MRI and CT in the diagnosis of coronary artery disease: indications and applications

Cardiac positron emission tomography and other modalities for coronary artery disease assessment: A snapshot from the medicare data

BACKGROUND

Positron emission tomography (PET) is an important tool for assessing coronary artery disease (CAD), but its widespread utilization is limited due to various factors, including limited local champion availability. This study aims to compare the frequency of PET procedures and their interpreters with other common CAD assessment modalities.

METHODS

Using Medicare data, we examined the number of cardiac PET procedures billed and compared them with single-photon emission computed tomography (SPECT), coronary computed tomography angiography (CCTA), stress magnetic resonance imaging (MRI), and stress echocardiography. Healthcare Common Procedure Coding System codes were used to identify procedures. We calculated the total number of PET myocardial perfusion imaging (MPI) procedures, the proportion of PET/CT and myocardial blood flow (MBF) assessments, and the median number of studies read per physician. We also analyzed the trends in the use of different CAD assessment modalities between 2018 and 2022. Descriptive statistics summarized the data.

RESULTS

In 2022, Medicare billed for 212,106 PET MPI scans. SPECT was six times more frequent (1,343,519), whereas stress echocardiography (201,676) and CCTA (118,734) had similar or lower use. Stress MRI (3,932) was least used. Of the PET MPI scans, 46% were PET/CT, and 39% included MBF measurements. Cardiologists interpreted 86% of PET scans, with a median of 58 studies per reader; 23% interpreted ≤25 studies annually. SPECT had a median of 63 studies per reader, and CCTA, stress MRI, and stress echocardiography had medians of 27, 20, and 24, respectively. PET, CT, and MRI use increased from 2018 to 2022, whereas SPECT and stress echocardiography declined.

CONCLUSION

In the Medicare population, radionuclide perfusion imaging (SPECT and PET) remained the preferred method for assessment of CAD, with SPECT being the most frequently used modality and PET being the second most frequently used modality for this application. However, PET/CT and MBF are underutilized, limiting diagnostic and prognostic capabilities. Efforts to enhance education and awareness of PET's advantages and to address barriers to its wider adoption are essential to maximize its clinical benefits and improve patient outcomes.

Computed Tomography Evaluation of Coronary Atherosclerosis: The Road Travelled, and What Lies Ahead

Coronary CT angiography (CCTA) is now endorsed by all major cardiology guidelines for the investigation of chest pain and assessment for coronary artery disease (CAD) in appropriately selected patients. CAD is a leading cause of morbidity and mortality. There is extensive literature to support CCTA diagnostic and prognostic value both for stable and acute symptoms. It enables rapid and cost-effective rule-out of CAD, and permits quantification and characterization of coronary plaque and associated significance. In this comprehensive review, we detail the road traveled as CCTA evolved to include quantitative assessment of plaque stenosis and extent, characterization of plaque characteristics including high-risk features, functional assessment including fractional flow reserve-CT (FFR-CT), and CT perfusion techniques. The state of current guideline recommendations and clinical applications are reviewed, as well as future directions in the rapidly advancing field of CT technology, including photon counting and applications of artificial intelligence (AI).

Harnessing the Heart's Magnetic Field for Advanced Diagnostic Techniques

Heart diseases remain one of the leading causes of morbidity and mortality worldwide, necessitating innovative diagnostic methods for early detection and intervention. An electrocardiogram (ECG) is a well-known technique for the preliminary diagnosis of heart conditions. However, it can not be used for continuous monitoring due to skin irritation. It is well known that every body organ generates a magnetic field, and the heart generates peak amplitudes of about 10 to 100 pT (measured at a distance of about 3 cm above the chest). This poses challenges to capturing such signals. This paper reviews the different techniques used to capture the heart's magnetic signals along with their limitations. In addition, this paper provides a comprehensive review of the different approaches that use the heart-generated magnetic field to diagnose several heart diseases. This research reveals two aspects. First, as a noninvasive tool, the use of the heart's magnetic field signal can lead to more sensitive advanced heart disease diagnosis tools, especially when continuous monitoring is possible and affordable. Second, its current use is limited due to the lack of accurate, affordable, and portable sensing technology.

Effects of lung resection on heart structure and function: A tissue Doppler ultrasound survey of 43 cases

Changes in heart structure and function after lung resection in patients with lung cancer are challenging to manage. Therefore, a non-invasive and reliable measurement tool to gauge such changes is critical. The purpose of the present study was to compare cardiological changes before and after lung resection using tissue Doppler imaging (TDI). A total of 43 patients (19 men and 24 women) with primary non-small cell lung cancer (n=37) and metastatic cancer in the lungs (n=6) were enrolled in the study.nTDI was used to determine the thickness of the ascending aorta, the open size of the ascending valve, the anterior-oposterior diameters of the left atrium and left ventricle, and the thickness of the ventricular septum and right ventricle before and after lung resection. Left ventricular (LV) ejection fraction (EF), pulmonary valve flow rate, tricuspid annular or mitral leaflet tip early (E) peak/late (A) diastolic blood flow velocities, tricuspid regurgitation flow, the lateral mitral annulus early (e') diastolic velocity and mitral E/e' ratio were used to determine LV filling pressure. Results revealed no significant differences between male and female patients in terms of the open size of the ascending valve, the anterior-posterior diameter of the left ventricle and the mitral E/e' ratio. Significant differences were found in the width of the ascending aorta, anterior-posterior diameter of the left atrium, width of the LV septum and right ventricular (RV) diameter before and after lung resection. Finally, there were significantchanges in EF and tricuspid pressure. The results indicated that TDI was useful as a non-invasive method for assessing left and right heart function following lung resection. The LV and RV dimensions were affected, but LV filling pressure was preserved after lobectomy.

Identifying and Treating Vulnerable Atherosclerotic Plaques

Acute coronary syndromes and, in particular, ST-elevation myocardial infarction are usually caused by coronary thrombosis in which the thrombus develops either on a disrupted plaque (usually a thin-capped fibroatheroma) or an eroded atherosclerotic plaque. These thrombus-prone plaques are vulnerable or high-risk. Although, traditionally, cardiologists have concentrated on treating significant coronary obstruction, there has been great interest over the last 2 decades in possibly preventing the thrombotic causes of myocardial infarction/sudden coronary death by mostly identifying and stabilizing these asymptomatic vulnerable or high-risk plaques, which, at least on invasive angiography, are mostly nonobstructive. Computed tomographic angiography and intravascular imaging during invasive coronary angiography have now been shown to identify a majority of these vulnerable or high-risk plaques before symptoms, thus opening up new preventive strategies. In conclusion, this article discusses the identification and management of these thrombus-prone lesions and patients with these lesions either with noninvasive techniques and systemic therapies or possibly through a new and bold interventional paradigm.

EDRL: Entropy-guided disentangled representation learning for unsupervised domain adaptation in semantic segmentation

BACKGROUND AND OBJECTIVE

Deep learning-based approaches are excellent at learning from large amounts of data, but can be poor at generalizing the learned knowledge to testing datasets with domain shift, i.e., when there exists distribution discrepancy between the training dataset (source domain) and the testing dataset (target domain). In this paper, we investigate unsupervised domain adaptation (UDA) techniques to train a cross-domain segmentation method which is robust to domain shift, eliminating the requirement of any annotations on the target domain.

METHODS

To this end, we propose an Entropy-guided Disentangled Representation Learning, referred as EDRL, for UDA in semantic segmentation. Concretely, we synergistically integrate image alignment via disentangled representation learning with feature alignment via entropy-based adversarial learning into one network, which is trained end-to-end. We additionally introduce a dynamic feature selection mechanism via soft gating, which helps to further enhance the task-specific feature alignment. We validate the proposed method on two publicly available datasets: the CT-MR dataset and the multi-sequence cardiac MR (MS-CMR) dataset.

RESULTS

On both datasets, our method achieved better results than the state-of-the-art (SOTA) methods. Specifically, on the CT-MR dataset, our method achieved an average DSC of 84.8% when taking CT as the source domain and MR as the target domain, and an average DSC of 84.0% when taking MR as the source domain and CT as the target domain.

CONCLUSIONS

Results from comprehensive experiments demonstrate the efficacy of the proposed EDRL model for cross-domain medical image segmentation.

Machine learning-based diagnosis and risk classification of coronary artery disease using myocardial perfusion imaging SPECT: A radiomics study

This study aimed to investigate the diagnostic performance of machine learning-based radiomics analysis to diagnose coronary artery disease status and risk from rest/stress Myocardial Perfusion Imaging (MPI) single-photon emission computed tomography (SPECT). A total of 395 patients suspicious of coronary artery disease who underwent 2-day stress-rest protocol MPI SPECT were enrolled in this study. The left ventricle myocardium, excluding the cardiac cavity, was manually delineated on rest and stress images to define a volume of interest. Added to clinical features (age, sex, family history, diabetes status, smoking, and ejection fraction), a total of 118 radiomics features, were extracted from rest and stress MPI SPECT images to establish different feature sets, including Rest-, Stress-, Delta-, and Combined-radiomics (all together) feature sets. The data were randomly divided into 80% and 20% subsets for training and testing, respectively. The performance of classifiers built from combinations of three feature selections, and nine machine learning algorithms was evaluated for two different diagnostic tasks, including 1) normal/abnormal (no CAD vs. CAD) classification, and 2) low-risk/high-risk CAD classification. Different metrics, including the area under the ROC curve (AUC), accuracy (ACC), sensitivity (SEN), and specificity (SPE), were reported for models' evaluation. Overall, models built on the Stress feature set (compared to other feature sets), and models to diagnose the second task (compared to task 1 models) revealed better performance. The Stress-mRMR-KNN (feature set-feature selection-classifier) reached the highest performance for task 1 with AUC, ACC, SEN, and SPE equal to 0.61, 0.63, 0.64, and 0.6, respectively. The Stress-Boruta-GB model achieved the highest performance for task 2 with AUC, ACC, SEN, and SPE of 0.79, 0.76, 0.75, and 0.76, respectively. Diabetes status from the clinical feature family, and dependence count non-uniformity normalized, from the NGLDM family, which is representative of non-uniformity in the region of interest were the most frequently selected features from stress feature set for CAD risk classification. This study revealed promising results for CAD risk classification using machine learning models built on MPI SPECT radiomics. The proposed models are helpful to alleviate the labor-intensive MPI SPECT interpretation process regarding CAD status and can potentially expedite the diagnostic process.

Preoperative investigations for elective surgical patients in a resource limited setting: Systematic review

Background

Preoperative investigation for surgical patients is important to check for conditions that may affect surgical outcome. It helps the anesthetist and surgeon to plan perioperative anesthesia and surgical management appropriately. However, 60-70% of laboratory tests before surgery are not really required. This review was conducted to develop evidence-based recommendations on preoperative investigations for patients waiting for surgery in a resource limited setting.

Methods

After formulating the key questions, scope, and eligibility criteria for the articles to be included, advanced search strategy of electronic sources from data bases and websites was conducted. Duplication of literatures was avoided by endnote. Screening of literatures was conducted with proper appraisal. This review was reported in accordance with the preferred reporting items for systematic reviews and meta-analysis (PRISMA) 2020 statement.

Results

A total of 553 articles were identified from data bases and websites using an electronic search. 75 articles were removed for duplication and 223 studies were excluded after reviewing titles and abstracts. At the screening stage, 82 articles were retrieved and evaluated for eligibility. Finally, 46 studies met the eligibility criteria and were included in this systematic review.

Conclusion

and recommendation: Selective laboratory ordering reduces the number and cost of investigations. Preoperative tests should be guided by the patient's clinical history, co-morbidities, and physical examination. Patients with signs or symptoms of certain types of disease should be evaluated with appropriate testing. Therefore, adherence to recommendations of guidelines on preoperative investigation is important for good surgical outcome and patient satisfaction.

MRI findings of epipericardial fat necrosis: As a rare cause of acute chest pain in a healthy man

Epipericardial fat necrosis (EPFN) is a rare, benign cause of acute chest pain imitating symptoms of life-threatening diseases, such as acute coronary syndrome. Here We report a 37-year-old, healthy male presented to the emergency department (ED) with sudden-onset pleuritic chest pain after an isometric physical training. Initial cardiac workup included ECG, echocardiography was unremarkable, but diagnosis of an inflammatory process that involved the epipericardial fat tissue surrounding the heart was made by showing encapsulated fatty lesion, enhanced adjacent parietal pericardium using of contrast‐enhanced magnetic resonance imaging (MRI). Magnetic resonance imaging would help physicians to differentiate EPFN from severe and life-treating conditions.

Evaluation of Coronary Plaques and Stents with Conventional and Photon-counting CT: Benefits of High-Resolution Photon-counting CT

PURPOSE

To compare the performance of energy-integrating detector (EID) CT, photon-counting detector CT (PCCT), and high-resolution PCCT (HR-PCCT) for the visualization of coronary plaques and reduction of stent artifacts in a phantom model.

MATERIALS AND METHODS

An investigational scanner with EID and PCCT subsystems was used to image a coronary artery phantom containing cylindrical probes simulating different plaque compositions. The phantom was imaged with and without coronary stents using both subsystems. Images were reconstructed with a clinical cardiac kernel and an additional HR-PCCT kernel. Regions of interest were drawn around probes and evaluated for in-plane diameter and a qualitative comparison by expert readers. A linear mixed-effects model was used to compare the diameter results, and a Shrout-Fleiss intraclass correlation coefficient was used to assess consistency in the reader study.

RESULTS

Comparing in-plane diameter to the physical dimension for nonstented and stented phantoms, measurements of the HR-PCCT images were more accurate (nonstented: 4.4% ± 1.1 [standard deviation], stented: -9.4% ± 4.6) than EID (nonstented: 15.5% ± 4.0, stented: -19.5% ± 5.8) and PCCT (nonstented: 19.4% ± 2.5, stented: -18.3% ± 4.4). Our analysis of variance found diameter measurements to be different across image groups for both nonstented and stented cases (P < .001). HR-PCCT showed less change on average in percent stenosis due to the addition of a stent (-5.5%) than either EID (+90.5%) or PCCT (+313%). For both nonstented and stented phantoms, observers rated the HR-PCCT images as having higher plaque conspicuity and as being the image type that was least impacted by stent artifacts, with a high level of agreement (interclass correlation coefficient = 0.85).

CONCLUSION

Despite increased noise, HR-PCCT images were able to better visualize coronary plaques and reduce stent artifacts compared with EID or PCCT reconstructions.Keywords: CT-Spectral Imaging (Dual Energy), Phantom Studies, Cardiac, Physics, Technology Assessment© RSNA, 2021.

The recent advances, drawbacks, and the future directions of CMRI in the diagnosis of IHD

Ischemic heart disease (IHD), also known as coronary artery disease (CAD), is a leading cause of morbidity and mortality in adults. The aims of this research were to study the recent advances on the prognostic and diagnostic value, drawbacks, and the future directions of cardiac magnetic resonance imaging (CMRI) in the diagnosis of IHD. One hundred patients with IHD who had been clinically diagnosed were enrolled in this study prospectively. CMRI; Siemens Magnetom Sola 1.5 T MRI scanner was used to examine the patients. To confirm the diagnosis, conventional coronary angiography was used. CMRI revealed that the left ventricular (LV) volumes and systolic function of male and female patients differed by age decile were 28.9 ± 3.5%; 32 ± 1.7%, 53.3 ± 11.2; 58 ± 6.6 ml, 100.6 ± 7.1; 98.3 ± 14.7 bpm, 5.4 ± 1.4; 5.8 ± 1.5 L/min, 189 ± 14.3; 180 ± 10.9 ml, and 136 ± 3.1; 123 ± 4.4 ml for the left ventricle ejection fraction (LVEF), stroke volume (SV), heart rate, cardiac output, end diastolic volume (EDV), and end systolic volume (ESV), respectively. CMRI has sensitivity, specificity, and accuracy of 97%, 33.33%, and 95.15%, respectively. Finally, CMRI provides a comprehensive assessment of LV function, myocardial perfusion, and viability, as well as coronary anatomy.

Sources of Inaccuracy in Photoplethysmography for Continuous Cardiovascular Monitoring

Photoplethysmography (PPG) is a low-cost, noninvasive optical technique that uses change in light transmission with changes in blood volume within tissue to provide information for cardiovascular health and fitness. As remote health and wearable medical devices become more prevalent, PPG devices are being developed as part of wearable systems to monitor parameters such as heart rate (HR) that do not require complex analysis of the PPG waveform. However, complex analyses of the PPG waveform yield valuable clinical information, such as: blood pressure, respiratory information, sympathetic nervous system activity, and heart rate variability. Systems aiming to derive such complex parameters do not always account for realistic sources of noise, as testing is performed within controlled parameter spaces. A wearable monitoring tool to be used beyond fitness and heart rate must account for noise sources originating from individual patient variations (e.g., skin tone, obesity, age, and gender), physiology (e.g., respiration, venous pulsation, body site of measurement, and body temperature), and external perturbations of the device itself (e.g., motion artifact, ambient light, and applied pressure to the skin). Here, we present a comprehensive review of the literature that aims to summarize these noise sources for future PPG device development for use in health monitoring.

CT Angiography or Cardiac MRI for Detection of Coronary Artery Aneurysms in Kawasaki Disease

Background: Kawasaki disease (KD) is an acute vasculitis that mainly affects the coronary arteries. This inflammation can cause coronary artery aneurysms (CAAs). Patients with KD need cardiac assessment for risk stratification for the development of myocardial ischemia, based on Z-score (luminal diameter of the coronary artery corrected for body surface area). Echocardiography is the primary imaging modality in KD but has several important limitations. Coronary computed tomographic angiography (cCTA) and Cardiac MRI (CMR) are non-invasive imaging modalities and of additional value for assessment of CAAs with a high diagnostic yield. The objective of this single center, retrospective study is to explore the diagnostic potential of coronary artery assessment of cCTA vs. CMR in children with KD. Methods and Results: Out of 965 KD patients from our database, a total of 111 cCTAs (104 patients) and 311 CMR (225 patients) have been performed since 2010. For comparison, we identified 54 KD patients who had undergone both cCTA and CMR. CMR only identified eight patients with CAAs compared to 14 patients by cCTA. CMR missed 50% of the CAAs identified by cCTA. Conclusions: Our single center study demonstrates that cCTA may be a more sensitive diagnostic tool to detect CAAs in KD patients, compared to CMR.

High contrast power Doppler imaging in side-viewing intravascular ultrasound imaging via angular compounding

The ability to assess likelihood of plaque rupture can determine the course of treatment in coronary artery disease. One indicator of plaque vulnerability is the development of blood vessels within the plaque, or intraplaque neovascularization. In order to visualize these vessels with increased sensitivity in the cardiac catheterization lab, a new approach for imaging blood flow in small vessels using side-viewing intravascular ultrasound (IVUS) is proposed. This approach based on compounding adjacent angular acquisitions was evaluated in tissue mimicking phantoms and ex vivo vessels. In phantom studies, the Doppler CNR increased from 3.3 ± 1.0 to 13 ± 2.6 (conventional clutter filtering) and from 1.9 ± 0.15 to 7.5 ± 1.1 (SVD filtering) as a result of applying angular compounding. When imaging flow at a rate of 5.6 mm/s in 200 µm tubes adjacent to the lumen of ex vivo porcine arteries, the Doppler CNR increased from 5.3 ± 0.95 to 7.2 ± 1.3 (conventional filtering) and from 23 ± 3.3 to 32 ± 6.7 (SVD filtering). Applying these strategies could allow increased sensitivity to slow flow in side-viewing intravascular ultrasound imaging.

Guideline for Cardiovascular Magnetic Resonance Imaging from the Korean Society of Cardiovascular Imaging-Part 1: Standardized Protocol

Cardiac magnetic resonance (CMR) imaging is widely used in many areas of cardiovascular disease assessment. This is a practical, standard CMR protocol for beginners that is designed to be easy to follow and implement. This protocol guideline is based on previously reported CMR guidelines and includes sequence terminology used by vendors, essential MR physics, imaging planes, field strength considerations, MRI-conditional devices, drugs for stress tests, various CMR modules, and disease/symptom-based protocols based on a survey of cardiologists and various appropriate-use criteria. It will be of considerable help in planning and implementing tests. In addressing CMR usage and creating this protocol guideline, we particularly tried to include useful tips to overcome various practical issues and improve CMR imaging. We hope that this document will continue to standardize and simplify a patient-based approach to clinical CMR and contribute to the promotion of public health.

Unpaired Multi-Modal Segmentation via Knowledge Distillation

Multi-modal learning is typically performed with network architectures containing modality-specific layers and shared layers, utilizing co-registered images of different modalities. We propose a novel learning scheme for unpaired cross-modality image segmentation, with a highly compact architecture achieving superior segmentation accuracy. In our method, we heavily reuse network parameters, by sharing all convolutional kernels across CT and MRI, and only employ modality-specific internal normalization layers which compute respective statistics. To effectively train such a highly compact model, we introduce a novel loss term inspired by knowledge distillation, by explicitly constraining the KL-divergence of our derived prediction distributions between modalities. We have extensively validated our approach on two multi-class segmentation problems: i) cardiac structure segmentation, and ii) abdominal organ segmentation. Different network settings, i.e., 2D dilated network and 3D U-net, are utilized to investigate our method's general efficacy. Experimental results on both tasks demonstrate that our novel multi-modal learning scheme consistently outperforms single-modal training and previous multi-modal approaches.

Peptide-Based Soft Hydrogels Modified with Gadolinium Complexes as MRI Contrast Agents

Poly-aromatic peptide sequences are able to self-assemble into a variety of supramolecular aggregates such as fibers, hydrogels, and tree-like multi-branched nanostructures. Due to their biocompatible nature, these peptide nanostructures have been proposed for several applications in biology and nanomedicine (tissue engineering, drug delivery, bioimaging, and fabrication of biosensors). Here we report the synthesis, the structural characterization and the relaxometric behavior of two novel supramolecular diagnostic agents for magnetic resonance imaging (MRI) technique. These diagnostic agents are obtained for self-assembly of DTPA(Gd)-PEG8-(FY)3 or DOTA(Gd)-PEG8-(FY)3 peptide conjugates, in which the Gd-complexes are linked at the N-terminus of the PEG8-(FY)3 polymer peptide. This latter was previously found able to form self-supporting and stable soft hydrogels at a concentration of 1.0% wt. Analogously, also DTPA(Gd)-PEG8-(FY)3 and DOTA(Gd)-PEG8-(FY)3 exhibit the trend to gelificate at the same range of concentration. Moreover, the structural characterization points out that peptide (FY)3 moiety keeps its capability to arrange into β-sheet structures with an antiparallel orientation of the β-strands. The high relaxivity value of these nanostructures (~12 mM⁻¹·s⁻¹ at 20 MHz) and the very low in vitro cytotoxicity suggest their potential application as supramolecular diagnostic agents for MRI.

Localization of common carotid artery transverse section in B-mode ultrasound images using faster RCNN: a deep learning approach

Cardiologists can acquire important information related to patients' cardiac health using carotid artery stiffness, its lumen diameter (LD), and its carotid intima-media thickness (cIMT). The sonographers primarily concern about the location of the artery in B-mode ultrasound images. Localization using manual methods is tedious and time-consuming and also may lead to some errors. On the other hand, automated approaches are more objective and can provide the localization of the artery at near real time. Above arterial parameters may be determined after localization of the artery in real time.A novel method of localization of common carotid artery (CCA) transverse section is presented in this work. The method is known as fast region convolutional neural network (FRCNN)-based localization method and is designed using a stack of three layers viz. convolutional layers, fully connected layers, and pooling layers. These organized layers constitute a region proposal network (RPN) and an object class detection network (OCDN). We obtain an outcome as a bounding box along with a score of prediction around the cross-section of the CCA.B-mode ultrasound image database of CCA is split into training and testing set, to accomplish this, three partition methods K = 2, 5, and 10 are used in our work. The training is extended for 30, 200, and 2000 epochs in order to achieve fine-tuned features from the convolutional neural network. After 2000 epochs, we obtain 95% validation accuracy; however, mean of the accuracies up to 2000 epochs is 89.36% for K = 10 partitions protocol (training 90%, testing 10%). Generated CNN model is tested on a different dataset of 433 images and the acquired accuracy is 87.99%. Thus, the proposed method including an advanced deep learning technique demonstrates promising localization for carotid artery transverse section. Graphical abstract.

Evaluation of algorithms for Multi-Modality Whole Heart Segmentation: An open-access grand challenge

Knowledge of whole heart anatomy is a prerequisite for many clinical applications. Whole heart segmentation (WHS), which delineates substructures of the heart, can be very valuable for modeling and analysis of the anatomy and functions of the heart. However, automating this segmentation can be challenging due to the large variation of the heart shape, and different image qualities of the clinical data. To achieve this goal, an initial set of training data is generally needed for constructing priors or for training. Furthermore, it is difficult to perform comparisons between different methods, largely due to differences in the datasets and evaluation metrics used. This manuscript presents the methodologies and evaluation results for the WHS algorithms selected from the submissions to the Multi-Modality Whole Heart Segmentation (MM-WHS) challenge, in conjunction with MICCAI 2017. The challenge provided 120 three-dimensional cardiac images covering the whole heart, including 60 CT and 60 MRI volumes, all acquired in clinical environments with manual delineation. Ten algorithms for CT data and eleven algorithms for MRI data, submitted from twelve groups, have been evaluated. The results showed that the performance of CT WHS was generally better than that of MRI WHS. The segmentation of the substructures for different categories of patients could present different levels of challenge due to the difference in imaging and variations of heart shapes. The deep learning (DL)-based methods demonstrated great potential, though several of them reported poor results in the blinded evaluation. Their performance could vary greatly across different network structures and training strategies. The conventional algorithms, mainly based on multi-atlas segmentation, demonstrated good performance, though the accuracy and computational efficiency could be limited. The challenge, including provision of the annotated training data and the blinded evaluation for submitted algorithms on the test data, continues as an ongoing benchmarking resource via its homepage (www.sdspeople.fudan.edu.cn/zhuangxiahai/0/mmwhs/).

Simulation of the Perfusion of Contrast Agent Used in Cardiac Magnetic Resonance: A Step Toward Non-invasive Cardiac Perfusion Quantification

This work presents a new mathematical model to describe cardiac perfusion in the myocardium as acquired by cardiac magnetic resonance (CMR) perfusion exams. The combination of first pass (or contrast-enhanced CMR) and late enhancement CMR is a widely used non-invasive exam that can identify abnormal perfused regions of the heart via the use of a contrast agent (CA). The exam provides important information to the diagnosis, management, and prognosis of ischemia and infarct: perfusion on different regions, the status of microvascular structures, the presence of fibrosis, and the relative volume of extracellular space. This information is obtained by inferring the spatiotemporal dynamics of the contrast in the myocardial tissue from the acquired images. The evaluation of these physiological parameters plays an important role in the assessment of myocardial viability. However, the nature of cardiac physiology poses great challenges in the estimation of these parameters. Briefly, these are currently estimated qualitatively via visual inspection of images and comparison of relative brightness between different regions of the heart. Therefore, there is a great urge for techniques that can help to quantify cardiac perfusion. In this work, we propose a new mathematical model based on multidomain flow in porous media. The model is based on a system of partial differential equations. Darcy's law is used to obtain the pressure and velocity distribution. CA dynamics is described by reaction-diffusion-advection equations in the intravascular space and in the interstitial space. The interaction of fibrosis and the CA is also considered. The new model treats the domains as anisotropic media and imposes a closed loop of intravascular flow, which is necessary to reproduce the recirculation of the CA. The model parameters were adjusted to reproduce clinical data. In addition, the model was used to simulate different scenarios: normal perfusion; endocardial ischemia due to stenosis in a coronary artery in the epicardium; and myocardial infarct. Therefore, the computational model was able to correlate anatomical features, stenosis and the presence of fibrosis, with functional ones, cardiac perfusion. Altogether, the results suggest that the model can support the process of non-invasive cardiac perfusion quantification.

Quantification of uncertainty in the assessment of coronary plaque in CCTA through a dynamic cardiac phantom and 3D-printed plaque model

The purpose of this study was to develop a dynamic physical cardiac phantom with a realistic coronary plaque to investigate stenosis measurement accuracy under clinically relevant heart-rates. The coronary plaque model (5 mm diameter, 50% stenosis, and 32 mm long) was designed and 3D-printed with tissue equivalent materials (calcified plaque with iodine-enhanced lumen). Realistic cardiac motion was modeled by converting computational cardiac motion vectors into compression and rotation profiles executed by a commercial base cardiac phantom. The phantom was imaged on a dual-source CT system applying a retrospective gated coronary CT angiography (CCTA) protocol using synthesized motion-synchronized electrocardiogram (ECG) waveforms. Multiplanar reformatted images were reconstructed along vessel centerlines. Enhanced lumens were segmented by five independent operators. On average, stenosis measurement accuracy was 0.9% positively biased for the motion-free condition. Average measurement accuracy monotonically decreased from 0.9% positive bias for the motion-free condition to 18.5% negative bias at 90 beats per minute. Contrast-to-noise ratio, lumen circularity, and segmentation conformity also decreased monotonically with increasing heart-rate. These results demonstrate successful implementation of a base cardiac phantom with a 3D-printed coronary plaque model, relevant motion profile, and coordinated ECG waveform. They further show the utility of the model to ascertain metrics of CCTA accuracy and image quality under realistic plaque, motion, and acquisition conditions.

Digital stethoscope: technology update

Cardiovascular disease (CVD) is recognized as the leading cause of mortality throughout the world. About one-third of global mortality is attributable to CVD. In addition to clinical presentation, specific clinical exam findings can assist in treating and preventing CVD. CVD may initially manifest as pulmonary pathology, and thus, accurate cardiopulmonary auscultation is paramount to establishing accurate diagnosis. One of the most powerful tools available to physicians is the stethoscope. The stethoscope first emerged in the year 1818, invented by a French physician, René Laennec. Since then, the initial modest monaural wooden tube has evolved into a sophisticated digital device. This paper provides an analysis of the evolution of the stethoscope as well as highlights the advancement made by the modern digital stethoscope including the application of this tool in advancing care for patients suffering from CVD.

Linear-regression convolutional neural network for fully automated coronary lumen segmentation in intravascular optical coherence tomography

Intravascular optical coherence tomography (OCT) is an optical imaging modality commonly used in the assessment of coronary artery diseases during percutaneous coronary intervention. Manual segmentation to assess luminal stenosis from OCT pullback scans is challenging and time consuming. We propose a linear-regression convolutional neural network to automatically perform vessel lumen segmentation, parameterized in terms of radial distances from the catheter centroid in polar space. Benchmarked against gold-standard manual segmentation, our proposed algorithm achieves average locational accuracy of the vessel wall of 22 microns, and 0.985 and 0.970 in Dice coefficient and Jaccard similarity index, respectively. The average absolute error of luminal area estimation is 1.38%. The processing rate is 40.6 ms per image, suggesting the potential to be incorporated into a clinical workflow and to provide quantitative assessment of vessel lumen in an intraoperative time frame.

The Role of Coronary Computed Tomography Angiography and Cardiac Magnetic Resonance in STEMI Patients with Normal Coronary Angiography

Usually, the diagnosis of myocardial infarction based on patient symptoms, electrocardiogram (ECG) changes, and cardiac enzymes, is not a challenge for cardiologists. The correlation between coronary anatomy and the ECG territories that present ischemic changes can help the clinician to estimate which coronary artery presents lesions upon performing a coronary angiogram. In certain situations, the diagnosis of myocardial infarction can be difficult due to the lack of correlations between the clinical and paraclinical examinations and the coronary angiogram. In some cases, patients with chest pain and ST-segment elevation on the ECG tracing present with a normal coronary angiography. In other cases, patients without important changes on the ECG can present critical lesions or even occlusions upon angiographic examination. The aim of this article is to highlight the role of noninvasive coronary magnetic resonance and multi-slice computed tomography in patients with ST-segment elevation myocardial infarction and normal coronary angiography.

ANMCO-SIMEU Consensus Document: in-hospital management of patients presenting with chest pain

Chest pain is a common general practice presentation that requires careful diagnostic assessment because of its diverse and potentially serious causes. However, the evaluation of acute chest pain remains challenging, despite many new insights over the past two decades. The percentage of patients presenting to the emergency departments because of acute chest pain appears to be increasing. Nowadays, there are two essential chest pain-related issues: (i) the missed diagnoses of acute coronary syndromes with a poor short-term prognosis; and (ii) the increasing percentage of hospitalizations of low-risk cases. It is well known that hospitalization of a low-risk chest pain patient can lead to unnecessary tests and procedures, with an increasing trend of complications and burden of costs. Therefore, the significantly reduced financial resources of healthcare systems induce physicians and administrators to improve the efficiency of care protocols for patients with acute chest pain. Despite the efforts of the Scientific Societies in producing statements on this topic, in Italy there is still a significant difference between emergency physicians and cardiologists in managing patients with chest pain. For this reason, the aim of the present consensus document is double: first, to review the evidence-based efficacy and utility of various diagnostic tools, and, second, to delineate the critical pathways (describing key steps) that need to be implemented in order to standardize the management of chest pain patients, making a correct diagnosis and treatment as uniform as possible across the entire country.

Part 2 - Coronary angiography with gadofosveset trisodium: a prospective intra-subject comparison for dose optimization for 100 % efficiency imaging

Background

Three tesla (3T) coronary magnetic resonance angiography (MRA) may be optimized using gadolinium-based contrast agents (GBCA) such as gadofosveset trisodium. The goal of this study was to evaluate if there is a qualitative or quantitative improvement in the coronary arteries with variation in contrast dose.

Methods

Twenty-eight healthy volunteers were prospectively recruited for coronary MRA at 3T using a steady state injection technique for 3D radial whole-heart image acquisition with retrospective respiratory self-gating (ClinicalTrials.gov identifier: NCT01853592). Nineteen volunteers completed both single- and double-dose imaging instances (0.03 and 0.06 mmol/kg, respectively). Intra-individual comparison of image quality was assessed by measurement of apparent signal/contrast-to-noise ratio (aSNR/aCNR) and subjective evaluation of image quality by 2 independent reviewers.

Results

The average duration of coronary MRA acquisition was 7.2 ± 1.2 min. There was significantly higher (60 %, p < 0.001) aSNR of the aorta and right/left ventricle for the double dose compared to single dose injection scheme and aSNR of the coronary arteries increased by 70 % (p < 0.001) for the double dose injection. aCNR increased by +55 % and +60 % in the ventricles and coronary arteries, respectively (p < 0.001). Overall segmental artery visualization for single dose was possible 47 % of the time, which improved to 60 % with double dose (p = 0.019), predominantly driven by improvements in more distal segment visualization (+40 % improvement in mid arterial segments, p = 0.013).

Conclusions

Gadofosveset trisodium dose of 0.06 mmol/kg significantly quantitatively and qualitatively improves the coronary artery image quality compared to 0.03 mmol/kg at 3T for moderate duration (6–8 min) steady state contrast enhanced coronary MRA.

Correlation of coronary plaque characteristics and obstructive stenosis with chronic kidney disease by coronary CT angiography

BACKGROUND

Chronic kidney disease (CKD) is an independent risk factor for cardiovascular events. We evaluated the correlation of coronary plaque characteristics and obstructive stenosis with CKD by coronary computed tomographic angiography (CCTA).

METHODS

We enrolled 491 subjects who were suspected coronary artery disease (CAD) undergoing CCTA. Estimated glomerular filtration rate (eGFR) was calculated by the modification of diet in renal disease (MDRD) equation. Patients were subdivided into four groups based on their eGFR: normal GFR (n=213, eGFR ≥90 mL/min/1.73 m(2)), mild renal insufficiency (n=191, eGFR 60-89 mL/min/1.73 m(2)), moderate renal insufficiency(n=78, eGFR <60 mL/min/1.73 m(2), ≥30 mL/min/1.73 m(2)), and severe renal insufficiency (n=9, eGFR <30 mL/min/1.73 m(2), ≥15 mL/min/1.73 m(2)).

RESULTS

Spearman correlation regression analysis showed that the prevalence of any plaque, calcified plaque (CP), mixed plaque (MP) were positively correlate with CKD (r=0.173, P<0.001; r=0.127, P=0.005; r=0.171, P<0.001), after adjustment for traditional risk factors the prevalence of any plaque and MP were still positively correlate with CKD (r=0.106, P=002; r=0.178, P<0.001). And the prevalence of any stenosis and severe stenosis were positively correlate with CKD (r=0.13, P<0.001; r=0.149, P<0.001), after adjustment for traditional risk factors were still positively correlate with CKD (r=0.134, P=0.003; r=0.174, P<0.001).

CONCLUSIONS

CKD is closely related with occurrence of CAD. CKD patients from mild renal insufficiency to severe renal insufficiency are the risk factors for CAD. More serious renal function impairment will indicates higher risk of coronary plaque, MP and obstructive stenosis.

Three-dimensional coronary dark-blood interleaved with gray-blood (cDIG) magnetic resonance imaging at 3 tesla

PURPOSE

Three-dimensional (3D) dark-blood MRI has shown great potential in coronary artery plaque evaluation. However, substantial variability in quantification could result from superficial calcification because of its low signal. To address this issue, a 3D coronary dark-blood interleaved with gray-blood (cDIG) technique was developed.

METHODS

cDIG is based on a balanced steady-state free precession readout combined with a local re-inversion-based double-inversion-recovery (LocReInv-DIR) preparation. The LocReInv-DIR is applied every two RR intervals. Dark-blood and gray-blood contrasts are collected in the first and second RR interval, respectively. To improve the respiratory gating efficiency, two independent navigators were developed to separately gate the respiratory motion for the two interleaved acquisitions. In vivo experiments in eight healthy subjects and one patient were conducted to validate the technique.

RESULTS

cDIG provided dual-contrasts without compromise in scan time. The dark-blood images with cDIG demonstrated excellent wall and lumen signal performances and morphological measurements. Advantageously, cDIG yielded a second contrast that was shown to help identify the superficial calcification in the coronary plaque of a patient.

CONCLUSION

A novel technique was developed for obtaining 3D coronary vessel wall and gray lumen images. The additional contrast may aid in identifying calcified nodules and thus potentially improve the evaluation of coronary plaque burden.

Trends in percutaneous coronary intervention and angiography in Ireland, 2004-2011: Implications for Ireland and Europe

BACKGROUND/OBJECTIVES

To study temporal trends in crude and age standardised rates of cardiac catheterisation and percutaneous coronary intervention (PCI) in Ireland, 2004-2011.

METHODS

Two data sources were used: a) a survey of publicly and privately funded hospitals with cardiac catheter laboratories to obtain the annual number of procedures performed and b) anonymised data from the Hospital In-Patient Enquiry (HIPE) for angiography and PCI in acute publicly funded hospitals; age standardised rates were calculated to study trends over time.

RESULTS

From 2004 to 2011 the crude rate of angiography and PCI increased by 47.8% and 35.9% respectively, with rates of 6689 and 1825 per million population in 2011. Following age standardisation, however, PCI activity showed a non-significant decrease over time. The PCI to angiography ratio decreased from 30% to 27% and PCI was performed predominantly for stable coronary heart disease (54%) in 2011.

CONCLUSION

Angiography and PCI rates have increased in Ireland but PCI crude and age adjusted rates show divergent trends. While Ireland differs from USA and UK, with a higher proportion of PCI being performed for stable CHD in recent years, little systematic surveillance of cardiological interventions within Europe is available to benchmark improvements in Ireland.

Role of cardiac magnetic resonance in the evaluation of dilated cardiomyopathy: diagnostic contribution and prognostic significance

Dilated cardiomyopathy (DCM) represents the final common morphofunctional pathway of various pathological conditions in which a combination of myocyte injury and necrosis associated with tissue fibrosis results in impaired mechanical function. Recognition of the underlying aetiology of disease and accurate disease monitoring may be crucial to individually optimize therapeutic strategies and stratify patient's prognosis. In this regard, CMR has emerged as a new reference gold standard providing important information for differential diagnosis and new insight about individual risk stratification. The present review article will focus on the role of CMR in the evaluation of present condition, analysing respective strengths and limitations in the light of current literature and technological developments.

Integrating anatomical and functional imaging for the assessment of coronary artery disease

Coronary artery disease (CAD) is a leading cause of morbidity and mortality. Invasive cardiac angiography with fractional flow reserve measurement allows for the anatomical and functional assessment of CAD. Given the invasive nature of invasive cardiac angiography and the risks of procedure-related complications, research has focused upon noninvasive methods for anatomical and functional measures of CAD. As such, there is growing interest in the development of hybrid imaging because it may provide incremental diagnostic information over each imaging modality alone. We will provide an overview of the evidence to date on the anatomical and functional stratification of CAD and current hybrid techniques.

Multi-modal imaging technologies in cardiovascular risk assessment

Atherosclerotic plaques can be responsible for life-threatening cardiovascular and cerebrovascular events. Some features of the plaque, such as a thin fibrous cap, large necrotic core, macrophage infiltration, neovascularization, and intraplaque hemorrhage, are associated with a major risk of such events and so their assessment is fundamental. Novel imaging techniques, each one with its own strength and drawbacks, can help in the evaluation and quantification of atherosclerosis. An analysis of the recent literature was carried out. The different techniques were compared by evaluating the accuracy of each one in the detection and assessment of the atherosclerotic plaque's features named above.