Search Results (421)

Background: Segmenting computed tomography (CT) is crucial in various clinical applications, such as tailoring personalized cardiac ablation for managing cardiac arrhythmias. Automating segmentation through machine learning (ML) is hindered by the necessity for large, labeled training data, which can be challenging to obtain. This article proposes a novel approach for automated, robust labeling using domain knowledge to achieve high-performance segmentation by ML from a small training set. The approach, the domain knowledge-encoding (DOKEN) algorithm, reduces the reliance on large training datasets by encoding cardiac geometry while automatically labeling the training set. The method was validated in a hold-out dataset of CT results from an atrial fibrillation (AF) ablation study. Methods: The DOKEN algorithm parses left atrial (LA) structures, extracts “anatomical knowledge” by leveraging digital LA models (available publicly), and then applies this knowledge to achieve high ML segmentation performance with a small number of training samples. The DOKEN-labeled training set was used to train a nnU-Net deep neural network (DNN) model for segmenting cardiac CT in N = 20 patients. Subsequently, the method was tested in a hold-out set with N = 100 patients (five times larger than training set) who underwent AF ablation. Results: The DOKEN algorithm integrated with the nn-Unet model achieved high segmentation performance with few training samples, with a training to test ratio of 1:5. The Dice score of the DOKEN-enhanced model was 96.7% (IQR: 95.3% to 97.7%), with a median error in surface distance of boundaries of 1.51 mm (IQR: 0.72 to 3.12) and a mean centroid–boundary distance of 1.16 mm (95% CI: −4.57 to 6.89), similar to expert results (r = 0.99; p < 0.001). In digital hearts, the novel DOKEN approach segmented the LA structures with a mean difference for the centroid–boundary distances of −0.27 mm (95% CI: −3.87 to 3.33; r = 0.99; p < 0.0001). Conclusions: The proposed novel domain knowledge-encoding algorithm was able to perform the segmentation of six substructures of the LA, reducing the need for large training data sets. The combination of domain knowledge encoding and a machine learning approach could reduce the dependence of ML on large training datasets and could potentially be applied to AF ablation procedures and extended in the future to other imaging, 3D printing, and data science applications. Full article

Background: Neuron-specific enolase (NSE) has traditionally been used as a biomarker to predict neurologic outcomes after cardiac arrest. This study aimed to evaluate the utility of NSE in predicting neurologic outcomes in patients undergoing extracorporeal cardiopulmonary resuscitation (ECPR). Methods: This observational cohort study included 47 consecutive adult ECPR patients (median age, 59.0 years; 74.5% males) treated between January 2018 and December 2021 at a tertiary extracorporeal life support center. The primary outcome was a poor neurologic outcome, defined as a Cerebral Performance Category score of 3–5 at hospital discharge. Results: Twelve (25.5%) patients had abnormal findings on computed tomography of the brain. A poor neurologic outcome was demonstrated in 22 (46.8%) patients. The NSE level at 72 h after ECPR showed the best prediction power for a poor neurologic outcome compared with NSE at 24 and 48 h. A cutoff value exceeding 61.9 μg/L for NSE at 72 h yielded an area under the curve (AUC) of 0.791 for predicting poor neurologic outcomes and exceeding 62.1 μg/L with an AUC of 0.838 for 30-day mortality. Conclusions: NSE levels at 72 h after ECPR appear to be a reliable biomarker for predicting poor neurologic outcomes and 30-day mortality in ECPR patients. Full article

Single photon emission tomography/computed tomography (SPECT/CT) is a mature imaging technology with a dynamic role in the diagnosis and monitoring of a wide array of diseases. This paper reviews the technological advances, clinical impact, and future directions of SPECT and SPECT/CT imaging. The focus of this review is on signal amplifier devices, detector materials, camera head and collimator designs, image reconstruction techniques, and quantitative methods. Bulky photomultiplier tubes (PMTs) are being replaced by position-sensitive PMTs (PSPMTs), avalanche photodiodes (APDs), and silicon PMs to achieve higher detection efficiency and improved energy resolution and spatial resolution. Most recently, new SPECT cameras have been designed for cardiac imaging. The new design involves using specialised collimators in conjunction with conventional sodium iodide detectors (NaI(Tl)) or an L-shaped camera head, which utilises semiconductor detector materials such as CdZnTe (CZT: cadmium–zinc–telluride). The clinical benefits of the new design include shorter scanning times, improved image quality, enhanced patient comfort, reduced claustrophobic effects, and decreased overall size, particularly in specialised clinical centres. These noticeable improvements are also attributed to the implementation of resolution-recovery iterative reconstructions. Immense efforts have been made to establish SPECT and SPECT/CT imaging as quantitative tools by incorporating camera-specific modelling. Moreover, this review includes clinical examples in oncology, neurology, cardiology, musculoskeletal, and infection, demonstrating the impact of these advancements on clinical practice in radiology and molecular imaging departments. Full article

Background/Objectives: The aim of this study was to analyze a group of patients with a bicuspid aortic valve (BAV) examined with ECG-gated cardiac CT (ECG-CT), focusing on the assessment of the clinical reasons for cardiac CT, cardiovascular abnormalities coexisting with their BAV, and coronary artery stenosis. Methods: A detailed statistical analysis was conducted on 700 patients with a BAV from a group of 15,670 patients examined with ECG-CT. Results: The incidence of a BAV in ECG-CT was 4.6%. The most common reason for examination was suspicion of coronary heart disease—31.1%. Cardiovascular defects most frequently associated with a BAV were a VSD (4.3%) and coarctation of the aorta (3.6%), while among coronary anomalies, they were high-take-off coronary arteries (6.4%) and paracommissural orifice of coronary arteries (4.4%). The analysis of the coronary artery calcium index showed significantly lower values for type 2 BAV compared to other valve types (p < 0.001), with the lowest average age in this group of patients. Moreover, the presence of a raphe between the coronary and non-coronary cusps was associated with a higher rate of significant coronary stenosis compared to other types of BAVs (p < 0.001). Conclusions: The most common reason for referral for cardiac ECG-CT in the group ≤ 40-year-olds with a BAV was the suspicion of congenital cardiovascular defects, while in the group of over 40-year-olds, it was the suspicion of coronary artery disease. The incidence of cardiovascular abnormalities co-occurring with BAV and diagnosed with ECG-CT differs among specific patient subgroups. The presence of a raphe between the coronary and non-coronary cusps appears to be a potential risk factor for significant coronary stenosis in patients with BAVs. Full article

Background: The electrodes of implantable cardiac devices (ICDs) may cause significant problems in cardiac computed tomography (CT) because they are a source of artifacts that obscure surrounding structures and possible pathology. There are a few million patients currently with ICDs, and some of these patients will require cardiac imaging due to coronary artery disease or problems with ICDs. Modern CT scanners can reduce some of the metal artifacts because of MAR software, but in some vendors, it does not work with ECG gating. Introduced in 2008, dual-energy CT scanners can generate virtual monoenergetic images (VMIs), which are much less susceptible to metal artifacts than standard CT images. Objective: This study aimed to evaluate if dual-energy CT can reduce metal artifacts caused by ICD leads by using VMIs. The second objective was to determine how the angle between the electrode and the plane of imaging affects the severity of the artifacts in three planes of imaging. Methods: A 3D-printed model was constructed to obtain a 0–90-degree field at 5-degree intervals between the electrode and each of the planes: axial, coronal, and sagittal. This electrode was scanned in dual-energy and single-energy protocols. VMIs with an energy of 40–140 keV with 10 keV intervals were reconstructed. The length of the two most extended artifacts originating from the tip of the electrode and 2 cm above it—at the point where the thick metallic defibrillating portion of the electrode begins—was measured. Results: For the sagittal plane, these observations were similar for both points of the ICDs that were used as the reference location. VMIs with an energy over 80 keV produce images with fewer artifacts than similar images obtained in the single-energy scanning mode. Conclusions: Virtual monoenergetic imaging techniques may reduce streak artifacts arising from ICD electrodes and improve the quality of the image. Increasing the angle of the electrode as well as the imaging plane can reduce artifacts. The angle between the electrode and the beam of X-rays can be increased by tilting the gantry of the scanner or lifting the upper body of the patient. Full article

Infective endocarditis is a rare disease with an increasing incidence and an unaltered high mortality rate, despite medical development. Imaging plays an integrative part in the diagnosis of infective endocarditis, with echocardiography as the initial diagnostic test. Research data in the utility of cardiac computed tomography (CCT) in the diagnostic algorithm of IE are rising, which indicates its importance in detection of IE-related lesion along with the exclusion of coronary artery disease. The latest 2023 European Society of Cardiology Guidelines in the management of IE classified CCT as class of recommendation I and level of evidence B in detection of both valvular and paravalvular lesions in native and prosthetic valve endocarditis. This review article provides a comprehensive and contemporary review of the role of CCT in the diagnosis of IE, the optimization of acquisition protocols, the morphology characteristics of IE-related lesions, the published data of the diagnostic performance of CCT in comparison to echocardiography as the state-of-art method, as well as the limitations and future possibilities. Full article

Background: In arrhythmogenic right ventricular cardiomyopathy (ARVC) non-invasive scar evaluation is not included among the diagnostic criteria or the predictors of ventricular arrhythmias (VA) and sudden death (SD). Computed tomography (CT) has excellent spatial resolution and allows a clear distinction between myocardium and fat; thus, it has great potential for the evaluation of myocardial scar in ARVC. Objective: The objective of this study is to evaluate the feasibility, and the diagnostic and prognostic value of semi-automated quantification of right ventricular (RV) fat replacement from CT images. Methods: An observational case–control study was carried out including 23 patients with a definite (19) or borderline (4) ARVC diagnosis and 23 age- and sex-matched controls without structural heart disease. All patients underwent contrast-enhanced cardiac CT. RV images were semi-automatically reconstructed with the ADAS-3D software (ADAS3D Medical, Barcelona, Spain). A fibrofatty scar was defined as values of Hounsfield Units (HU) <−10. Within the scar, a border zone (between −10 HU and −50 HU) and dense scar (<−50 HU) were distinguished. Results: All ARVC patients had an RV scar and all scar-related measurements were significantly higher in ARVC cases than in controls (p < 0.001). The total scar area and dense scar area showed no overlapping values between cases and controls, achieving perfect diagnostic performance (sensitivity and specificity of 100%). Among ARVC patients, 16 (70%) had experienced sustained VA or aborted SD. Among all clinical, ECG and imaging parameters, the dense scar area was the only one with a statistically significant association with VA and SD (p = 0.003). Conclusions: In ARVC, RV myocardial fat quantification from CT is feasible and may have considerable diagnostic and prognostic value. Full article

Background: Raghib syndrome is a rare malformation complex consisting of the drainage of the left superior vena cava (LSVC) into the left atrium, ostial atresia of the coronary sinus and an atrial septal defect (ASD). Case Report: This report aims to present the case of a child newly diagnosed with Raghib syndrome, complicated by pulmonary arterial hypertension, and to review previously published cases with the same diagnosis. A six-year-old female patient presented with signs and symptoms of heart failure (Ross III), reduced exercise tolerance and severe delay in stature and ponderal development. The imagistic work-up included echocardiography, followed by computer tomography (CT) and magnetic resonance imaging (MRI), through which a diagnosis of Raghib syndrome was established, complicated by pulmonary hypertension. As in other cases presented in the literature, MRI allowed for an accurate diagnosis, detecting the absent coronary sinus. The decision regarding the surgical closure of the ASD was made, with the patient having a favorable clinical evolution but with the persistence of elevated pulmonary artery pressure, for which Sildenafil therapy was instituted. Conclusions: The malformation complex consisting of an atrial septal defect, ostium atresia of the coronary sinus, uncovered coronary sinus, and persistent left superior vena cava, as identified through multiple imagistic investigations, was suggestive of the rare diagnosis of Raghib syndrome in this case. Among the limited number of cases of Raghib syndrome available in the literature, the present case is distinguished by the severity of the pulmonary artery hypertension at a very young age and in the absence of other concurrent cardiac malformations. Full article

Background: Congenital absence of pericardium is a rare cardiac disorder with a reported incidence of less than 1 in 10,000. Although most of the cases are of little clinical significance, some of them are associated with serious complications, including risk of herniation and strangulation or coronary artery compression. Detailed Case Description: We report a case of a 36-year-old male referred for routine cardiovascular examination. He had a medical history of a heart murmur since childhood. Electrocardiogram (ECG) revealed sinus rhythm, normal axis, poor R-wave progression in the precordial leads and repolarization abnormalities with negative T waves in leads V1–V4. On 2D transthoracic echocardiography (TTE), an unusual heart position was noted with poor image quality from the standard acoustic windows. The parasternal long axis view gave the impression of right ventricular dilatation. The findings raised the suspicion of left to right shunt and possible atrial septal defect. For further evaluation, the patient was referred for cardiac magnetic resonance which demonstrated complete left-sided absence of the pericardium. Discussion: Due to indistinct and atypical symptoms and lack of clinical awareness, pericardial congenital absence is frequently misdiagnosed. Patients may complain of atypical chest pain. Patient’s history and physical examination are often nonspecific. In cases with complete pericardial absence, ECG findings may include right axis deviation, right bundle block and sinus bradycardia. Echocardiography findings are also not characteristic, but some may raise the clinical suspicion of this diagnosis. The imaging modalities of choice are computed tomography and cardiac magnetic resonance. Treatment depends on the type of defect and clinical symptoms. Full article

Cardiovascular diseases (CVDs) are the leading cause of premature death and disability globally, leading to significant increases in healthcare costs and economic strains. Artificial intelligence (AI) is emerging as a crucial technology in this context, promising to have a significant impact on the management of CVDs. A wide range of methods can be used to develop effective models for medical applications, encompassing everything from predicting and diagnosing diseases to determining the most suitable treatment for individual patients. This literature review synthesizes findings from multiple studies that apply AI technologies such as machine learning algorithms and neural networks to electrocardiograms, echocardiography, coronary angiography, computed tomography, and cardiac magnetic resonance imaging. A narrative review of 127 articles identified 31 papers that were directly relevant to the research, encompassing a broad spectrum of AI applications in cardiology. These applications included AI models for ECG, echocardiography, coronary angiography, computed tomography, and cardiac MRI aimed at diagnosing various cardiovascular diseases such as coronary artery disease, hypertrophic cardiomyopathy, arrhythmias, pulmonary embolism, and valvulopathies. The papers also explored new methods for cardiovascular risk assessment, automated measurements, and optimizing treatment strategies, demonstrating the benefits of AI technologies in cardiology. In conclusion, the integration of artificial intelligence (AI) in cardiology promises substantial advancements in diagnosing and treating cardiovascular diseases. Full article

Cardiovascular disease (CVD), particularly coronary heart disease (CHD), is the leading cause of death in the US, with a high economic impact. Coronary artery calcium (CAC) is a known marker for CHD and a useful tool for estimating the risk of atherosclerotic cardiovascular disease (ASCVD). Although CACS is recommended for informing the decision to initiate statin therapy, the current standard requires a dedicated CT protocol, which is time-intensive and contributes to radiation exposure. Non-dedicated CT protocols can be taken advantage of to visualize calcium and reduce overall cost and radiation exposure; however, they mainly provide visual estimates of coronary calcium and have disadvantages such as motion artifacts. Artificial intelligence is a growing field involving software that independently performs human-level tasks, and is well suited for improving CACS efficiency and repurposing non-dedicated CT for calcium scoring. We present a review of the current studies on automated CACS across various CT protocols and discuss consideration points in clinical application and some barriers to implementation. Full article

Chronic coronary syndrome (CCS) is one of the leading cardiovascular causes of morbidity, mortality, and use of medical resources. After the introduction by international guidelines of the same level of recommendation to non-invasive imaging techniques in CCS evaluation, a large debate arose about the dilemma of choosing anatomical (with coronary computed tomography angiography (CCTA)) or functional imaging (with stress echocardiography (SE), cardiovascular magnetic resonance (CMR), or nuclear imaging techniques) as a first diagnostic evaluation. The determinant role of the atherosclerotic burden in defining cardiovascular risk and prognosis more than myocardial inducible ischemia has progressively increased the use of a first anatomical evaluation with CCTA in a wide range of pre-test probability in CCS patients. Functional testing holds importance, both because the role of revascularization in symptomatic patients with proven ischemia is well defined and because functional imaging, particularly with stress cardiac magnetic resonance (s-CMR), gives further prognostic information regarding LV function, detection of myocardial viability, and tissue characterization. Emerging techniques such as stress computed tomography perfusion (s-CTP) and fractional flow reserve derived from CT (FFRCT), combining anatomical and functional evaluation, appear capable of addressing the need for a single non-invasive examination, especially in patients with high risk or previous revascularization. Furthermore, CCTA in peri-procedural planning is promising to acquire greater importance in the non-invasive planning and guiding of complex coronary revascularization procedures, both by defining the correct strategy of interventional procedure and by improving patient selection. This review explores the different roles of non-invasive imaging techniques in managing CCS patients, also providing insights into preoperative planning for percutaneous or surgical myocardial revascularization. Full article

Background: The advancement of medical interventions towards minimally invasive procedures highlights the crucial role of precise pre-procedural evaluation, particularly in catheter-based treatments for heart and cardiovascular conditions. This study investigates innovative techniques such as mitral loop cerclage (MLC) and transcatheter intramyocardial radiofrequency ablation (TIRA), emphasizing the importance of preprocedural cardiac CT scans for accurate anatomical guidance in these emerging therapies. Purpose: The objective of this study was to assess the cardiac cycle through examination of the proximal septal vein (ps) for mitral loop cerclage and the distal septal vein (ds) for transcatheter intramyocardial radiofrequency ablation. Materials and Methods: Forty patients (mean age 59.4 ± 14.7 years) undergoing third-generation dual-source computed tomography (DSCT) for chest pain evaluation were enrolled. CT scans, utilizing dual-energy CT (DECT) with iopamidol and saline, encompassed the carina to the heart base. A noise-optimized linear blended image was reconstructed at 10% intervals throughout the cardiac cycle, and the presence of ps and ds in each phase was noted by two radiologists. Results: This study identified ps in 62.5% and ds in 72.5% of patients, with both present in 45% of cases. The observation of septal veins occurred more frequently in the sequence of 70, 60, 40, 80, 30, 20, and 10% for ps, and 60, 70, 40, 80, 30, 90, 20, and 10% for ds, respectively. Conclusions: DECT in cardiac imaging is instrumental in assessing septal vein frequency. The 70% phase is optimal for MLC, while the 60% phase is preferred for TIRA. Full article

The automatic segmentation of cardiac computed tomography (CT) and magnetic resonance imaging (MRI) plays a pivotal role in the prevention and treatment of cardiovascular diseases. In this study, we propose an efficient network based on the multi-scale, multi-head self-attention (MSMHSA) mechanism. The incorporation of this mechanism enables us to achieve larger receptive fields, facilitating the accurate segmentation of whole heart structures in both CT and MRI images. Within this network, features extracted from the shallow feature extraction network undergo a MHSA mechanism that closely aligns with human vision, resulting in the extraction of contextual semantic information more comprehensively and accurately. To improve the precision of cardiac substructure segmentation across varying sizes, our proposed method introduces three MHSA networks at distinct scales. This approach allows for fine-tuning the accuracy of micro-object segmentation by adapting the size of the segmented images. The efficacy of our method is rigorously validated on the Multi-Modality Whole Heart Segmentation (MM-WHS) Challenge 2017 dataset, demonstrating competitive results and the accurate segmentation of seven cardiac substructures in both cardiac CT and MRI images. Through comparative experiments with advanced transformer-based models, our study provides compelling evidence that despite the remarkable achievements of transformer-based models, the fusion of CNN models and self-attention remains a simple yet highly effective approach for dual-modality whole heart segmentation. Full article

Pigs as laboratory animals are used in preclinical studies aimed at developing medical devices for cardiac surgery. The anatomy of the cardiovascular system of these animals has been well studied and acknowledged as suitable for use and the testing of new cardiovascular devices developed for humans. However, there are no morphometric characteristics of the aortic root and thoraco-abdominal part of porcine aorta. This can lead to difficulties in experimental surgery and even result in the death of experimental animals due to the mismatch in the size of the implantable devices. Thus, such information is essential to enhance the efficiency of surgical technologies used for eliminating aortic pathologies in their various sections. The purpose of our research is to study the anatomy of the aorta in mini pigs and to assess whether the size, age, and sex of the animals affect the size of the main structures in their aortas. In addition, we attempted to compare the results obtained by transesophageal echocardiography (TEE) and angiography. We studied 28 laboratory mini pigs, dividing them into three groups by body weight (40–70 kg, 71–90 kg, and 90 kg). We did not find any relationship between the external somatometric characteristics of the animals and the size of their aortas. Animals have individual anatomical variability in their cardiovascular systems, which means that they need to be examined in terms of preoperative planning by any available method—echocardiography, angiography, or multispiral computed tomography (CT). Full article