Abstract 1122‐000188: 3D Analysis of Atherosclerotic Plaque Enhancement and the Parent Vessel

Introduction : High resolution vessel wall imaging (HR‐VWI) is a promising tool in studying intracerebral atherosclerotic disease. The analysis of the interplay between the patterns of enhancement between the plaque and its parent vessel can generate further insights on the biology of these lesions. We have developed a 3D method of plaque and parent vessel analysis. Methods : Images from fifty‐five plaques were obtained using 7T HR‐VWI. T1 and T1+Gd sequences were performed. 3D reconstructions of the plaque and its parent vessel were generated with 3D Slicer. Using an in‐house code, probes were orthogonally extended from the lumen of the vessel into the vessel wall and the plaque. Signal intensity values were then normalized to the corpus callosum. 3D heat maps and histograms were generated from hundreds of data points. A detailed analysis of the morphology of the histograms was performed to determine the uptake of gadolinium (Gd) by the parent vessel and the plaque. Variations in the width of the histogram were measured with the standard deviation. Results : Forty‐one patients with 55 plaques (41 culprit and 15 non culprit) were included. There was no difference in enhancement in T1‐pre between culprit and non‐culprit plaques when compared to the parent vessel (width = 0.14 ± 0.05 and 0.14 ± 0.03, respectively; p = 0.91). On the T1+Gd culprit plaques were significantly more enhancing compared to the parent vessel (0.26 ± 0.10) than non‐culprit plaques (0.20 ± 0.06) (p = 0.02). The presence of an enhancing plaque creates a bimodal distribution that increases the width of the histogram curve (figure). Conclusions : Culprit plaques exhibit different patterns of enhancement relative to the parent vessel compared to non‐culprit plaques. Histogram analysis of the parent vessel and its plaques provides a new set of metrics that may be used as a biomarker of disease progression.

Susceptibility to capillary plugging can predict brain region specific vessel loss with aging

Vessel loss in the aging brain is commonly reported, yet important questions remain concerning whether there are regional vulnerabilities and what mechanisms could account for these regional differences, if they exist. Here we imaged and quantified vessel length, tortuosity and width in 15 brain regions in young adult and aged mice. Our data indicate that vessel loss was most pronounced in white matter followed by cortical, then subcortical grey matter regions, while some regions (visual cortex, amygdala, thalamus) showed no decline with aging. Regions supplied by the anterior cerebral artery were more vulnerable to loss than those supplied by middle or posterior cerebral arteries. Vessel width and tortuosity generally increased with age but neither reliably predicted regional vessel loss. Since capillaries are naturally prone to plugging and prolonged obstructions often lead to vessel pruning, we hypothesized that regional susceptibilities to plugging could help predict vessel loss. By mapping the distribution of microsphere-induced capillary obstructions, we discovered that regions with a higher density of persistent obstructions were more likely to show vessel loss with aging and vice versa. These findings indicate that age-related vessel loss is region specific and can be explained, at least partially, by regional susceptibilities to capillary plugging.

Optical coherence tomography angiography for the assessment of choroidal vasculature in high myopia

AimsTo assess specific layers of the choroid in highly myopic young adults and to examine their associations with levels of myopia.MethodsWe recruited 51 young myopes (n=91 eyes) from the Singapore Cohort of Risk Factors for Myopia cohort. We performed standardised optical coherence tomography (OCT) and OCT angiography imaging and developed a novel segmentation technique assessing choroidal layers’ thickness (overall choroidal thickness (CT), medium-vessel choroidal layer (MVCL) thickness, large-vessel choroidal layer (LVCL)) and vasculature (choroidal vessel density (%), choroidal branch area (CBA, %) and mean choroidal vessel width (MCVW, mm)).ResultsWe found that eyes with extreme myopia (EM) had thinner vascular layers compared with high myopia (HM), that is, LVCL (36.0±1.5 vs 39.2±1.2 µm, p=0.002) and MVCL (185.5±5.7 vs 198.2±4.6 µm, p=0.014). Overall CT was thinnest in the nasal and inferior quadrants in EM (nasal: 157.1±9.6 vs 187.2±8.3 µm, p<0.001; superior: 236.6±11.1 vs 257.0±9.5 µm, p=0.02; temporal: 228.0±10.6 vs 254.3±8.8 µm, p=0.012; and inferior quadrant: 198.7±10.0 vs 239.8±8.3 µm, p=<0.001) when compared with HM. We also observed significantly more vessel branching in eyes with EM as compared with eyes with HM (CBA, 10.2%±0.7% vs 9.95%±0.8%, p=0.018).ConclusionsThe novel segmentation technique and introduced choroidal parameters may serve as new biomarkers to study disease conditions in myopia.

Retinal Image Vessel Width Analysis in Retinopathy of Prematurity

This paper aims at development of Oscillating Pendulum Based Algorithm (OPBA) for retinal image width computation and analysis for the investigation of Retinopathy of prematurity (ROP). The algorithms have been explained in detail with theoretical investigations and simulations, images from local hospital data base were considered in the investigation. Further this paper also presents an overview of direct retinal vessel width computation method along with the comparative analysis. The results obtained are found to be encouraging for analysis of plus disease under ROP.

Boundary Extraction and Vessel Width Calculation in Retinal Fundus Images

A retinal vessel width measurement algorithm is presented towards ROP (Retinopathy of Prematurity) plus diagnostic automation. The algorithm involving geometrical feature extraction with the image processing is used to compute the effective width of the major vessels in a retinal image. Width measurement is shown to be a statistical parameter estimation related to the statistics of the retinal information. The algorithm is applied to the generic data bases available and the results are found to be satisfactory with ophthalmologist opinion. The effectiveness of the algorithm depends on the fundus image capturing settings.

A Novel Retinal Recognition System for Pathological Retina To Enhance Security

Biometric acknowledgment gives a characteristic and solid answer for the issue of individual distinguishing proof. One of the biometric ID framework utilized with high exactness is the retinal verification as a result of its many-sided quality in spoofing. However in these frameworks, acknowledgment rate is enormously influenced by the vasculature multifaceted nature of retinal images. This vascular example turns out to be exceptionally perplexing in sick retinal pictures because of the nearness of obsessive signs. In this manner, we require a computerized productive calculation which can evacuate these abnormalities before matching and decision making. The proposed novel hybrid clustering algorithm Adaptive Weighted Neighbour (AWN) Classification Algorithm classifies the input retinal image based on the features extracted and match the features with the trained features. The proposed feature vector consists of blood vessel structure, bifurcation points, bifurcation angles and vessel width. Results from the AWN are compared with state of the art classifier. It enables high security, good performance and greater accuracy. Also it provides better FAR, FRR and decreases the error rate.