Vessel Edges Research Articles

Lung vessel segmentation based on random forests

Lung vessel segmentation of computed tomography (CT) images is important in clinical practise and challenging due to difficulties associated with minor size and blurred edges of lung vessels. A vessel segmentation method is proposed for lung images based on a random forest classifier and sparse auto-encoder features. First, the multi-scale representations of lung images are obtained using the Gaussian pyramid. Second, a sparse auto-encoder of three layers is trained using randomly selected patches of these images. Next, the trained weight of the sparse auto-encoder is used as the convolution kernel to extract features of different scale images. Finally, a random forest classifier is exploited to segment the vessels. The proposed method was evaluated on the original and noise-added VESSEL12 dataset that is publicly available. Comparison with some classical methods and existing machine learning methods shows that the proposed method reaches the state-of-the-art accuracy. The results also show that a shallow neural network is a powerful feature extraction tool.

Automatic Detection of Optic Disc and Blood Vessel in Retinal Images using Morphological Operations and Ipachi Model

Automated detection of Optic disc and blood vessel fabrication is becoming of virtual interest for better management of diabetic disease. In this paper, we propose morphology technique and new infinite active contour model that uses hybrid region information of image to approach this problem. For optic disc detection scheme utilizes operations such as edge detection, binary threshold and morphological operation. For vessel detection we use an infinite perimeter regularize, provided by using L2 Lebesgue measure of the boundaries, allows for better detection of small oscillatory structures than the models based on length of a feature’s boundaries. The advantage of using different types of region information, Eigen based enhancement, such as the combination of image intensity information and local phase based enhancement. The local phase based enhancement map is used for preserving vessel edges while the given intensity information will give a correct feature’s segmentation.

Enhanced visualization of retinal vasculature in fundus images through image processing

PurposeTo develop a digital filter that enhances visualization of retinal blood vessels.MethodsFour‐hundred 24‐bit color fundus images were analyzed and properties of red, green, and blue channels were extracted. Then, using hemoglobin absorption coefficients, the relevant weights for gray‐scale conversion that emphasizes retinal vessels were calculated. To evaluate images, edges were detected via convolutional 2D Laplacian kernel from the processed images, and the number of edges, number of effective edges, and sum of intensities of edges were evaluated.ResultsThe values of weights for red, green, and blue channels were calculated to be −0.0572, 0.7335, and 2.2079, respectively. When comparing the images that were processed using the new digital filter based on these values with the original image, gray‐scale, green, red, blue, and green and blue digital filter images, the number of edges, effective edges, and sum of intensities of edges were all found to be significantly higher in the images processed with the new filter (P < 10–16).ConclusionsThe RGB filter developed here was based on actual fundus images. The hemoglobin absorbance reinforced the edges of retinal blood vessels, verifying that the new RGB filter can enhance the visualization of retinal vasculature.

Quantification of choroidal neovascularization vessel length using optical coherence tomography angiography.

Quantification of choroidal neovascularization (CNV) as visualized by optical coherence tomography angiography (OCTA) may have importance clinically when diagnosing or tracking disease. Here, we present an automated algorithm to quantify the vessel skeleton of CNV as vessel length. Initial segmentation of the CNV on en face angiograms was achieved using saliency-based detection and thresholding. A level set method was then used to refine vessel edges. Finally, a skeleton algorithm was applied to identify vessel centerlines. The algorithm was tested on nine OCTA scans from participants with CNV and comparisons of the algorithm’s output to manual delineation showed good agreement.

Longitudinal live imaging of retinal α-synuclein::GFP deposits in a transgenic mouse model of Parkinson's Disease/Dementia with Lewy Bodies.

Abnormal α-synuclein (α-syn) accumulation in the CNS may underlie neuronal cell and synaptic dysfunction leading to motor and cognitive deficits in synucleinopathies including Parkinson’s disease (PD) and Dementia with Lewy Bodies (DLB). Multiple groups demonstrated α-syn accumulation in CNS accessory structures, including the eyes and olfactory terminals, as well as in peripheral organs of Parkinsonian patients. Retinal imaging studies of mice overexpressing fused α-syn::GFP were conducted to evaluate the presence and progression of retinal pathology in a PD/DLB transgenic mouse model. Bright-field image retinal maps and fluorescent images were acquired at 1-month intervals for 3 months. Retinal imaging revealed the accumulation of GFP-tagged α-syn in retinal ganglion cell layer and in the edges of arterial blood vessels in the transgenic mice. Double labeling studies confirmed that the α-syn::GFP-positive cells were retinal ganglion cells containing α-syn. Accumulation of α-syn persisted in the same cells and increased with age. Accumulation of α-syn::GFP was reduced by immunization with single chain antibodies against α-syn. In conclusion, longitudinal live imaging of the retina in the PDGF-α-syn::GFP mice might represent a useful, non-invasive tool to monitor the fate of α-syn accumulation in the CNS and to evaluate the therapeutic effects of compounds targeting α-syn.

Investigation of partially-premixed combustion in a household cooker-top burner

The present paper provides an examination of the CH4/air flame in a self-aerated cooker-top burner currently in production. The operating conditions, the design characteristics and their effects on the combustion were investigated by calculating velocity, turbulence, temperature and reactive scalars using a modified temperature-composition pdf method. The two-stream nature of the problem allowed the use of the non-premixed formulation in that the calculations were started from the premixing chamber wherein fuel and air inflows were separated. The ingredients of the present study also included in-situ measurements of velocity with a PIV and the visualization of temperature by a line-of-sight infrared light detection system. The study shows that the current modelling of turbulent combustion is successful in predicting the location of the reaction zone as well as the shape and the properties of the flame. The results reveal that the present burner seems to produce flames which impinge only on the edges of the standard cooking vessel and lose the most of the available energy to the surrounding ambient air. Hence, the current flame position does not only reduce the thermal efficiency, but also re-cycles a large amount of burned gases into the premixing chamber. This situation decreases the aeration efficiency and eventually leads to an incomplete combustion and increased emissions of carbon monoxide. However, the flue gas recirculation also reduces the combustion intensity and the peak flame temperatures so that the thermal NO formation is expected to be inhibited.

Consistent treatment of viscoelastic effects at junctions in one-dimensional blood flow models

While the numerical discretization of one-dimensional blood flow models for vessels with viscoelastic wall properties is widely established, there is still no clear approach on how to couple one-dimensional segments that compose a network of viscoelastic vessels. In particular for Voigt-type viscoelastic models, assumptions with regard to boundary conditions have to be made, which normally result in neglecting the viscoelastic effect at the edge of vessels. Here we propose a coupling strategy that takes advantage of a hyperbolic reformulation of the original model and the inherent information of the resulting system. We show that applying proper coupling conditions is fundamental for preserving the physical coherence and numerical accuracy of the solution in both academic and physiologically relevant cases.

Fetal thymus size in human pregnancies reveals inverse association with regulatory T cell frequencies in cord blood

ObjectiveTo determine fetal thymus growth and its relationship with fetal weight and cord blood T-regulatory cells in a prospective study. Assessment of fetal immune organs by ultrasound could provide a screening approach to identify fetuses at risk of impaired postnatal immunity. Study design and outcome measuresThymus size was measured with four ultrasound techniques. The approaches with lowest coefficient of variation (thymus transverse diameter, 3 vessel edge) were used to longitudinally assess fetal and thymus growth in 137 cases at four time points between a gestational age (GA) of 13 and 37 weeks. Cord blood at birth was analyzed by flow-cytometry to evaluate the frequency of regulatory T (Treg) cells. Results and conclusionFetal thymus growth is significantly correlated with fetal weight (GA 23–25 weeks r=0.40, p<0.01; GA 28–30 weeks r=0.21, p=0.04, GA 35–37 weeks r=0.56, p<0.01). We observed an inverse correlation between fetal thymus size at GA 23–25 weeks and cord blood Treg cells (r=0.37, p=0.01). Thymus growth occurs in a linear fashion throughout pregnancy and can be reliably measured using ultrasound. Our findings of an inverse correlation between thymus growth and Treg cells in cord blood suggests a link between fetal growth, thymus development and immune-status at birth.

Application of Silicone Rubber Stents in Intracranial Arterial Microanastomosis for Vessels with Intimal Dissection:A Technical Note

Intracranial arterial microanastomosis remains an important neurosurgical technique. Intimal dissection of donor or recipient arteries can cause bypass failure. We used a silicone rubber stent while performing arterial microanastomoses, and achieved an excellent postoperative patency rate. In this study, we evaluated the efficacy of the stent in cases of extensive intimal dissection. In 5 cases involving extensive intimal dissection of vessels out of a total of 856 microanastomoses that were performed between November 2000 and August 2014, we placed a silicone rubber stent in the lumen of the recipient artery for donor to recipient suturing. Surgery was performed in 3 cases of cerebrovascular atherosclerotic disease and in 2 cases requiring cerebral revascularization for the treatment of aneurysm recurrence. In one of the 5 cases in which arterial microanastomosis was performed in the spasm period after subarachnoid hemorrhage, a patent anastomosis could not be confirmed. We observed the following advantages of silicone stent use: clear visualization of the orifice created in the vessel, avoidance of suturing or damaging the contralateral side vessel edges, and maintenance of the shape of the anastomosed vessel segment. These advantages made it easier to visualize the intima and to achieve fixation by using tacking sutures.

Ultra-High-Resolution Computed Tomography of the Lung: Image Quality of a Prototype Scanner.

PurposeThe image noise and image quality of a prototype ultra-high-resolution computed tomography (U-HRCT) scanner was evaluated and compared with those of conventional high-resolution CT (C-HRCT) scanners.Materials and MethodsThis study was approved by the institutional review board. A U-HRCT scanner prototype with 0.25 mm x 4 rows and operating at 120 mAs was used. The C-HRCT images were obtained using a 0.5 mm x 16 or 0.5 mm x 64 detector-row CT scanner operating at 150 mAs. Images from both scanners were reconstructed at 0.1-mm intervals; the slice thickness was 0.25 mm for the U-HRCT scanner and 0.5 mm for the C-HRCT scanners. For both scanners, the display field of view was 80 mm. The image noise of each scanner was evaluated using a phantom. U-HRCT and C-HRCT images of 53 images selected from 37 lung nodules were then observed and graded using a 5-point score by 10 board-certified thoracic radiologists. The images were presented to the observers randomly and in a blinded manner.ResultsThe image noise for U-HRCT (100.87 ± 0.51 Hounsfield units [HU]) was greater than that for C-HRCT (40.41 ± 0.52 HU; P < .0001). The image quality of U-HRCT was graded as superior to that of C-HRCT (P < .0001) for all of the following parameters that were examined: margins of subsolid and solid nodules, edges of solid components and pulmonary vessels in subsolid nodules, air bronchograms, pleural indentations, margins of pulmonary vessels, edges of bronchi, and interlobar fissures.ConclusionDespite a larger image noise, the prototype U-HRCT scanner had a significantly better image quality than the C-HRCT scanners.

Retinal vessel segmentation: an efficient graph cut approach with retinex and local phase.

Our application concerns the automated detection of vessels in retinal images to improve understanding of the disease mechanism, diagnosis and treatment of retinal and a number of systemic diseases. We propose a new framework for segmenting retinal vasculatures with much improved accuracy and efficiency. The proposed framework consists of three technical components: Retinex-based image inhomogeneity correction, local phase-based vessel enhancement and graph cut-based active contour segmentation. These procedures are applied in the following order. Underpinned by the Retinex theory, the inhomogeneity correction step aims to address challenges presented by the image intensity inhomogeneities, and the relatively low contrast of thin vessels compared to the background. The local phase enhancement technique is employed to enhance vessels for its superiority in preserving the vessel edges. The graph cut-based active contour method is used for its efficiency and effectiveness in segmenting the vessels from the enhanced images using the local phase filter. We have demonstrated its performance by applying it to four public retinal image datasets (3 datasets of color fundus photography and 1 of fluorescein angiography). Statistical analysis demonstrates that each component of the framework can provide the level of performance expected. The proposed framework is compared with widely used unsupervised and supervised methods, showing that the overall framework outperforms its competitors. For example, the achieved sensitivity (0:744), specificity (0:978) and accuracy (0:953) for the DRIVE dataset are very close to those of the manual annotations obtained by the second observer.

Automated Vessel Segmentation Using Infinite Perimeter Active Contour Model with Hybrid Region Information with Application to Retinal Images.

Automated detection of blood vessel structures is becoming of crucial interest for better management of vascular disease. In this paper, we propose a new infinite active contour model that uses hybrid region information of the image to approach this problem. More specifically, an infinite perimeter regularizer, provided by using L(2) Lebesgue measure of the γ -neighborhood of boundaries, allows for better detection of small oscillatory (branching) structures than the traditional models based on the length of a feature's boundaries (i.e., H(1) Hausdorff measure). Moreover, for better general segmentation performance, the proposed model takes the advantage of using different types of region information, such as the combination of intensity information and local phase based enhancement map. The local phase based enhancement map is used for its superiority in preserving vessel edges while the given image intensity information will guarantee a correct feature's segmentation. We evaluate the performance of the proposed model by applying it to three public retinal image datasets (two datasets of color fundus photography and one fluorescein angiography dataset). The proposed model outperforms its competitors when compared with other widely used unsupervised and supervised methods. For example, the sensitivity (0.742), specificity (0.982) and accuracy (0.954) achieved on the DRIVE dataset are very close to those of the second observer's annotations.

Calibration-free coronary artery measurements for interventional device sizing using inverse geometry x-ray fluoroscopy: in vivo validation.

Proper sizing of interventional devices to match coronary vessel dimensions improves procedural efficiency and therapeutic outcomes. We have developed a method that uses an inverse geometry x-ray fluoroscopy system [scanning beam digital x-ray (SBDX)] to automatically determine vessel dimensions from angiograms without the need for magnification calibration or optimal views. For each frame period (1/15th of a second), SBDX acquires a sequence of narrow beam projections and performs digital tomosynthesis at multiple plane positions. A three-dimensional model of the vessel is reconstructed by localizing the depth of the vessel edges from the tomosynthesis images, and the model is used to calculate the length and diameter in units of millimeters. The in vivo algorithm performance was evaluated in a healthy porcine model by comparing end-diastolic length and diameter measurements from SBDX to coronary computed tomography angiography (CCTA) and intravascular ultrasound (IVUS), respectively. The length error was -0.49 ± 1.76 mm(SBDX- CCTA, mean ± 1 SD). The diameter error was 0.07 ± 0.27 mm (SBDX - minimum IVUS diameter, mean ± 1 SD). The in vivo agreement between SBDX-based vessel sizing and gold standard techniques supports the feasibility of calibration-free coronary vessel sizing using inverse geometry x-ray fluoroscopy.

Development and reliability of retinal arteriolar central light reflex quantification system: a new approach for severity grading.

To describe the methodology and assess the reliability of novel computer-based semiautomated software that quantifies retinal arteriolar central light reflex (CR) from digital retinal photographs. A total of 150 optic disc-centered digital color retinal photographs were selected from a population-based cross-sectional study of persons aged 40 to 80 years (the Singapore Malay Eye Study [SiMES]). Computer-assisted software was developed to quantify retinal arteriolar CR by selecting vessel edge points semiautomatically. This software then automatically computes the CR, vessel diameter, and the CR-to-vessel diameter ratio (CRR). Reliability was assessed using the intraclass correlation coefficient (ICC) and Bland-Altman plots. Multiple linear regression analyses were performed to assess the associations between CRR and systemic and ocular factors, to further validate the novel software. The ICCs for the intergrader and intragrader CRR measurement were 0.76 (95% confidence interval [CI] 0.53-0.89) and 0.86 (95% CI 0.67-0.94), respectively. The ICC for intravisit repeatability was 0.87 (95% CI 0.71-0.95). In the multivariate model, a higher CRR was associated with elevated mean arterial blood pressure (per 10 mm Hg increase) (β = 0.017, P < 0.001). Quantitative assessment of retinal arteriolar wall opacification is a reliable method using a new computer-assisted system. This new CRR measurement system is a potentially useful tool to study retinal arteriolar abnormalities with systemic diseases.

Ubersense: using a free video analysis app to evaluate and improve microsurgical skills.

Sir: As surgical residency programs move toward more objective-based training protocols, curricula will need to include tangible measures of the advancement of a surgical trainee.1,2 The evaluation of microsurgical skills lacks the standardized criteria necessary for an adequate assessment, and in a world dominated by metrics, developing a reproducible, valid, low-cost, and easy-to-administer evaluation instrument is essential for self-improvement.3 Recent reports have used an online video system to assess microsurgical skills.4 In a similar fashion, the authors present the use of emerging technology in video analysis to improve microsurgical skills. Ubersense, a free and already available iPod/iPad App, allows athletes and coaches to improve their performance through “slow-motion video analysis.” Videos of the desired activity are captured and subsequently uploaded. The video can be analyzed at slower speeds or in a frame-by-frame fashion. The drawing tool allows marks to be made on the video, including various measurements (i.e., the angle a golf driver makes with the body at the highest point of a backswing). The video can be trimmed, and the user can view videos uploaded by others. A video can be simultaneously compared in a side-by-side fashion with any other video recording (Fig. 1). This technology is directly applicable to microsurgical training.Fig. 1: Video comparison of a golf swing before and after adjustments.A video of a senior surgeon placing microsurgical sutures is taken from the operating microscope, and the same is done for a trainee. These videos are uploaded to Ubersense, and each video is analyzed in a frame-by-frame fashion to obtain data points: Needle-to–needle driver angle. Needle tip–to–needle driver distance. The distance of suture entry and exit in relationship to the vessel edge. Needle-to–vessel wall angle. Suture tail length. Number of ancillary movements. Time to completion. The data points obtained from the two are compared, and the differences are calculated. The videos are then viewed in a side-by-side fashion to appreciate the differences between the senior staff and the trainee (Fig. 2). When the video analysis is reviewed together, opportunities for development arise as the senior surgeon can demonstrate exactly what the trainee can improve on by having a “correct” version to directly compare to.Fig. 2: Side-by-side video comparison of senior staff and resident trainee performing microsurgery. Immediate comparisons can be made and feedback given based on the differences seen in the video comparison.Although we have only begun using this technology to evaluate microsurgical skills, the possibilities are numerous. A compendium of norms for the data points mentioned previously could be compiled to calculate a true standard, which the trainees could be evaluated against. Trainees could view videos of their own progress in a side-by-side fashion to ensure their skills are advancing. Experts could upload videos of different suture techniques, and trainees could then compare their technique with mentors that are not directly available at their institution. This can all be accomplished with zero cost to the trainee or the institution. Therefore, we encourage readers to download the application and begin using the technology—athletes are not the only ones who can “raise their game.” SUBJECT CONSENT The man shown in Figure 1 provided written consent for the use of his images. DISCLOSURE The authors have no commercial associations or disclosures that might pose or create a conflict of interest with the information presented in this article. Ajul Shah, M.D. Megan Rowlands, B.S. Anup Patel, M.D., M.B.A. Stefano Fusi, M.D. Jeffrey Salomon, M.D. Section of Plastic and Reconstructive Surgery Yale University School of Medicine New Haven, Conn.

Cerebral aneurysm pulsation: do iterative reconstruction methods improve measurement accuracy in vivo?

Electrocardiogram-gated 4D-CTA is a promising technique allowing new insight into aneurysm pathophysiology and possibly improving risk prediction of cerebral aneurysms. Due to the extremely small pulsational excursions (<0.1 mm in diameter), exact segmentation of the aneurysms is of critical importance. In vitro examinations have shown improvement of the accuracy of vessel delineation by iterative reconstruction methods. We hypothesized that this improvement shows a measurable effect on aneurysm pulsations in vivo. Ten patients with cerebral aneurysms underwent 4D-CTA. Images were reconstructed with filtered back-projection and iterative reconstruction. The following parameters were compared between both groups: image noise, absolute aneurysm volumes, pulsatility, and sharpness of aneurysm edges. In iterative reconstruction images, noise was significantly reduced (mean, 9.8 ± 4.0 Hounsfield units versus 8.0 ± 2.5 Hounsfield units; P = .04), but the sharpness of aneurysm edges just missed statistical significance (mean, 3.50 ± 0.49 mm versus 3.42 ± 0.49 mm; P = .06). Absolute volumes (mean, 456.1 ± 775.2 mm(3) versus 461.7 ± 789.9 mm(3); P = .31) and pulsatility (mean, 1.099 ± 0.088 mm(3) versus 1.095 ± 0.082 mm(3); P = .62) did not show a significant difference between iterative reconstruction and filtered back-projection images. CT images reconstructed with iterative reconstruction methods show a tendency toward shorter vessel edges but do not affect absolute aneurysm volumes or pulsatility measurements in vivo.

A retinal vessel boundary tracking method based on Bayesian theory and multi-scale line detection

A retinal vessel tracking method based on Bayesian theory and multi-scale line detection is proposed in this paper. The optic disk is located by a PCA method and the initial points of tracking are identified. In each step, candidate points for vessel edges are selected on a semi-ellipse. Three types of vessel structure are considered in the tracking: normal vessel, branching, and crossing. To determine the new pair of edge points, the characteristics of the vessel intensity profiles along both the cross section and the longitudinal direction are considered in the tracking. A Gaussian model is assumed in the cross section and multi-scale line detection is employed in the longitudinal direction. The advantage of the proposed method is that two dimensional vessel information is employed, which makes it work better than methods using one dimensional information only. Our method is tested on the REVIEW database and a comparison study is performed. Experimental results show that the proposed method is precise and robust in tracking vessel edges.

English

An automated classification of coronary artery disease using discrete wavelet watershed transform and back propagation neural network has been proposed which basically segments the blood vessels of the coronary angiogram image as a first step, which in turn&nbsp; involves various stages such as pre-processing, image enhancement, and segmentation using discrete wavelet transform and watershed transform along with morphological operations. Pre-processing is done to remove the noise using the bicubic interpolation method followed by Daubechies 4 discrete wavelet transform and Weiner filtering. Further, image enhancement is done to improve the quality of the image using the histogram equalization technique. Auto thresholding is done to segment the edges of the blood vessel accurately and efficiently using distance and watershed transforms followed by normalization and median filtering. Finally, morphological operations are performed to remove the noise due to segmentation. Features such as area, mean, standard deviation, variance, brightness, diameter, smoothness, compactness, skewness, kurtosis, eccentricity and circularity are extracted from the segmented coronary blood vessel to train the neural network using back propagation network. Thus, the system is able to achieve 93.75% normal classification and 83.33% abnormal classification. Also, 90% efficiency is achieved in classifying Type 1 and 92% efficiency is achieved in classifying Type 2 stenosis at a learning rate of 0.7 and Type 1 classification efficiency of 85% and Type 2 classification of 89% has been achieved for 50 hidden units of the neural network. Key words: Coronary artery disease, discrete wavelet transform, watershed transform, morphological operations, back propagation neural network.

High Spatial Resolution Coronary Magnetic Resonance Angiography at 7 T

The aim of this study was to compare bright blood high spatial resolution (HR) coronary magnetic resonance angiography (MRA) with low spatial resolution (LR) bright blood coronary MRA at 7 T. Twenty-four healthy volunteers underwent navigator-gated 3-dimensional imaging of the right coronary artery at 7 T using 2 sequences: HR bright blood and LR bright blood. Image postprocessing involved newly developed multiplanar reformatting to straighten the right coronary artery. Image quality was determined by vessel edge sharpness, signal-to-noise ratio, contrast-to-noise ratio, visible vessel length, and vessel diameter. Vessel edge sharpness was statistically significantly higher in HR as compared with LR (0.57 ± 0.1 vs 0.46 ± 0.06; P < 0.001), at the cost of lower signal-to-noise ratio (HR, 32.9 ± 11.0 vs LR, 112.5 ± 48.9; P < 0.001) and contrast-to-noise ratio (HR, 17.9 ± 7.4 vs LR, 50.5 ± 26.1; P < 0.001). Visible vessel length and vessel diameter were similar for both sequences (P > 0.05). High spatial resolution bright blood coronary MRA at 7 T is feasible and improves vessel edge sharpness as compared with LR bright blood imaging.

A Pilot Quantitative Study of Topographic Correlation between Reticular Pseudodrusen and the Choroidal Vasculature Using En Face Optical Coherence Tomography

PurposeTo analyze the topographic correlation between reticular pseudodrusen (RPD) visualized on infrared reflectance (IR) and choroidal vasculature using en-face volumetric spectral-domain optical coherence tomography (SD-OCT).MethodsA masked observer marked individual RPD on IR images using ImageJ (NIH, Bethesda, MD). Using the macular volume scan (Cirrus, Carl Zeiss Meditec Inc, Dublin, CA), the RPE slab function was used to generate a C-scan of the most superficial choroidal vasculature. An independent masked grader created a topographic binary map of the choroidal vasculature by thresholding the en-face image, which was overlaid onto the IR map of RPD. For each IR image, ImageJ was used to generate a random set of dots as “control lesions”.Results17 eyes of 11 patients (78±13.7 years) with RPD were analyzed. The average number of RPD lesions identified on IR images was 414±71.5, of which 49.6±4.3% were located overlying the choroidal vasculature, compared to 45.4±4.0% in controls (p = 0.014). 50.4±4.3% of lesions overlay the choroidal stroma, of which 76.5±3.1% were ≤3 pixels from the choroidal vessels. The percentage of RPD lesions located within ≤3 pixels from the choroidal vasculature was significantly greater than the percentage located ≥7 pixels away. (p<0.0001). Compared to controls (71.6±3.8%), RPD were more likely to be located ≤3 pixels away from choroidal vessels (p = 0.014). In contrast, control lesions were more likely to be ≥7 pixels away from choroidal vessels than RPD (9.1±1.9% vs. 4.8±1.2%, respectively, p = 0.002).ConclusionsOur analysis shows that RPD lesions follow the underlying choroidal vasculature. Approximately half the RPD directly overlay the choroidal vessels and the majority of the remaining lesions were ≤3 pixels (≤30microns) from the vessel edge, supporting the hypothesis that RPD maybe related to pathologic changes at the choroidal level.