Reconstruction Of Coronary Arteries Research Articles

A continuous-action deep reinforcement learning-based agent for coronary artery centerline extraction in coronary CT angiography images.

The lumen centerline of the coronary artery allows vessel reconstruction used to detect stenoses and plaques. Discrete-action-based centerline extraction methods suffer from artifacts and plaques. This study aimed to develop a continuous-action-based method which performs more effectively in cases involving artifacts or plaques. A continuous-action deep reinforcement learning-based model was trained to predict the artery's direction and radius value. The model is based on an Actor-Critic architecture. The Actor learns a deterministic policy to output the actions made by an agent. These actions indicate the centerline's direction and radius value consecutively. The Critic learns a value function to evaluate the quality of the agent's actions. A novel DDR reward was introduced to measure the agent's action (both centerline extraction and radius estimate) at each step. The method achieved an average OV of 95.7%, OF of 93.6%, OT of 97.3%, and AI of 0.22 mm in 80 test data. In 53 cases with artifacts or plaques, it achieved an average OV of 95.0%, OF of 91.5%, OT of 96.7%, and AI of 0.23 mm. The 95% limits of agreement between the reference and estimated radius values were 0.46 mm and 0.43 mm in the 80 test data. Experiments demonstrate that the Actor-Critic architecture can achieve efficient centerline extraction and radius estimate. Compared with discrete-action-based methods, our method performs more effectively in cases involving artifacts or plaques. The extracted centerlines and radius values allow accurate coronary artery reconstruction that facilitates the detection of stenoses and plaques.

Early surgical outcomes in the composite-valve root replacement with bioprosthesis after surgery for acute type A aortic dissection.

This study aimed to evaluate the surgical outcomes of composite-valve root replacement with bioprosthesis (b-CVRR) after acute type A aortic dissection (AAAD) repair. We included 41 patients who underwent b-CVRR after surgery for AAAD from 2007 to 2022. We excluded seven patients with VSRR, three with mechanical valve use, one with mycotic aneurysm, and one with cardiopulmonary resuscitation. The overlapping surgical indications for b-CVRR were pseudoaneurysm in 21 patients (51.2%), severe AI in 19 (46.3%), re-dissection in 15 (36.6%), root dilatation (> 50mm) in 12 (41.5%), and rupture in 3 (7.3%). The coronary artery reconstruction methods were bilateral Carrel patch in 13 patients (32%), Carrel patch with Piehler in 16 patients (38%), bilateral Piehler in six patients (15%), and Piehler with coronary artery bypass (CABG) in six patients (15%). Four patients who underwent the Carrel patch technique required additional intraoperative CABG. Three hospital mortality occurred (7.3%; myonephropathic metabolic syndrome, heart failure, bleeding from the thyroid carotid artery without injury). No thrombosis of the reconstructed site was observed with the Piehler procedure. Surgical outcomes for patients treated with b-CVRR after AAAD repair were acceptable. Intraoperative coronary artery events occurred due to stenosis caused by traction on the reconstructed coronary artery due to adhesions.

Effective descriptor extraction strategies for correspondence matching in coronary angiography images

The importance of 3D reconstruction of coronary arteries using multiple coronary angiography (CAG) images has been increasingly recognized in the field of cardiovascular disease management. This process relies on the camera matrix’s optimization, needing correspondence info for identical point positions across two images. Therefore, an automatic method for determining correspondence between two CAG images is highly desirable. Despite this need, there is a paucity of research focusing on image matching in the CAG images. Additionally, standard deep learning image matching techniques often degrade due to unique features and noise in CAG images. This study aims to fill this gap by applying a deep learning-based image matching method specifically tailored for the CAG images. We have improved the structure of our point detector and redesigned loss function to better handle sparse labeling and indistinct local features specific to CAG images. Our method include changes to training loss and introduction of a multi-head descriptor structure leading to an approximate 6% improvement. We anticipate that our work will provide valuable insights into adapting techniques from general domains to more specialized ones like medical imaging and serve as an improved benchmark for future endeavors in X-ray image-based correspondence matching.

The Usefulness of Transesophageal Echocardiography to Assess Coronary Artery Blood Flow

Evaluation of coronary artery blood flow using transesophageal echocardiography is a very useful noninvasive and rapid test, although there are some problems such as technical differences between examiners and angle dependency of blood flow evaluation. In coronary artery bypass surgery, it is useful to determine the degree of preoperative coronary artery stenosis and to evaluate grafts, and in Bentall surgery, it is useful to confirm that no medically induced coronary artery stenosis caused by coronary artery reconstruction has occurred. Further studies will be conducted to improve the accuracy and usefulness of this method.

A hybrid convolutional and transformer network for segmentation of coronary computed tomography angiographic slices

AbstractCoronary artery three‐dimensional reconstruction is essential for preventing, diagnosing, and treating coronary heart disease. This study introduces SegUnet, a lightweight hybrid CNN‐Transformer network for pixel‐level segmentation of coronary artery computed tomography angiography (CTA) slices to enhance the precision of coronary artery reconstruction. The overall SegUnet adopts a U‐shaped encoder‐decoder structure, with a hierarchical Transformer structure serving as the encoder to extract global contextual information; the decoder is enhanced with spatial attention mechanism (SAM) and residual structure to improve its perception and adaptive adjustment abilities for coronary artery vessels. In contrast to other methods, we propose an interpolation‐based multi‐feature fusion bridge to integrate multi‐scale features between encoder levels, capturing their semantic dependencies. Experimental results show that SegUnet achieves a prediction accuracy of 97.23% on the test set of coronary arteries 2D slices. Moreover, the network exhibits excellent performance on Synapse Multi‐Organ Segmentation, highlighting the superiority, effectiveness, and robustness of our proposed method. The outstanding performance of SegUnet in coronary artery segmentation has elevated the quality of three‐dimensional reconstruction of the coronary arteries, exerting a positive impact on the enhancement of diagnosis and treatment of coronary artery diseases.

Completion Bentall procedure for a huge aortic root pseudoaneurysm after surgery for acute aortic dissection: A case report

A 56-year-old man with a history of emergency ascending aortic and aortic valve replacement for acute type A aortic dissection 6 months previously developed a huge pseudoaneurysm arising from the sinus of Valsalva due to recurrent aortic root dissection. The patient urgently underwent the completion Bentall procedure with coronary artery reconstruction using interposing grafts. During surgery, the non-coronary sinus of Valsalva was repeatedly dissected and ruptured, where surgical glue was applied in the previous operation. The 25-mm REGENT mechanical valve® from the previous operation was left in place, and 2-0 bladed mattress sutures were circumferentially placed in the sewing ring of the prosthesis. A 28-mm Valsalva graft® was cut at the middle of its skirt portion, through which these sutures were passed and tied, and was seated to completely cover the valve cuff. The completion Bentall procedure is considered a feasible technique for reoperative aortic root replacement in patients with a prosthetic aortic valve following acute type A aortic dissection repair. It is important to accurately measure the outer diameter of the prosthetic valve to ensure proper fit of the graft and to minimize the risk of bleeding.

Methodology of generation of CFD meshes and 4D shape reconstruction of coronary arteries from patient-specific dynamic CT

Due to the difficulties in retrieving both the time-dependent shapes of the vessels and the generation of numerical meshes for such cases, most of the simulations of blood flow in the cardiac arteries use static geometry. The article describes a methodology for generating a sequence of time-dependent 3D shapes based on images of different resolutions and qualities acquired from ECG-gated coronary artery CT angiography. The precision of the shape restoration method has been validated using an independent technique. The original proposed approach also generates for each of the retrieved vessel shapes a numerical mesh of the same topology (connectivity matrix), greatly simplifying the CFD blood flow simulations. This feature is of significant importance in practical CFD simulations, as it gives the possibility of using the mesh-morphing utility, minimizing the computation time and the need of interpolation between boundary meshes at subsequent time instants. The developed technique can be applied to generate numerical meshes in arteries and other organs whose shapes change over time. It is applicable to medical images produced by other than angio-CT modalities.

Rapid automated lumen segmentation of coronary optical coherence tomography images followed by 3D reconstruction of coronary arteries.

Optical coherence tomography has emerged as an important intracoronary imaging technique for coronary artery disease diagnosis as it produces high-resolution cross-sectional images of luminal and plaque morphology. Precise and fast lumen segmentation is essential for efficient OCT morphometric analysis. However, due to the presence of various image artifacts, including side branches, luminal blood artifacts, and complicated lesions, this remains a challenging task. Our research study proposes a rapid automatic segmentation method that utilizes nonuniform rational B-spline to connect limited pixel points and identify the edges of the OCT lumen. The proposed method suppresses image noise and accurately extracts the lumen border with a high correlation to ground truth images based on the area, minimal diameter, and maximal diameter. We evaluated the method using 3300 OCT frames from 10 patients and found that it achieved favorable results. The average time taken for automatic segmentation by the proposed method is 0.17s per frame. Additionally, the proposed method includes seamless vessel reconstruction following the lumen segmentation. The developed automated system provides an accurate, efficient, robust, and user-friendly platform for coronary lumen segmentation and reconstruction, which can pave the way for improved assessment of the coronary artery lumen morphology.

Early results of Left Anterior Descending Coronary artery (LAD) reconstruction in patients with poor target LAD in Coronary Artery Bypass Grafting procedure

Early results of Left Anterior Descending Coronary artery (LAD) reconstruction in patients with poor target LAD in Coronary Artery Bypass Grafting procedure

3D Vector Reconstruction of Coronary Arteries from Korean Visible Woman Sections at the Clinical and Numerical Anatomy Laboratory of the Faculty of Medicine and Odontostomatology in Bamako

3D Vector Reconstruction of Coronary Arteries from Korean Visible Woman Sections at the Clinical and Numerical Anatomy Laboratory of the Faculty of Medicine and Odontostomatology in Bamako

CMAR: A Pipeline for Cross-Modal Alignment and 3-D Reconstruction of Coronary Arteries Based on Key Bifurcation Vessel Measurements

CMAR: A Pipeline for Cross-Modal Alignment and 3-D Reconstruction of Coronary Arteries Based on Key Bifurcation Vessel Measurements

Surgical coronary angioplasty of both coronary ostia after chest radiotherapy. Is it good alternative to conventional coronary bypass surgery?

Isolated coronary ostial stenosis of both ostia is a rare, potentially life-threatening condition, occurring in 0.1%-0.2% of patients undergoing coronary angiography. We present a case of a 69-year-old woman with a past medical history of breast cancer, who had been treated with radiotherapy, which most likely caused significant stenosis of both coronary ostia and likely accelerated aortic stenosis. Surgical angioplasty with autopericardium patch reconstruction of the left main coronary artery and right coronary arteries due to proximal stenotic disease was performed instead of venous or arterial bypasses with concomitant aortic valve replacement. The postoperative course was uneventful. There were no cardiovascular events 5years after operation, and the patient remained free of any symptoms. Surgical coronary angioplasty offers an alternative to conventional coronary artery bypass grafting in isolated coronary ostial lesions and is advantageous in restoring more physiological myocardial perfusion, especially in those cases when conduits are suspected to be fibrotic, scarred or stenosed after radiation therapy or if there is the need to preserve conduits for future myocardial revascularisation in young patients.

Early and midterm outcomes of left anterior descending coronary artery reconstruction in extensive coronary artery atherosclerosis

Early and midterm outcomes of left anterior descending coronary artery reconstruction in extensive coronary artery atherosclerosis

An All-in-One Tool for 2D Atherosclerotic Disease Assessment and 3D Coronary Artery Reconstruction.

Diagnosis of coronary artery disease is mainly based on invasive imaging modalities such as X-ray angiography, intravascular ultrasound (IVUS) and optical coherence tomography (OCT). Computed tomography coronary angiography (CTCA) is also used as a non-invasive imaging alternative. In this work, we present a novel and unique tool for 3D coronary artery reconstruction and plaque characterization using the abovementioned imaging modalities or their combination. In particular, image processing and deep learning algorithms were employed and validated for the lumen and adventitia borders and plaque characterization at the IVUS and OCT frames. Strut detection is also achieved from the OCT images. Quantitative analysis of the X-ray angiography enables the 3D reconstruction of the lumen geometry and arterial centerline extraction. The fusion of the generated centerline with the results of the OCT or IVUS analysis enables hybrid coronary artery 3D reconstruction, including the plaques and the stent geometry. CTCA image processing using a 3D level set approach allows the reconstruction of the coronary arterial tree, the calcified and non-calcified plaques as well as the detection of the stent location. The modules of the tool were evaluated for efficiency with over 90% agreement of the 3D models with the manual annotations, while a usability assessment using external evaluators demonstrated high usability resulting in a mean System Usability Scale (SUS) score equal to 0.89, classifying the tool as "excellent".

Intra-atrial coronary artery reconstruction during surgery for cardiac angiosarcoma.

A cardiac angiosarcoma is usually located in the right atrium and tends to involve the right coronary artery. Our goal was to report a novel reconstruction technique after en bloc resection of a cardiac angiosarcoma with right coronary artery invasion. This technique includes orthotopic reconstruction of the invaded artery and atrial patch suturing onto the epicardium lateral to the reconstructed right coronary artery. Intra-atrial reconstruction with an end-to-end anastomosis can enhance the graft patency compared to a distal side-to-end anastomosis and can reduce the risk of anastomotic stenosis. Moreover, suturing the graft patch to the epicardium did not increase the risk of bleeding because the pressure in the right atrium was low.

Surgical Reconstruction of the Anomalous Left Coronary Artery From the Pulmonary Artery.

The anomalous left coronary artery from the pulmonary artery is a rare congenital disease. Early surgical reconstruction is mandatory to prevent adverse cardiac events. Direct coronary button transfer, vein graft interposition, ligation, and coronary artery bypass construction are the most commonly used techniques. This case report presents a modified technique of Dacron graft interposition and reimplantation anomalous left coronary artery from the pulmonary artery on the ascending aorta.

Retracted: The Value of Iterative Reconstruction of Algorithm-Based Coronary Artery Computed Tomography Imaging in the Diagnosis of Old Myocardial Infarction.

[This retracts the article DOI: 10.1155/2021/4383963.].

Abstract 15038: Collateral Flow From the Right Coronary Artery Alone is Not Sufficient for Adult Alcapa: Clinical Case Report

Introduction: Myocardial ischemia in adult ALCAPA (Anomalous left coronary artery from the pulmonary artery) may lead to sudden death as the first clinical presentation. Cardiac blood supply from the right coronary artery alone is not sufficient for an adult ALCAPA. The aim of the present study was to describe a clinical case of severe myocardial ischemia in an adult female with ALCAPA supplied by the right coronary artery alone. Patient and Clinical data: 45-year-old female patient admitted to our hospital due to recurrent palpitation with tachypnoea after physical exertion for 2 years. Resting ECG on admission with ST-T changes and frequent premature ventricular contractions (PVC) indicated significant myocardial ischemia. Transthoracic echocardiography (TTE) showed dilated left ventricle (LVDd 64mm) with regional systolic dysfunction anterolateral and posterolateral with EF of 44% and dilated right coronary artery. An ALCAPA was observed with dilated caliber of 9 mm at ostium (Panel A) which was confirmed by computed tomographic angiography of the coronary artery and coronary angiography. Well-developed collateral vessels between peripheral right posterior descending (RPD) and distal left anterior descending (LAD) were demonstrated (Panel F). No collateral vessel was found between bronchial artery and ALCAPA. The bronchial arteries were visualized in normal size. The left coronary ostium was not found in the aortic root at aortography. The patient underwent anatomical reconstruction of left main coronary artery by using autologous pulmonary flap and recovered well postoperatively. Results: Postoperative ECG showed that the preoperative ST-T changes and PVC disappeared completely. Cardiac magnetic resonance imaging and TTE one month and 6 months postoperatively demonstrated continuously improved LV systolic function and myocardial perfusion posterolaterally and anterolaterally. Conclusion: Collateral flow from the right coronary artery alone is not sufficient for adult ALCAPA and completely surgical correction is necessary.

Murray law-based quantitative flow ratio for assessment of left main bifurcation derived from a single fluoroscopic angiographic view as compared to FFRCT

Abstract Background In patients with complex CAD, the presence of left main (LM) disease is an important prognostic factor in assessing the risk balance between PCI and CABG. Functional assessment has become standard of care to evaluate the significance of coronary stenosis and to justify the performance of PCI in the contemporary practice. FFRCT is a well-established method based on 3D reconstruction of coronary artery derived from CCTA. The Murray law-based quantitative flow reserve (μQFR) is a novel computational method of invasive angiography relying on a single angiographic view that takes into account side branches diameters to compute fractal flow division. The aim of the current analysis is to evaluate in patients with complex CAD the feasibility of μQFR in LM bifurcation and its diagnostic concordance with FFRCT. The impact of the optimal viewing angle defined by CCTA on the physiological assessment of the LM bifurcation using a single angiographic view was also evaluated. Methods In 299 consecutive patients with 3-vessel disease with or without LM coronary artery disease, up to 3 analyzable fluoroscopic projections per patient were analysed with μQFR retrospectively. FFRCT and μQFR were measured at 3 fiducial landmark points: i) point of LM bifurcation (POB); ii) proximal LAD 10 mm distal to POB; ii) proximal LCX 10 mm distal to POB. CCTA-based “optimal viewing angle” of LM bifurcation are computed by creating a 3-point closed spline involving the LM, LAD, and LCX at 5mm from the POB and subsequently by reconstructing the “en face” fluoroscopic viewing angle of the spline. The en face viewing angle provides an optimal assessment of the bifurcation geometry [1]. In terms of Rx gantry angulation, the closest angiographic projection to the optimal viewing angle derived from CCTA was defined as the “best fluoroscopic projection” for each patient. Results In 299 patients, 793 projections were analysed with μQFR and compared to FFRCT. Single view μQFR was analyzable in 100%. Correlation and agreement between μQFR and FFRCT for 793 projections in 299 patients are shown in Figure 1A, 2A. The Spearman's correlation coefficient showed moderate correlations at POB (r=0.481, p<0.001) and LCX (r=0.584, p<0.001), and strong correlation at LAD (r=0.642, p<0.001). Correlation and agreement between μQFR and FFRCT for best projections from each patient are shown in Figure 1B, 2B. Correlations were improved in the best projections with the following Spearman's correlation coefficient: at POB (r=0.522, p<0.001), LCX (r=0.622, p<0.001), and LAD (r=0.695, p<0.001). Conclusion Computation of μQFR from a single angiographic view has a high feasibility. Tailored optimal fluoroscopic view is essential for the physiological assessment of the LM bifurcation using a single angiographic view. Evaluation of diagnostic accuracy of μQFR warrants further analysis of the LMCAD after prospective planning of the optimal fluoroscopic view based on the selection of the best CCTA 3D view. Funding Acknowledgement Type of funding sources: None.

X-ray coronary centerline extraction based on C-UNet and a multifactor reconnection algorithm

Background and objective: Accurate extraction of the coronary artery centerline is crucial in the processes of coronary artery reconstruction, coronary artery stenosis or lesion detection, and surgical navigation. Furthermore, in clinical medicine, the complex background of angiography, low signal-to-noise ratio, and complex vascular structure make coronary artery centerline extraction challenging. In this study, a direct centerline extraction method is proposed that automatically and accurately extracts vascular centerlines from X-ray coronary angiography images based on deep learning and conventional methods.Methods: In this study, a coronary artery centerline extraction method is proposed that comprises two parts: the preliminary centerline extraction network based on U-Net with a residual network, called C-UNet, and the multifactor centerline reconnection algorithm based on the geometric characteristics of blood vessels.Results: The qualitative and quantitative results demonstrate the effectiveness of the presented method. In this study, three widely used evaluation indices were adopted to evaluate the performance of the method: precision, recall, and F1_Score. The experimental results show that this method can accurately extract coronary artery centerlines.Conclusions: The proposed centerline extraction method accurately extracts centerlines from X-ray coronary angiography images and improves both the accuracy and continuity of centerline extraction.