Cardiac CT fractal analysis of LV noncompaction and common cardiomyopathies.

Background: Left ventricular noncompaction (LVNC), or hypertrabeculation, is a myocardial condition that remains challenging to diagnose and differentiate from other cardiomyopathies. This study evaluated the ability of cardiac CT to differentiate between LVNC, hypertrophic cardiomyopathy (HCM), dilated cardiomyopathy (DCM), and controls using fractal analysis of LV trabeculae.

Methods: Subjects with LVNC, HCM, DCM, as well as controls, who underwent coronary CT angiography were included.

Predicting Late Adverse Events in Uncomplicated Stanford Type B Aortic Dissection: Results From the ROADMAP Validation Study.

Background: Risk stratification is highly desirable in patients with uncomplicated Stanford type B aortic dissection but inadequately supported by evidence. We sought to validate externally a published prediction model for late adverse events (LAEs), consisting of 1 clinical (connective tissue disease) and 4 imaging variables: maximum aortic diameter, false lumen circumferential angle, false lumen outflow, and number of identifiable intercostal arteries.

Methods: We assembled a retrospective multicenter cohort (ROADMAP [Registry of Aortic Diseases to Model Adverse Events and Progression]) of 401 patients with uncomplicated Stanford type B aortic dissection presenting to 1 of 8 aortic centers between 2001 and 2013, followed until 2020.

Assessment of Aortic Dissection Remodeling With Patient-Specific Fluid-Structure Interaction Models.

Aortic dissection leads to late complications due tochronic degeneration and dilatation of the false lumen. This study examines the interaction between hemodynamics and long-term remodeling of a patient's aortic dissection, tracked from pre-dissection to the chronic phase using CT angiography. Fluid-structure interaction models with tissue prestress, external support, and anisotropic properties were used to analyze hemodynamic markers.

Early three-dimensional growth in uncomplicated type B aortic dissection is associated with long-term outcomes.

Objective: Late adverse events (LAEs) are common among initially uncomplicated type B aortic dissection (uTBAD); however, identifying those patients at highest risk of LAEs remains a significant challenge. Early false lumen (FL) growth has been suggested to increase risk, but confident determination of growth is often hampered by error in two-dimensional clinical measurements. Semi-automated three-dimensional (3D) mapping of aortic growth, such as by vascular deformation mapping (VDM), can potentially overcome this limitation using computed tomography angiograms (CTA).

Quantitative metrics of the LV trabeculated layer by cardiac CT and cardiac MRI in patients with suspected noncompaction cardiomyopathy.

Objectives: To compare cardiac computed tomography (CCT) and cardiac magnetic resonance (CMR) for the quantitative assessment of the left ventricular (LV) trabeculated layer in patients with suspected noncompaction cardiomyopathy (NCCM).

Materials And Methods: Subjects with LV excessive trabeculation who underwent both CMR and CCT imaging as part of the prospective international multicenter NONCOMPACT clinical study were included. For each subject, short-axis CCT and CMR slices were matched.

Automated cross-sectional view selection in CT angiography of aortic dissections with uncertainty awareness and retrospective clinical annotations.

Surveillance imaging of patients with chronic aortic diseases, such as aneurysms and dissections, relies on obtaining and comparing cross-sectional diameter measurements along the aorta at predefined aortic landmarks, over time. The orientation of the cross-sectional measuring planes at each landmark is currently defined manually by highly trained operators. Centerline-based approaches are unreliable in patients with chronic aortic dissection, because of the asymmetric flow channels, differences in contrast opacification, and presence of mural thrombus, making centerline computations or measurements difficult to generate and reproduce.

Inter-observer variability of expert-derived morphologic risk predictors in aortic dissection.

Objectives: Establishing the reproducibility of expert-derived measurements on CTA exams of aortic dissection is clinically important and paramount for ground-truth determination for machine learning.

Methods: Four independent observers retrospectively evaluated CTA exams of 72 patients with uncomplicated Stanford type B aortic dissection and assessed the reproducibility of a recently proposed combination of four morphologic risk predictors (maximum aortic diameter, false lumen circumferential angle, false lumen outflow, and intercostal arteries). For the first inter-observer variability assessment, 47 CTA scans from one aortic center were evaluated by expert-observer 1 in an unconstrained clinical assessment without a standardized workflow and compared to a composite of three expert-observers (observers 2-4) using a standardized workflow.

Deep Learning-Based 3D Segmentation of True Lumen, False Lumen, and False Lumen Thrombosis in Type-B Aortic Dissection.

Patients with initially uncomplicated typeB aortic dissection (uTBAD) remain at high risk for developing late complications. Identification of morphologic features for improving risk stratification of these patients requires automated segmentation of computed tomography angiography (CTA) images. We developed three segmentation models utilizing a 3D residual U-Net for segmentation of the true lumen (TL), false lumen (FL), and false lumen thrombosis (FLT).

Semi-automatic vessel detection for challenging cases of peripheral arterial disease.

Objectives: Manual or semi-automated segmentation of the lower extremity arterial tree in patients with Peripheral arterial disease (PAD) remains a notoriously difficult and time-consuming task. The complex manifestations of the disease, including discontinuities of the vascular flow channels, the presence of calcified atherosclerotic plaque in close vicinity to adjacent bone, and the presence of metal or other imaging artifacts currently preclude fully automated vessel identification. New machine learning techniques may alleviate this challenge, but require large and reasonably well segmented training data.

CT-based True- and False-Lumen Segmentation in Type B Aortic Dissection Using Machine Learning.

Purpose: To develop a segmentation pipeline for segmentation of aortic dissection CT angiograms into true and false lumina on multiplanar reformations (MPRs) perpendicular to the aortic centerline and derive quantitative morphologic features, specifically aortic diameter and true- or false-lumen cross-sectional area.

Materials And Methods: An automated segmentation pipeline including two convolutional neural network (CNN) segmentation algorithms was developed. The algorithm derives the aortic centerline, generates MPRs orthogonal to the centerline, and segments the true and false lumina.

Fluid-structure interaction simulations of patient-specific aortic dissection.

Credible computational fluid dynamic (CFD) simulations of aortic dissection are challenging, because the defining parallel flow channels-the true and the false lumen-are separated from each other by a more or less mobile dissection membrane, which is made up of a delaminated portion of the elastic aortic wall. We present a comprehensive numerical framework for CFD simulations of aortic dissection, which captures the complex interplay between physiologic deformation, flow, pressures, and time-averaged wall shear stress (TAWSS) in a patient-specific model. Our numerical model includes (1) two-way fluid-structure interaction (FSI) to describe the dynamic deformation of the vessel wall and dissection flap; (2) prestress and (3) external tissue support of the structural domain to avoid unphysiologic dilation of the aortic wall and stretching of the dissection flap; (4) tethering of the aorta by intercostal and lumbar arteries to restrict translatory motion of the aorta; and a (5) independently defined elastic modulus for the dissection flap and the outer vessel wall to account for their different material properties.

Single-stage bone resection and cranioplastic reconstruction: comparison of a novel software-derived PEEK workflow with the standard reconstructive method.

The combined resection of skull-infiltrating tumours and immediate cranioplastic reconstruction predominantly relies on freehand-moulded solutions. Techniques that enable this procedure to be performed easily in routine clinical practice would be useful. A cadaveric study was developed in which a new software tool was used to perform single-stage reconstructions with prefabricated implants after the resection of skull-infiltrating pathologies.

Novel Software-Derived Workflow in Extracranial-Intracranial Bypass Surgery Validated by Transdural Indocyanine Green Videoangiography.

Background: The introduction of image-guided methods to bypass surgery has resulted in optimized preoperative identification of the recipients and excellent patency rates. However, the recently presented methods have also been resource-consuming. In the present study, we have reported a cost-efficient planning workflow for extracranial-intracranial (EC-IC) revascularization combined with transdural indocyanine green videoangiography (tICG-VA).

AR in VR: assessing surgical augmented reality visualizations in a steerable virtual reality environment.

PURPOSE  : Augmented reality (AR) has emerged as a promising approach to support surgeries; however, its application in real world scenarios is still very limited. Besides sophisticated registration tasks that need to be solved, surgical AR visualizations have not been studied in a standardized and comparative manner. To foster the development of future AR applications, a steerable framework is urgently needed to rapidly evaluate new visualization techniques, explore their individual parameter spaces and define relevant application scenarios.

Popup-Plots: Warping Temporal Data Visualization.

Temporal data visualization is used to analyze dependent variables that vary over time, with time being an independent variable. Visualizing temporal data is inherently difficult, due to the many aspects that need to be communicated to the users (e.g.

Multipath Curved Planar Reformations of Peripheral CT Angiography: Diagnostic Accuracy and Time Efficiency.

Objectives: To compare diagnostic performance and time efficiency between 3D multipath curved planar reformations (mpCPRs) and axial images of CT angiography for the pre-interventional assessment of peripheral arterial disease (PAD), with digital subtraction angiography as the standard of reference.

Methods: Forty patients (10 females, mean age 72 years), referred to CTA prior to endovascular treatment of PAD, were prospectively included and underwent peripheral CT angiography. A semiautomated toolbox was used to render mpCPRs.

A BMI-adjusted ultra-low-dose CT angiography protocol for the peripheral arteries-Image quality, diagnostic accuracy and radiation exposure.

Objectives: To investigate radiation exposure, objective image quality, and the diagnostic accuracy of a BMI-adjusted ultra-low-dose CT angiography (CTA) protocol for the assessment of peripheral arterial disease (PAD), with digital subtraction angiography (DSA) as the standard of reference.

Methods: In this prospective, IRB-approved study, 40 PAD patients (30 male, mean age 72 years) underwent CTA on a dual-source CT scanner at 80kV tube voltage. The reference amplitude for tube current modulation was personalized based on the body mass index (BMI) with 120 mAs for [BMI≤25] or 150 mAs for [25 View Article and Find Full Text PDF

Computed Tomography Imaging Features in Acute Uncomplicated Stanford Type-B Aortic Dissection Predict Late Adverse Events.

Background: Medical treatment of initially uncomplicated acute Stanford type-B aortic dissection is associated with a high rate of late adverse events. Identification of individuals who potentially benefit from preventive endografting is highly desirable.

Methods And Results: The association of computed tomography imaging features with late adverse events was retrospectively assessed in 83 patients with acute uncomplicated Stanford type-B aortic dissection, followed over a median of 850 (interquartile range 247-1824) days.

Placenta Maps: In Utero Placental Health Assessment of the Human Fetus.

The human placenta is essential for the supply of the fetus. To monitor the fetal development, imaging data is acquired using (US). Although it is currently the gold-standard in fetal imaging, it might not capture certain abnormalities of the placenta.

New hybrid reformations of peripheral CT angiography: do we still need axial images?

Purpose: To quantify the detectability of peripheral artery stenosis on hybrid CT angiography (CTA) reformations.

Methods: Hybrid reformations were developed by combining multipath curved planar reformations (mpCPR) and maximum intensity projections (MIP). Fifty peripheral CTAs were evaluated twice: either with MIP, mpCPR and axial images or with hybrid reformations only.

Vessel visualization using curved surface reformation.

Visualizations of vascular structures are frequently used in radiological investigations to detect and analyze vascular diseases. Obstructions of the blood flow through a vessel are one of the main interests of physicians, and several methods have been proposed to aid the visual assessment of calcifications on vessel walls. Curved Planar Reformation (CPR) is a wide-spread method that is designed for peripheral arteries which exhibit one dominant direction.