Retinal Vascular Features Offer Non-Invasive Tool for Early Prediction of Premature Ovarian Insufficiency

Premature Ovarian Insufficiency (POI) is a condition in which a woman's ovaries stop functioning before the age of 40, leading to infertility and hormonal imbalances. Early diagnosis of POI is crucial for timely intervention and management. A novel study conducted at the Affiliated Shenzhen Maternity & Child Healthcare Hospital aimed to establish a non-invasive clinical diagnosis model using retinal vascular features to accurately predict the risk of POI as published in BMC Journal Of Ovarian Research by Jiaman Wu and colleagues.

The study included 78 women with spontaneous POI and 48 healthy women. Automated retinal image analysis was performed to analyze retinal characteristics in both groups. Binary logistic regression was used to identify POI cases and develop predictive models.

● The findings revealed significant differences in retinal vascular features between the POI group and the healthy control group.

● Women with POI exhibited larger central retinal artery equivalent (CRAE) (POI: 160.3 ± 15.7 μm, Control: 155.1 ± 14.4 μm, P = 0.006) and central retinal vein equivalent (CRVE) (POI: 222.6 ± 18.2 μm, Control: 213.7 ± 19.5 μm, P = 0.001).

● They had increased index of venules asymmetry (Vasym) (POI: 0.12 ± 0.07, Control: -0.04 ± 0.10, P < 0.001), arterioles bifurcation angles (Aangle) (POI: 76.9 ± 8.6 degrees, Control: 72.4 ± 8.5 degrees, P = 0.001), and venule bifurcation coefficient (BCV) (POI: 0.53 ± 0.10, Control: 0.46 ± 0.11, P = 0.001).

● Arteriovenous nipping (Nipping) was more pronounced in the POI group (POI: 0.15 ± 0.08, Control: 0.11 ± 0.07, P = 0.005), while the arteriole-to-venule ratio (AVR) was lower (POI: 0.78 ± 0.07, Control: 0.82 ± 0.06, P = 0.012).

● The odds ratio (OR) for Vasym was 6.72e-32 (95% C.I. 4.62e-49–9.79e-15, P < 0.001), for BCV was 5.66e-20 (95% C.I. 1.93e-34–.0000, P < 0.001), and for Nipping was 6.65e-06 (95% C.I. 6.33e-10–.0698, P = 0.012).

● The area under the ROC curve for the binary logistic regression with retinal characteristics was 0.8582, indicating a high level of accuracy in predicting POI risk. The fitting degree of regression models was 60.48%, suggesting that retinal image analysis may be a valuable tool for POI identification.

The study demonstrates that retinal image analysis offers valuable information for identifying and predicting POI. Specific retinal vascular features were found to be associated with POI, providing a non-invasive approach for early clinical diagnosis. Early detection of POI can lead to timely intervention and improved management of this condition. The findings of this study contribute to the growing field of non-invasive diagnostic tools for reproductive health disorders.

Reference:

Wu, J., Tan, L., Ning, Y., Yuan, W., Lee, Z., Ma, F., Wang, E., & Zhuo, Y. (2023). Characteristics of retinal image associated with premature ovarian insufficiency: a case control study. Journal of Ovarian Research, 16(1). BMC Journal Of Ovarian Research https://doi.org/10.1186/s13048-023-01231-0