Validation of Macular Telangiectasia Type-2 (MacTel) multimodal imaging-based classification system in a cohort from India

在印度人群中验证基于多模态成像的2型黄斑毛细血管扩张症(MacTel)分类系统

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Abstract

BACKGROUND: To validate the recently proposed Macular Telangiectasia Type-2 (MacTel) Classification and Regression Trees (CART)-based multimodal imaging grading by the Chew et al. MacTel research group. METHODS: Cross-sectional multicentre study in India. We reviewed the medical records of 1432 eyes of 733 participants from the MacTel registry of three retinal centres. Multimodal imaging analysis of colour fundus photograph, spectral-domain optical coherence tomography (SD-OCT), and fundus autofluorescence images was performed to validate the CART-based grading of MacTel. It is a decision tree where each fork is split into a predictor variable, with each node ultimately predicting the target variable at its end. To design a CART-based grading system for categories without a clear progression, multiple combinations of OCT features were explored to identify the best representation of progressive decline in best corrected visual acuity (BCVA). The primary outcome was to demonstrate whether BCVA decreases with increasing severity of MacTel as per this classification. RESULTS: This seven-step severity scale correlated with BCVA in our study group. BCVA decreased in the following order from: grade 0, no OCT features were present with well-preserved BCVA, grade 1 characterized by non-central ellipsoid zone (EZ) loss, grade 2 with central EZ loss, grade 3 marked by non-central pigment, grade 4 by outer retinal hyper-reflectivity, grade 5 with central pigment, to grade 6 associated with exudative neovascularization, which may or may not include central pigment. CONCLUSIONS: Our study validates the Chew et al. classification and further reinforces the application of this grading scale in clinical practice.

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