Evidence map›Paper›PMID 39258228›Full record

ArticleFrontiers in cell and developmental biology2024

Unveiling the hidden: a deep learning approach to unraveling subzone-specific changes in peripapillary atrophy in type 2 diabetes.

Yingying Li, Xinxin Hu, Xinyu Guo, Xueqiong Ye, Dandan Wang, Juntao Zhang, Weina Ren, Na Zhao, Yitian Zhao, Qinkang Lu

Abstract read
In one paragraph

Article in Frontiers in cell and developmental biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Yingying Li *Department of Ophthalmology, The Affiliated People's Hospital of Ningbo University, Ningbo University, Ningbo, China.
Xinxin Hu *Department of Ophthalmology, The Affiliated People's Hospital of Ningbo University, Ningbo University, Ningbo, China.
Xinyu GuoLaboratory of Advanced Theranostic Materials and Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, China.
Xueqiong YeDepartment of Ophthalmology, The Affiliated People's Hospital of Ningbo University, Ningbo University, Ningbo, China.
Dandan WangDepartment of Ophthalmology, The Affiliated People's Hospital of Ningbo University, Ningbo University, Ningbo, China.
Juntao ZhangDepartment of Ophthalmology, The Affiliated People's Hospital of Ningbo University, Ningbo University, Ningbo, China.
Weina RenDepartment of Ophthalmology, The Affiliated People's Hospital of Ningbo University, Ningbo University, Ningbo, China.
Na ZhaoDepartment of Ophthalmology, The Affiliated People's Hospital of Ningbo University, Ningbo University, Ningbo, China.
Yitian ZhaoLaboratory of Advanced Theranostic Materials and Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, China.
Qinkang LuDepartment of Ophthalmology, The Affiliated People's Hospital of Ningbo University, Ningbo University, Ningbo, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: This study aimed to evaluate the optical coherence tomography angiography (OCTA) changes in subzones of peripapillary atrophy (PPA) among type 2 diabetic patients (T2DM) with or without diabetic retinopathy (DR) using well-designed deep learning models. Methods: A multi-task joint deep-learning model was trained and validated on 2,820 images to automate the determination and quantification of the microstructure and corresponding microcirculation of beta zone and gamma zone PPA. This model was then applied in the cross-sectional study encompassing 44 eyes affected by non-proliferative diabetic retinopathy (NPDR) and 46 eyes without DR (NDR). OCTA was utilized to image the peripapillary area in four layers: superficial capillary plexus (SCP), deep capillary plexus (DCP), choroidal capillary (CC) and middle-to-large choroidal vessel (MLCV). Results: The patients in both groups were matched for age, sex, BMI, and axial length. The width and area of the gamma zone were significantly smaller in NPDR group compared to the NDR group. Multiple linear regression analysis revealed a negative association between the diagnosis of DR and the width and area of the gamma zone. The gamma zone exhibited higher SCP, DCP and MLCV density than the beta zone, while the beta zone showed higher CC density than the gamma zone. In comparison to the NDR group, the MLCV density of gamma zone was significantly lower in NPDR group, and this density was positively correlated with the width and area of the gamma zone. Discussion: DR-induced peripapillary vascular changes primarily occur in gamma zone PPA. After eliminating the influence of axial length, our study demonstrated a negative correlation between DR and the gamma zone PPA. Longitudinal studies are required to further elucidate the role of the gamma zone in the development and progression of DR.

Indexed as

beta zonedeep learningdiabetic retinopathygamma zoneperipapillary atrophy

Identifiers

PMID39258228
PMCPMC11385310

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.