczenie

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.

Wprowadzenie

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 "skeletonized vascular density" and perfusion density as "vessel/vascular density." 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'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).

Protokół

This protocol was approved by Sala Uno'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

  1. Select the menu for retinal analysis in the OCTA device.
  2. Select a 3 x 3 mm retinal map; select superficial if the OCTA device measures different capillary plexuses.
  3. Select vessel length density (or its equivalent, e.g., skeletonized vascular density).
  4. Measure vessel length density in mm-1 in a 3 x 3 mm retinal map.
    NOTE: The map is divided into two regions: center (within a 1 mm circle, concentric to the foveal center) and inner (outside the 1 mm center circle, Figure 3). The equipment also measures a full density (within the 3 mm circle) and subdivides the inner region into four fields: superior, inferior, temporal, and nasal (Figure 4). Each region is specified so that the vessel length densities are measured automatically. The instruments display the values for center, inner, and full densities and for superior, temporal, inferior, and nasal fields of the inner density.
  5. Return to the menu for retinal analysis.
  6. Select a 3 x 3 mm retinal map; select superficial if the OCTA device measures different capillary plexuses.
  7. Select perfusion density (or its equivalent, e.g., vessel density).
  8. Measure perfusion density in % in a 3 x 3 mm retinal map.
    NOTE: The map is divided into two regions: center (within a 1 mm circle, concentric to the foveal center) and inner (outside the 1 mm center circle). The equipment also measures a full density (within the 3 mm circle) and subdivides the inner region into four fields: superior, inferior, temporal, and nasal. Each region is specified so that the perfusion densities are measured automatically. The instruments display the values for center, inner, and full densities and for superior, temporal, inferior, and nasal fields of the inner density.
  9. Verify that the density maps have a signal strength > 7; then, verify that the maps have no measurement errors resulting from artifacts or eye movements.
  10. 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 a spreadsheet.

2. Calculation of the coefficients of determination using a spreadsheet

  1. Select the variables to be evaluated (e.g., center vessel length density and center perfusion density). Select the values of both variables for a defined group (e.g., group 1).
  2. In the toolbar, click on insert.
  3. Click on the recommended charts button in the graphs section. Wait for a scatter chart to appear as a suggestion in a window. Click the OK button to accept the suggestion.
  4. Inspect the scatter chart of the data. Right-click on the series to display an options menu.
  5. Select the add trendline option. Wait for a linear trendline to be added to the chart and for a menu on the right side of the screen.
  6. Displace the menu downwards to find the Display R-squared value on chart option. Select this option to display the R-squared value on the chart. Select the R-squared-value.
  7. Select Home on the toolbar and then click on the copy button.
  8. Prepare a chart of coefficients of determination on a new page.
  9. Select a destination cell (e.g., center coefficient of determination for group 1). Click on the right mouse button. Select paste with keep source formatting.
  10. Prepare a new chart to show the percentage of perfusion density changes explained by changes in vessel density.
  11. Select the cell with the coefficient of determination in the previous chart. Click on the right mouse button. Select copy.
  12. Select a destination cell in the new chart (e.g., center in group 1). Click on the right mouse button. Select paste.
  13. Select the cell with the pasted value; then, in the toolbar, select home | percent style in the number menu.
  14. Select increase decimal in the number menu and click it once.
    NOTE: The resulting number is the percentage of changes in perfusion density explained by the changes in vessel density.
  15. Prepare another table to show the percentage of perfusion density explained by the changes in vessels larger than capillaries.
  16. Select a destination cell (e.g., center in group 1). Subtract the last result from 1.
  17. Select this cell. Select home in the toolbar.
  18. Select percent style in the number menu.
  19. Click once on increase decimals in the number menu.
  20. Format the charts to display the contribution of capillaries (vessel density) and vessels larger than capillaries to the changes in perfusion density.
  21. Repeat the procedure to obtain the values of inner vessel/perfusion densities and superior, inferior, temporal, and nasal vessel/perfusion densities in group 3.

3. Comparison of the coefficients of determination

  1. Compare the coefficients of determination in three groups: 1, healthy people; 2, patients with arterial hypertension without hypertensive retinopathy; and 3, patients with type 2 diabetes mellitus without diabetic retinopathy. In group 3, also compare the coefficients of determination between fields: superior, inferior, temporal, and nasal.

4. Compare the percentage differences in the contribution of capillaries and vessels larger than capillaries to perfusion density, between groups and between fields in group 3

Wyniki

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...

Dyskusje

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...

Ujawnienia

The authors declare that they have no conflicts of interest to disclose.

Podziękowania

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

Materiały

NameCompanyCatalog NumberComments
Cirrus 6000 with AngioplexCarl Zeiss Meditec Inc., Dublin CAN/A3 x 3 vessel and perfusion density maps
ExcelMicrosoftN/Aspreadsheet
Personal computerGenericN/Afor running the calculations on the spreadsheet

Odniesienia

  1. Ong, J. X., Fawzi, A. A. Perspectives on diabetic retinopathy from advanced retinal vascular imaging. Eye. , (2022).
  2. Tan, A. C. S., et al. An overview of the clinical applications of optical coherence tomography angiography. Eye. 32 (2), 262-286 (2018).
  3. Elnahry, A. G., Ramsey, D. J. Optical coherence tomography angiography imaging of the retinal microvasculature is unimpeded by macula xanthophyll pigment. Clinical and Experimental Ophthalmology. 48 (7), 1012-1014 (2020).
  4. Elnahry, A. G., Ramsey, D. J. Automated image alignment for comparing microvascular changes detected by fluorescein angiography and optical coherence tomography angiography in diabetic retinopathy. Seminars in Ophthalmology. 36 (8), 757-764 (2021).
  5. Rosenfeld, P. J., et al. Zeiss AngioPlex spectral domain optical coherence tomography angiography: technical aspects. Developments in Ophthalmology. 56, 18-29 (2016).
  6. Nesper, P. L., et al. Hemodynamic response of the three macular capillary plexuses in dark adaptation and flicker stimulation using optical coherence tomography angiography. Investigative Ophthalmology and Visual Science. 60 (2), 694-703 (2019).
  7. Zhang, Y. S., Lee, H. E., Kwan, C. C., Schwartz, G. W., Fawzi, A. A. Caffeine delays retinal neurovascular coupling during dark to light adaptation in healthy eyes revealed by optical coherence tomography angiography. Investigative Ophthalmology and Visual Science. 61 (4), 37 (2020).
  8. Barraso, M., et al. Optical coherence tomography angiography in type 1 diabetes mellitus. Report 1: Diabetic Retinopathy. Translational Vision Science and Technology. 9, 34 (2020).
  9. Xu, Q., Sun, H., Huang, X., Qu, Y. Retinal microvascular metrics in untreated essential hypertensives using optical coherence tomography angiography. Graefe's Archive for Clinical and Experimental Ophthalmology. 259 (2), 395-403 (2021).
  10. Yeh, R. Y., Nischal, K. K., LeDuc, P., Cagan, J. Written in blood: applying grammars to retinal vasculatures. Translational Vision Science & Technology. 9, 36 (2020).
  11. Corvi, F., Sadda, S. R., Staurenghi, G., Pellegrini, M. Thresholding strategies to measure vessel density by optical coherence tomography angiography. Canadian Journal of Ophthalmology. 55 (4), 317-322 (2020).
  12. Pathak, P., Panday, S. B., Ahn, J. Artificial neural network model effectively estimates muscle and fat mass using simple demographic and anthropometric measures. Clinical Nutrition. 41 (1), 144-152 (2022).
  13. OFee, K., Deych, E., Ciani, O., Brown, D. L. Assessment of nonfatal myocardial infarction as a surrogate for all-cause and cardiovascular mortality in treatment or prevention of coronary artery disease: a meta-analysis of randomized clinical trials. JAMA Internal Medicine. 181 (12), 1575-1587 (2021).
  14. Kushner-Lenhoff, S., Ashimatey, B. S., Kashani, A. H. Retinal vascular reactivity as assessed by optical coherence tomography angiography. Journal of Visualized Experiments: JoVE. (157), e60948 (2020).
  15. Sousa, D. C., et al. A protocol to evaluate retinal vascular response using optical coherence tomography angiography. Frontiers in Neuroscience. 13, 566 (2019).
  16. Falavarjani, K. G., et al. Effect of segmentation error correction on optical coherence tomography angiography measurements in healthy subjects and diabetic macular oedema. British Journal of Ophthalmology. 104 (2), 162-166 (2020).
  17. Warner, R. L., et al. Full-field flicker evoked changes in parafoveal retinal blood flow. Scientific Reports. 10 (1), 16051 (2020).
  18. Zhang, Y. S., et al. Reversed neurovascular coupling on optical coherence tomography is the earliest detectable abnormality before clinical diabetic retinopathy. Journal of Clinical Medicine. 9 (11), 3523 (2020).

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