The impact of pre-treatment aneurysm angulation. What happens with WEB devices at follow-up?

Background: WEB shape modification has been analyzed in relation to the aneurysm occlusion outcome and techniques have been presented with one-dimensional measurements of the device to quantify the change after implantation. In this work, we present an analysis of pre-treatment vascular morphology and hemodynamics of cases treated with WEB devices, which were three-dimensionally quantified in morphology and position to detect modifications.

Methods: Seventeen WEB-treated aneurysms with pre-treatment, post-treatment and follow-up 3D flat-panel CT were included.

A Self-supervised Deep Learning Model for Diagonal Sulcus Detection with Limited Labeled Data.

Sulci are a fundamental part of brain morphology, closely linked to brain function, cognition, and behavior. Tertiary sulci, characterized as the shallowest and smallest subtype, pose a challenging task for detection. The diagonal sulcus (ds), located in a crucial area in language processing, has a prevalence between 50% and 60%.

Assessing flow diverter porosity: a comparative analysis of quantification techniques based on imaging and simulation.

Background/purpose: Flow diverter porosity directly influences the blood flow reduction at the aneurysm neck level and the anatomical result of the treatment. In this research, we present and compare three methodologies to determine the local porosity of deployed flow diverters.

Method: Three-dimensional rotational angiography was used to obtain computational vessel models of three patients.

Modification of Woven Endo-Bridge After Intracranial Aneurysm Treatment: A Methodology for Three-Dimensional Analysis of Shape and Relative Position Changes.

During follow-up of patients treated with WEB devices, shape changes have been observed. The quantitative three-dimensional measurement of the WEB shape modification (WSM) would offer useful information to be studied in association with the anatomical results and try to better understand mechanisms implicated in this modification phenomenon. We present a methodology to quantify the morphology and position of the WEB device in relation to the vascular anatomy.

Evaluating sleep-stage classification: how age and early-late sleep affects classification performance.

Sleep stage classification is a common method used by experts to monitor the quantity and quality of sleep in humans, but it is a time-consuming and labour-intensive task with high inter- and intra-observer variability. Using wavelets for feature extraction and random forest for classification, an automatic sleep-stage classification method was sought and assessed. The age of the subjects, as well as the moment of sleep (early-night and late-night), were confronted to the performance of the classifier.

Comparative Study of Automated Algorithms for Brain Arteriovenous Malformation Nidus Extent Identification Using 3DRA.

Purpose: When performing a brain arteriovenous malformation (bAVMs) intervention, computer-assisted analysis of bAVMs can aid clinicians in planning precise therapeutic alternatives. Therefore, we aim to assess currently available methods for bAVMs nidus extent identification over 3DRA. To this end, we establish a unified framework to contrast them over the same dataset, fully automatising the workflows.

NORHA: A NORmal Hippocampal Asymmetry Deviation Index Based on One-Class Novelty Detection and 3D Shape Features.

Radiologists routinely analyze hippocampal asymmetries in magnetic resonance (MR) images as a biomarker for neurodegenerative conditions like epilepsy and Alzheimer's Disease. However, current clinical tools rely on either subjective evaluations, basic volume measurements, or disease-specific models that fail to capture more complex differences in normal shape. In this paper, we overcome these limitations by introducing NORHA, a novel NORmal Hippocampal Asymmetry deviation index that uses machine learning novelty detection to objectively quantify it from MR scans.

Simulation of intra-saccular devices for pre-operative device size selection: Method and validation for sizing and porosity simulation.

Intra-saccular devices (ID) are novel braided devices used for complex intracranial aneurysms treatment. Treatment success is associated with correct device size selection. A technique that predicts the ID size within the aneurysm before intervention will provide a powerful computational tool to aid the interventionist during device selection.

Cerebral Aneurysm Occlusion at 12-Month Follow-Up After Flow-Diverter Treatment: Statistical Modeling for V&V With Real-World Data.

Flow-Diverter (FD) porosity has been pointed as a critical factor in the occlusion of cerebral aneurysms after treatment. Verification and Validation of computational models in terms of predictive capacity, relating FD porosity and occlusion after cerebral aneurysms treatment. Sixty-four aneurysms, with pre-treatment and follow-up images, were considered.

Intra-saccular device modeling for treatment planning of intracranial aneurysms: from morphology to hemodynamics.

Motivation: Intra-saccular devices (ID), developed for the treatment of bifurcation aneurysms, offer new alternatives for treating complex terminal and bifurcation aneurysms. In this work, a complete workflow going from medical images to post-treatment CFD analysis is described and used in the assessment of a concrete clinical problem.

Materials And Methods: Two different intra-saccular device sizes were virtually implanted in 3D models of the patient vasculature using the ID-Fit method.

Machine learning for filtering out false positive grey matter atrophies in single subject voxel based morphometry: A simulation based study.

Single subject VBM (SS-VBM), has been used as an alternative tool to standard VBM for single case studies. However, it has the disadvantage of producing an excessively large number of false positive detections. In this study we propose a machine learning technique widely used for automated data classification, namely Support Vector Machine (SVM), to refine the findings produced by SS-VBM.

Stenting as porous media in anatomically accurate geometries. A comparison of models and spatial heterogeneity.

Modelling intracranial aneurysm blood flow after flow diverter treatment has proven to be of great scientific and clinical interest. One of the reasons for not having CFD as an everyday clinical tool yet is the time required to set-up such simulations plus the required computational time. The speed-up of these simulations can have a considerable impact during treatment planning and device selection.

VBM sensitivity to localization and extent of mouse brain lesions: A simulation approach.

Background And Objectives: Voxel-based morphometry (VBM) is a popular neuroimaging technique, used to detect and quantify morphological differences in brain tissues between groups. Widely used in human studies, VBM approaches have tremendous potential for neuroimaging studies in animal models. A significant challenge for applying VBM to small animal studies is the poor understanding of how the design of preprocessing pipelines impacts quantitative results.

Regional assessment of vascular morphology and hemodynamics: methodology and evaluation for abdominal aortic aneurysms after endovascular repair.

Abdominal aortic aneurysm is a deadly disease that can be treated with different endovascular devices that will distinctly alter the aortic morphology. Computational methods can be used to understand the effect of anatomical changes on aortic hemodynamics. We propose a standardized method to assess morphological and hemodynamic changes of the abdominal aorta through the longitudinal axis of the vessel.

Role of distal cerebral vasculature in vessel constriction after aneurysm treatment with flow diverter stents.

Background: Treatment of intracranial aneurysms with flow diverter stent (FDS) procedures can lead to caliber changes of jailed vessels. The reason some branches remain unchanged and others are affected by narrowing remains unknown.

Objective: To investigate the influence of resistance to flow from distal vasculature on stent-induced hemodynamic modifications affecting bifurcating vessels.

Improving realism in patient-specific abdominal ultrasound simulation using CycleGANs.

Purpose: In this paper, we propose to apply generative adversarial neural networks trained with a cycle consistency loss, or CycleGANs, to improve realism in ultrasound (US) simulation from computed tomography (CT) scans.

Methods: A ray-casting US simulation approach is used to generate intermediate synthetic images from abdominal CT scans. Then, an unpaired set of these synthetic and real US images is used to train CycleGANs with two alternative architectures for the generator, a U-Net and a ResNet.

Lumen-intima and media-adventitia segmentation in IVUS images using supervised classifications of arterial layers and morphological structures.

Background: Intravascular ultrasound (IVUS) provides axial grey-scale images of blood vessels. The large number of images require automatic analysis, specifically to identify the lumen and outer vessel wall. However, the high amount of noise, the presence of artifacts and anatomical structures, such as bifurcations, calcifications and fibrotic plaques, usually hinder the proper automatic segmentation of the vessel wall.

Improved biomechanical metrics of cerebral vasospasm identified via sensitivity analysis of a 1D cerebral circulation model.

Cerebral vasospasm (CVS) is a life-threatening condition that occurs in a large proportion of those affected by subarachnoid haemorrhage and stroke. CVS manifests itself as the progressive narrowing of intracranial arteries. It is usually diagnosed using Doppler ultrasound, which quantifies blood velocity changes in the affected vessels, but has low sensitivity when CVS affects the peripheral vasculature.

Software-based simulation for preprocedural assessment of braided stent sizing: a validation study.

Objective: The authors sought to validate the use of a software-based simulation for preassessment of braided self-expanding stents in the treatment of wide-necked intracranial aneurysms.

Methods: This was a retrospective, observational, single-center study of 13 unruptured and ruptured intracranial aneurysms treated with braided self-expanding stents. Pre- and postprocedural angiographic studies were analyzed.

Real-World Variability in the Prediction of Intracranial Aneurysm Wall Shear Stress: The 2015 International Aneurysm CFD Challenge.

Purpose: Image-based computational fluid dynamics (CFD) is widely used to predict intracranial aneurysm wall shear stress (WSS), particularly with the goal of improving rupture risk assessment. Nevertheless, concern has been expressed over the variability of predicted WSS and inconsistent associations with rupture. Previous challenges, and studies from individual groups, have focused on individual aspects of the image-based CFD pipeline.

A comparative study of porous medium CFD models for flow diverter stents: Advantages and shortcomings.

In computational fluid dynamics, there is a high interest in modeling flow diverter stents as porous media due to its reduced computational loads. One of the main difficulties of such models is proper parameter setup. Most authors assume flow diverter's wire screen as an isotropic and homogeneous medium, while others proposes anisotropic configurations, yet very little is discussed about the effect of these assumptions on model's accuracy.

Effects on Aortoiliac Fluid Dynamics After Endovascular Sealing of Abdominal Aneurysms.

Objectives:: To evaluate the effects on aortoiliac fluid dynamics after the implantation of an endograft based on endovascular aneurysm sealing (EVAS) versus endovascular aneurysm repair (EVAR) strategy.

Methods:: An adaptive geometrical deformable model was used for aortic lumen segmentation in 8 patients before and after the surgery. Abdominal aneurysms were treated with an endograft based on the EVAS system (Nellix, n = 4) and with a device based on an anatomical fixation technology (n = 4).

Carotid Intima Media Thickness Reference Intervals for a Healthy Argentinean Population Aged 11-81 Years.

Reference intervals (RIs) of carotid intima media thickness (CIMT) from large healthy population are still lacking in Latin America. The aim of this study was to determine CIMT RIs in a cohort of 1012 healthy subjects from Argentina. We evaluated if RIs for males and females and for left and right carotids were necessary.

Validation of an Open-Source Tool for Measuring Carotid Lumen Diameter and Intima-Media Thickness.

In low- and middle-income regions, a relatively large number of deaths occur from cardiovascular disease or stroke. Carotid intima-media thickness (cIMT) and carotid lumen diameter (cLD) are strong indicators of cardiovascular event risk and stenosis severity, respectively. The interactive open-source software described here, Cimtool, is based on active contours for measuring these indicators in clinical practice and thus helping in preventive diagnosis and treatment.