We read with interest the research article by Sonoda and associates entitiled “Luminal and Stromal Areas of Choroid Determined by Binarization Method of Optical Coherence Tomographic Images.” This paper was built on a previous paper by the same group, which described a new method to segment choroid using ImageJ, an open source software.

The authors computed the proportion of luminal to stromal areas in the circumscribed cross-sectional choroidal area after segmenting the choroidal scans obtained from spectral-domain optical coherence tomographic (SD OCT) images based on an enhanced depth imaging platform (EDI OCT). The purpose of calculating this area was to determine if an increase or decrease in cross-sectional choroidal area was due to a relative increase or decrease in luminal or stromal area. The authors described that the cross-sectional choroidal area decreased with increasing age. Since the luminal/stromal area also decreased with increasing age, the conclusion was that the area of vascularity decreased more than the stromal area with increasing age. However, proportionate change in the choroidal vasculature relative to total cross-sectional choroidal area was not elucidated.

We would like to suggest an alternative measurement that could potentially be a more stable and reliable tool to monitor the changes in the choroid. By calculating the proportion of luminal area to cross-sectional choroid area, which we termed choroidal vascularity index , we can compare the vascularity of the choroid between subjects without having to first compare cross-sectional choroid area, which we termed total choroidal area . We can also use percentage change in choroidal vascularity index as a follow-up tool to present the proportionate change in vasculature of the choroid as a more stable and consistent biomarker of disease progression.

The authors have not calculated the choroidal vascularity index; however, when we calculated this index using values from the results presented in the paper, we determined that the mean choroidal vascularity index was 65.76%. In their previous paper, the authors have also calculated this index and determined that the mean choroidal vascularity index was approximately 65%. Branchini and associates have assessed morphologic features of the choroid obtained using SD OCT scans and have computed the ratio of large choroidal vessel layer thickness to the total choroidal thickness beneath the fovea as 0.7 ± 0.06 and choroidal stromal area to the choroidal vessel lumen areas as 0.27 ± 0.08.

We postulate that in diseases involving the choroid, such as posterior uveitis, age-related macular degeneration, and diabetic retinopathy, the proportion of vasculature, which is the choroidal vascularity index, would be a good optical tool for choroidal perfusion status and disease progression. This is because in these pathologies, it is primarily the vasculature that is affected. However, in such studies, it is hard to quantify the change in vasculature using luminal/stromal area.

In conclusion, image binarization of EDI SD OCT images allows us to study the structural changes in the choroid. We propose that measuring the choroidal vascularity index and percentage change in choroidal vascularity index on follow-up scans could potentially be a more stable and reliable tool to monitor vascular changes in the choroid.