Dataset Information

Macular Telangiectasia Type 2: A Classification System Using MultiModal Imaging MacTel Project Report Number 10.

ABSTRACT:

Purpose

To develop a severity classification for macular telangiectasia type 2 (MacTel) disease using multimodal imaging.

Design

An algorithm was used on data from a prospective natural history study of MacTel for classification development.

Subjects

A total of 1733 participants enrolled in an international natural history study of MacTel.

Methods

The Classification and Regression Trees (CART), a predictive nonparametric algorithm used in machine learning, analyzed the features of the multimodal imaging important for the development of a classification, including reading center gradings of the following digital images: stereoscopic color and red-free fundus photographs, fluorescein angiographic images, fundus autofluorescence images, and spectral-domain (SD)-OCT images. Regression models that used least square method created a decision tree using features of the ocular images into different categories of disease severity.

Main outcome measures

The primary target of interest for the algorithm development by CART was the change in best-corrected visual acuity (BCVA) at baseline for the right and left eyes. These analyses using the algorithm were repeated for the BCVA obtained at the last study visit of the natural history study for the right and left eyes.

Results

The CART analyses demonstrated 3 important features from the multimodal imaging for the classification: OCT hyper-reflectivity, pigment, and ellipsoid zone loss. By combining these 3 features (as absent, present, noncentral involvement, and central involvement of the macula), a 7-step scale was created, ranging from excellent to poor visual acuity. At grade 0, 3 features are not present. At the most severe grade, pigment and exudative neovascularization are present. To further validate the classification, using the Generalized Estimating Equation regression models, analyses for the annual relative risk of progression over a period of 5 years for vision loss and for progression along the scale were performed.

Conclusions

This analysis using the data from current imaging modalities in participants followed in the MacTel natural history study informed a classification for MacTel disease severity featuring variables from SD-OCT. This classification is designed to provide better communications to other clinicians, researchers, and patients.

Financial disclosures

Proprietary or commercial disclosure may be found after the references.

SUBMITTER: Chew EY

PROVIDER: S-EPMC9944556 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature

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Publications

Macular Telangiectasia Type 2: A Classification System Using MultiModal Imaging MacTel Project Report Number 10.

Chew Emily Y EY Peto Tunde T Clemons Traci E TE Sallo Ferenc B FB Pauleikhoff Daniel D Leung Irene I Jaffe Glenn J GJ Heeren Tjebo F C TFC Egan Catherine A CA Charbel Issa Peter P Balaskas Konstantinos K Holz Frank G FG Gaudric Alain A Bird Alan C AC Friedlander Martin M

Ophthalmology science 20221208 2

<h4>Purpose</h4>To develop a severity classification for macular telangiectasia type 2 (MacTel) disease using multimodal imaging.<h4>Design</h4>An algorithm was used on data from a prospective natural history study of MacTel for classification development.<h4>Subjects</h4>A total of 1733 participants enrolled in an international natural history study of MacTel.<h4>Methods</h4>The Classification and Regression Trees (CART), a predictive nonparametric algorithm used in machine learning, analyzed t ...[more]

PMID: 36846105

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Project description:PurposeTo report the visual acuity measures from the macular telangiectasia type 2 (MacTel) registry and to investigate and describe phenotypic findings in eyes with substantial vision loss resulting from MacTel.DesignCross-sectional multicenter study.ParticipantsParticipants in the MacTel Natural History Observation Registration Study.MethodsBest-corrected visual acuity (BCVA) data, retinal imaging data, and clinical data were accessed from the MacTel Study databases in May 2019.Main outcome measuresFrequency distribution of BCVA and its relationship to age; morphologic changes in eyes with very late disease stages, defined by a BCVA of 20/200 or worse; average retinal thickness of macular subfields on OCT; and dimensions of the area affected by MacTel (i.e., the MacTel area).ResultsBest-corrected visual acuity was 20/50 or worse in 37.3% and 20/200 or worse in 3.8% of 4449 eyes of 2248 patients; 18.4% and 0.7% of all patients showed bilateral BCVA of 20/50 or worse and 20/200 or worse, respectively. Asymmetry between right and left eyes was present (median BCVA, 71 letters vs. 74 letters), a finding supported by more advanced morphologic changes in right eyes. Participant age correlated with BCVA, but the effect size was small. If a neovascularization or macular hole were present, bilateral occurrence was frequent (33% or 17%, respectively), and BCVA was better than 20/200 (79% or 78%, respectively) or 20/50 or better (26% or 13%, respectively). Eyes with advanced disease (BCVA, ≤20/200) showed the following characteristics: (1) atrophy of the foveal photoreceptor layer with or without associated subretinal fibrosis; (2) an affected area, termed MacTel area, limited to a horizontal diameter not exceeding the distance between the temporal optic disc margin and foveal center, and the vertical diameter not exceeding approximately 0.8 times this distance (exceptions were eyes with large active or inactive neovascular membranes); (3) reduced retinal thickness measures within the MacTel area; and (4) less frequent retinal greying and more frequent hyperpigmentations compared with eyes that have better BCVA.ConclusionsSevere vision loss is rare in MacTel and is related to photoreceptor atrophy in most people. Results indicate disease asymmetry with slightly worse vision and more advanced disease manifestation in right eyes. MacTel-related neurodegeneration does not spread beyond the limits of the MacTel area.

Project description:Macular telangiectasia type 2 is a bilateral disease of unknown cause with characteristic alterations of the macular capillary network and neurosensory atrophy. Its prevalence may be underestimated and has recently been shown to be as high as 0.1% in persons 40 years and older. Biomicroscopy may show reduced retinal transparency, crystalline deposits, mildly ectatic capillaries, blunted venules, retinal pigment plaques, foveal atrophy, and neovascular complexes. Fluorescein angiography shows telangiectatic capillaries predominantly temporal to the foveola in the early phase and a diffuse hyperfluorescence in the late phase. High-resolution optical coherence tomography (OCT) may reveal disruption of the photoreceptor inner segment-outer segment border, hyporeflective cavities at the level of the inner or outer retina, and atrophy of the retina in later stages. Macular telangiectasia type 2 shows a unique depletion of the macular pigment in the central retina and recent therapeutic trials showed that such depleted areas cannot re-accumulate lutein and zeaxanthin after oral supplementation. There have been various therapeutic approaches with limited or no efficacy. Recent clinical trials with compounds that block vascular endothelial growth factor (VEGF) have established the role of VEGF in the pathophysiology of the disease, but have not shown significant efficacy, at least for the non-neovascular disease stages. Recent progress in structure-function correlation may help to develop surrogate outcome measures for future clinical trials. In this review article, we summarize the current knowledge on macular telangiectasia type 2, including the epidemiology, the genetics, the clinical findings, the staging and the differential diagnosis of the disease. Findings using retinal imaging are discussed, including fluorescein angiography, OCT, adaptive optics imaging, confocal scanning laser ophthalmoscopy, and fundus autofluorescence, as are the findings using visual function testing including visual acuity and fundus-controlled microperimetry. We provide an overview of the therapeutic approaches for both non-neovascular and neovascular disease stages and provide a perspective of future directions including animal models and potential therapeutic approaches.

Dataset Information

Macular Telangiectasia Type 2: A Classification System Using MultiModal Imaging MacTel Project Report Number 10.

Purpose

Design

Subjects

Methods

Main outcome measures

Results

Conclusions

Financial disclosures

Publications

Macular Telangiectasia Type 2: A Classification System Using MultiModal Imaging MacTel Project Report Number 10.

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