A personalized medical approach can make diabetic retinopathy treatment more effective. To select effective methods of treatment, deep analysis and diagnostic data of a patient’s fundus are required. For this purpose, flat optical coherence tomography images are used to restore the three-dimensional structure of the fundus. Heat propagation through this structure is simulated via numerical methods. The article proposes algorithms for smooth segmentation of the retina for 3D model reconstruction and mathematical modeling of laser exposure while considering various parameters. The experiment was based on a two-fold improvement in the number of intervals and the calculation of the root mean square deviation between the modeled temperature values and the corresponding coordinates shown for the convergence of the integro-interpolation method (balance method). By doubling the number of intervals for a specific spatial or temporal coordinate, a decrease in the root mean square deviation takes place between the simulated temperature values by a factor of 1.7–5.9. This modeling allows us to estimate the basic parameters required for the actual practice of diabetic retinopathy treatment while optimizing for efficiency and safety. Mathematical modeling is used to estimate retina heating caused by the spread of heat from the vascular layer, where the temperature rose to 45 °C in 0.2 ms. It was identified that the formation of two coagulates is possible when they are located at least 180 μm from each other. Moreover, the distance can be reduced to 160 μm with a 15 ms delay between imaging.
Aim: to compare the uniformity and adequacy of the placement of laser spots after mono-impulse and pattern photocoagulation for diabetic macular edema (DME). Patients and Methods: fundus photographs of 83 patients (121 eyes) taken right after retinal photocoagulation for DME were analyzed. Group 1 included images of 63 eyes after pattern photocoagulation and group 2 included images of 58 eyes after mono-impulse photocoagulation. Laser burns of varying intensity based on LʹEsperance scale (including grade 0 burns that were not seen on fundus photos) were calculated. Grade 2 burns were considered optimal. The number of non-optimal laser burns placed on retinal hemorrhages, blood vessels, hard exudates or healthy retina was calculated. The uniformity of the position of laser spots was assessed by calculating the standard deviation from the average distance between laser spots. Results: the percentage of laser spots of optimal intensity was 31.85% in group 1 and 25.15% in group 2. The percentage of non-optimally placed laser spots was 24.34% in group 1 and 7.99% in group 2. The uniformity of the placement was good in both groups (8.16 pixels and 8.44 pixels, respectively), no significant difference was reported (p=0.0591). Conclusion: pattern photocoagulation is preferable for DME compared to mono-impulse photocoagulation to provide adequate intensity of laser burns. Meanwhile, mono-impulse regimen provides more precise placement of laser spots. However, both conventional techniques are not effective enough due many intrinsic drawback, i.e., many laser spots are non-optimal in terms of intensity or placement. In routine practice, these drawbacks are outweighed by the skills and experience of laser surgeon. Planned precise placement of laser spots and the introduction of techniques of more precise preventive adjustment of energy level for each laser spot will contribute to the maximum effect of photocoagulation for DME. Further studies on personalized precise laser photocoagulation will improve the quality and efficacy of the treatment of macular edema. Keywords: diabetic retinopathy, diabetic macular edema, mono-impulse photocoagulation, pattern photocoagulation, navigated photocoagulation. For citation: Zamytskiy E.A., Zolotarev A.V., Karlova E.V. et al. Comparative quantitative assessment of the placement and intensity of laser spots for treating diabetic macular edema. Russian Journal of Clinical Ophthalmology. 2021;21(2):58–62. DOI: 10.32364/2311-7729- 2021-21-2-58-62.
The paper proposes a method for selection the region of diabetic macular edema in fundus images using OCT data. The relevance of the work is due to the need to create support systems for laser coagulation to increase its effectiveness. The proposed algorithm is based on a set of image segmentation methods, as well as searching for specific points and compiling their descriptors. The Canny method is used to find the boundary between the vitreous body and the retina in OCT images. The segmentation method, based on the Kruskal algorithm for constructing the minimum spanning tree of a weighted connected undirected graph, is used to select the retina to the pigment layer in the image. Using the results of segmentation, a map of the thickness of the retina of the eye and its deviation from the norm were constructed. In the course of the research, the optimal parameter values were selected in the Canny and graph segmentation algorithms, which allow to achieve a segmentation error of 5 %. SIFT, SURF, and AKAZE methods were considered for super-imposing calculated maps of the retina thickness and its deviation from the norm on the fundus image. In cases where a picture from the fundus camera of the OCT apparatus is provided along with OCT data, using the SURF method, it is possible to accurately combine with the fundus image.
Diabetic retinopathy is among the most severe complications of diabetes, most often leading to rapid and irreversible vision loss. The laser coagulation procedure, which consists of applying microburns to the fundus, has proven to be an effective method for treating diabetic retinopathy. Unfortunately, modern research does not pay enough attention to the study of the arrangement of microburns in the edema area—one of the key factors affecting the quality of therapy. The aim of this study was to propose a computational decision-making support system for retina laser photocoagulation based on the analysis of photocoagulation plans. Firstly, we investigated a set of prognostic factors based on 29 features describing the geometric arrangement of coagulates. Secondly, we designed a technology for the intelligent analysis of the photocoagulation plan that allows the effectiveness of the treatment to be predicted. The studies were carried out using a large database of fundus images from 108 patients collected in clinical trials. The results demonstrated a high classification accuracy at a level of over 85% using the proposed prognostic factors. Moreover, the designed technology proved the superiority of the proposed algorithms for the automatic arrangement of coagulates, predicting a 99% chance of a positive therapeutic effect.
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