During the enrollment period (from January 2018 to October 2021), 89 eyes of 89 subjects affected by exudative AMD were recruited to the Eye Clinic of the University of Naples Federico II.

The criteria for inclusion were age greater than 50 years and diagnosis of treatment-naïve exudative AMD due to the presence of type 1 MNV.

The exclusion criteria were MNV secondary to causes other than AMD, idiopathic polypoidal choroidal vasculopathy (PCV), retinal angiomatous proliferation (RAP), type 2 MNV, previous intravitreal injections of anti-VEGF for CNV, geographic atrophy, subretinal fibrosis, vitreoretinal diseases, retinal vascular diseases, myopia greater than 6 diopters, history of intraocular surgery, and significant lens opacity. We also excluded images with visible eye motion or blinking artifacts and low-quality images obtained with OCTA.

Each patient underwent a complete ophthalmological evaluation, including the evaluation of best-corrected visual acuity (BCVA) according to the Early Treatment of Diabetic Retinopathy Study (ETDRS), slit-lamp biomicroscopy, applanation tonometry, fundus examination, FA, ICGA (Spectralis, Heidelberg Engineering, Heidelberg, Germany), spectral domain (SD)-OCT (Spectralis, Heidelberg Engineering, Heidelberg, Germany), and OCTA (AngioVue, RTVue XR Avanti, Optovue, Inc., Freemont, CA).

The study was registered on ClinicalTrials.gov (NCT05108285), and all investigations adhered to the tenets of the Declaration of Helsinki. Written informed consent was obtained from the patients enrolled in the study.

OCTA images with the Optovue Angiovue System (software ReVue XR version 2017.1.0.151, Optovue Inc., Fremont, CA, USA) were performed following a standardized protocol based on the split spectrum amplitude decorrelation algorithm (SSADA), as previously described [16].

The AngioAnalyticTM software automatically calculated the vessel density (VD) of the choriocapillaris on a 6 mm × 6 mm macular area. The VD was defined as the percentage area occupied by the microvasculature in the whole scan area and in all sections [17].

The 3D Projection Artifact Removal (PAR) algorithm was performed to improve the quality of OCTA images. For each eye analyzed, the software automatically elaborated the vessel density in the whole scanned area and in all sections of the grid in the choriocapillaris region selected by the operator in retinal angiogram (between upper: Bruch membrane offset − 9 μm and lower: Bruch membrane offset 31 μm).

Excluded from the analysis were images with a signal strength index of less than 80, residual motion artifacts, incorrect segmentation, or low centration or focus.

Dark halo is defined as a choriocapillaris area, surrounding the MNV, characterized by a flow deficit detected by OCTA. The hypofluorescent halo (dark edge of hypofluorescence) around the MNV is also present in the early phase of ICGA and could correspond to the area of dark halo identified by OCTA.

To measure dark halo areas, OCTA and ICGA images were assessed separately, independently by two ophthalmologists (FF and LC). In case of disagreement, a third senior retinal specialist (GC) was asked to evaluate the image.

Firstly, the authors collected and analyzed both choriocapillaris flow density images and scan segmentation by OCTA. The blue space area around the MNV corresponding to dark halo was measured using ImageJ software (Version 1.50i; National Institutes of Health, Bethesda, MD, USA) as previously described [11]. Before the analysis, we used “the set scale” selection tool, entering the known distance and the unit of measurement in pixels to scale the image in millimeter square. The ophthalmologists converted any OCTA images to 8-bit images and then selected the adjust threshold function with the intensity threshold set from 0 to 50 for choriocapillaris OCTA images. The red pixel area around the MNV corresponded to dark halo, and it was manually identified and automatically quantified with the “measure tool” by ImageJ software and collected for statistical analysis.

The readers also collected ICGA images, used for delineation of the dark halo area, taken within 1–4 min after dye injection, according to a previous study [18]. Similar to the analysis performed with OCTA, the ICGA image was manually detected and automatically computed in ImageJ.

For both OCTA and ICGA images, the whole area, including the MNV and surrounding dark halo, was detected manually and measured automatically using ImageJ. Then, the contour of the MNV area was delineated point by point and measured in millimeter square. On binarized images, the dark halo was calculated as the difference between the whole area and the MNV area (Fig. 1).

Top row. Right eye of a patient with age-related macular degeneration (AMD) complicated with type 1 macular neovascularization (MNV). The whole area (including MNV and dark halo area) and the MNV at indocyanine green angiography (ICGA) were manually selected and automatically measured using ImageJ (A, B). The whole area and the MNV at optical coherence tomography angiography (OCTA) were manually detected and automatically measured using ImageJ (C, D). The difference between the whole area and the MNV corresponds to the dark halo

Statistical analysis was performed with SPSS (Version 25 for Windows; SPSS Inc, Chicago, IL, USA). The Shapiro–Wilk test confirmed that all variables were normally distributed. Continuous variables are expressed as mean ± standard deviation (SD). The paired Student’s test was used to evaluate the differences in the dark halo measurements between OCTA and ICGA images. The intraclass correlation coefficients (ICCs) and 95% CIs were used to assess the absolute agreement between the dark halo area measurements from different types of OCTA and ICGA scans. ICC values of < 0.5, between 0.5 and 0.75, between 0.75 and 0.90, and > 0.90 indicated poor, moderate, good, and excellent agreement, respectively. A p-value of < 0.05 was considered statistically significant.