Quantitative analysis of retinopathy in type 2 diabetes: identification of prognostic parameters for developing visual loss secondary to diabetic maculopathy

Abstract

ABSTRACT.Purpose: To describe whether quantitative assessment of early changes in the morphology of retinopathy lesions can predict development of vision-threatening diabetic maculopathy. Methods: We used a nested case-control study, and we studied 11 type 2 diabetes patients who had developed visual loss secondary to diabetic maculopathy. For each diabetes patient, we also studied three matched control patients who had been followed for a comparable period of time without developing visual loss. Fundus photographs describing the early development of retinopathy were digitized and subjected to a full manual quantitative grading on a computer monitor. Differences in the early development of retinal morphology were compared between the two groups. The outcome parameters were changes in the number and area of haemorrhages and exudates in different regions of the fundus, and the weighted distance of these lesions from the fovea and the optic disc. Results: In patients who developed visual loss secondary to diabetic maculopathy there was significant early progression in the total area and number of haemorrhages and exudates. The haemorrhages had progressed in all retinal areas except the area around the optic disc and the temporal vascular arcades. The exudates had progressed temporally from the fovea and in the retinal periphery. Conclusions:The results suggest that a quantitative description of the regional development of early diabetic retinopathy may help in identifying patients who will later develop vision-threatening maculopathy.

Lack of differences in the regional variation of oxygen saturation in larger retinal vessels in diabetic maculopathy and proliferative diabetic retinopathy

“…The lesions display a regional distribution that in the early stages of the disease reflects underlying risk factors and can predict the progression of the disease 4 5. In the late stages of the disease the two vision threatening complications diabetic maculopathy (DM) and proliferative diabetic retinopathy (PDR) can be distinguished by differences in the distribution and type of lesions 3 6.…”

The role of retinopathy distribution and other lesion types for the definition of examination intervals during screening for diabetic retinopathy

“…In a previously developed decision model, it was found that with a consideration of risk factors such as sex, age, age of onset of diabetes mellitus, HgbA1c and blood pressure, the average control interval could be prolonged 2.8 times for patients with type 1 diabetes and 1.2 times for patients with type 2 diabetes without losing a patient with visionthreatening changes (Mehlsen et al 2012). It was concluded that this limitation might be due to factors unrelated to diabetic retinopathy or the location of lesions, which has been shown to be an independent risk factor for progression of the disease to a treatment-requiring stage (Hove et al 2004(Hove et al , 2006, but which was not included in the model. It was concluded that this limitation might be due to factors unrelated to diabetic retinopathy or the location of lesions, which has been shown to be an independent risk factor for progression of the disease to a treatment-requiring stage (Hove et al 2004(Hove et al , 2006, but which was not included in the model.…”

“…A second software tool was created to allow the marking of two circles around the fovea (C1 and C2) and three ellipses (E1, E2 and E3) delimiting areas with known accumulation of DR lesions (Hove et al 2004), and to save these markings in a separate file associated with each fundus photograph. The first author marked the four types of lesions manually, that is dot haemorrhages/ microaneurysms (DH/MA) with a diameter smaller than the diameter of the temporal venules at the crossing of the OD, large haemorrhages (all other haemorrhages), hard exudates and cotton wool spots.…”

“…However, this rule-based approach also implies that patients with slow disease progression will undergo a number of superfluous examinations with no consequences for the management of the disease. The predictive value of this model was found to be lowest for patients with more severe retinopathy, and it was concluded that the grader might have included other factors than the severity of retinopathy in the decision, such as the location of retinopathy lesions or conditions unrelated to diabetic retinopathy (Bek & Helgesen 2001;Hove et al 2004Hove et al , 2006. A newly developed decision model considering risk factors such as sex, age at onset of diabetes mellitus, diabetes type, diabetes duration, HbA1c and blood pressure can allow a significant prolongation of the control interval without increasing the risk of developing vision-threatening retinopathy (Mehlsen et al 2012).…”

Adaptive Neuro-Fuzzy Inference System Approach for the Automatic Screening of Diabetic Retinopathy in Fundus Images

“…In the proposed approach, automatic exudates detection is presented in order to detect and treat DR in an early stage using fundus images. Screening of diabetic patients for the development of diabetic retinopathy can potentially reduce the risk of blindness in these patients by 50% (Ege et al, 2000;Hove et al, 2004;Hsu et al, 2001). A novel approach utilizing Shannon entropy other than the evaluation of derivates of the image is used in detecting edges in gray level images (Singh and Singh, 2008).…”