3D reconstruction of coronary arteries using frequency domain optical coherence tomography images and biplane angiography

Fully-Automatic 3D Intuitive Visualization of Age-Related Macular Degeneration Fluid Accumulations in OCT Cubes

Age-related macular degeneration is the leading cause of vision loss in developed countries, and wet-type AMD requires urgent treatment and rapid diagnosis because it causes rapid irreversible vision loss. Currently, AMD diagnosis is mainly carried out using images obtained by optical coherence tomography. This diagnostic process is performed by human clinicians, so human error may occur in some cases. Therefore, fully automatic methodologies are highly desirable adding a layer of robustness to the diagnosis. In this work, a novel computer-aided diagnosis and visualization methodology is proposed for the rapid identification and visualization of wet AMD. We adapted a convolutional neural network for segmentation of a similar domain of medical images to the problem of wet AMD segmentation, taking advantage of transfer learning, which allows us to work with and exploit a reduced number of samples. We generate a 3D intuitive visualization where the existence, position and severity of the fluid were represented in a clear and intuitive way to facilitate the analysis of the clinicians. The 3D visualization is robust and accurate, obtaining satisfactory 0.949 and 0.960 Dice coefficients in the different evaluated OCT cube configurations, allowing to quickly assess the presence and extension of the fluid associated to wet AMD.

The effect of the degree and location of coronary stenosis on the hemodynamic status of a coronary vessel

The ongoing advances in the field of cardiovascular modelling during the past years have allowed for the creation of accurate three-dimensional models of the major coronary arteries. The aforementioned 3D models can accurately mimic the human coronary vasculature if they are combined with sophisticated computational fluid dynamics algorithms and shed light to non-trivial issues that concern the clinicians. One of these issues is to define whether a coronary lesion is more dangerous to present with ischemia if it is at a proximal or a distal part of the vessel. In this work, we aim to investigate the aforementioned issue by reconstructing in 3D a coronary arterial model from a healthy subject using Computed Tomography Coronary Angiography images and by editing it to create eight diseased arterial models that contain one or two lesions of different severities. After carrying out the appropriate blood flow simulations using the finite element method, we observed that the distal lesions are more dangerous than the proximal ones in terms of hemodynamic significance. Moreover, the distal severe stenosis (i.e. 70% diameter reduction) present with the highest peak Wall Shear Stress (WSS) values in comparison to the proximal ones.

The effect of the stenosis location at a coronary arterial bifurcation: a parametric study

The advances in cardiovascular modelling over the past two decades have given the opportunity to create accurate three dimensional models of the coronary vasculature which, combined with advanced computational fluid dynamics algorithms can shed light to intriguing matters that concern clinicians. One of these issues is the presence of a stenosis near bifurcations in one of the major coronary vessels. In this work, we try to shed light on the aforementioned matter by creating a healthy arterial bifurcation reconstructed using the fusion of Optical Coherence Tomography and X-Ray angiography images. The healthy model was edited by adding an artificial stenosis of 50% diameter reduction into three different locations after the bifurcation, thus creating three diseased models. After performing the appropriate blood flow simulations, we observed that the location of the stenosis affects the Wall Shear Stress (WSS) distribution but it does not affect the functional significance of the stenosis itself.

The Evolution of Data Fusion Methodologies Developed to Reconstruct Coronary Artery Geometry From Intravascular Imaging and Coronary Angiography Data: A Comprehensive Review

Understanding the mechanisms that regulate atherosclerotic plaque formation and evolution is a crucial step for developing treatment strategies that will prevent plaque progression and reduce cardiovascular events. Advances in signal processing and the miniaturization of medical devices have enabled the design of multimodality intravascular imaging catheters that allow complete and detailed assessment of plaque morphology and biology. However, a significant limitation of these novel imaging catheters is that they provide two-dimensional (2D) visualization of the lumen and vessel wall and thus they cannot portray vessel geometry and 3D lesion architecture. To address this limitation computer-based methodologies and user-friendly software have been developed. These are able to off-line process and fuse intravascular imaging data with X-ray or computed tomography coronary angiography (CTCA) to reconstruct coronary artery anatomy. The aim of this review article is to summarize the evolution in the field of coronary artery modeling; we thus present the first methodologies that were developed to model vessel geometry, highlight the modifications introduced in revised methods to overcome the limitations of the first approaches and discuss the challenges that need to be addressed, so these techniques can have broad application in clinical practice and research.

Optimized Computer-Aided Segmentation and Three-Dimensional Reconstruction Using Intracoronary Optical Coherence Tomography

We present a novel and time-efficient method for intracoronary lumen detection, which produces three-dimensional (3-D) coronary arteries using optical coherence tomographic (OCT) images. OCT images are acquired for multiple patients and longitudinal cross-section (LOCS) images are reconstructed using different acquisition angles. The lumen contours for each LOCS image are extracted and translated to 2-D cross-sectional images. Using two angiographic projections, the centerline of the coronary vessel is reconstructed in 3-D, and the detected 2-D contours are transformed to 3-D and placed perpendicular to the centerline. To validate the proposed method, 613 manual annotations from medical experts were used as gold standard. The 2-D detected contours were compared with the annotated contours, and the 3-D reconstructed models produced using the detected contours were compared to the models produced by the annotated contours. Wall shear stress (WSS), as dominant hemodynamics factor, was calculated using computational fluid dynamics and 844 consecutive 2-mm segments of the 3-D models were extracted and compared with each other. High Pearson's correlation coefficients were obtained for the lumen area (r = 0.98) and local WSS (r = 0.97) measurements, while no significant bias with good limits of agreement was shown in the Bland-Altman analysis. The overlapping and nonoverlapping areas ratio between experts' annotations and presented method was 0.92 and 0.14, respectively. The proposed computer-aided lumen extraction and 3-D vessel reconstruction method is fast, accurate, and likely to assist in a number of research and clinical applications.

Bimodal intravascular volumetric imaging combining OCT and MPI

PURPOSE

Intravascular optical coherence tomography (IVOCT) is a catheter-based image modality allowing for high-resolution imaging of vessels. It is based on a fast sequential acquisition of A-scans with an axial spatial resolution in the range of 5-10 μm, that is, one order of magnitude higher than in conventional methods like intravascular ultrasound or computed tomography angiography. However, position and orientation of the catheter in patient coordinates cannot be obtained from the IVOCT measurements alone. Hence, the pose of the catheter needs to be established to correctly reconstruct the three-dimensional vessel shape. Magnetic particle imaging (MPI) is a three-dimensional tomographic, tracer-based, and radiation-free image modality providing high temporal resolution with unlimited penetration depth. Volumetric MPI images are angiographic and hence suitable to complement IVOCT as a comodality. We study simultaneous bimodal IVOCT MPI imaging with the goal of estimating the IVOCT pullback path based on the 3D MPI data.

METHODS

We present a setup to study and evaluate simultaneous IVOCT and MPI image acquisition of differently shaped vessel phantoms. First, the influence of the MPI tracer concentration on the optical properties required for IVOCT is analyzed. Second, using a concentration allowing for simultaneous imaging, IVOCT and MPI image data are acquired sequentially and simultaneously. Third, the luminal centerline is established from the MPI image volumes and used to estimate the catheter pullback trajectory for IVOCT image reconstruction. The image volumes are compared to the known shape of the phantoms.

RESULTS

We were able to identify a suitable MPI tracer concentration of 2.5 mmol/L with negligible influence on the IVOCT signal. The pullback trajectory estimated from MPI agrees well with the centerline of the phantoms. Its mean absolute error ranges from 0.27 to 0.28 mm and from 0.25 mm to 0.28 mm for sequential and simultaneous measurements, respectively. Likewise, reconstructing the shape of the vessel phantoms works well with mean absolute errors for the diameter ranging from 0.11 to 0.21 mm and from 0.06 to 0.14 mm for sequential and simultaneous measurements, respectively.

CONCLUSIONS

Magnetic particle imaging can be used in combination with IVOCT to estimate the catheter trajectory and the vessel shape with high precision and without ionizing radiation.

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.

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.

Patient-Specific Modeling of Stented Coronary Arteries Reconstructed from Optical Coherence Tomography: Towards a Widespread Clinical Use of Fluid Dynamics Analyses

The recent widespread application of optical coherence tomography (OCT) in interventional cardiology has improved patient-specific modeling of stented coronary arteries for the investigation of local hemodynamics. In this review, the workflow for the creation of fluid dynamics models of stented coronary arteries from OCT images is presented. The algorithms for lumen contours and stent strut detection from OCT as well as the reconstruction methods of stented geometries are discussed. Furthermore, the state of the art of studies that investigate the hemodynamics of OCT-based stented coronary artery geometries is reported. Although those studies analyzed few patient-specific cases, the application of the current reconstruction methods of stented geometries to large populations is possible. However, the improvement of these methods and the reduction of the time needed for the entire modeling process are crucial for a widespread clinical use of the OCT-based models and future in silico clinical trials.

Vessel centerline reconstruction from non-isocentric and non-orthogonal paired monoplane angiographic images

PURPOSE

Three-dimensional reconstruction of a vessel centerline from paired planar coronary angiographic images is critical to reconstruct the complex three-dimensional structure of the coronary artery lumen and the relative positioning of implanted devices. In this study, a new vessel centerline reconstruction method that can utilize non-isocentric and non-orthogonal pairs of angiographic images was developed and tested.

METHODS

Our new method was developed in in vitro phantom models of bifurcated coronary artery with and without stent, and then tested in in vivo swine models (twelve coronary arteries). This method was also validated using data from six patients.

RESULTS

Our new method demonstrated high accuracy (root mean square error = 0.27 mm or 0.76 pixel), and high reproducibility across a broad imaging angle (20°-130°) and between different cardiac cycles in vitro and in vivo. Use of this method demonstrated that the vessel centerline in the stented segment did not deform significantly over a cardiac cycle in vivo. In addition, the total movement of the isocenter in each image could be accurately estimated in vitro and in vivo. The performance of this new method for patient data was similar to that for in vitro phantom models and in vivo animal models.

CONCLUSIONS

We developed a vessel centerline reconstruction method for non-isocentric and non-orthogonal angiographic images. It demonstrated high accuracy and good reproducibility in vitro, in vivo, and in clinical setting, suggesting that our new method is clinically applicable despite the small sample size of clinical data.

Automated Segmentation of Bioresorbable Vascular Scaffold Struts in Intracoronary Optical Coherence Tomography Images

Bioresorbable vascular scaffolds (BVS), the next step in the continuum of minimally invasive vascular interventions present new opportunities for patients and clinicians but challenges as well. As they are comprised of polymeric materials standard imaging is challenging. This is especially problematic as modalities like optical coherence tomography (OCT) become more prevalent in cardiology. OCT, a light-based intracoronary imaging technique, provides cross-sectional images of plaque and luminal morphology. Until recently segmentation of OCT images for BVS struts was performed manually by experts. However, this process is time consuming and not tractable for large amounts of patient data. Several automated methods exist to segment metallic stents, which do not apply to the newer BVS. Given this current limitation coupled with the emerging popularity of the BVS technology, it is crucial to develop an automated methodology to segment BVS struts in OCT images. The objective of this paper is to develop a novel BVS strut detection method in intracoronary OCT images. First, we preprocess the image to remove imaging artifacts. Then, we use a K-means clustering algorithm to automatically segment the image. Finally, we isolate the stent struts from the rest of the image. The accuracy of the proposed method was evaluated using expert estimations on 658 annotated images acquired from 7 patients at the time of coronary arterial interventions. Our proposed methodology has a positive predictive value of 0.93, a Pearson Correlation coefficient of 0.94, and a F1 score of 0.92. The proposed methodology allows for rapid, accurate, and fully automated segmentation of BVS struts 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.

Reconstruction of stented coronary arteries from optical coherence tomography images: Feasibility, validation, and repeatability of a segmentation method

Optical coherence tomography (OCT) is an established catheter-based imaging modality for the assessment of coronary artery disease and the guidance of stent placement during percutaneous coronary intervention. Manual analysis of large OCT datasets for vessel contours or stent struts detection is time-consuming and unsuitable for real-time applications. In this study, a fully automatic method was developed for detection of both vessel contours and stent struts. The method was applied to in vitro OCT scans of eight stented silicone bifurcation phantoms for validation purposes. The proposed algorithm comprised four main steps, namely pre-processing, lumen border detection, stent strut detection, and three-dimensional point cloud creation. The algorithm was validated against manual segmentation performed by two independent image readers. Linear regression showed good agreement between automatic and manual segmentations in terms of lumen area (r>0.99). No statistically significant differences in the number of detected struts were found between the segmentations. Mean values of similarity indexes were >95% and >85% for the lumen and stent detection, respectively. Stent point clouds of two selected cases, obtained after OCT image processing, were compared to the centerline points of the corresponding stent reconstructions from micro computed tomography, used as ground-truth. Quantitative comparison between the corresponding stent points resulted in median values of ~150 μm and ~40 μm for the total and radial distances of both cases, respectively. The repeatability of the detection method was investigated by calculating the lumen volume and the mean number of detected struts per frame for seven repeated OCT scans of one selected case. Results showed low deviation of values from the median for both analyzed quantities. In conclusion, this study presents a robust automatic method for detection of lumen contours and stent struts from OCT as supported by focused validation against both manual segmentation and micro computed tomography and by good repeatability.

Computational estimation of the severity of coronary lesions with intravascular ultrasound images: a pilot study

The fast and accurate hemodynamic functional assessment of the coronary vasculature is of utmost importance in clinical practice due to the fact that Cardiovascular Diseases have become the leading cause of death globally. In this work we propose a novel method that combines two of the most efficient methods of hemodynamic status assessment of coronary arteries, Intravascular UtraSound and virtual Functional Assessment Index, an index that correlates well to the measured Fractional Flow Reserve. One Left Anterior Descending segment was reconstructed both in a straight manner (using only IVUS images) as well as using the actual 3D geometry of the vessel (using IvUS images combined with the respective coronary angiographic images [2]). The generated vFAI values were almost identical (Straight=0.80, 3D=0.79), presenting a relative error of 1.27%, thus proving the efficacy of the proposed method. We also calculated the Endothelial Shear Stress for the two models under rest (i.e. flow rate of 1 ml/s), observing a similar trend throughout the artery, but with a statistically important relative error of 13.49%, as expected.

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.

Computational assessment of the fractional flow reserve from intravascular ultrasound and coronary angiography data: a pilot study

Cardiovascular disease is one of the primary causes of morbidity and mortality around the globe. Thus, the diagnosis of critical lesions in coronary arteries is of utmost importance in clinical practice. One useful and efficient method to assess the functional severity of one or multiple lesions in a coronary artery is the calculation of the fractional flow reserve (FFR). In the current work, we present a method which allows the calculation of the FFR value computationally, without the use of a pressure wire and the induction of hyperemia, using intravascular ultrasound (IVUS) and biplane angiography images for three-dimensional (3D) coronary artery reconstruction and measurements of the volumetric flow rate derived from angiographic sequences. The simulated FFR values were compared to the invasively measured FFR values in 7 cases, presenting high correlation (r=0.85) and good agreement (mean difference=0.002). FFR assessment without employing a pressure wire and the induction of hyperemia is feasible using 3D reconstructed coronary artery models from angiographic and IVUS data coupled with computational fluid dynamics.

Three-dimensional virtual surgery models for percutaneous coronary intervention (PCI) optimization strategies

Percutaneous coronary intervention (PCI), especially coronary stent implantation, has been shown to be an effective treatment for coronary artery disease. However, in-stent restenosis is one of the longstanding unsolvable problems following PCI. Although stents implanted inside narrowed vessels recover normal flux of blood flows, they instantaneously change the wall shear stress (WSS) distribution on the vessel surface. Improper stent implantation positions bring high possibilities of restenosis as it enlarges the low WSS regions and subsequently stimulates more epithelial cell outgrowth on vessel walls. To optimize the stent position for lowering the risk of restenosis, we successfully established a digital three-dimensional (3-D) model based on a real clinical coronary artery and analysed the optimal stenting strategies by computational simulation. Via microfabrication and 3-D printing technology, the digital model was also converted into in vitro microfluidic models with 3-D micro channels. Simultaneously, physicians placed real stents inside them; i.e., they performed “virtual surgeries”. The hydrodynamic experimental results showed that the microfluidic models highly inosculated the simulations. Therefore, our study not only demonstrated that the half-cross stenting strategy could maximally reduce restenosis risks but also indicated that 3-D printing combined with clinical image reconstruction is a promising method for future angiocardiopathy research.

Patient-specific coronary stenoses can be modeled using a combination of OCT and flow velocities to accurately predict hyperemic pressure gradients

Computational fluid dynamics (CFD) is increasingly being developed for the diagnostics of arterial diseases. Imaging methods such as computed tomography (CT) and angiography are commonly used. However, these have limited spatial resolution and are subject to movement artifact. This study developed a new approach to generate CFD models by combining high-fidelity, patient-specific coronary anatomy models derived from optical coherence tomography (OCT) imaging with patient-specific pressure and velocity phasic data. Additionally, we used a new technique which does not require the catheter to be used to determine the centerline of the vessel. The CFD data were then compared with invasively measured pressure and velocity. Angiography imaging data of 21 vessels collected from 19 patients were fused with OCT visualizations of the same vessels using an algorithm that produces reconstructions inheriting the in-plane (10 μm) and longitudinal (0.2 mm) resolution of OCT. Proximal pressure and distal velocity waveforms ensemble averaged from invasively measured data were used as inlet and outlet boundary conditions, respectively, in CFD simulations. The resulting distal pressure waveform was compared against the measured waveform to test the model. The results followed the shape of the measured waveforms closely (cross-correlation coefficient = 0.898 ± 0.005, ), indicating realistic modeling of flow resistance, the mean of differences between measured and simulated results was -3. 5 mmHg, standard deviation of differences (SDD) = 8.2 mmHg over the cycle and -9.8 mmHg, SDD = 16.4 mmHg at peak flow. Models incorporating phasic velocity in patient-specific models of coronary anatomy derived from high-resolution OCT images show a good correlation with the measured pressure waveforms in all cases, indicating that the model results may be an accurate representation of the measured flow conditions.

Assessing the hemodynamic influence between multiple lesions in a realistic right coronary artery segment: A computational study

Coronary artery disease is the primary cause of morbidity and mortality worldwide. Therefore, detailed assessment of lesions in the coronary vasculature is critical in current clinical practice. Fractional flow reserve (FFR) has been proven as an efficient method for assessing the hemodynamic severity of a coronary stenosis. However, functional assessment of a coronary segment with multiple stenoses (≥ 2) remains complex for guiding the strategy of percutaneous coronary intervention due to the hemodynamic interplay between adjacent stenoses. In this work, we created four 3-dimensional (3D) arterial models that derive from a healthy patient-specific right coronary artery segment. The initial healthy model was reconstructed using fusion of intravascular ultrasound (IVUS) and biplane angiographic patient data. The healthy 3D model presented a measured FFR value of 0.96 (pressure-wire) and a simulated FFR value of 0.98. We then created diseased models with two artificial sequential stenoses of 90% lumen area reduction or with the proximal and distal stenosis separately. We calculated the FFR value for each case: 0.65 for the case with the two stenoses, 0.73 for the case with the distal stenosis and 0.90 for the case with the proximal stenosis. This leads to the conclusion that although both stenoses had the same degree of lumen area stenosis, there was a large difference in hemodynamic severity, thereby indicating that angiographic lumen assessment by itself is often not adequate for accurate assessment of coronary lesions.

Fusion of optical coherence tomographic and angiographic data for more accurate evaluation of the endothelial shear stress patterns and neointimal distribution after bioresorbable scaffold implantation: comparison with intravascular ultrasound-derived reconstructions

Intravascular ultrasound (IVUS)-based reconstructions have been traditionally used to examine the effect of endothelial shear stress (ESS) on neointimal formation. The aim of this analysis is to compare the association between ESS and neointimal thickness (NT) in models obtained by the fusion of optical coherence tomography (OCT) and coronary angiography and in the reconstructions derived by the integration of IVUS and coronary angiography. We analyzed data from six patients implanted with an Absorb bioresorbable vascular scaffold that had biplane angiography, IVUS and OCT investigation at baseline and 6 or 12 months follow-up. The IVUS and OCT follow-up data were fused separately with the angiographic data to reconstruct the luminal morphology at baseline and follow-up. Blood flow simulation was performed on the baseline reconstructions and the ESS was related to NT. In the OCT-based reconstructions the ESS were lower compared to the IVUS-based models (1.29 ± 0.66 vs. 1.87 ± 0.66 Pa, P = 0.030). An inverse correlation was noted between the logarithmic transformed ESS and the measured NT in all the OCT-based models which was higher than the correlation reported in five of the six IVUS-derived models (-0.52 ± 0.19 Pa vs. -0.10 ± 0.04, P = 0.028). Fusion of OCT and coronary angiography appears superior to IVUS-based reconstructions; therefore it should be the method of choice for the study of the effect of the ESS on neointimal proliferation.