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January 21, 2022
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Expert provides update on latest in retinal imaging

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WAIKOLOA, Hawaii — Recent advances in imaging technologies and automated image analysis are bringing about a new era in retinal diagnostics and treatment decision-making.

“We are in the midst of a golden era of retinal imaging and can expect dramatic advancements that will completely transform ophthalmology over the next few years,” SriniVas Sadda, MD, said at Retina 2022.

Devices continue to be created and continuously expand the imaging tool kit available to care for patients. In his presentation, Sadda focused on a few that are nearly ready for prime time.

SriniVas Sadda

Retromode imaging uses retroillumination to provide additional contrast and enhance detection of subtle abnormalities in the retina, highlighting patients at a higher risk for progression to advanced disease.

Hyperspectral imaging captures information from multiple spectral bands across the electromagnetic spectrum, supporting the identification of specific biomarkers of retinal diseases.

Fluorescence lifetime imaging ophthalmoscopy quantifies the decay time of fluorescence signals. Sadda was the lead author of a pilot study in which fluorescence lifetime imaging ophthalmoscopy was used to detect retinal changes occurring in patients with Alzheimer’s disease from the early preclinical stages.

“Ophthalmologists are called upon to be more involved in this kind of systemic diagnosis since we have access to these imaging tools,” he said.

Widefield OCT allows visualization of smaller targeted regions in the peripheral retina. A study showed that 86 of 125 eyes had peripheral-only pathologies. In 86% of them, the addition of peripheral OCT affected clinical decision-making.

Finally, Sadda spoke about artificial intelligence in retinal image analysis. FDA-cleared technologies such as the IDx-DR (Digital Diagnostics) and EyeArt (Eyenuk) have shown good sensitivity and specificity and have potential for screening programs, telemedicine and home monitoring of retinal diseases. A machine learning algorithm paired with the Notal Home OCT system (Notal Vision) showed the ability to perform automated analysis of retinal changes, detect fluid and automatically generate reports for the treating physician. In a cohort of more than 300 patients, sensitivity and specificity were 97% and 95%, respectively.

References:

  • Keenan TDL, et al. Ophthalmology. 2021;doi:10.1016/j.ophtha.2020.06.038.
  • Sadda SR, et al. Eye (Lond). 2019;doi:10.1038/s41433-019-0406-2.
  • Sodhi SK, et al. Int Ophthalmol. 2021;doi:10.1007/s10792-021-01837-7.