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1.
Sci Rep ; 14(1): 12718, 2024 06 03.
Article in English | MEDLINE | ID: mdl-38830921

ABSTRACT

This study evaluated retinal and choroidal microvascular changes in night shift medical workers and its correlation with melatonin level. Night shift medical workers (group A, 25 workers) and non-night shift workers (group B, 25 workers) were recruited. The images of macula and optic nerve head were obtained by swept-source OCT-angiography. Vessel density of retina, choriocapillaris (CC), choriocapillaris flow deficit (CC FD), choroidal thickness (CT) and choroidal vascularity index (CVI) were measured. 6-sulfatoxymelatonin concentration was analyzed from the morning urine. CC FD and CVI were significantly decreased and CT was significantly increased in group A (all P < 0.05). 6-sulfatoxymelatonin concentration was significantly lower in group A (P < 0.05), which was significantly positively correlated with CC FD size (r = 0.318, P = 0.024) and CVI of the most regions (maximum r-value was 0.482, P < 0.001), and was significantly negatively associated with CT of all regions (maximum r-value was - 0.477, P < 0.001). In night shift medical workers, the reduction of melatonin was significantly correlated with CT thickening, CVI reduction and CC FD reduction, which suggested that they might have a higher risk of eye diseases. CC FD could be a sensitive and accurate indicator to reflect CC perfusion.


Subject(s)
Choroid , Melatonin , Microvessels , Retinal Vessels , Tomography, Optical Coherence , Humans , Choroid/blood supply , Choroid/diagnostic imaging , Tomography, Optical Coherence/methods , Male , Adult , Female , Melatonin/urine , Melatonin/analogs & derivatives , Microvessels/diagnostic imaging , Retinal Vessels/diagnostic imaging , Middle Aged , Shift Work Schedule/adverse effects , Angiography/methods , Retina/diagnostic imaging
2.
BMJ Open Ophthalmol ; 8(1)2023 12 21.
Article in English | MEDLINE | ID: mdl-38135350

ABSTRACT

PURPOSE: To develop a Vision Transformer model to detect different stages of diabetic maculopathy (DM) based on optical coherence tomography (OCT) images. METHODS: After removing images with poor quality, a total of 3319 OCT images were extracted from the Eye Center of the Renmin Hospital of Wuhan University and randomly split the images into training and validation sets in a 7:3 ratio. All macular cross-sectional scan OCT images were collected retrospectively from the eyes of DM patients from 2016 to 2022. One of the OCT stages of DM, including early diabetic macular oedema (DME), advanced DME, severe DME and atrophic maculopathy, was labelled on the collected images, respectively. A deep learning (DL) model based on Vision Transformer was trained to detect four OCT grading of DM. RESULTS: The model proposed in our paper can provide an impressive detection performance. We achieved an accuracy of 82.00%, an F1 score of 83.11%, an area under the receiver operating characteristic curve (AUC) of 0.96. The AUC for the detection of four OCT grading (ie, early DME, advanced DME, severe DME and atrophic maculopathy) was 0.96, 0.95, 0.87 and 0.98, respectively, with an accuracy of 90.87%, 89.96%, 94.42% and 95.13%, respectively, a precision of 88.46%, 80.31%, 89.42% and 87.74%, respectively, a sensitivity of 87.03%, 88.18%, 63.39% and 89.42%, respectively, a specificity of 93.02%, 90.72%, 98.40% and 96.66%, respectively and an F1 score of 87.74%, 84.06%, 88.18% and 88.57%, respectively. CONCLUSION: Our DL model based on Vision Transformer demonstrated a relatively high accuracy in the detection of OCT grading of DM, which can help with patients in a preliminary screening to identify groups with serious conditions. These patients need a further test for an accurate diagnosis, and a timely treatment to obtain a good visual prognosis. These results emphasised the potential of artificial intelligence in assisting clinicians in developing therapeutic strategies with DM in the future.


Subject(s)
Diabetes Mellitus , Diabetic Retinopathy , Macular Degeneration , Retinal Diseases , Humans , Tomography, Optical Coherence/methods , Artificial Intelligence , Retrospective Studies , Cross-Sectional Studies , Diabetic Retinopathy/diagnosis , Retina
3.
Retina ; 43(7): 1122-1131, 2023 07 01.
Article in English | MEDLINE | ID: mdl-36893447

ABSTRACT

PURPOSE: To present and compare the clinical features and multimodal imaging (MMI) findings of the primary form of multiple evanescent white dot syndrome (MEWDS) and MEWDS secondary to multifocal choroiditis/punctate inner choroidopathy (MFC/PIC). METHODS: A prospective case series. Thirty eyes of 30 MEWDS patients were included and divided into the primary MEWDS group and MEWDS secondary to MFC/PIC group. Demographic, epidemiologic, and clinical characteristics and MEWDS-related MMI findings of the two groups were compared. RESULTS: Seventeen eyes from 17 patients with primary MEWDS and 13 eyes from 13 patients with MEWDS secondary to MFC/PIC were evaluated. Patients with MEWDS secondary to MFC/PIC tended to have a higher degree of myopia than those with primary MEWDS. No other significant differences in demographic, epidemiologic, and clinical characteristics and MMI findings were found between the two groups. CONCLUSION: "MEWDS-like reaction" hypothesis seems to be correct for MEWDS secondary to MFC/PIC, and the authors highlight the importance of MMI examinations in MEWDS. Further research is needed to confirm whether the hypothesis is applicable to other forms of secondary MEWDS.


Subject(s)
Choroiditis , White Dot Syndromes , Humans , Multifocal Choroiditis/complications , Choroiditis/complications , Choroiditis/diagnosis , White Dot Syndromes/diagnosis , White Dot Syndromes/complications , Fundus Oculi , Fluorescein Angiography
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