115 research outputs found

    Retinal and Optic Nerve Head Vascular Reactivity in Primary Open Angle Glaucoma

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    The global aim of this thesis was to assess retinal vascular reactivity in glaucoma patients using a standardised hypercapnic stimulus. There is a suggestion of disturbance in the regulation of retinal and optic nerve head (ONH) hemodynamics in patients with Primary Open Angle Glaucoma (POAG), although much of the work to-date has either been equivocal or speculative. Previous studies have used non-standardised hypercapnic stimuli to assess vascular reactivity. To explain, hypercapnia induces hyperventilation which disturbs arterial oxygen concentration, an effect that varies between individuals resulting in the non-standardised provocation of vascular reactivity. Therefore, a normoxic hypercapnic provocation was developed to avoid additional and potentially uncontrolled vasoconstriction in what is thought to be a vasospastic disease. The development of a safe, sustained and stable normoxic hypercapnic stimulus was essential for the assessment of retinal arteriolar vascular reactivity so that repeated hemodynamic measurements could be obtained. Furthermore, most techniques used to measure vascular reactivity do not comprehensively assess retinal hemodynamics, in terms of the simultaneous measurement of vessel diameter and blood velocity in order to calculate flow. In this respect, this study utilized a technique that quantitatively assesses retinal blood flow and vascular reactivity of the major arterioles in close proximity to the ONH. The stimulus and vascular reactivity quantification technique was validated in healthy controls and then was clinically applied in patients with POAG. Newly diagnosed patients with untreated POAG (uPOAG) were recruited in order to avoid any confounding pharmacological effects and patients with progressive POAG (pPOAG) were also selected since they are thought to likely manifest vascular dysregulation. Finally, the results of the functional vascular reactivity assessment were compared to those of systemic biochemical markers of endothelial function in patients with untreated and progressive POAG and in healthy controls. Overall summary A safe, sustained, stable and repeatable normoxic hypercapnic stimulus was developed, evaluated and validated. In terms of the physiology of retinal vascular regulation, the percent magnitude of vascular reactivity of the arterioles and capillaries was found to be comparable in terms of flow. The new stimulus was successfully applied in POAG and in healthy controls to assess vascular reactivity and was also compared to plasma levels of ET-1 and cGMP. In terms of the patho-physiology of POAG, the study revealed a clear impairment of vascular reactivity in the uPOAG and pPOAG groups. There were reduced levels of plasma ET-1 in the uPOAG and ntPOAG groups. In addition, treatment with Dorzolamide improved vascular reactivity in the ntPOAG group in the absence of any change in the expression of plasma ET-1 or cGMP. Future work will address this apparent contradiction between the outcome of the functional vascular reactivity assessment and the biochemical markers of endothelial function in newly diagnosed POAG patients treated with Dorzolamide. Aims of chapters Chapter 3: To determine the effect of hypercapnia on retinal capillary blood flow in the macula and ONH using scanning laser Doppler flowmetry (SLDF) in young healthy subjects. Chapter 4: To describe a new manual methodology that permits the comprehensive assessment of retinal arteriolar vascular reactivity in response to a sustained and stable hypercapnic stimulus. The secondary aim was to determine the magnitude of the vascular reactivity response of the retinal arterioles to hypercapnic provocation in young healthy subjects. Chapter 5: To compare the magnitude of vascular reactivity of the retinal arterioles in terms of percentage change of flow to that of the retinal capillaries using a novel automated standardized methodology to provoke normoxic, or isoxic, hypercapnia. Chapter 6: To determine the magnitude of retinal arteriolar vascular reactivity to normoxic hypercapnia in patients with untreated POAG (uPOAG), progressive POAG (pPOAG) and controls. The secondary aim was to determine retinal vascular reactivity in newly treated POAG (ntPOAG, i.e. after treatment with 2% Dorzolamide, twice daily for 2 weeks). Chapter 7: To compare plasma endothelin-1 (ET-1) and cyclic guanosine monophosphate (cGMP) between groups of patients with untreated primary open angle glaucoma (uPOAG), progressive POAG (pPOAG), newly treated POAG (ntPOAG) and controls. The effect of normoxic hypercapnia on plasma ET-1 and cGMP was also assessed. The functional measures of retinal blood flow and vascular reactivity were correlated with systemic biochemical markers of endothelial function. Methods Chapters 3, 4 and 5 were conducted on young healthy control subjects, where as Chapters 6 and 7 were conducted on patients with glaucoma and healthy controls. Chapter 3: Subjects breathed unrestricted air for 15 minutes (baseline) via a sequential gas delivery circuit and then the fractional (percent) end-tidal concentration of CO2 (FETCO2) was manually raised for 15 minutes by adding a low flow of CO2 to the inspired air. For the last 15 minutes, FETCO2 was returned to baseline values to establish a recovery period. Heidelberg Retina Flowmeter (HRF) images centered on both the ONH and the macula were acquired during each phase. Chapter 4: Subjects breathed air via a sequential gas delivery circuit for 15 minutes and the air flow was then manually decreased so that subjects inspired gases from the rebreathing reservoir until a stable 10-15% increase in FETCO2 concentration was achieved for 20 minutes. Air flow rate was then manually elevated so that subjects breathed primarily from the fresh gas reservoir to return FETCO2 back to baseline for the last 15 minutes. Retinal arteriolar hemodynamics was assessed using the Canon Laser Blood Flowmeter (CLBF) during all three breathing phases. Chapter 5: Normoxic, or isoxic, hypercapnia was induced using an automated gas flow controller (RespirActTM, Thornhill Research Inc. Toronto, Canada). Subjects breathed air with PETCO2 normalized at 38 mmHg. An increase in PETCO2 of 15% above baseline, whilst maintaining normoxia, was then implemented for 20 minutes and then PETCO2 was returned to baseline conditions for 10 minutes. Retinal and ONH hemodynamic measurements were performed using the CLBF and HRF in random order across sessions. Chapter 6: Retinal arteriolar vascular reactivity was assessed in patients with uPOAG, pPOAG (defined by the occurrence of optic disc hemorrhage within the past 24 months) and controls during normoxic hypercapnia. Using the automated gas flow controller, patients breathed air for 10 mins and PETCO2 was maintained at 38mmHg. Following this normoxic hypercapnia (a 15% increase in PETCO2 while PETO2 was maintained at resting levels) was induced for 15 mins and then for the last 10 mins PETCO2 was returned to baseline (post-hypercapnia) to establish recovery blood flow values. Retinal arteriolar diameter, blood velocity and blood flow was assessed using the CLBF in both patient groups and controls. A similar paradigm was repeated in the newly treated POAG group (ntPOAG, i.e. after treatment with 2% Dorzolamide, twice daily for 2 weeks). Chapter 7: Blood samples were collected from the cubital vein of all participants (uPOAG, pPOAG, ntPOAG and controls) during baseline conditions (PETCO2=38mmHg) and then during normoxic hypercapnia (i.e. a 15% increase in PETCO2 relative to the baseline) using the paradigm described for Chapter 6. ET-1 and cGMP was assessed using immunoassay. Results Chapter 3: The group mean nasal macula capillary blood flow increased from 127.17 a.u. (SD 32.59) at baseline to 151.22 a.u. (SD 36.67) during hypercapnia (p=0.028), while foveal blood flow increased from 92.71 a.u. (SD 28.07) to 107.39 a.u. (SD 34.43) (p=0.042). There was a concomitant and uncontrolled +13% increase in the group mean PETO2 during the hypercapnic provocation of +14% increase in PETCO2. Chapter 4: Retinal arteriolar diameter, blood velocity and blood flow increased by 3.2% (p=0.0045), 26.4% (p<0.0001) and 34.9% (p<0.0001), respectively during hypercapnia. There was a stable ¬+12% increase in PETCO2 during hypercapnia and a concomitant -6% decrease in PETO2. Chapter 5: Using an automated gas flow controller the co-efficient of repeatability (COR) was 5% of the average PETCO2 at baseline and during normoxic hypercapnia. The COR for PETO2 was 10% and 7% of the average PETO2 at baseline and during normoxic hypercapnia, respectively. Group mean PETCO2 increased by approximately +14.4% and there was only a +4.3% increase in PETO2 during hypercapnia across both study sessions. Retinal arteriolar hemodynamics increased during hypercapnia (p<0.001). Similarly, there was an increase in the capillary blood flow of the temporal rim of the ONH (p<0.001), nasal macula (p<0.001) and foveal areas (p<0.006) during hypercapnia. A non-significant trend for capillary blood flow to increase in the macula temporal area (+8.2%) was noted. In terms of percentage change of blood flow, retinal capillary vascular reactivity (i.e. all 4 analyzed areas = 22.4%) was similar to the magnitude of arteriolar (= 24.9%) vascular reactivity. Chapter 6: Retinal arteriolar diameter, blood velocity and flow did not increase during normoxic hypercapnia in uPOAG compared to controls. Diameter and blood velocity did not change in pPOAG during normoxic hypercapnia but there was a significant increase in blood flow (+9.1%, p=0.030). After treatment with 2% Dorzolamide for 2 weeks there was a 3% (p=0.040), 19% (p<0.001) and 26% (p<0.001) increase in diameter, velocity and flow, respectively, in the ntPOAG group. Group mean PETCO2 increased by approximately +15% in all the groups and there was only a +3% increase in PETO2 during hypercapnia. Chapter 7: Plasma ET-1 levels were significantly different across groups at baseline (one way ANOVA; p=0.0012) and this was repeated during normoxic hypercapnia (one way ANOVA; p=0.0014). ET-1 levels were lower in uPOAG compared to pPOAG and controls at baseline and during normoxic hypercapnia (Tukey’s honestly significant difference test). Similarly, ntPOAG group also showed lower ET-1 levels compared to the pPOAG and controls at baseline and during normoxic hypercapnia (Tukey’s honestly significant difference test). The cGMP at baseline and during normoxic hypercapnia across all groups was not different. In the control group, the change in ET-1 during normoxic hypercapnia was negatively correlated with change in retinal arteriolar blood flow (r = -0.52, p=0.04), that is, as the change in ET-1 reduced, the change in blood flow increased. A weak correlation was noted between change in cGMP during normoxic hypercapnia and the change in arteriolar blood flow (r = +0.45, p=0.08). Conclusions Chapter 3: Hypercapnia resulted in a quantifiable capillary vascular reactivity response in 2 of the 3 assessed retinal locations (i.e., nasal macula and fovea). There was no vascular reactivity response of the ONH. It is critical to minimise the concomitant change in PETO2 during hypercapnia in order to obtain robust vascular reactivity responses. Chapter 4: A technique to comprehensively assess vascular reactivity during stable and sustained hypercapnia was described. Retinal arteriolar diameter, blood velocity and blood flow increased in response to hypercapnia. The vascular reactivity results of this study served as a reference for future studies using the hypercapnic provocation and CLBF. Also, the concomitant change in PETO2 using the partial rebreathing technique was reduced compared to the manual addition of CO2 technique described in Chapter 3 but was still greater than optimal. Chapter 5: A new automated gas flow controller was used to induce standardised normoxic, or isoxic, hypercapnia. The magnitude of vascular reactivity in both retinal arterioles and capillaries in response to the new hypercapnic stimulus was robust compared to the previous stimuli. There was a clear ONH vascular reactivity response in this study, unlike the result attained in Chapter 3. Although theoretically it is predictable that the percent magnitude of vascular reactivity of the arterioles and capillaries should be similar, this is the first study to show that they are indeed comparable. The magnitude of hypercapnia was repeatable and the concomitant change in PETO2 was minimal and physiologically insignificant. Chapter 6: The normal response of the retinal arterioles and capillaries to normoxic hypercapnia is impaired in both uPOAG and pPOAG compared to controls. Short term treatment with 2% topical Dorzolamide for two weeks improved retinal vascular reactivity in ntPOAG. However, it is still unclear whether this improvement is a direct effect of Dorzolamide or as a secondary effect of the decrease in intraocular pressure (IOP). Chapter 7: We found a reduction in the plasma ET-1 at baseline and during normoxic hypercapnia in the uPOAG and in the ntPOAG groups. This is the first study to show a lower plasma ET-1 level in uPOAG. The fact that this finding was repeated after 2 weeks treatment with Dorzolamide in the ntPOAG group further validates these results. It also suggests that Dorzolamide treatment does not impact ET-1 and cGMP measures, although it clearly results in an improvement of vascular reactivity. Correlation results suggest that as the change in ET-1 reduced during normoxic hypercapnia, the change in blood flow increased in the controls

    Microcirculatory model predicts blood flow and autoregulation range in the human retina:in vivo investigation with laser speckle flowgraphy

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    In this study, we mathematically predict retinal vascular resistance (RVR) and retinal blood flow (RBF), we test predictions using laser speckle flowgraphy (LSFG), we estimate the range of vascular autoregulation, and we examine the relationship of RBF with the retinal nerve fiber layer (RNFL) and ganglion cell complex (GCC). Fundus, optical coherence tomography (OCT), and OCT-angiography images, systolic/diastolic blood pressure (SBP/DBP), and intraocular pressure (IOP) measurements were obtained float 36 human subjects. We modeled two circulation markers (RVR and RBF) and estimated individualized lower/higher autoregula tion limits (LARL/HARL), using retinal vessel calibers, fractal dimen- sion, perfusion pressure, and population-based hematocrit values. Quantitative LSFG waveforms were extracted from vessels of the same eyes, before and during IOP elevation. LSFG metrics explained most variance in RVR (R-2 =0.77/P = 6.9.10(-9)) and RBF (R-2 =0.65/P = 1.0.10(-6)), suggesting that the markers strongly reflect blood flow physiology. Higher RBF was associated with thicker RNFL (P = 4.0.10(-4)) and GCC (P = 0.003), thus also verifying agreement with structural measurements. LARL was at SBP/DBP of 105/65 mmHg for the average subject without arterial hypertension and at 115/75 mmHg for the average hypertensive subject. Moreover, during IOP elevation, changes in RBF were more pronounced than changes in RVR. These observations physiologically imply that healthy subjects are already close to LARL, thus prone to hypoperfusion. In conclusion, we modeled two clinical markers and described a novel method to predict individualized autoregulation limits. These findings could improve understanding of retinal perfusion and pave the way for personalized intervention decisions, when treating patients with coexisting ophthalmic and cardiovascular pathologies. NEW & NOTEWORTHY We describe and test a new approach to quantify retinal blood flow, based on standard clinical examinations and imaging techniques, linked together with a physiological model. We use these findings to generate individualized estimates of the autoregulation range. We provide evidence that healthy subjects are closer to the lower autoregulation limit than thought before. This suggests that some retinas are less prepared to withstand hypoperfusion, even after small intraocular pressure rises or blood pressure drops

    On the Indeterminates of Glaucoma:the Controversy of Arterial Blood Pressure and Retinal Perfusion

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    Glaucoma is a chronic eye disease characterized by thinning of the retina, death of ganglion cells, and progressive loss of vision, eventually leading to blindness. The prevalence of glaucoma is estimated at 1-3% of those over 40 years old. With a constantly aging population, this number is expected to increase significantly over the next 10 years. Even with treatment, about 15% of people with glaucoma currently develop residual vision or tunnel vision and eventually become blind or partially sighted. The mechanisms behind ganglion cell death are poorly understood. Elevated eye pressure is the main risk factor for glaucoma, but treatment in the form of medication, laser, or surgery can only slow the decline, not stop it. In addition, high intraocular pressure is neither necessary nor sufficient for the development of glaucoma, indicating the existence of other unknown risk factors. It has been established that the death of ganglion cells results in a decreased oxygen demand and a concomitant decrease in blood flow. However, there is also a hypothesis that reduced or unstable blood supply is not only a consequence, but also a cause of glaucoma. This is known as the ‘chicken-egg’ dilemma in glaucoma. It is supported by the observation that the risk of developing glaucoma is higher in people with very low blood pressure (sometimes even as a result of overtreatment of high blood pressure).This dissertation is an attempt to methodically examine whether blood pressure can be linked to changes in the retina that could suggest susceptibility to glaucoma. For this purpose, we analyze epidemiological data from the Groningen Longitudinal Glaucoma Study, we use advanced imaging techniques to model the microcirculation, and we describe its relationship with the neural structure and oxygen consumption of the retina. We provide evidence leaning towards the existence of a vascular component, likely pertinent to glaucoma

    REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs

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    [EN] Glaucoma is one of the leading causes of irreversible but preventable blindness in working age populations. Color fundus photography (CFP) is the most cost-effective imaging modality to screen for retinal disorders. However, its application to glaucoma has been limited to the computation of a few related biomarkers such as the vertical cup-to-disc ratio. Deep learning approaches, although widely applied for medical image analysis, have not been extensively used for glaucoma assessment due to the limited size of the available data sets. Furthermore, the lack of a standardize benchmark strategy makes difficult to compare existing methods in a uniform way. In order to overcome these issues we set up the Retinal Fundus Glaucoma Challenge, REFUGE (https://refuge.grand-challenge.org), held in conjunction with MIC-CAI 2018. The challenge consisted of two primary tasks, namely optic disc/cup segmentation and glaucoma classification. As part of REFUGE, we have publicly released a data set of 1200 fundus images with ground truth segmentations and clinical glaucoma labels, currently the largest existing one. We have also built an evaluation framework to ease and ensure fairness in the comparison of different models, encouraging the development of novel techniques in the field. 12 teams qualified and participated in the online challenge. This paper summarizes their methods and analyzes their corresponding results. In particular, we observed that two of the top-ranked teams outperformed two human experts in the glaucoma classification task. Furthermore, the segmentation results were in general consistent with the ground truth annotations, with complementary outcomes that can be further exploited by ensembling the results.This work was supported by the Christian Doppler Research Association, the Austrian Federal Ministry for Digital and Economic Affairs and the National Foundation for Research, Technology and Development, J.I.O is supported by WWTF (Medical University of Vienna: AugUniWien/FA7464A0249, University of Vienna: VRG12- 009). Team Masker is supported by Natural Science Foundation of Guangdong Province of China (Grant 2017A030310647). Team BUCT is partially supported by the National Natural Science Foundation of China (Grant 11571031). The authors would also like to thank REFUGE study group for collaborating with this challenge.Orlando, JI.; Fu, H.; Breda, JB.; Van Keer, K.; Bathula, DR.; Diaz-Pinto, A.; Fang, R.... (2020). 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    Evidence Report: Risk of Spaceflight Associated Neuro-ocular Syndrome (SANS)

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    A subset of astronauts develop neuro-ocular structural and functional changes during prolonged periods of spaceflight that may lead to additional neurologic and ocular consequences upon return to Earth

    Learning to Address Intra-segment Misclassification in Retinal Imaging

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    Accurate multi-class segmentation is a long-standing challenge in medical imaging, especially in scenarios where classes share strong similarity. Segmenting retinal blood vessels in retinal photographs is one such scenario, in which arteries and veins need to be identified and differentiated from each other and from the background. Intra-segment misclassification, i.e. veins classified as arteries or vice versa, frequently occurs when arteries and veins intersect, whereas in binary retinal vessel segmentation, error rates are much lower. We thus propose a new approach that decomposes multi-class segmentation into multiple binary, followed by a binary-to-multi-class fusion network. The network merges representations of artery, vein, and multi-class feature maps, each of which are supervised by expert vessel annotation in adversarial training. A skip-connection based merging process explicitly maintains class-specific gradients to avoid gradient vanishing in deep layers, to favor the discriminative features. The results show that, our model respectively improves F1-score by 4.4%, 5.1%, and 4.2% compared with three state-of-the-art deep learning based methods on DRIVE-AV, LES-AV, and HRF-AV data sets. Code: https://github.com/rmaphoh/Learning-AVSegmentatio

    Learning to Address Intra-segment Misclassification in Retinal Imaging

    Get PDF
    Accurate multi-class segmentation is a long-standing challenge in medical imaging, especially in scenarios where classes share strong similarity. Segmenting retinal blood vessels in retinal photographs is one such scenario, in which arteries and veins need to be identified and differentiated from each other and from the background. Intra-segment misclassification, i.e. veins classified as arteries or vice versa, frequently occurs when arteries and veins intersect, whereas in binary retinal vessel segmentation, error rates are much lower. We thus propose a new approach that decomposes multi-class segmentation into multiple binary, followed by a binary-to-multi-class fusion network. The network merges representations of artery, vein, and multi-class feature maps, each of which are supervised by expert vessel annotation in adversarial training. A skip-connection based merging process explicitly maintains class-specific gradients to avoid gradient vanishing in deep layers, to favor the discriminative features. The results show that, our model respectively improves F1-score by 4.4%, 5.1%, and 4.2% compared with three state-of-the-art deep learning based methods on DRIVE-AV, LES-AV, and HRF-AV data sets. Code: https://github.com/rmaphoh/Learning-AVSegmentatio
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