Comparison of Widefield OCT Angiography Features Between Severe Non-Proliferative and Proliferative Diabetic Retinopathy

被引:0
作者
Drira, Ines [1 ,2 ]
Noor, Maha [1 ]
Stone, Amy [1 ]
D'Souza, Yvonne [1 ]
John, Binu [1 ]
Mcgrath, Orlaith [1 ]
Patel, Praveen J. [3 ,4 ]
Aslam, Tariq [1 ]
机构
[1] Univ Manchester, Manchester Royal Eye Hosp, Oxford Rd, Manchester M13 9WL, Lancs, England
[2] Hosp Toulouse, Pl Du Dr Joseph Baylac, F-31300 Toulouse, France
[3] Natl Hlth Serv Fdn Trust, Moorfields Eye Hosp, Natl Inst Hlth & Care Res, Biomed Res Ctr, London, England
[4] UCL, Inst Ophthalmol, London, England
关键词
Proliferative diabetic retinopathy; Severe diabetic retinopathy; OCT-A; Image analysis; New vessels; Retinal ischemia; OCT-A metrics; Fluorescein angiography; COHERENCE TOMOGRAPHY ANGIOGRAPHY;
D O I
10.1007/s40123-024-00886-2
中图分类号
R77 [眼科学];
学科分类号
100212 ;
摘要
IntroductionThere is a high and ever-increasing global prevalence of diabetic retinopathy (DR) and invasive imaging techniques are often required to confirm the presence of proliferative disease. The aim of this study was to explore the images of a rapid and non-invasive technique, widefield optical coherence tomography angiography (OCT-A), to study differences between patients with severe non-proliferative and proliferative DR (PDR).MethodsWe conducted an observational longitudinal study from November 2022 to March 2023. We recruited 75 patients who were classified into a proliferative group (28 patients) and severe non-proliferative group (47 patients). Classification was done by specialist clinicians who had full access to any multimodal imaging they required to be confident of their diagnosis, including fluorescein angiography. For all patients, we performed single-shot 4 x 4 and 10 x 10 mm (widefield) OCT-A imaging and when possible, the multiple images required for mosaic 17.5 x 17.5 mm (ultra widefield) OCT-A imaging. We assessed the frequency with which proliferative disease was identifiable solely from these OCT-A images and used custom-built MATLAB software to analyze the images and determine computerized metrics such as density and intensity of vessels, foveal avascular zone, and ischemic areas.ResultsOn clinically assessing the OCT-A 10 x 10 fields, we were only able to detect new vessels in 25% of known proliferative images. Using ultra-widefield mosaic images, however, we were able to detect new vessels in 100% of PDR patients. The image analysis metrics of 4 x 4 and 10 x 10 mm images did not show any significant differences between the two clinical groups. For mosaics, however, there were significant differences in the capillary density in patients with PDR compared to severe non-PDR (9.1% +/- 1.9 in the PDR group versus 11.0% +/- 1.9 for severe group). We also found with mosaics a significant difference in the metrics of ischemic areas; average area of ischemic zones (253,930.1 +/- 108,636 for the proliferative group versus 149,104.2 +/- 55,101.8 for the severe group.ConclusionsOur study showed a high sensitivity for detecting PDR using only ultra-widefield mosaic OCT-A imaging, compared to multimodal including fluorescein angiography imaging. It also suggests that image analysis of aspects such as ischemia levels may be useful in identifying higher risk groups as a warning sign for future conversion to neovascularization.
引用
收藏
页码:819 / 830
页数:12
相关论文
共 30 条
[1]   Swept-Source OCT Angiography Imaging of the Foveal Avascular Zone and Macular Capillary Network Density in Diabetic Retinopathy [J].
Al-Sheikh, Mayss ;
Akil, Handan ;
Pfau, Maximilian ;
Sadda, SriniVas R. .
INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE, 2016, 57 (08) :3907-3913
[2]   Widefield Optical Coherence Tomography Angiography in Diabetic Retinopathy [J].
Amato, Alessia ;
Nadin, Francesco ;
Borghesan, Federico ;
Cicinelli, Maria Vittoria ;
Chatziralli, Irini ;
Sadiq, Saena ;
Mirza, Rukhsana ;
Bandello, Francesco .
JOURNAL OF DIABETES RESEARCH, 2020, 2020
[3]   Differentiation of Diabetic Status Using Statistical and Machine Learning Techniques on Optical Coherence Tomography Angiography Images [J].
Aslam, Tariq Mehmood ;
Hoyle, David Charles ;
Puri, Vikram ;
Bento, Goncalo .
TRANSLATIONAL VISION SCIENCE & TECHNOLOGY, 2020, 9 (04)
[4]  
Centers for Disease Control and Prevention, 2020, National Diabetes Statistics Report
[5]   Characterization of Risk Profiles for Diabetic Retinopathy Progression [J].
Cunha-Vaz, Jose ;
Mendes, Luis .
JOURNAL OF PERSONALIZED MEDICINE, 2021, 11 (08)
[6]   A Multi-Branch Convolutional Neural Network for Screening and Staging of Diabetic Retinopathy Based on Wide-Field Optical Coherence Tomography Angiography [J].
Dong, B. ;
Wang, X. ;
Qiang, X. ;
Du, F. ;
Gao, L. ;
Wu, Q. ;
Cao, G. ;
Dai, C. .
IRBM, 2022, 43 (06) :614-620
[7]   Adverse events and complications associated with intravitreal injection of anti-VEGF agents: a review of literature [J].
Falavarjani, K. Ghasemi ;
Nguyen, Q. D. .
EYE, 2013, 27 (07) :787-794
[8]   Visual side effects of successful scatter laser photocoagulation surgery for proliferative diabetic retinopathy [J].
Fong, Donald S. ;
Girach, Aniz ;
Boney, April .
RETINA-THE JOURNAL OF RETINAL AND VITREOUS DISEASES, 2007, 27 (07) :816-824
[9]  
fr.mathworks, HESSIAN BASED FRANGI
[10]  
Frangi AF, 1998, LECT NOTES COMPUT SC, V1496, P130, DOI 10.1007/BFb0056195