Multilayer flow modulator enhances vital organ perfusion in patients with type B aortic dissection.

Management of aortic dissections (AD) is still challenging, with no universally approved guideline among possible surgical, endovascular, or medical therapies. Approximately 25% of patients with AD suffer postintervention malperfusion syndrome or hemodynamic instability, with the risk of sudden death if left untreated. Part of the issue is that vascular implants may themselves induce flow disturbances that critically impact vital organs. A multilayer mesh construct might obviate the induced flow disturbances, and it is this concept we investigated. We used preintervention and post-multilayer flow modulator implantation (PM) geometries from clinical cases of type B AD. In-house semiautomatic segmentation routines were applied to computed tomography images to reconstruct the lumen. The device was numerically reconstructed and adapted to the PM geometry concentrically fit to the true lumen centerline. We also numerically designed a pseudohealthy case, where the geometry of the aorta was extracted interpolating geometric features of preintervention, postimplantation, and published representative healthy volunteers. Computational fluid dynamics methods were used to study the time-dependent flow patterns, shear stress metrics, and perfusion to vital organs. A three-element Windkessel lumped parameter module was coupled to a finite-volume solver to assign dynamic outlet boundary conditions. Multilayer flow modulator not only significantly reduced false lumen blood flow, eliminated local flow disturbances, and globally regulated wall shear stress distribution but also maintained physiological perfusion to peripheral vital organs. We propose further investigation to focus the management of AD on both modulation of blood flow and restoration of physiologic end-organ perfusion rather than mere restoration of vascular lamina morphology. NEW & NOTEWORTHY The majority of aortic dissection modeling efforts have focused on the maintenance of physiological flow using minimally invasive placed grafts. The multilayer flow modulator is a complex mesh construct of wires, designed to eliminate flow disruptions in the lumen, regulate the physiological wall stresses, and enhance endothelial function and offering the promise of improved perfusion of vital organs. This has never been fully proved or modeled, and these issues we confirmed using a dynamic framework of time-varying arterial waveforms.

Patient-specific computational modeling of subendothelial LDL accumulation in a stenosed right coronary artery: effect of hemodynamic and biological factors.

Atherosclerosis is a systemic disease with local manifestations. Low-density lipoprotein (LDL) accumulation in the subendothelial layer is one of the hallmarks of atherosclerosis onset and ignites plaque development and progression. Blood flow-induced endothelial shear stress (ESS) is causally related to the heterogenic distribution of atherosclerotic lesions and critically affects LDL deposition in the vessel wall. In this work we modeled blood flow and LDL transport in the coronary arterial wall and investigated the influence of several hemodynamic and biological factors that may regulate LDL accumulation. We used a three-dimensional model of a stenosed right coronary artery reconstructed from angiographic and intravascular ultrasound patient data. We also reconstructed a second model after restoring the patency of the stenosed lumen to its nondiseased state to assess the effect of the stenosis on LDL accumulation. Furthermore, we implemented a new model for LDL penetration across the endothelial membrane, assuming that endothelial permeability depends on the local lumen LDL concentration. The results showed that the presence of the stenosis had a dramatic effect on the local ESS distribution and LDL accumulation along the artery, and areas of increased LDL accumulation were observed in the downstream region where flow recirculation and low ESS were present. Of the studied factors influencing LDL accumulation, 1) hypertension, 2) increased endothelial permeability (a surrogate of endothelial dysfunction), and 3) increased serum LDL levels, especially when the new model of variable endothelial permeability was applied, had the largest effects, thereby supporting their role as major cardiovascular risk factors.

Artificial intelligence to generate medical images: augmenting the cardiologist's visual clinical workflow.

Artificial intelligence (AI) offers great promise in cardiology, and medicine broadly, for its ability to tirelessly integrate vast amounts of data. Applications in medical imaging are particularly attractive, as images are a powerful means to convey rich information and are extensively utilized in cardiology practice. Departing from other AI approaches in cardiology focused on task automation and pattern recognition, we describe a digital health platform to synthesize enhanced, yet familiar, clinical images to augment the cardiologist's visual clinical workflow. In this article, we present the framework, technical fundamentals, and functional applications of the methodology, especially as it pertains to intravascular imaging. A conditional generative adversarial network was trained with annotated images of atherosclerotic diseased arteries to generate synthetic optical coherence tomography and intravascular ultrasound images on the basis of specified plaque morphology. Systems leveraging this unique and flexible construct, whereby a pair of neural networks is competitively trained in tandem, can rapidly generate useful images. These synthetic images replicate the style, and in several ways exceed the content and function, of normally acquired images. By using this technique and employing AI in such applications, one can ameliorate challenges in image quality, interpretability, coherence, completeness, and granularity, thereby enhancing medical education and clinical decision-making.

A Domain Enriched Deep Learning Approach to Classify Atherosclerosis using Intravascular Ultrasound Imaging.

Intravascular ultrasound (IVUS) imaging is widely used for diagnostic imaging in interventional cardiology. The detection and quantification of atherosclerosis from acquired images is typically performed manually by medical experts or by virtual histology IVUS (VH-IVUS) software. VH-IVUS analyzes backscattered radio frequency (RF) signals to provide a color-coded tissue map, and is the method of choice for assessing atherosclerotic plaque in situ. However, a significant amount of tissue cannot be analyzed in reasonable time because the method can be applied just once per cardiac cycle. Furthermore, only hardware and software compatible with RF signal acquisition and processing may be used. We present an image-based tissue characterization method that can be applied to entire acquisition sequences post hoc for the assessment of diseased vessels. The pixel-based method utilizes domain knowledge of arterial pathology and physiology, and leverages technological advances of convolutional neural networks to segment diseased vessel walls into the same tissue classes as virtual histology using only grayscale IVUS images. The method was trained and tested on patches extracted from VH-IVUS images acquired from several patients, and achieved overall accuracy of 93.5% for all segmented tissue. Imposing physically-relevant spatial constraints driven by domain knowledge was key to achieving such strong performance. This enriched approach offers capabilities akin to VH-IVUS without the constraints of RF signals or limited once-per-cycle analysis, offering superior potential information acquisition speed, reduced hardware and software requirements, and more widespread applicability. Such an approach may well yield promise for future clinical and research applications.

Hemodynamic consequences of a multilayer flow modulator in aortic dissection.

Aortic dissections are challenging for it remains perplexing to determine when surgical, endovascular, or medical therapies are optimal. We studied the effect of the multilayer flow modulator (MFM) device in patients with different forms of type-B aortic dissections. CT scans were performed pre-, immediately post-MFM implantation, and multiple times within a 24-month follow-up. Three-dimensional reconstructions were created from these scans and the multilayer or single-layer mesh device placed virtually into the true lumen. We observed that MFM device can sufficiently restore flow perfusion, reduce the false lumen, eliminate local flow recirculation, and reduce wall shear stress distribution globally. Single-layer devices can reduce false lumen dimensions; however, they generate local disturbance and recirculation zones in selected areas at specific time points. Moreover, in polar extremes of dissection, the MFM device restored flow to vital organs perfusing vessels independent of effects on luminal patency. Management of aortic dissections should focus on modulation of blood flow, suppression of local recirculation, and restoration of vital organ perfusion rather than primarily restoring vascular lumen morphology. While the latter restores the geometry of the true lumen, only the former restores homeostasis. Graphical abstract.

A Mechanical Approach for Smooth Surface Fitting to Delineate Vessel Walls in Optical Coherence Tomography Images.

Automated analysis of vascular imaging techniques is limited by the inability to precisely determine arterial borders. Intravascular optical coherence tomography (OCT) offers unprecedented detail of artery wall structure and composition, but does not provide consistent visibility of the outer border of the vessel due to the limited penetration depth. Existing interpolation and surface fitting methods prove insufficient to accurately fill the gaps between the irregularly spaced and sometimes unreliably identified visible segments of the vessel outer border. This paper describes an intuitive, efficient, and flexible new method of 3D surface fitting and smoothing suitable for this task. An anisotropic linear-elastic mesh is fit to irregularly spaced and uncertain data points corresponding to visible segments of vessel borders, enabling the fully automated delineation of the entire inner and outer borders of diseased vessels in OCT images for the first time. In a clinical dataset, the proposed smooth surface fitting approach had great agreement when compared with human annotations: areas differed by just 11 ± 11% (0.93 ± 0.84 mm2), with a coefficient of determination of 0.89. Overlapping and non-overlapping area ratios were 0.91 and 0.18, respectively, with a sensitivity of 90.8 and specificity of 99.0. This spring mesh method of contour fitting significantly outperformed all alternative surface fitting and interpolation approaches tested. The application of this promising proposed method is expected to enhance clinical intervention and translational research using OCT.

Art care: A multi-modality coronary 3D reconstruction and hemodynamic status assessment software.

BACKGROUND: Due to the incremental increase of clinical interest in the development of software that allows the 3-dimensional (3D) reconstruction and the functional assessment of the coronary vasculature, several software packages have been developed and are available today. OBJECTIVE: Taking this into consideration, we have developed an innovative suite of software modules that perform 3D reconstruction of coronary arterial segments using different coronary imaging modalities such as IntraVascular UltraSound (IVUS) and invasive coronary angiography images (ICA), Optical Coherence Tomography (OCT) and ICA images, or plain ICA images and can safely and accurately assess the hemodynamic status of the artery of interest. METHODS: The user can perform automated or manual segmentation of the IVUS or OCT images, visualize in 3D the reconstructed vessel and export it to formats, which are compatible with other Computer Aided Design (CAD) software systems. We employ finite elements to provide the capability to assess the hemodynamic functionality of the reconstructed vessels by calculating the virtual functional assessment index (vFAI), an index that corresponds and has been shown to correlate well to the actual fractional flow reserve (FFR) value. RESULTS: All the modules of the proposed system have been thoroughly validated. In brief, the 3D-QCA module, compared to a successful commercial software of the same genre, presented very good correlation using several validation metrics, with a Pearson's correlation coefficient (R) for the calculated volumes, vFAI, length and minimum lumen diameter of 0.99, 0.99, 0.99 and 0.88, respectively. Moreover, the automatic lumen detection modules for IVUS and OCT presented very high accuracy compared to the annotations by medical experts with the Pearson's correlation coefficient reaching the values of 0.94 and 0.99, respectively. CONCLUSIONS: In this study, we have presented a user-friendly software for the 3D reconstruction of coronary arterial segments and the accurate hemodynamic assessment of the severity of existing stenosis.

Polymeric endovascular strut and lumen detection algorithm for intracoronary optical coherence tomography images.

Polymeric endovascular implants are the next step in minimally invasive vascular interventions. As an alternative to traditional metallic drug-eluting stents, these often-erodible scaffolds present opportunities and challenges for patients and clinicians. Theoretically, as they resorb and are absorbed over time, they obviate the long-term complications of permanent implants, but in the short-term visualization and therefore positioning is problematic. Polymeric scaffolds can only be fully imaged using optical coherence tomography (OCT) imaging-they are relatively invisible via angiography-and segmentation of polymeric struts in OCT images is performed manually, a laborious and intractable procedure for large datasets. Traditional lumen detection methods using implant struts as boundary limits fail in images with polymeric implants. Therefore, it is necessary to develop an automated method to detect polymeric struts and luminal borders in OCT images; we present such a fully automated algorithm. Accuracy was validated using expert annotations on 1140 OCT images with a positive predictive value of 0.93 for strut detection and an R2 correlation coefficient of 0.94 between detected and expert-annotated lumen areas. The proposed algorithm allows for rapid, accurate, and automated detection of polymeric struts and the luminal border in OCT images.

A novel hybrid approach for reconstruction of coronary bifurcations using angiography and OCT.

The aim of this study is to present a new method for three-dimensional (3D) reconstruction of coronary bifurcations using biplane Coronary Angiographies and Optical Coherence Tomography (OCT) imaging. The method is based on a five step approach by improving a previous validated work in order to reconstruct coronary arterial bifurcations. In the first step the lumen borders are detected on the Frequency Domain (FD) OCT images. In the second step a semi-automated method is implemented on two angiographies for the extraction of the 2D bifurcation coronary artery centerline. In the third step the 3D path of the bifurcation artery is extracted based on a back projection algorithm. In the fourth step the lumen borders are placed onto the 3D catheter path. Finally, in the fifth step the intersection of the main and side branches produces the reconstructed model of the coronary bifurcation artery. Data from three patients are acquired for the validation of the proposed methodology and the results are compared against a reconstruction method using quantitative coronary angiography (QCA). The comparison between the two methods is achieved using morphological measures of the vessels as well as comparison of the wall shear stress (WSS) mean values.

Prediction of Atherosclerotic Plaque Development in an In Vivo Coronary Arterial Segment Based on a Multilevel Modeling Approach.

OBJECTIVE: The aim of this study is to explore major mechanisms of atherosclerotic plaque growth, presenting a proof-of-concept numerical model. METHODS: To this aim, a human reconstructed left circumflex coronary artery is utilized for a multilevel modeling approach. More specifically, the first level consists of the modeling of blood flow and endothelial shear stress (ESS) computation. The second level includes the modeling of low-density lipoprotein (LDL) and high-density lipoprotein and monocytes transport through the endothelial membrane to vessel wall. The third level comprises of the modeling of LDL oxidation, macrophages differentiation, and foam cells formation. All modeling levels integrate experimental findings to describe the major mechanisms that occur in the arterial physiology. In order to validate the proposed approach, we utilize a patient specific scenario by comparing the baseline computational results with the changes in arterial wall thickness, lumen diameter, and plaque components using follow-up data. RESULTS: The results of this model show that ESS and LDL concentration have a good correlation with the changes in plaque area [R2 = 0.365 (P = 0.029, adjusted R2 = 0.307) and R2 = 0.368 (P = 0.015, adjusted R2 = 0.342), respectively], whereas the introduction of the variables of oxidized LDL, macrophages, and foam cells as independent predictors improves the accuracy in predicting regions potential for atherosclerotic plaque development [R2 = 0.847 (P = 0.009, adjusted R2 = 0.738)]. CONCLUSION: Advanced computational models can be used to increase the accuracy to predict regions which are prone to plaque development. SIGNIFICANCE: Atherosclerosis is one of leading causes of death worldwide. For this purpose computational models have to be implemented to predict disease progression.

Three-dimensional reconstruction of coronary arteries and plaque morphology using CT angiography - comparison and registration using IVUS.

The aim of this study is to present a new method for three-dimensional (3D) reconstruction of coronary arteries and plaque morphology using Computed Tomography (CT) Angiography. The method is summarized in three steps. In the first step, image filters are applied to CT images and an initial estimation of the vessel borders is extracted. In the second step, the 3D centerline is extracted using the center of gravity of each rough artery border. Finally in the third step, the borders and the plaque are detected and placed onto the 3D centerline constructing a 3D surface. By using as gold standard the results of a recently presented Intravascular Ultrasound (IVUS) plaque characterization method, high correlation is observed for calcium objects detected by CT and IVUS. The correlation coefficients for objects' volume, surface area, length and angle are r=0.51, r=0.89, r=0.96 and r=0.93, respectively.

A proof-of-concept study for predicting the region of atherosclerotic plaque development based on plaque growth modeling in carotid arteries.

In this work, we present a computational model for plaque growth utilizing magnetic resonance data of a patient's carotid artery. More specifically, we model blood flow utilizing the Navier-Stokes equations, as well as LDL and HDL transport using the convection-diffusion equation in the arterial lumen. The accumulated LDL in the arterial wall is oxidized considering the protective effect of HDL. Macrophages recruitment and foam cells formation are the final step of the proposed multi-level modeling approach of the plaque growth. The simulated results of our model are compared with the follow-up MRI findings in 12 months regarding the change to the arterial wall thickness. WSS and LDL may indicate potential regions of plaque growth (R(2)=0.35), but the contribution of foam cells formation, macrophages and oxidized LDL increased the prediction significantly (R(2)=0.75).

Validation study of a 3D-QCA coronary reconstruction method using a hybrid intravascular ultrasound and angiography reconstruction method and patient-specific Fractional Flow Reserve data.

The estimation of the severity of coronary lesions is of utmost importance in today's clinical practice, since Cardiovascular diseases often have fatal consequences. The most efficient method to estimate the severity of a lesion is the calculation of the Fractional Flow Reserve. The necessary use of a pressure wire, however, makes this method invasive and strenuous for the patient. In this work, we present a novel 3-Dimensional Quantitative Coronary Analysis coronary reconstruction method and a framework for the computation of the virtual Functional Assessment Index (vFAI). In a dataset of 5 coronary arterial segments, we use the aforementioned method to reconstruct them in 3D, and compare them to the respective 3D models reconstructed from our already validated hybrid IVUS-angiography reconstruction method [2]. The obtained results indicate a high correlation between the two methods in terms of the calculated FFR values, presenting a difference of 3.19% in the worst case scenario. Furthermore, when compared to the actual FFR values that derive from a pressure wire, the differences were statistically insignificant.

Patient-specific simulation of coronary artery pressure measurements: an in vivo three-dimensional validation study in humans.

Pressure measurements using finite element computations without the need of a wire could be valuable in clinical practice. Our aim was to compare the computed distal coronary pressure values with the measured values using a pressure wire, while testing the effect of different boundary conditions for the simulation. Eight coronary arteries (lumen and outer vessel wall) from six patients were reconstructed in three-dimensional (3D) space using intravascular ultrasound and biplane angiographic images. Pressure values at the distal and proximal end of the vessel and flow velocity values at the distal end were acquired with the use of a combo pressure-flow wire. The 3D lumen and wall models were discretized into finite elements; fluid structure interaction (FSI) and rigid wall simulations were performed for one cardiac cycle both with pulsatile and steady flow in separate simulations. The results showed a high correlation between the measured and the computed coronary pressure values (coefficient of determination [r(2)] ranging between 0.8902 and 0.9961), while the less demanding simulations using steady flow and rigid walls resulted in very small relative error. Our study demonstrates that computational assessment of coronary pressure is feasible and seems to be accurate compared to the wire-based measurements.

Computerized methodology for micro-CT and histological data inflation using an IVUS based translation map.

A framework for the inflation of micro-CT and histology data using intravascular ultrasound (IVUS) images, is presented. The proposed methodology consists of three steps. In the first step the micro-CT/histological images are manually co-registered with IVUS by experts using fiducial points as landmarks. In the second step the lumen of both the micro-CT/histological images and IVUS images are automatically segmented. Finally, in the third step the micro-CT/histological images are inflated by applying a transformation method on each image. The transformation method is based on the IVUS and micro-CT/histological contour difference. In order to validate the proposed image inflation methodology, plaque areas in the inflated micro-CT and histological images are compared with the ones in the IVUS images. The proposed methodology for inflating micro-CT/histological images increases the sensitivity of plaque area matching between the inflated and the IVUS images (7% and 22% in histological and micro-CT images, respectively).

Anatomically correct three-dimensional coronary artery reconstruction using frequency domain optical coherence tomographic and angiographic data: head-to-head comparison with intravascular ultrasound for endothelial shear stress assessment in humans.

AIMS: To develop a methodology that permits accurate 3-dimensional (3D) reconstruction from FD-OCT and angiographic data enabling reliable evaluation of the ESS distribution, and to compare the FD-OCT-derived models against the established models based on angiography/IVUS. METHODS AND RESULTS: Fifteen patients (17 coronary arteries) who underwent angiography, FD-OCT and IVUS examination during the same procedure were studied. The FD-OCT and IVUS lumen borders were placed onto the 3D luminal centreline derived from angiographic data. Three-dimensional geometry algorithms and anatomical landmarks were used to estimate the orientation of the borders appropriately. ESS was calculated using computational fluid dynamics. In 188 corresponding consecutive 3-mm segments, FD-OCT- and IVUS-derived models were highly correlated for lumen area (r=0.96) and local ESS (r=0.89) measurements. FD-OCT-based 3D reconstructions had a high diagnostic accuracy for detecting regions exposed to proatherogenic low ESS identified on the IVUS-based 3D models, considered as the gold standard (receiver operator characteristic area under the curve: 94.9%). CONCLUSIONS: FD-OCT-based 3D coronary reconstruction provides anatomically correct models and permits reliable ESS computation. ESS assessment in combination with the superior definition of plaque characteristics by FD-OCT is expected to provide valuable insights into the effect of the haemodynamic environment on the development and destabilisation of high-risk plaques.

Error propagation in the characterization of atheromatic plaque types based on imaging.

Imaging systems transmit and acquire signals and are subject to errors including: error sources, signal variations or possible calibration errors. These errors are included in all imaging systems for atherosclerosis and are propagated to methodologies implemented for the segmentation and characterization of atherosclerotic plaque. In this paper, we present a study for the propagation of imaging errors and image segmentation errors in plaque characterization methods applied to 2D vascular images. More specifically, the maximum error that can be propagated to the plaque characterization results is estimated, assuming worst-case scenarios. The proposed error propagation methodology is validated using methods applied to real datasets, obtained from intravascular imaging (IVUS) and optical coherence tomography (OCT) for coronary arteries, and magnetic resonance imaging (MRI) for carotid arteries. The plaque characterization methods have recently been presented in the literature and are able to detect the vessel borders, and characterize the atherosclerotic plaque types. Although, these methods have been extensively validated using as gold standard expert annotations, by applying the proposed error propagation methodology a more realistic validation is performed taking into account the effect of the border detection algorithms error and the image formation error into the final results. The Pearson's coefficient of the detected plaques has changed significantly when the method was applied to IVUS and OCT, while there was not any variation when the method was applied to MRI data.

Methodology for micro-CT data inflation using intravascular ultrasound images.

In this paper, a framework for the inflation of micro-CT data using intravascular ultrasound (IVUS) images, is presented. The proposed methodology consists of four steps. In the first step a centerline is extracted from the micro-CT images. In the second step the micro CT images are segmented automatically using the k-means algorithm. In the third step IVUS- micro-CT images are co-registered based on fiducial markers selected manually by the experts. Finally, the images are inflated by applying a transformation method on each image. The transformation method is based on the IVUS and micro-CT contour difference. The proposed methodology for inflating micro-CT images could increase the reliability of correct plaque labeling process as well to enhance the accuracy of the produced training dataset from the micro-CT images.

Finite element analysis of stent implantation in a three-dimensional reconstructed arterial segment.

Endovascular stent deployment is a mechanical procedure used to rehabilitate a diseased arterial segment by restoring blood flow in occluded regions. The success or failure of the stent implantation depends on the stent device and the deployment technique. The optimal stent deployment can be predicted by investigating the factors that influence this minimally invasive procedure. In this study, we propose a methodology which evaluates the alterations in the arterial environment caused by stent deployment. A finite element model of a reconstructed right coronary artery with a stenosis was created based on anatomical information provided by intravascular ultrasound and angiography. The model was used to consider placement and performance after intervention with a commercially available Leader Plus stent. The performance of the stent, within this patient-specific arterial segment is presented, as well as the induced arterial deformation and straightening. The arterial stress distribution is analyzed with respect to possible regions of arterial injury. Our approach can be used to optimize stent deployment and to provide cardiologists with a valuable tool to visually select the position and deploy stents in patient-specific reconstructed arterial segments, thereby enabling new methods for optimal cardiovascular stent positioning.