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

Non-calcified plaque-based coronary stenosis grading in contrast enhanced CT

BACKGROUND

The high mortality rate associated with coronary heart disease has led to state-of-the-art non-invasive methods for cardiac diagnosis including computed tomography and magnetic resonance imaging. However, stenosis computation and clinical assessment of non-calcified plaques has been very challenging due to their ambiguous intensity response in CT i.e. a significant overlap with surrounding muscle tissues and blood. Accordingly, this research presents an approach for computation of coronary stenosis by investigating cross-sectional lumen behaviour along the length of 3D coronary segments.

METHODS

Non-calcified plaques are characterized by comparatively lower-intensity values with respect to the surrounding. Accordingly, segment-wise orthogonal volume was reconstructed in 3D space using the segmented coronary tree. Subsequently, the cross sectional volumetric data was investigated using proposed CNN-based plaque quantification model and subsequent stenosis grading in clinical context was performed. In the last step, plaque-affected orthogonal volume was further investigated by comparing vessel-wall thickness and lumen area obstruction w.r.t. expert-based annotations to validate the stenosis grading performance of model.

RESULTS

The experimental data consists of clinical CT images obtained from the Rotterdam CT repository leading to 600 coronary segments and subsequent 15786 cross-sectional images. According to the results, the proposed method quantified coronary vessel stenosis i.e. severity of the non-calcified plaque with an overall accuracy of 83%. Moreover, for individual grading, the proposed model show promising results with accuracy equal to 86%, 90% and 79% respectively for severe, moderate and mild stenosis. The stenosis grading performance of the proposed model was further validated by performing lumen-area versus wall-thickness analysis as per annotations of manual experts. The statistical results for lumen area analysis precisely correlates with the quantification performance of the model with a mean deviation of 5% only.

CONCLUSION

The overall results demonstrates capability of the proposed model to grade the vessel stenosis with reasonable accuracy and precision equivalent to human experts.

A comparative analysis of deep learning-based location-adaptive threshold method software against other commercially available software

Automatic segmentation of the coronary artery using coronary computed tomography angiography (CCTA) images can facilitate several analyses related to coronary artery disease (CAD). Accurate segmentation of the lumen or plaque region is one of the most important factors. This study aimed to analyze the performance of the coronary artery segmentation of a software platform with a deep learning-based location-adaptive threshold method (DL-LATM) against commercially available software platforms using CCTA. The dataset from intravascular ultrasound (IVUS) of 26 vessel segments from 19 patients was used as the gold standard to evaluate the performance of each software platform. Statistical analyses (Pearson correlation coefficient [PCC], intraclass correlation coefficient [ICC], and Bland-Altman plot) were conducted for the lumen or plaque parameters by comparing the dataset of each software platform with IVUS. The software platform with DL-LATM showed the bias closest to zero for detecting lumen volume (mean difference = -9.1 mm3, 95% confidence interval [CI] = -18.6 to 0.4 mm3) or area (mean difference = -0.72 mm2, 95% CI = -0.80 to -0.64 mm2) with the highest PCC and ICC. Moreover, lumen or plaque area in the stenotic region was analyzed. The software platform with DL-LATM showed the bias closest to zero for detecting lumen (mean difference = -0.07 mm2, 95% CI = -0.16 to 0.02 mm2) or plaque area (mean difference = 1.70 mm2, 95% CI = 1.37 to 2.03 mm2) in the stenotic region with significantly higher correlation coefficient than other commercially available software platforms (p < 0.001). The result shows that the software platform with DL-LATM has the potential to serve as an aiding system for CAD evaluation.

Characteristics and evaluation of atherosclerotic plaques: an overview of state-of-the-art techniques

Atherosclerosis is an important cause of cerebrovascular and cardiovascular disease (CVD). Lipid infiltration, inflammation, and altered vascular stress are the critical mechanisms that cause atherosclerotic plaque formation. The hallmarks of the progression of atherosclerosis include plaque ulceration, rupture, neovascularization, and intraplaque hemorrhage, all of which are closely associated with the occurrence of CVD. Assessing the severity of atherosclerosis and plaque vulnerability is crucial for the prevention and treatment of CVD. Integrating imaging techniques for evaluating the characteristics of atherosclerotic plaques with computer simulations yields insights into plaque inflammation levels, spatial morphology, and intravascular stress distribution, resulting in a more realistic and accurate estimation of plaque state. Here, we review the characteristics and advancing techniques used to analyze intracranial and extracranial atherosclerotic plaques to provide a comprehensive understanding of atheroma.

Customizable Angioplasty Balloon-Forming Machine: Towards Precision Medicine in Coronary Bifurcation Lesion Interventions

The ability to customize the size and shape of angioplasty balloons may be useful in many clinical and research applications of coronary and endovascular intervention. Fully customizable balloons are outside the reach of most researchers due to their prohibitive cost. A small-scale balloon-forming machine was developed to produce fully customizable balloons. This study describes the creation of this customizable balloon-forming machine and identifies the key components of manufacturing a patient-specific balloon. Using a standard balloon-shaped mold created with a novel application of 3D stereolithography-printed resin, 104 PET balloon formation tests were conducted. A statistical study was conducted in which molding temperature and inflation air pressure were independent variables ranging from 100 to 130 °C and from 3.7 to 6.8 atm, respectively. The criteria for balloon-forming success were defined; pressure and temperature combined were found to have a significant impact on the success (p = 0.011), with 120 °C and 4.76 atm resulting in the highest chance for success based on a regression model.

Relationship of Endothelial Shear Stress with Plaque Features with Coronary CT Angiography and Vasodilating Capability with PET

Background Advances in three-dimensional reconstruction techniques and computational fluid dynamics of coronary CT angiography (CCTA) data sets make feasible evaluation of endothelial shear stress (ESS) in the vessel wall. Purpose To investigate the relationship between CCTA-derived computational fluid dynamics metrics, anatomic and morphologic characteristics of coronary lesions, and their comparative performance in predicting impaired coronary vasodilating capability assessed by using PET myocardial perfusion imaging (MPI). Materials and Methods In this retrospective study, conducted between October 2019 and September 2020, coronary vessels in patients with stable chest pain and with intermediate probability of coronary artery disease who underwent both CCTA and PET MPI with oxygen 15-labeled water or nitrogen 13 ammonia and quantification of myocardial blood flow were analyzed. CCTA images were used in assessing stenosis severity, lesion-specific total plaque volume (PV), noncalcified PV, calcified PV, and plaque phenotype. PET MPI was used in assessing significant coronary stenosis. The predictive performance of the CCTA-derived parameters was evaluated by using area under the receiver operating characteristic curve (AUC) analysis. Results There were 92 coronary vessels evaluated in 53 patients (mean age, 65 years ± 7; 31 men). ESS was higher in lesions with greater than 50% stenosis versus those without significant stenosis (mean, 15.1 Pa ± 30 vs 4.6 Pa ± 4 vs 3.3 Pa ± 3; P = .004). ESS was higher in functionally significant versus nonsignificant lesions (median, 7 Pa [interquartile range, 5-23 Pa] vs 2.6 Pa [interquartile range, 1.8-5 Pa], respectively; P ≤ .001). Adding ESS to stenosis severity improved prediction (change in AUC, 0.10; 95% CI: 0.04, 0.17; P = .002) for functionally significant lesions. Conclusion The combination of endothelial shear stress with coronary CT angiography (CCTA) stenosis severity improved prediction of an abnormal PET myocardial perfusion imaging result versus CCTA stenosis severity alone. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Kusmirek and Wieben in this issue.

Novel preclinical method for evaluating the efficacy of a percutaneous treatment in human ex vivo calcified plaque

The lack of suitable atherosclerotic calcification models and testing strategies inhibits preclinical efficacy testing of existing and novel percutaneous devices. The goal of this study is to develop a preclinical testing method for quantitatively and qualitatively evaluating the efficacy of noncompliant balloon angioplasty (NC BA) treatment in human ex vivo calcified plaque (CP). NC BA using a 3- and 4-mm diameter balloon was performed on an ex vivo tibial calcified vessel obtained from an amputation. Three-dimensional microcomputed tomography (μ-CT) imaging was performed pre- and post-BA to compare crack density in the CP. Comparing the pre- and posttreatment three-dimensional μ-CT images showed a glass-like cracking that occurred in the CP due to the BA procedure. Expansion of the 3-mm balloon showed little tissue deformation and no CP cracking. Although expansion of the 4-mm balloon occurred nonuniformly along balloon length and across the perpendicular projections, the balloon generated cracking throughout the CP, which allowed the surrounding elastic tissue to be dilated. This combined X-ray microscopy and μ-CT technique is a useful preclinical tool for quantifying the efficacy of percutaneous treatments for CP. Because of its nondestructive nature, the CP structure can be visualized pre- and posttreatment to determine the treatment effect.

Extraction of Coronary Atherosclerotic Plaques From Computed Tomography Imaging: A Review of Recent Methods

Background: Atherosclerotic plaques are the major cause of coronary artery disease (CAD). Currently, computed tomography (CT) is the most commonly applied imaging technique in the diagnosis of CAD. However, the accurate extraction of coronary plaque geometry from CT images is still challenging.

Summary of Review: In this review, we focused on the methods in recent studies on the CT-based coronary plaque extraction. According to the dimension of plaque extraction method, the studies were categorized into two-dimensional (2D) and three-dimensional (3D) ones. In each category, the studies were analyzed in terms of data, methods, and evaluation. We summarized the merits and limitations of current methods, as well as the future directions for efficient and accurate extraction of coronary plaques using CT imaging.

Conclusion: The methodological innovations are important for more accurate CT-based assessment of coronary plaques in clinical applications. The large-scale studies, de-blooming algorithms, more standardized datasets, and more detailed classification of non-calcified plaques could improve the accuracy of coronary plaque extraction from CT images. More multidimensional geometric parameters can be derived from the 3D geometry of coronary plaques. Additionally, machine learning and automatic 3D reconstruction could improve the efficiency of coronary plaque extraction in future studies.

The TAXINOMISIS Project: A multidisciplinary approach for the development of a new risk stratification model for patients with asymptomatic carotid artery stenosis

INTRODUCTION

Asymptomatic carotid artery stenosis (ACAS) may cause future stroke and therefore patients with ACAS require best medical treatment. Patients at high risk for stroke may opt for additional revascularization (either surgery or stenting) but the future stroke risk should outweigh the risk for peri/post-operative stroke/death. Current risk stratification for patients with ACAS is largely based on outdated randomized-controlled trials that lack the integration of improved medical therapies and risk factor control. Furthermore, recent circulating and imaging biomarkers for stroke have never been included in a risk stratification model. The TAXINOMISIS Project aims to develop a new risk stratification model for cerebrovascular complications in patients with ACAS and this will be tested through a prospective observational multicentre clinical trial performed in six major European vascular surgery centres.

METHODS AND ANALYSIS

The risk stratification model will compromise clinical, circulating, plaque and imaging biomarkers. The prospective multicentre observational study will include 300 patients with 50%-99% ACAS. The primary endpoint is the three-year incidence of cerebrovascular complications. Biomarkers will be retrieved from plasma samples, brain MRI, carotid MRA and duplex ultrasound. The TAXINOMISIS Project will serve as a platform for the development of new computer tools that assess plaque progression based on radiology images and a lab-on-chip with genetic variants that could predict medication response in individual patients.

CONCLUSION

Results from the TAXINOMISIS study could potentially improve future risk stratification in patients with ACAS to assist personalized evidence-based treatment decision-making.

AI in Medical Imaging Informatics: Current Challenges and Future Directions

This paper reviews state-of-the-art research solutions across the spectrum of medical imaging informatics, discusses clinical translation, and provides future directions for advancing clinical practice. More specifically, it summarizes advances in medical imaging acquisition technologies for different modalities, highlighting the necessity for efficient medical data management strategies in the context of AI in big healthcare data analytics. It then provides a synopsis of contemporary and emerging algorithmic methods for disease classification and organ/ tissue segmentation, focusing on AI and deep learning architectures that have already become the de facto approach. The clinical benefits of in-silico modelling advances linked with evolving 3D reconstruction and visualization applications are further documented. Concluding, integrative analytics approaches driven by associate research branches highlighted in this study promise to revolutionize imaging informatics as known today across the healthcare continuum for both radiology and digital pathology applications. The latter, is projected to enable informed, more accurate diagnosis, timely prognosis, and effective treatment planning, underpinning precision medicine.

Assessment of the value of 3D-DSA combined with neurointerventional thrombolysis in the treatment of senile cerebrovascular occlusion

Assessment of the value of three-dimensional digital subtraction angiography (3D-DSA) combined with neurointerventional thrombolysis in the treatment of senile cerebrovascular occlusion was investigated. A total of 129 patients with senile cerebrovascular occlusion admitted to the Affiliated Hospital of Zunyi Medical University from August 2015 to September 2017 were collected. Among them, 69 patients who underwent neurointerventional catheter thrombolysis under 3D-DSA were included in the study group, and 60 patients treated with neurointerventional thrombolysis were the control group. The levels of inflammatory cytokines IL-6, IL-1β and IL-8 in the two groups were measured by enzyme linked immunosorbent assay (ELISA) before treatment (T0), 7 days (7d) after treatment (T1) and 14 days (14d) after treatment (T2). The score of the National Institute of Health Stroke Scale and the clinical efficacy of patients in the two groups were compared before and after treatment, and Barthel index (BI) was used for investigation before and after treatment. The recurrence rate of disease in the two groups within 1 year was recorded. At T1, IL-6, IL-1β and IL-8 in the study group were significantly lower than those in the control group (P<0.05). The NIHSS score in the study group was lower than that in the control group after treatment (P<0.05). The BI score in the study group was significantly higher than that in the control group after treatment (P<0.05). After the prognostic follow-up, the disease recurrence rate of the study group was significantly lower than that of the control group (P<0.05). In conclusion, 3D-DSA combined with neurointerventional thrombolysis can significantly reduce the expression of inflammatory cytokines and improve the quality of life in patients with cerebrovascular occlusion, which has a high clinical value.

InSilc: 3D Reconstruction and plaque characterization tool

Coronary artery disease (CAD) is the leading cause of mortality in Europe and worldwide. Atherosclerosis is the most common pathologic process that is highly related with CAD, while the implantation of drug-eluting Bioresorbable Vascular Scaffolds (BVS) is the most promising procedure for treating patients with CAD. InSilc is an textbfin silico clinical trial (ISCT) platform for the development and assessment of drugeluting BVS. The InSilc platform provides insight in the performance of drug-eluting BVS in their short term and medium/long term through the Mechanical Modelling Module, the Deployment Module, the Fluid Dynamics Module, the Myocardial Perfusion Module, the Drug-delivery Module and the Degradation Module. In order for the aforementioned modules to be developed, the utilization of the reconstructed patient specific arterial segment and the BVS design are required, which is achieved through the 3D reconstruction and plaque characterization tool.In this study, the overall architecture of the InSilc platform is presented with special emphasis on the 3D reconstruction and plaque characterization tool. The tool will be able to implement different medical image processing workflows. The workflows will require minimum user intervention in order to be used in large scale clinical trials.

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.

Intraoperative Imaging and Image Fusion for Venous Interventions

Advanced imaging for intraoperative evaluation of venous pathologies has played an increasingly significant role in this era of evolving minimally invasive surgical and interventional therapies. The evolution of dedicated venous stents and other novel interventional devices has mandated the need for advanced imaging tools to optimize safe and accurate device deployment. Most venous interventions are typically performed using a combination of standard 2-dimensional (2D) fluoroscopy, digital-subtraction angiography, and intravascular ultrasound imaging techniques. Latest generation computer tomography (CT) and magnetic resonance imaging (MRI) scanners have been shown to provide high-resolution 3D and 4D information about venous vasculature. In addition to morphological imaging, novel MRI techniques such as 3D time-resolved MR venography and 4D flow sequences can provide quantitative information and help visualize intricate flow patterns to better understand complex venous pathologies. Moreover, the high-fidelity information from multiple imaging techniques can be integrated using image fusion to overcome the limitations of current intraoperative imaging techniques. For example, the limitations of standard 2D fluoroscopy and luminal angiography can be compensated for by perivascular and soft-tissue information from MRI during complex venous interventions using image fusion techniques. Intraoperative dynamic evaluation of devices such as venous stents and real-time understanding of changes in flow patterns during venous interventions may be routinely available in future interventional suites with integrated multimodality CT or MR imaging capabilities. The purpose of this review is to discuss the outlook for intraoperative imaging and multimodality image fusion techniques and highlight their value during complex venous interventions.

Position Paper Computational Cardiology

Computational cardiology is the scientific field devoted to the development of methodologies that enhance our mechanistic understanding, diagnosis and treatment of cardiovascular disease. In this regard, the field embraces the extraordinary pace of discovery in imaging, computational modeling, and cardiovascular informatics at the intersection of atherogenesis and vascular biology. This paper highlights existing methods, practices, and computational models and proposes new strategies to support a multidisciplinary effort in this space. We focus on the means by that to leverage and coalesce these multiple disciplines to advance translational science and computational cardiology. Analyzing the scientific trends and understanding the current needs we present our perspective for the future of cardiovascular treatment.

Framework for detection and localization of coronary non-calcified plaques in cardiac CTA using mean radial profiles

BACKGROUND AND OBJECTIVE

The high mortality rate associated with coronary heart disease (CHD) has driven intensive research in cardiac imaging and image analysis. The advent of computed tomography angiography (CTA) has turned non-invasive diagnosis of cardiovascular anomalies into reality as calcified coronary plaques can be easily identified due to their high intensity values. However, the detection of non-calcified plaques in CTA is still a challenging problem because of lower intensity values, which are often similar to the nearby blood and muscle tissues. In this work, we propose the use of mean radial profiles for the detection of non-calcified plaques in CTA imagery.

METHODS

Accordingly, we computed radial profiles by averaging the image intensity in concentric rings around the vessel centreline in a first stage. In the subsequent stage, an SVM classifier is applied to identify the abnormal coronary segments. For occluded segments, we further propose a derivative-based method to localize the position and length of the plaque inside the segment.

RESULTS

A total of 32 CTA volumes were analysed and a detection accuracy of 88.4% with respect to the manual expert was achieved. The plaque localization accuracy was computed using the Dice similarity coefficient and a mean of 83.2% was achieved.

CONCLUSION

The consistent performance for multi-vendor, multi-institution data demonstrates the reproducibility of our method across different CTA datasets with a good agreement with manual expert annotations.

Computational estimation of the hemodynamic significance of coronary stenoses in arterial branches deriving from CCTA: A proof-of-concept study

The development of non-invasive methods for the accurate hemodynamic assessment of the coronary vasculature has become a non-trivial matter for the everyday clinical practice. Virtual Functional Assessment Index has already been suggested as a valid alternative to the invasively measured FFR but only on coronary arterial segments. In this work, we propose a novel method for the estimation of the severity of coronary lesions in arterial branches from CCTA derived images. Four left arterial branches were reconstructed in 3D using our in-house developed 3D reconstruction algorithm, and were subjected to computational blood flow simulations for the final calculation of the vFAI through the whole arterial branch. Strong correlation was found (r=0.82) between the two methods. A small relative error of 3.2% and a small trend of overestimation (0.023, SD=0.088) were also observed. All pathological cases presenting ischemia, were correctly discriminated by our method as hemodynamically significant lesions.

SMARTool: A tool for clinical decision support for the management of patients with coronary artery disease based on modeling of atherosclerotic plaque process

SMARTool aims to the development of a clinical decision support system (CDSS) for the management and stratification of patients with coronary artery disease (CAD). This will be achieved by performing computational modeling of the main processes of atherosclerotic plaque growth. More specifically, computed tomography coronary angiography (CTCA) is acquired and 3-dimensional (3D) reconstruction is performed for the arterial trees. Then, blood flow and plaque growth modeling is employed simulating the major processes of atherosclerosis, such as the estimation of endothelial shear stress (ESS), the lipids transportation, low density lipoprotein (LDL) oxidation, macrophages migration and plaque development. The plaque growth model integrates information from genetic and biological data of the patients. The SMARTool system enables also the calculation of the virtual functional assessment index (vFAI), an index equivalent to the invasively measured fractional flow reserve (FFR), to provide decision support for patients with stenosed arteries. Finally, it integrates modeling of stent deployment. In this work preliminary results are presented. More specifically, the reconstruction methodology has mean value of Dice Coefficient and Hausdorff Distance is 0.749 and 1.746, respectively, while low ESS and high LDL concentration can predict plaque progression.