Near-infrared reflectance imaging of neovascularization in proliferative diabetic retinopathy

Investigating the Utility of Near-Infrared Reflectance Imaging for Diabetic Retinopathy Screening

BACKGROUND AND OBJECTIVE

We investigated the reliability of near-infrared reflectance (NIR) imaging as a method of assessing severity of diabetic retinopathy (DR).

PATIENTS AND METHODS

One hundred ninety-five NIR images were reviewed by two graders for the number of hyporeflective foci, presence or absence of vascular abnormalities, and presumptive DR stage; these were correlated to fundus photography-defined DR stage. Interrater reliability was confirmed via one-way random effects model of intraclass correlation coefficients. Analysis of variance was used in subgroup analysis, receiver operating characteristic (ROC) curves were created to validate reliability of the model, and logistic regression was used to model foci and vascular abnormalities as predictors for moderate or worse disease.

RESULTS

A statistically significant difference in mean number of hyporeflective foci was found between no DR and moderate non-proliferative DR (NPDR; P < 0.0001), no DR and severe NPDR (P < 0.001), no DR and proliferative DR (PDR; P < 0.0001), mild and moderate NPDR (P = 0.008), mild and severe NPDR (P < 0.001), and mild NPDR and PDR (P < 0.001). The area under the ROC curve was 0.849 (CI: 0.792 to 0.905). The threshold for detection of moderate NPDR or worse was 4.75 foci, with a sensitivity of 79.0% and a false positive rate of 20.0%. Multivariate logistic regression model incorporating hyporeflective foci with vascular abnormalities (odds ratio [OR] = 1.592, 95% CI: 1.381 to 1.835; P < 0.001) was able to accurately predict moderate disease or worse, just moderate disease (OR = 1.045, 95% CI: 1.003 to 1.089; P = 0.035), severe disease (OR = 1.050, 95% CI: 1.006 to 1.096; P = 0.027), and proliferative disease (OR = 1.050, 95% CI: 1.008 to 1.095; P = 0.018).

CONCLUSIONS

NIR imaging may be an adjunct tool in screening for DR. [Ophthalmic Surg Lasers Imaging Retina 2024;55:318-325.].

An Optical Coherence Tomography-Based Measure as an Independent Estimate of Retinal Function in Retinitis Pigmentosa

BACKGROUND

With the clinical advances in the field of gene therapy, the development of objective measures of visual function of patients with inherited retinal dystrophies (IRDs) is of utmost importance. Here, we propose one such measure.

METHODS

We retrospectively analyzed data from a cohort of 194 eyes of 97 genetically diagnosed patients with retinitis pigmentosa (RP), the most common IRD, followed at the UPMC Vision Institute. The analyzed data included the reflectivity ratio (RR) of the retinal nerve fiber layer (RNFL) to that of the entire retina, visual acuity (VA) and the thickness of the retinal outer nuclear layer (ONL) and the RNFL.

RESULTS

There was a strong positive correlation between the RR and VA. Both VA and the RR were negatively correlated with disease duration; VA, but not the RR, was negatively correlated with age. The RR correlated with the ONL but not with the RNFL thickness or the intraocular pressure. Age, RR, disease duration and ONL thickness were found to be independent predictors of VA by multivariate analysis.

CONCLUSION

The OCT RR could serve as an independent predictor of visual acuity, and by extension of retinal function, in genetically diagnosed RP patients. Such objective measures can be of great value in patient selection for therapeutic trials.

Hyperreflective Vasculature: A Negative Prognostic Sign for Retinal Vein Occlusion on Near-Infrared Reflectance Imaging

BACKGROUND AND OBJECTIVE

To investigate the clinical significance of hyperreflective vasculature visualized on near-infrared reflectance (NIR) in patients with retinal vein occlusion (RVO).

METHODS

In this retrospective study, RVO patients with NIR imaging and at least 1-year follow-up, and without confounding disease, were included. Two blinded independent graders identified vascular hyperreflectivity (HR) by detection of whiter signals in vessels. Visual acuity (VA), macular thickness (MT), and number of administered anti-vascular endothelial growth factor (anti-VEGF) injections were assessed.

RESULTS

RVO patients with HR (n = 20) and without HR (n = 31) demonstrated similarity in age, sex, and class of RVO. At presentation, the HR group had higher MT (P = 0.002) but no difference in VA (P = 0.1018). At 1 year, patients with HR had worse VA (P = 0.001), decreased MT (P = 0.011), and received more anti-VEGF injections (P < 0.001).

CONCLUSION

RVO patients with HR on NIR had significantly worse visual outcomes. Vascular HR on NIR imaging may be a biomarker, portending worse visual prognoses in RVO. [Ophthalmic Surg Lasers Imaging Retina 2023;54:266-270.].

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.

Current status and future possibilities of retinal imaging in diabetic retinopathy care applicable to low- and medium-income countries

Diabetic retinopathy (DR) is a leading cause of blindness among adults and the numbers are projected to rise. There have been dramatic advances in the field of retinal imaging since the first fundus image was captured by Jackman and Webster in 1886. The currently available imaging modalities in the management of DR include fundus photography, fluorescein angiography, autofluorescence imaging, optical coherence tomography, optical coherence tomography angiography, and near-infrared reflectance imaging. These images are obtained using traditional fundus cameras, widefield fundus cameras, handheld fundus cameras, or smartphone-based fundus cameras. Fluorescence lifetime ophthalmoscopy, adaptive optics, multispectral and hyperspectral imaging, and multicolor imaging are the evolving technologies which are being researched for their potential applications in DR. Telemedicine has gained popularity in recent years as remote screening of DR has been made possible. Retinal imaging technologies integrated with artificial intelligence/deep-learning algorithms will likely be the way forward in the screening and grading of DR. We provide an overview of the current and upcoming imaging modalities which are relevant to the management of DR.