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. 2024 Sep-Oct;52(7):774-782.
doi: 10.1111/ceo.14405. Epub 2024 May 30.

Clinical performance of predicting late age-related macular degeneration development using multimodal imaging

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Clinical performance of predicting late age-related macular degeneration development using multimodal imaging

Kai Lyn Goh et al. Clin Exp Ophthalmol. 2024 Sep-Oct.

Abstract

Background: To examine whether the clinical performance of predicting late age-related macular degeneration (AMD) development is improved through using multimodal imaging (MMI) compared to using colour fundus photography (CFP) alone, and how this compares with a basic prediction model using well-established AMD risk factors.

Methods: Individuals with AMD in this study underwent MMI, including optical coherence tomography (OCT), fundus autofluorescence, near-infrared reflectance and CFP at baseline, and then at 6-monthly intervals for 3-years to determine MMI-defined late AMD development. Four retinal specialists independently assessed the likelihood that each eye at baseline would progress to MMI-defined late AMD over 3-years with CFP, and then with MMI. Predictive performance with CFP and MMI were compared to each other, and to a basic prediction model using age, presence of pigmentary abnormalities, and OCT-based drusen volume.

Results: The predictive performance of the clinicians using CFP [AUC = 0.75; 95% confidence interval (CI) = 0.68-0.82] improved when using MMI (AUC = 0.79; 95% CI = 0.72-0.85; p = 0.034). However, a basic prediction model outperformed clinicians using either CFP or MMI (AUC = 0.85; 95% CI = 0.78-91; p ≤ 0.002).

Conclusions: Clinical performance for predicting late AMD development was improved by using MMI compared to CFP. However, a basic prediction model using well-established AMD risk factors outperformed retinal specialists, suggesting that such a model could further improve personalised counselling and monitoring of individuals with the early stages of AMD in clinical practice.

Keywords: age‐related macular degeneration; colour fundus photography; multimodal imaging; optical coherence tomography.

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References

REFERENCES

    1. Ferris FL 3rd, Wilkinson CP, Bird A, et al. Clinical classification of age‐related macular degeneration. Ophthalmology. 2013;120(4):844‐851.
    1. Ferris FL, Davis MD, Clemons TE, et al. A simplified severity scale for age‐related macular degeneration: AREDS report no. 18. Arch Ophthalmol. 2005;123(11):1570‐1574.
    1. Thee EF, Meester‐Smoor MA, Luttikhuizen DT, et al. Performance of classification systems for age‐related macular degeneration in the Rotterdam study. Transl Vis Sci Technol. 2020;9(2):26.
    1. Guymer R, Wu Z. Age‐related macular degeneration (AMD): more than meets the eye. The role of multimodal imaging in today's management of AMD‐A review. Clin Exp Ophthalmol. 2020;48(7):983‐995.
    1. Garrity ST, Sarraf D, Freund KB, Sadda SR. Multimodal imaging of nonneovascular age‐related macular degeneration. Invest Ophthalmol Vis Sci. 2018;59(4):AMD48‐AMD64.

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