Optimization of diagnostics of retinopathy of prematurity stages based on the integration of clinical data using the Key to Diagnosis I software

Author:

Pererva O. A.1,Kovalevskaya M. A.1

Affiliation:

1. N. N. Burdenko Voronezh State Medical University

Abstract

   Despite the improvement of algorithms of preterm infants’ management, methods for predicting, diagnosing and treating ROP remains a vital issue.   Purpose:  to improve the diagnostics of retinopathy of prematurity based on the assessment of vascular system configuration, using Key to Diagnosis I software.   Material and methods.  279 patients with ROP were divided into 6 groups: group 1 included 152 patients (304 eyes) with stage I; group 2 — 45patients (90 eyes) with stage II; group 3 — 8patients (12 eyes) with stage III; group 4 — 7 patients (8 eyes) with stage IVA; group 5 — 7 patients (14 eyes) with posterior aggressive ROP; control group 6 — 60patients (120 eyes) diagnosed with immature retina who have no ROP signs. 28 eyes were analyzed using wide-field imaging, while 400 eyes were analyzed by separate images. The presence o f“mute” zones, macula localization, traction index of the macular zone (Tm), zone and span of pathological changes, fractal dimension (Df) and complexity of vascular system (СVS) were assessed on automatically created wide-field images, obtained by Ret-Cam Shuttle.   Results.  We revealed strong correlation between Df and stages (p = 0.85, p = 0.01); moderate negative correlation of Тm and stages (p = 0.62, p = 0.01), except for posterior aggressive ROP; strong positive correlation between CVS and stages ( p  = 0.91, p = 0.001). Diagnostic modules of the software have been developed to create wide-field fundus imaging in infants, localize the macula as a marker for morphometry, and isolate the vascular system using deep convolutional neural networks.     Conclusions.  The developed algorithm for multivari­ate analysis of the retinal vascular system reduces the risks of subjective assessment of retinal changes.

Publisher

Real Time, Ltd.

Subject

Ophthalmology

Reference29 articles.

1. Blencowe H., Lawn J. E., Vazquez T., Fielder A., Gilbert C. Preterm-associated visual impairment and estimates of retinopathy of prematurity at regional and global levels for 2010. Pediatric research. 2013; 74 (1): 35–49. https://doi.org/10.1038/pr.2013.205

2. Tereshchenko A. V. Morfometricheskoe issledovanie sostoyaniya retinal'nykh sosudov na rannikh stadiyakh retinopatii nedonoshennykh / A. V. Tereshchenko [i dr.] // Oftal'mologiya. – 2013. – 10 (3): 33–8. [Tereshchenko A. V., Bely Yu. A., Isaev S. V., Trifanenkova I. G., Yudina Yu. A. The morphometric study of retinal vessels in the early stages of retinopathy of prematurity. Ophthalmology. 2013; 10 (3): 33–8 (in Russian)].

3. Katargina L. A. Angiotenzin-II kak puskovoi faktor razvitiya retinopatii nedonoshennykh / L. A. Katargina [i dr.] // Oftal'mologiya. – 2020. – 17 (4): 746–51. [Katargina L. A., Chesnokova N. B., Beznos O. V., Osipova N. A., Panova A. U. Angiotensin-II as a triggering factor in the development of retinopathy of prematurity. Ophthalmology. 2020; 17 (4): 746–51 (in Russian)]. https://doi.org/10.18008/1816-5095-2020-4-746-751

4. Scruggs B. A., Chan R. P., Kalpathy-Cramer J., Chiang M. F., Campbell J. P. Artificial intelligence in retinopathy of prematurity diagnosis. Trans. Vis. Sci. Technol. 2020; 9 (2): 5. https://doi.org/10.1167/tvst.9.2.5

5. Valikodath N., Cole E., Chiang M. F., Campbell J. P., Chan R. V. P. Imaging in retinopathy of prematurity. Asia Pac. J. Ophthalmol. (Phila). 2019; 8 (2): 178–86 https://doi.org/10.22608/APO.201963

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