Structural OCT Parameters Associated with Treatment Response and Macular Neovascularization Onset in Central Serous Chorioretinopathy

Application and progress of artificial intelligence technology in the segmentation of hyperreflective foci in OCT images for ophthalmic disease research

With the advancement of retinal imaging, hyperreflective foci (HRF) on optical coherence tomography (OCT) images have gained significant attention as potential biological biomarkers for retinal neuroinflammation. However, these biomarkers, represented by HRF, present pose challenges in terms of localization, quantification, and require substantial time and resources. In recent years, the progress and utilization of artificial intelligence (AI) have provided powerful tools for the analysis of biological markers. AI technology enables use machine learning (ML), deep learning (DL) and other technologies to precise characterization of changes in biological biomarkers during disease progression and facilitates quantitative assessments. Based on ophthalmic images, AI has significant implications for early screening, diagnostic grading, treatment efficacy evaluation, treatment recommendations, and prognosis development in common ophthalmic diseases. Moreover, it will help reduce the reliance of the healthcare system on human labor, which has the potential to simplify and expedite clinical trials, enhance the reliability and professionalism of disease management, and improve the prediction of adverse events. This article offers a comprehensive review of the application of AI in combination with HRF on OCT images in ophthalmic diseases including age-related macular degeneration (AMD), diabetic macular edema (DME), retinal vein occlusion (RVO) and other retinal diseases and presents prospects for their utilization.

Artificial intelligence in chorioretinal pathology through fundoscopy: a comprehensive review

BACKGROUND

Applications for artificial intelligence (AI) in ophthalmology are continually evolving. Fundoscopy is one of the oldest ocular imaging techniques but remains a mainstay in posterior segment imaging due to its prevalence, ease of use, and ongoing technological advancement. AI has been leveraged for fundoscopy to accomplish core tasks including segmentation, classification, and prediction.

MAIN BODY

In this article we provide a review of AI in fundoscopy applied to representative chorioretinal pathologies, including diabetic retinopathy and age-related macular degeneration, among others. We conclude with a discussion of future directions and current limitations.

SHORT CONCLUSION

As AI evolves, it will become increasingly essential for the modern ophthalmologist to understand its applications and limitations to improve patient outcomes and continue to innovate.

En-face optical coherence tomography hyperreflective foci of choriocapillaris in central serous chorioretinopathy

The purpose of this study is to evaluate choroidal hyperreflective foci (HRF) changes in central serous chorioretinopathy (CSC) on en-face optical coherence tomography (OCT). Retrospective analysis of 42 patients with unilateral CSC (84 eyes, including fellow eyes for controls) and 42 age- and sex-matched controls. With 4.5 × 4.5 mm macular scans, structural en-face OCT choriocapillaris (CC) slabs were used to calculate the density and number of HRF in acute CSC eyes with serous retinal detachment (SRD), resolved CSC eyes without SRD, unaffected fellow eyes, control eyes, and 1-year follow-up eyes. Based on the 2-disc diameter (3000 μm), the en-face OCT scan was divided into foveal and perifoveal lesion and analyzed to consider the impact of SRF in HRF measurement. Regression analyses were performed on the several factors with HRF number and density in the acute and resolved CSC eyes. The perifoveal density and number of CC HRF was significantly lower in the resolved CSC eyes when compared to the acute CSC eyes (P = 0.002, both), fellow eyes (P = 0.042/density, 0.028/number), and controls (P = 0.021/density, P = 0.003/number). There was no significant difference between the acute CSC eyes, fellow eyes, controls, and 1-year follow-up eyes. As subfoveal choroidal thickness decreased and choroidal vascularity (CVI) increased, the perifoveal density and number of HRF was measured higher with a significant correlation in univariate regression analysis of the acute and resolved CSC eyes (all, P < 0.05). The authors hypothesized that stromal edema induced by choroidal congestion and hyperpermeability has the greatest influence on HRF measurement, possibly affected by inflammatory cells and materials extravasation.

Quantitative approaches in multimodal fundus imaging: State of the art and future perspectives

When it first appeared, multimodal fundus imaging revolutionized the diagnostic workup and provided extremely useful new insights into the pathogenesis of fundus diseases. The recent addition of quantitative approaches has further expanded the amount of information that can be obtained. In spite of the growing interest in advanced quantitative metrics, the scientific community has not reached a stable consensus on repeatable, standardized quantitative techniques to process and analyze the images. Furthermore, imaging artifacts may considerably affect the processing and interpretation of quantitative data, potentially affecting their reliability. The aim of this survey is to provide a comprehensive summary of the main multimodal imaging techniques, covering their limitations as well as their strengths. We also offer a thorough analysis of current quantitative imaging metrics, looking into their technical features, limitations, and interpretation. In addition, we describe the main imaging artifacts and their potential impact on imaging quality and reliability. The prospect of increasing reliance on artificial intelligence-based analyses suggests there is a need to develop more sophisticated quantitative metrics and to improve imaging technologies, incorporating clear, standardized, post-processing procedures. These measures are becoming urgent if these analyses are to cross the threshold from a research context to real-life clinical practice.