Artificial intelligence (AI) is gradually changing medical practice. With recent progress in digitized data acquisition, machine learning and computing infrastructure, AI applications are expanding into areas that were previously thought to be only the province of human experts. In this Review Article, we outline recent breakthroughs in AI technologies and their biomedical applications, identify the challenges for further progress in medical AI systems, and summarize the economic, legal and social implications of AI in healthcare.

Artificial Intelligence in Healthcare

Optical coherence tomography angiography: A comprehensive review of current methods and clinical applications.

Artificial intelligence in retina.

https://ecommons.aku.edu/cgi/viewcontent.cgi?article=1181&context=eastafrica_fhs_mc_paediatr_child_health

Diabetes in sub-Saharan Africa: from clinical care to health policy

The formation and accumulation of methylglyoxal (MGO), a highly reactive dicarbonyl compound, has been implicated in the pathogenesis of type 2 diabetes, vascular complications of diabetes, and sev...

https://journals.physiology.org/doi/pdf/10.1152/physrev.00001.2019

Methylglyoxal, a highly reactive dicarbonyl compound, in diabetes, its vascular complications and other age-related diseases

Diabetic retinopathy (DR) is a leading cause of vision-loss globally. Of an estimated 285 million people with diabetes mellitus worldwide, approximately one third have signs of DR and of these, a further one third of DR is vision-threatening DR, including diabetic macular edema (DME). The identification of established modifiable risk factors for DR such as hyperglycemia and hypertension has provided the basis for risk factor control in preventing onset and progression of DR. Additional research investigating novel risk factors has improved our understanding of multiple biological pathways involved in the pathogenesis of DR and DME, especially those involved in inflammation and oxidative stress. Variations in DR prevalence between populations have also sparked interest in genetic studies to identify loci associated with disease susceptibility. In this review, major trends in the prevalence, incidence, progression and regression of DR and DME are explored, and gaps in literature identified. Established and novel risk factors are also extensively reviewed with a focus on landmark studies and updates from the recent literature.

/pdf/epidemiology-of-diabetic-retinopathy-diabetic-macular-edema-16vzgjcxp4.pdf

Epidemiology of diabetic retinopathy, diabetic macular edema and related vision loss

Incidence and progression of diabetic retinopathy: a systematic review.

Non-recirculating resident memory (TRM) and recirculating T cells mount vigorous immune responses to both self and foreign antigens in barrier tissues like the skin, lung and gastrointestinal tract. Using impression cytology followed by flow cytometry we identified two TRM subsets and four recirculating T-subsets in the healthy human ocular surface. In dry eye disease, principal component analysis (PCA) revealed two clusters of patients with distinct T-cell signatures. Increased conjunctival central memory and naive T cells characterized Cluster-1 patients, and increased CD8+ TRMs and CD4+ recirculating memory T cells characterized Cluster-2 patients. Interestingly these T-cell signatures are associated with different clinical features: the first signature correlated with increased ocular redness, and the second with reduced tear break up times. These findings open the door to immune-based characterization of dry eye disease and T-subset specific immunotherapies to suppress T-subsets involved in disease. They may also help with patient stratification during clinical trials of immunomodulators.

/pdf/tissue-resident-memory-t-cells-in-the-human-conjunctiva-and-2219d6w5ve.pdf

Tissue resident memory T cells in the human conjunctiva and immune signatures in human dry eye disease.

Background It is difficult to standardize assessment of dry eye in different clinical settings. Increasingly, tear stability is recognized to be important for the definition and assessment of patients with dry eye. Recently, two commercially available instruments have been made available for objectively measuring noninvasive tear break-up time (NIBUT), as an indicator of tear stability: the Tomey RT-7000 Auto Refractor-Keratometer and Oculus Keratograph (K)5M. We aim to assess the agreement of NIBUT measurements using these modalities. Methods This prospective cross-sectional study was carried out in a tertiary referral eye center and involved 126 consecutive dry eye patients. NIBUT assessment was performed on the right eyes of participants with both the RT-7000 and the K5M techniques, with the order of assessment randomized. The Standardized Patient Evaluation of Eye Dryness (SPEED) questionnaires were administered to assess dry eye symptoms in the 2 weeks before assessment. Results The age of the participants was 56.0±14.3 years (69.84% females). Measurements for both modalities were non-normally distributed (right-skewed). The median RT-7000 and K5M readings were 4.2 (range 0.1-10.0) and 6.4 (0.1-24.9) seconds, respectively. RT-7000 and K5M readings were poorly correlated (ρ=0.061, P=0.495). Intraclass correlation coefficient between the modalities was 0.187 (95% confidence interval -0.097 to 0.406). The Bland-Altman plot showed no systematic differences between the readings with these machines. The agreement between machines was not different in different SPEED categories. Conclusion While there are theoretical and practical benefits of NIBUT for assessment of tear stability over dye-based methods, the agreement between the two modalities was poor. Hence, studies and trials assessing NIBUT should avoid using these modalities interchangeably for NIBUT assessment. More research is needed to improve consensus on how to determine NIBUT.

/pdf/agreement-of-non-invasive-tear-break-up-time-measurement-1hbqf9pk7l.pdf

Agreement of non-invasive tear break up time measurement between Tomey RT-7000 Auto Refractor-Keratometer and Oculus Keratograph 5M

Purpose
To identify ocular factors that affect signal strength in spectral-domain optical coherence tomography (SD-OCT).

Methods
Data from 1312 participants of the population-based Singapore Malay Eye Study-2 (SiMES-2) were included in the analysis. All participants underwent standardized ophthalmic examination, including measurements of best-corrected visual acuity (BCVA), refractive error, axial length, corneal curvature and presence of cataracts. Optic disc and macular cube scans were acquired using the Cirrus HD-OCT (software version 6.0, Carl Zeiss Meditec, Dublin, CA, USA). Signal strength of the optical coherence tomography (OCT) scan was recorded for each study eye. Multivariable linear regression analyses were performed to evaluate the associations between ocular factors and signal strength of the OCT scans.

Results
: The mean (±SD) age of our study participants was 61 ± 9 years, and 44.6% were male. Mean optic disc scan signal strength was 7.90 ± 1.25, range = 0–10, while mean macular scan signal strength was 8.80 ± 1.27, range = 0–10. In multivariable regression analyses, poorer signal strength in optic disc and macular cube scans was each associated with older age (per decade, β = −0.373, p < 0.001; β = −0.373, p < 0.001, respectively), poorer BCVA (per logMAR line; β = −0.123, p < 0.001; β = −0.156, p < 0.001, respectively), greater degree of myopia (per negative dioptre of spherical equivalent; β = −0.112, p < 0.001; β = −0.117, p < 0.001, respectively), presence of cortical cataracts (β = −0.331, p < 0.001; β = −0.314, p < 0.001, respectively) and presence of posterior subcapsular cataracts (β = −0.910, p < 0.001; β = −0.797, p < 0.001, respectively).

Conclusion
We found that older age, poorer BCVA, greater degree of myopia and presence of cortical and posterior subcapsular cataracts were associated with reduced signal strength in Cirrus SD-OCT. Our findings provide information on the barriers to obtaining good image quality when using SD-OCT, and allow clinicians to potentially identify individuals who are more likely to have unreliable OCT measurements.

https://onlinelibrary.wiley.com/doi/pdf/10.1111/aos.13443

Ryan Lee

Papers

Epidemiology of diabetic retinopathy, diabetic macular edema and related vision loss

Incidence and progression of diabetic retinopathy: a systematic review.

Tissue resident memory T cells in the human conjunctiva and immune signatures in human dry eye disease.

Agreement of non-invasive tear break up time measurement between Tomey RT-7000 Auto Refractor-Keratometer and Oculus Keratograph 5M

Factors affecting signal strength in spectral-domain optical coherence tomography.