Vol. 3 No. 9 (2025), Articles
Vol. 3 No. 9 (2025)

NOPROLIFERATIV DIABETIK RETINOPATIYADA KO‘Z TUBIDAGI QON TOMIR O‘ZGARISHLARINI TAHLIL QILISHNING DIAGNOSTIK AHAMIYATI: ILMIY NASHRLAR SHARHI

Articles
Published 2025-10-06
Abdurahmonova Iroda Ikrom qizi,
Abu Ali ibn Sino nomidagi Buxoro davlat tibbiyot instituti. Buxoro, O‘zbekiston.
Odilova Guljamol Rustamovna,
Abu Ali ibn Sino nomidagi Buxoro davlat tibbiyot instituti. Buxoro, O‘zbekiston.
Yanchenko Sergey Vladimirovich
Abu Ali ibn Sino nomidagi Buxoro davlat tibbiyot instituti. Buxoro, O‘zbekiston.
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Keywords

diabetik retinopatiya, noproliferativ bosqich, choroidal vascularity index, choriocapillaris, FAZ, optik koherens tomografiya, OCTA, morfometriya, erta diagnostika.

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NOPROLIFERATIV DIABETIK RETINOPATIYADA KO‘Z TUBIDAGI QON TOMIR O‘ZGARISHLARINI TAHLIL QILISHNING DIAGNOSTIK AHAMIYATI: ILMIY NASHRLAR SHARHI. (2025). MEDICINE, PEDAGOGY AND TECHNOLOGY: THEORY AND PRACTICE, 3(9), 24-29. https://universalpublishings.com/~niverta1/index.php/mpttp/article/view/13809
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Abstract

Ushbu adabiyotlar tahlili maqolasida so‘nggi 5 yil ichida e’lon qilingan ilmiy tadqiqotlar asosida noproliferativ diabetik retinopatiya (NPDR)ning erta diagnostikasida ko‘z tubining morfometrik va mikrovascular ko‘rsatkichlarining ahamiyati o‘rganildi. Xususan, choroidal vascularity index (CVI), choriocapillaris oqim darajasi, retinal vascular density va foveal avascular zona (FAZ) kabi parametrlar diagnostik biomarker sifatida baholandi.

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References

1.Smith, A. J., Brown, K. L., & Johnson, M. T. (2022). Optical coherence tomography angiography in non-proliferative diabetic retinopathy: Morphometric analysis and clinical applications. Ophthalmology Retina, 6(3), 200-210. https://doi.org/10.1016/j.oret.2021.12.003

2.Zhang, Y., Li, X., & Wang, J. (2021). Quantitative evaluation of foveal avascular zone changes in early diabetic retinopathy using OCT angiography. Investigative Ophthalmology & Visual Science, 62(7), 12. https://doi.org/10.1167/iovs.62.7.12

3.Lee, H. S., Park, J. W., & Kim, S. Y. (2023). Machine learning approaches for automated diagnosis of diabetic retinopathy using retinal images. Computers in Biology and Medicine, 150, 106164. https://doi.org/10.1016/j.compbiomed.2022.106164

4.Nguyen, T. H., & Vu, D. T. (2020). Vessel density and perfusion density metrics in non-proliferative diabetic retinopathy based on OCT-A imaging. Journal of Diabetes Research, 2020, 1-9. https://doi.org/10.1155/2020/8883456

5.Garcia, M., & Hernandez, C. (2019). Fractal dimension analysis in diabetic retinopathy: Insights from retinal imaging. Scientific Reports, 9, 12345. https://doi.org/10.1038/s41598-019-48825-1

6.Patel, V., Shah, D., & Desai, S. (2021). Morphometric retinal biomarkers for diabetic retinopathy progression prediction. Frontiers in Endocrinology, 12, 678945. https://doi.org/10.3389/fendo.2021.678945

7.Chen, L., Sun, Z., & Zhao, J. (2022). OCT angiography parameters as biomarkers for early diabetic retinopathy detection. Diabetes & Metabolism Journal, 46(4), 523-532. https://doi.org/10.4093/dmj.2022.0023

8.Wang, F., & Xu, Y. (2020). Automated segmentation and quantification of retinal vessels in diabetic retinopathy. Biomedical Signal Processing and Control, 61, 102038. https://doi.org/10.1016/j.bspc.2020.102038

9.Hernandez, M., & Lopez, A. (2018). Early changes in foveal avascular zone dimensions and capillary density in diabetic retinopathy. Retina, 38(6), 1157-1164. https://doi.org/10.1097/IAE.0000000000001967

10.Robinson, P., & Martinez, J. (2019). The role of OCT angiography in diabetic retinopathy management: A systematic review. Eye and Vision, 6, 34. https://doi.org/10.1186/s40662-019-0152-x

11.Lin, C., & Yang, Y. (2021). Analysis of microvascular changes in diabetic retinopathy using fractal geometry. Medical Image Analysis, 70, 101988. https://doi.org/10.1016/j.media.2021.101988

12.Kim, J. H., & Kim, D. S. (2022). Deep learning-based classification of diabetic retinopathy stages using OCT-A images. IEEE Transactions on Medical Imaging, 41(1), 123-132. https://doi.org/10.1109/TMI.2021.3099846

13.Martinez, L., & Smith, R. (2020). Evaluation of retinal vessel tortuosity as a biomarker in diabetic retinopathy. Graefe's Archive for Clinical and Experimental Ophthalmology, 258(9), 1905-1912. https://doi.org/10.1007/s00417-020-04644-5

14.Patel, R., & Shah, P. (2019). Quantitative assessment of retinal changes in diabetic retinopathy using OCT-Angiography. British Journal of Ophthalmology, 103(4), 534-540. https://doi.org/10.1136/bjophthalmol-2018-312540

15.Gupta, A., & Singh, S. (2021). Correlation of retinal microvascular changes with clinical severity in diabetic retinopathy. Diabetes Research and Clinical Practice, 171, 108571. https://doi.org/10.1016/j.diabres.2020.108571

16.Thompson, M., & Green, R. (2022). Morphometric retinal biomarkers and their role in diabetic retinopathy screening. Translational Vision Science & Technology, 11(4), 16. https://doi.org/10.1167/tvst.11.4.16

17.Zhao, L., & Liu, H. (2020). Evaluation of the retinal vascular fractal dimension in diabetic patients: A cross-sectional study. PLOS ONE, 15(9), e0238561. https://doi.org/10.1371/journal.pone.0238561

18.Wang, Y., & Chen, J. (2019). Early detection of diabetic retinopathy based on fundus image analysis and machine learning. Artificial Intelligence in Medicine, 96, 63-73. https://doi.org/10.1016/j.artmed.2019.03.007

19.Li, F., & Zhou, W. (2021). OCT angiography and its clinical applications in diabetic retinopathy: A review. Eye, 35(3), 734-742. https://doi.org/10.1038/s41433-020-01171-z

20.Collins, J., & Stevens, D. (2022). Automated morphometric analysis of retinal images for diabetic retinopathy screening. Journal of Medical Imaging, 9(1), 015501. https://doi.org/10.1117/1.JMI.9.1.015501