網膜中心静脈閉塞症における抗VEGF薬治療前後の視神経乳頭循環と視機能の相関 : 前向き、介入ケースシリーズ

広島大学(Hiroshima University)博士(医学)Doctor of Philosophy in Medical Sciencedoctora

Correlation between optic nerve head circulation and visual function before and after anti-VEGF therapy for central retinal vein occlusion : prospective, interventional case series

Background: To determine the correlation between the optic nerve head (ONH) circulation determined by laser speckle flowgraphy and the best-corrected visual acuity or retinal sensitivity before and after intravitreal bevacizumab or ranibizumab for central retinal vein occlusion. Methods: Thirty-one eyes of 31 patients were treated with intravitreal bevacizumab or ranibizumab for macular edema due to a central retinal vein occlusion. The blood flow in the large vessels on the ONH, the best-corrected visual acuity, and retinal sensitivity were measured at the baseline, and at 1, 3, and 6 months after treatment. The arteriovenous passage time on fluorescein angiography was determined. The venous tortuosity index was calculated on color fundus photograph by dividing the length of the tortuous retinal vein by the chord length of the same segment. The blood flow was represented by the mean blur rate (MBR) determined by laser speckle flowgraphy. To exclude the influence of systemic circulation and blood flow in the ONH tissue, the corrected MBR was calculated as MBR of ONH vessel area – MBR of ONH tissue area in the affected eye divided by the vascular MBR – tissue MBR in the unaffected eye. Pearson’s correlation tests were used to determine the significance of correlations between the MBR and the best-corrected visual acuity, retinal sensitivity, arteriovenous passage time, or venous tortuosity index. Results: At the baseline, the corrected MBR was significantly correlated with the arteriovenous passage time and venous tortuosity index (r = -0.807, P < 0.001; r = -0.716, P < 0.001; respectively). The corrected MBR was significantly correlated with the best-corrected visual acuity and retinal sensitivity at the baseline, and at 1, 3, and 6 months (all P < 0.050). The corrected MBR at the baseline was significantly correlated with the best-corrected visual acuity at 6 months (r = -0.651, P < 0.001) and retinal sensitivity at 6 months (r = 0.485, P = 0.005). Conclusions: The pre-treatment blood flow velocity of ONH can be used as a predictive factor for the best-corrected visual acuity and retinal sensitivity after anti-VEGF therapy for central retinal vein occlusion. Trial registration: Trial Registration number: UMIN000009072. Date of registration: 10/15/2012

Accurate tomographic detection of myopic macular diseases

This study examined and compared outcomes of deep learning (DL) in identifying swept-source optical coherence tomography (OCT) images without myopic macular lesions [i.e., no high myopia (nHM) vs. high myopia (HM)], and OCT images with myopic macular lesions [e.g., myopic choroidal neovascularization (mCNV) and retinoschisis (RS)]. A total of 910 SS-OCT images were included in the study as follows and analyzed by k-fold cross-validation (k = 5) using DL's renowned model, Visual Geometry Group-16: nHM, 146 images; HM, 531 images; mCNV, 122 images; and RS, 111 images (n = 910). The binary classification of OCT images with or without myopic macular lesions; the binary classification of HM images and images with myopic macular lesions (i.e., mCNV and RS images); and the ternary classification of HM, mCNV, and RS images were examined. Additionally, sensitivity, specificity, and the area under the curve (AUC) for the binary classifications as well as the correct answer rate for ternary classification were examined. The classification results of OCT images with or without myopic macular lesions were as follows: AUC, 0.970; sensitivity, 90.6%; specificity, 94.2%. The classification results of HM images and images with myopic macular lesions were as follows: AUC, 1.000; sensitivity, 100.0%; specificity, 100.0%. The correct answer rate in the ternary classification of HM images, mCNV images, and RS images were as follows: HM images, 96.5%; mCNV images, 77.9%; and RS, 67.6% with mean, 88.9%.Using noninvasive, easy-to-obtain swept-source OCT images, the DL model was able to classify OCT images without myopic macular lesions and OCT images with myopic macular lesions such as mCNV and RS with high accuracy. The study results suggest the possibility of conducting highly accurate screening of ocular diseases using artificial intelligence, which may improve the prevention of blindness and reduce workloads for ophthalmologists

Automated detection of retinal nonperfusion area caused by retinal vein occlusion

We aimed to assess the ability of deep learning (DL) and support vector machine (SVM) to detect a nonperfusion area (NPA) caused by retinal vein occlusion (RVO) with optical coherence tomography angiography (OCTA) images. The study included 322 OCTA images (normal: 148; NPA owing to RVO: 174 [128 branch RVO images and 46 central RVO images]). Training to construct the DL model using deep convolutional neural network (DNN) algorithms was provided using OCTA images. The SVM used a scikit-learn library with a radial basis function kernel. The area under the curve (AUC), sensitivity and specificity for detecting an NPA were examined. We compared the diagnostic ability (sensitivity, specificity and average required time) between the DNN, SVM and seven ophthalmologists. Heat maps were generated. With regard to the DNN, the mean AUC, sensitivity, specificity and average required time for distinguishing RVO OCTA images with an NPA from normal OCTA images were 0.986, 93.7%, 97.3% and 176.9 s, respectively. With regard to SVM, the mean AUC, sensitivity, and specificity were 0.880, 79.3%, and 81.1%, respectively. With regard to the seven ophthalmologists, the mean AUC, sensitivity, specificity and average required time were 0.962, 90.8%, 89.2%, and 700.6 s, respectively. The DNN focused on the foveal avascular zone and NPA in heat maps. The performance of the DNN was significantly better than that of SVM in all parameters (p < 0.01, all) and that of the ophthalmologists in AUC and specificity (p < 0.01, all). The combination of DL and OCTA images had high accuracy for the detection of an NPA, and it might be useful in clinical practice and retinal screening

Choroidal Changes After Coffee Intake

PURPOSE. The effects of coffee intake on the ratio of stromal and luminal components in the choroid and the underlying mechanism remain unclear. This prospective cross-sectional study aimed to explore how coffee intake affects the choroidal component ratio and circulation. METHODS. Forty-nine right eyes of healthy adult volunteers were evaluated as the coffee intake group. Thirty-two right eyes of healthy volunteers served as the control group. The participants consumed 185 mL of coffee or water, respectively, and the systemic hemodynamics, enhanced-depth imaging optical coherence tomographic (EDI-OCT) images, and foveal mean blur rate (MBR), an indicator of blood flow velocity, were recorded at baseline and after coffee or water intake. The EDI-OCT images were binarized using ImageJ software, and subfoveal choroidal thickness (SCT) and whole, luminal, and stromal choroidal areas were calculated. RESULTS. In the coffee intake group, significant decreases in SCT and luminal area peaked at 60 minutes after intake (both P < 0.001), whereas a significant increase in MBR peaked at 30 minutes (P < 0.001). No significant stromal area fluctuations were observed. SCT and luminal area fluctuations exhibited a significant positive correlation (r = 0.978, P < 0.001). Significant negative correlations of luminal area fluctuations with MBR fluctuations were observed by stepwise regression analysis (r = –0.220, P < 0.001). The control group exhibited no significant fluctuations. CONCLUSIONS. Coffee-induced choroidal thinning may result mainly from a reduction in the choroidal vessel lumen, and this vessel lumen reduction correlated with an increased choroidal blood flow velocity after coffee intake. These coffee-induced changes in choroidal component ratio and circulation should be considered when evaluating choroids

Prediction of age and brachial-ankle pulse-wave velocity using ultra-wide-field pseudo-color images by deep learning

This study examined whether age and brachial-ankle pulse-wave velocity (baPWV) can be predicted with ultra-wide-field pseudo-color (UWPC) images using deep learning (DL). We examined 170 UWPC images of both eyes of 85 participants (40 men and 45 women, mean age: 57.5 ± 20.9 years). Three types of images were included (total, central, and peripheral) and analyzed by k-fold cross-validation (k = 5) using Visual Geometry Group-16. After bias was eliminated using the generalized linear mixed model, the standard regression coefficients (SRCs) between actual age and baPWV and predicted age and baPWV from the UWPC images by the neural network were calculated, and the prediction accuracies of the DL model for age and baPWV were examined. The SRC between actual age and predicted age by the neural network was 0.833 for all images, 0.818 for central images, and 0.649 for peripheral images (all P < 0.001) and between the actual baPWV and the predicted baPWV was 0.390 for total images, 0.419 for central images, and 0.312 for peripheral images (all P < 0.001). These results show the potential prediction capability of DL for age and vascular aging and could be useful for disease prevention and early treatment

Deep Neural Network-Based Method for Detecting Central Retinal Vein Occlusion Using Ultrawide-Field Fundus Ophthalmoscopy

The aim of this study is to assess the performance of two machine-learning technologies, namely, deep learning (DL) and support vector machine (SVM) algorithms, for detecting central retinal vein occlusion (CRVO) in ultrawide-field fundus images. Images from 125 CRVO patients (n = 125 images) and 202 non-CRVO normal subjects (n = 238 images) were included in this study. Training to construct the DL model using deep convolutional neural network algorithms was provided using ultrawide-field fundus images. The SVM uses scikit-learn library with a radial basis function kernel. The diagnostic abilities of DL and the SVM were compared by assessing their sensitivity, specificity, and area under the curve (AUC) of the receiver operating characteristic curve for CRVO. For diagnosing CRVO, the DL model had a sensitivity of 98.4% (95% confidence interval (CI), 94.3–99.8%) and a specificity of 97.9% (95% CI, 94.6–99.1%) with an AUC of 0.989 (95% CI, 0.980–0.999). In contrast, the SVM model had a sensitivity of 84.0% (95% CI, 76.3–89.3%) and a specificity of 87.5% (95% CI, 82.7–91.1%) with an AUC of 0.895 (95% CI, 0.859–0.931). Thus, the DL model outperformed the SVM model in all indices assessed (P < 0.001 for all). Our data suggest that a DL model derived using ultrawide-field fundus images could distinguish between normal and CRVO images with a high level of accuracy and that automatic CRVO detection in ultrawide-field fundus ophthalmoscopy is possible. This proposed DL-based model can also be used in ultrawide-field fundus ophthalmoscopy to accurately diagnose CRVO and improve medical care in remote locations where it is difficult for patients to attend an ophthalmic medical center

Factors associated with extremely poor visual outcomes in patients with central retinal vein occlusion

Here, we examined prognostic factors for extremely poor visual outcomes in patients with central retinal vein occlusion (CRVO) in actual practices. We included 150 consecutive eyes with treatment-naïve acute CRVO from four different facilities and observed them for over 24 months. Macular edema (ME) was treated with one or three monthly anti-vascular endothelial growth factor injections (1 or 3 + pro re nata). According to the final Snellen visual acuity (VA), we divided the patients into very poor VA (< 20/200) and control (≥ 20/200) groups and examined risk factors for poor final visual outcomes. The baseline Snellen VA was hand motion to 20/13. The mean number of anti-VEGF injections for ME was 5.3 ± 3.7 during the follow-up period. In total, 49 (32.7%) patients exhibited a very poor final VA; this group comprised significantly older patients with a significantly poorer baseline VA (P < 0.01 for both) than the control group. Comorbid internal carotid artery disease and diabetic retinopathy were significantly associated with a poor final VA. In actual clinical practice, visual outcomes may be extremely poor despite ME treatment in certain patients with CRVO, with advanced age, poor baseline VA, and comorbid internal carotid artery disease and diabetic retinopathy being significant risk factors

Foveal Thickness Fluctuation in Anti-VEGF Treatment for Branch Retinal Vein Occlusion: A Long-term Study

PURPOSE: Branch retinal vein occlusion (BRVO) causes macular edema (ME), which can be controlled with anti-VEGF treatments. However, these treatments are not curative, necessitating additional anti-VEGF treatments at recurrence. Long-term results, optimal anti-VEGF treatment regimens, and the comprehensive effects of ME recurrence are largely unknown. Thus, we aimed to examine the effects of foveal thickness (FT) fluctuation (FTF) on the visual and morphologic outcomes of anti-VEGF treatments for BRVO-ME administered via a pro re nata regimen. DESIGN: A retrospective, observational case series. SUBJECTS: This study analyzed 309 treatment-naïve patients (309 eyes) with BRVO-ME between 2012 and 2021 at a multicenter retinal practice. METHODS: The FT was assessed using OCT at each study visit. MAIN OUTCOME MEASURES: We evaluated the logarithm of the minimal angle of resolution (logMAR) best corrected visual acuity (BCVA) and the defect length of the foveal ellipsoid zone (EZ) band using OCT. RESULTS: At baseline, the mean logMAR BCVA was 0.30 ± 0.30 and the mean FT was 503 ± 162 μm. The number of anti-VEGF injections for BRVO-ME was 5.8 ± 4.6 during the mean follow-up period (50.6 ± 22.2 months). At the final examination, the mean logMAR BCVA and FT values were significantly improved compared with those at the baseline. Multiple regression analyses showed that age, baseline logMAR BCVA, and FTF were significantly associated with the final logMAR BCVA (β = 0.20, 0.35, and 0.30, respectively). Foveal thickness fluctuation (divided into groups 0-3 in ascending order of FTF) was significantly associated with logMAR BCVA and the defect length of the foveal EZ band at the final examination. The defect lengths of the foveal EZ band were longitudinally shortened in groups 0 and 1 and were slightly prolonged in groups 2 and 3. The logMAR BCVA showed improvements in groups 0 and 1 and worsened slightly in groups 2 and 3. CONCLUSIONS: Foveal thickness fluctuation was significantly associated with visual acuity and foveal photoreceptor status. Thus, the morphologic and functional prognoses of eyes with BRVO may improve with the identification of the characteristics of eyes with greater FTF and consequently controlling the FTF more strictly

Changes in choroidal thickness in healthy pediatric individuals: a longitudinal study

AIM: To investigate the changes in the choroidal thickness in healthy pediatric children in a longitudinal study, and to determine the ocular and systemic parameters that were significantly correlated with the changes in the choroidal thickness. METHODS: This study included 64 eyes of 34 healthy Japanese children with a mean age (±SD) of 4.4 (±0.4)y (range, 3.6-5.8y) at baseline. Swept-source optical coherence tomography (SS-OCT) was used to record images of the retina and choroid at the baseline and after a mean follow-up period of about 1.5y. The 3D raster scan protocol was used to construct the choroidal thickness map. Mean choroidal thickness was calculated for each of the nine sectors of the Early Treatment Diabetic Retinopathy Study grid. Best-corrected visual acuity, axial length, body height, and weight were also measured. Changes in measurements were defined as the baseline values subtracted from the values at the final visit. A generalized estimating equation was used to eliminate the effect of within-subject intereye correlations. RESULTS: The mean central choroidal thickness was significantly reduced during the follow-up period (baseline, 301.8±8.6 µm; final visit, 286.6±8.0 µm, P<0.001). The decrease in the choroidal thickness was greatest in the central sector, followed by the sectors of the inner and outer rings. The inner and outer rings had diameters of 1 to 3 mm and 3 to 6 mm, respectively. The changes in the choroidal thickness in the central, inner ring, and outer ring sectors were significantly and negatively correlated with the age, baseline body height, baseline body weight, and elongation of the axial length. CONCLUSION: These results indicate that the choroidal thickness among preschool-aged Japanese children decreased significantly during the follow-up period. The choroidal thinning is significantly associated with the elongation of axial length. These characteristics should be considered in the evaluation of choroidal thickness in younger children with retinochoroidal disorders