Intralesional Vessel Diameter Measured by Optical Coherence Tomography Angiography Could Improve the Differential Diagnosis of Small Melanocytic Choroidal Lesions

Abstract

In this study, we aimed to identify the features of indeterminate choroidal melanocytic lesions visualized on optical coherence tomography angiography (OCTA) and to identify the predictors of growth. We retrospectively evaluated 86 patients with indeterminate lesions treated at our centre from 2016 to 2021. Clinical management involved active surveillance followed by brachytherapy if growth was detected. The lesions were classified into two groups according to whether they grew (small melanomas) or remained stable (choroidal nevi). Growth was detected in 19 (22.1%) lesions. All patients underwent OCTA at baseline. These images were compared to identify the possible predictors of growth. Significant between-group differences were observed in thickness (p = 0.00), greatest basal diameter (p = 0.00), number of risk factors (p = 0.00), symptoms (p = 0.001; relative risk [RR]: 4.3), orange pigment (p = 0.00; RR: 6.02), and ultrasonographic hollowness (Kappa sign); p = 0.000; RR: 5.3). The melanomas had significantly more vessels with a diameter ≥ 76.3 µm (p = 0.02; RR: 2.46). The time to growth in these lesions was significantly shorter (p = 0.05) than in lesions with smaller vessels. These findings show that vessel diameter quantified by OCTA can help differentiate between choroidal nevi and small melanomas, when considered together with clinical risk factors.

Keywords: OCTA; choroidal melanoma; choroidal nevus; optical coherence tomography angiography.

Figure 1

Manual segmentation of OCTA images. The choriocapillaris slab was expanded to a depth of 100 µm posteriorly to include the lesion (the analysed region is delimited by blue lines, purple dotting shows blood flow).

Figure 2

The (left) image is the AOCT of a lesion that remained stable during follow-up, with a fine, regular vascularisation pattern. To the (right), we can observe a lesion that grew, with larger vessels in the AOCT, avascular areas, and a complex vascularisation pattern with cross-links and loops (example shown by the yellow arrow).

Figure 3

(A). Each independent observer measured the diameter of three different vessels, selecting the largest vessels distinguished on the en face images (obtained measurements are shown in green next to the selected vessels). (B). Using ImageJ software, vessel density maps were analysed. The areas of greatest vascular density were selected according to colour (shown surrounded by a yellow contour line) to calculate the percentage area occupied by high versus low vascular density.

Figure 4

(A): Kaplan–Meier curve showing time to growth of lesions according to vessel diameter (< vs. ≥76.3 µm) (p = 0.05). (B): Kaplan–Meier curve showing time to growth of lesions according to vessel diameter (< vs. ≥100 µm) (p = 0.01).

Figure 4

(A): Kaplan–Meier curve showing time to growth of lesions according to vessel diameter (< vs. ≥76.3 µm) (p = 0.05). (B): Kaplan–Meier curve showing time to growth of lesions according to vessel diameter (< vs. ≥100 µm) (p = 0.01).

Figure 5

Relative risk of melanoma according to established clinical risk factors and greatest vessel diameter. Lesions with ≤4 risk factors at baseline had a significantly lower risk of melanoma (RR: 0.19); however, within this group, the presence of vessel diameters ≥ 76.3 µm implies a higher risk (RR: 1.45). Lesions with ≥5 risk factors had a higher risk of malignancy (RR: 5.23); nevertheless, the presence of vessels with diameters < 76.3 µm within this group was protective (RR: 0.5).