Peripapillary Choroidal Thickness Change of Polypoidal Choroidal Vasculopathy after Anti-vascular Endothelial Growth Factor

Lee, Kyou Ho; Kim, Seo Hee; Lee, Ji Min; Kang, Eui Chun; Koh, Hyoung Jun

doi:10.3341/kjo.2016.0101

Cited by 5 publications

(5 citation statements)

References 33 publications

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“…We attempt to use this Mask R-CNN model to depict the luminal area and stromal area of choroid layer in order to analyze both choroidal thickness and choroidal vascularity index from OCT images in future study. Recent studies reveal the correlation between the change of choroidal thickness and anti-VEGF injections [38,39]. To explore this association via the proposed model is also part of our future plans.…”

Section: Discussionmentioning

confidence: 90%

Automatic Segmentation of Choroid Layer Using Deep Learning on Spectral Domain Optical Coherence Tomography

et al. 2021

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The purpose of this article is to evaluate the accuracy of the optical coherence tomography (OCT) measurement of choroidal thickness in healthy eyes using a deep-learning method with the Mask R-CNN model. Thirty EDI-OCT of thirty patients were enrolled. A mask region-based convolutional neural network (Mask R-CNN) model composed of deep residual network (ResNet) and feature pyramid networks (FPNs) with standard convolution and fully connected heads for mask and box prediction, respectively, was used to automatically depict the choroid layer. The average choroidal thickness and subfoveal choroidal thickness were measured. The results of this study showed that ResNet 50 layers deep (R50) model and ResNet 101 layers deep (R101). R101 U R50 (OR model) demonstrated the best accuracy with an average error of 4.85 pixels and 4.86 pixels, respectively. The R101 ∩ R50 (AND model) took the least time with an average execution time of 4.6 s. Mask-RCNN models showed a good prediction rate of choroidal layer with accuracy rates of 90% and 89.9% for average choroidal thickness and average subfoveal choroidal thickness, respectively. In conclusion, the deep-learning method using the Mask-RCNN model provides a faster and accurate measurement of choroidal thickness. Comparing with manual delineation, it provides better effectiveness, which is feasible for clinical application and larger scale of research on choroid.

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Section: Discussionmentioning

confidence: 90%

Automatic Segmentation of Choroid Layer Using Deep Learning on Spectral Domain Optical Coherence Tomography

et al. 2021

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“…In addition to the macular area, studies on the measurement of CT at the extramacular area have been performed, since the characteristics of the whole body of the patient may also be reflected in the choroid outside of the macula 22 , 24 – 26 . In addition, measurement of CT at the macular area, and outside of the macula, allows observation of the relative changes in the choroid of the macular area in macular disease 4 , 27 – 29 . Although many studies have shown changes in macular CT in eyes with AMD or PSDs, few studies have focused on changes in CT outside the macular area 4 , 23 , 27 , 29 .…”

Section: Introductionmentioning

confidence: 99%

“…In addition, measurement of CT at the macular area, and outside of the macula, allows observation of the relative changes in the choroid of the macular area in macular disease 4 , 27 – 29 . Although many studies have shown changes in macular CT in eyes with AMD or PSDs, few studies have focused on changes in CT outside the macular area 4 , 23 , 27 , 29 . In this study, we hypothesized that CT profiles, including subfoveal CT, nasal peripapillary CT, and the ratio of subfoveal CT to peripapillary CT, can be the surrogate variables of the choroids in eyes with AMD and PSDs.…”

Section: Introductionmentioning

confidence: 99%

Clustering of eyes with age-related macular degeneration or pachychoroid spectrum diseases based on choroidal thickness profile

Kim

Lee

Kang

et al. 2021

Sci Rep

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Choroidal changes have been suggested to be involved in the pathophysiology of both age-related macular degeneration (AMD) and pachychoroid spectrum diseases (PSD). To find out the choroidal characteristics of each disease groups, various groups of AMD and PSD were classified into several clusters according to choroidal profiles based on subfoveal choroidal thickness (CT), peripapillary CT, the ratio of subfoveal CT to peripapillary CT and age. We retrospectively analyzed 661 eyes, including 190 normal controls and 471 with AMD or PSDs. In the AMD groups, eyes with soft drusen or reticular pseudodrusen were belonged to the same cluster as those with classic exudative AMD (all p < 0.001). However, eyes with pachydrusen were not clustered with eyes from other AMD groups; instead, they were classified in the same cluster as eyes from the PSD group (all p < 0.001). In the PSD group, eyes with pachychoroid neovasculopathy were grouped in the same cluster of those with polypoidal choroidal vasculopathy (p < 0.001). The cluster analysis based on the CT profiles, including subfoveal CT, peripapillary CT, and their ratio, revealed a clustering pattern of eyes with AMD and PSDs. These findings support the suggestion that pachydrusen has the common pathogenesis as PSD.

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“…No statistical significance was associated with change in choroidal thickness in patients treated with and without PDT (either standard or reduced fluence) or number of injections which was comparable to the study by Giridhar et al 8 Lee et al showed a significant decrease in mean choroidal thickness in PCV patients post anti VEGF therapy. 9 Mean choroidal thickness also decreased at 3 years follow up and was associated with number of intravitreal Ranibizumab injections in yet another study while no significant association between baseline CCT and mean CCT reduction at month 36 was noted by Azuma et al 10 It has been speculated that an increased extra vascular volume and increased choroidal hyper permeability may be associated with a thicker subfoveal choroid which may show a poor response owing to increased hydrostatic pressure. And these studies show a better response to anti VEGF therapy associated with thinner choroid.…”

Section: Discussionmentioning

confidence: 91%

How do polypoidal choroidal vasculopathy patients fare long term - A real world data

Iqbal¹,

Manoj

Indurkar³

et al. 2023

IJCEO

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The objective of this 5-year retrospective study of PCV eyes was to assess the clinical presentation and long-term real world visual and anatomical outcomes following therapy. Data included the baseline clinical and demographic profile, visual acuity and treatment details. Main outcome measured were anatomical and visual outcomes with treatment, treatment compliance and complications. Out the 45 PCV eyes (51 patients), 76.4% lesions occurred predominantly at the macula. Clinical presentations were variable though visible polyps (16.6%) and massive subretinal hemorrhage (17.7%) were less frequent. DLS with diffuse PEDs or thumb shaped PEDs were the most common finding in SD-OCT. OCTA was sensitive in identifying BVNs compared to ICGA but were poor in identifying polyps. Vision improvement was achieved in 42% eyes, while loss occurred in 26.6% eyes, with deterioration more in type 1 PCV. Baseline good vision, thicker CCT, smaller lesions and minimum recurrences at year 1 were risk factors associated with good outcomes. Mean number of injections was 18.7. 22% received primary PDT while 11% eyes received rescue PDT. Low fluence PDT was found to be as effective as standard fluence. Though not significant, PDT eyes required lesser injections than monotherapy. As an agent Aflibercept seemed to be better than Ranibizumab and was the most preferred switching agent (55% needed switch). Loading dose followed by PRN was the only feasible regimen with relatively reasonable compliance. Complications included RIP (11%) and 2 eyes requiring Vitrectomy for breakthrough vitreous hemorrhage. The superiority of aflibercept and the feasibility of a PRN approach is underlined in this study. In spite of suboptimal compliance this study reveals that nearly half the eyes demonstrated visual gains and anatomic stability.

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Peripapillary Choroidal Thickness Change of Polypoidal Choroidal Vasculopathy after Anti-vascular Endothelial Growth Factor

Cited by 5 publications

References 33 publications

Automatic Segmentation of Choroid Layer Using Deep Learning on Spectral Domain Optical Coherence Tomography

Automatic Segmentation of Choroid Layer Using Deep Learning on Spectral Domain Optical Coherence Tomography

Clustering of eyes with age-related macular degeneration or pachychoroid spectrum diseases based on choroidal thickness profile

How do polypoidal choroidal vasculopathy patients fare long term - A real world data

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