CMRI Insight: A GUI-based open-source tool for cardiac MRI segmentation and motion tracking application

Funding Acknowledgements Type of funding sources: None. Introduction Segmentation of cardiac magnetic resonance (CMR) images is an essential step for evaluating dimensional and functional ventricular parameters but may limited by noise artefacts, such as the increasing diffusion of implantable devices causing distortion of the magnetic field. Purpose The aim of this paper is to investigate the accuracy of a deep learning (DL) approach for automatic segmentation of cardiac structures from CMR images characterized by magnetic susceptibility artifact images. Methods A retrospective database of SAX (short axis) cine CMR images obtained from 216 patients using a 1.5 Tesla scanner was used to develop and validate the proposed DL approach, subdividing patients into two subgroups, considering the presence (n=86) or absence (n=130) of a cardiac implantable electronic device. A novel convolutional neural network (CNN) was proposed to extract the left (LV) and right (RV) ventricle endocardium and left ventricle epicardium (LV mass). The proposed network takes advantage from a spatial attention module which introduces an adaptive feature refinement through a spatial weighting strategy to identify salient image regions even in the presence of artifacts. To improve segmentation, especially for images with artifacts, a compounded loss function is introduced. Segmentation results were assessed against manual tracings and commercial CMR analysis software. Results Results of correlation and Bland-Altman analyses on images with artifacts were reported for the proposed CNN and the commercial software (CS) in respect to the manual gold standard (GT). Also interobserver variability between O1 and O2 was tested. The proposed method reached higher segmentation accuracy than CS, with performance comparable to expert inter-observer variability (Picture 1). It is possible to appreciate how all the contours were properly depicted using the proposed CNN, with results comparable to the manual tracings. On the opposite, the CS resulted in imprecise segmentations of LV and RV endocardium and LV epicardium in presence of susceptibility artefacts caused by cardiac implantable electronic device affecting images' quality (Picture 2). Furthermore, the automatic approach was at least 100 times faster than manual segmentation in providing cardiac parameters. Conclusion The proposed method reached promising performance in cardiac segmentation from CMR images with susceptibility artifacts and alleviates time consuming expert physician contourn segmentation.

PurposeCardiac motion tracking enables quantitative evaluation of myocardial strain, which is clinically interesting in cardiovascular disease research. However, motion tracking is difficult to perform manually. In this paper, we aim to develop and compare two fully automated motion tracking methods for the steady state free precession (SSFP) cine magnetic resonance imaging (MRI), and explore their use in real clinical scenario with different patient groups.MethodsWe proposed two automated cardiac motion tracking method: (a) a traditional registration‐based method, named full cardiac cycle registration, which simultaneously tracks all cine frames within a full cardiac cycle by joint registration of all frames; and (b) a modern convolutional neural network (CNN)‐based method, named Groupwise MotionNet, which enhances the temporal coherence by fusing motion along a continuous time scale. Both methods were evaluated on the healthy volunteer data from the MICCAI 2011 STACOM Challenge, as well as on patient data including hypertrophic cardiomyopathy (HCM) and myocardial infarction (MI).ResultsThe full cardiac cycle registration method achieved an average end‐point error (EPE) 2.89 ± 1.57 mm for cardiac motion tracking, with computation time of around 9 min per short‐axis cine MRI (size 128 × 128, 30 cardiac phases). In comparison, the Groupwise MotionNet achieved an average EPE of 0.94 ± 1.59 mm, taking < 1 s for a full cardiac phases. Further experiments showed that registration method had stable performance, independent of patient cohort and MRI machine, while the CNN‐based method relied on the training data to deliver consistently accurate results.ConclusionBoth registration‐based and CNN‐based method can track the cardiac motion from SSFP cine MRI in a fully automated manner, while taking temporal coherence into account. The registration method is generic, robust, but relatively slow; the CNN‐based method trained with heterogeneous data was able to achieve high tracking accuracy with real‐time performance.

Cardiac magnetic resonance (CMR) images play a growing role in the diagnostic imaging of cardiovascular diseases. Full coverage of the left ventricle (LV), from base to apex, is a basic criterion for CMR image quality and necessary for accurate measurement of cardiac volume and functional assessment. Incomplete coverage of the LV is identified through visual inspection, which is time-consuming and usually done retrospectively in the assessment of large imaging cohorts. This paper proposes a novel automatic method for determining LV coverage from CMR images by using Fisher-discriminative three-dimensional (FD3D) convolutional neural networks (CNNs). In contrast to our previous method employing 2D CNNs, this approach utilizes spatial contextual information in CMR volumes, extracts more representative high-level features and enhances the discriminative capacity of the baseline 2D CNN learning framework, thus achieving superior detection accuracy. A two-stage framework is proposed to identify missing basal and apical slices in measurements of CMR volume. First, the FD3D CNN extracts high-level features from the CMR stacks. These image representations are then used to detect the missing basal and apical slices. Compared to the traditional 3D CNN strategy, the proposed FD3D CNN minimizes within-class scatter and maximizes between-class scatter. We performed extensive experiments to validate the proposed method on more than 5,000 independent volumetric CMR scans from the UK Biobank study, achieving low error rates for missing basal/apical slice detection (4.9%/4.6%). The proposed method can also be adopted for assessing LV coverage for other types of CMR image data.

Segmentation of the left ventricle (LV) in echocardiography is an important task for the quantification of volume and mass in heart disease. Continuing advances in echocardiography have extended imaging capabilities into the 3D domain, subsequently overcoming the geometric assumptions associated with conventional 2D acquisitions. Nevertheless, the analysis of 3D echocardiography (3DE) poses several challenges associated with limited spatial resolution, poor contrast-to-noise ratio, complex noise characteristics, and image anisotropy. To develop automated methods for 3DE analysis, a sufficiently large, labeled dataset is typically required. However, ground truth segmentations have historically been difficult to obtain due to the high inter-observer variability associated with manual analysis. We address this lack of expert consensus by registering labels derived from higher-resolution subject-specific cardiac magnetic resonance (CMR) images, producing 536 annotated 3DE images from 143 human subjects (10 of which were excluded). This heterogeneous population consists of healthy controls and patients with cardiac disease, across a range of demographics. To demonstrate the utility of such a dataset, a state-of-the-art, self-configuring deep learning network for semantic segmentation was employed for automated 3DE analysis. Using the proposed dataset for training, the network produced measurement biases of -9 ± 16 ml, -1 ± 10 ml, -2 ± 5 %, and 5 ± 23 g, for end-diastolic volume, end-systolic volume, ejection fraction, and mass, respectively, outperforming an expert human observer in terms of accuracy as well as scan-rescan reproducibility. As part of the Cardiac Atlas Project, we present here a large, publicly available 3DE dataset with ground truth labels that leverage the higher resolution and contrast of CMR, to provide a new benchmark for automated 3DE analysis. Such an approach not only reduces the effect of observer-specific bias present in manual 3DE annotations, but also enables the development of analysis techniques which exhibit better agreement with CMR compared to conventional methods. This represents an important step for enabling more efficient and accurate diagnostic and prognostic information to be obtained from echocardiography.

Cardiac magnetic resonance (CMR) images play a growing role in diagnostic imaging of cardiovascular diseases. MRI is arguably the most comprehensive imaging modality for noninvasive and nonionizing imaging of the heart and great vessels and, hence, most suited for population imaging cohorts. Ensuring full coverage of the left ventricle (LV) is a basic criterion of CMR image quality. Complete LV coverage, from base to apex, precedes accurate cardiac volume and functional assessment. Incomplete coverage of the LV is identified through visual inspection, which is time-consuming and usually done retrospectively in large imaging cohorts. In this chapter, we propose a novel automatic method to check the coverage of LV from CMR images by using Fisher discriminative and dataset invariance (FDDI) three-dimensional (3D) convolutional neural networks (CNN) independently of image-acquisition parameters, such as imaging device, magnetic field strength, variations in protocol execution, etc. The proposed model is trained on multiple cohorts of different provenance to learn the appearance and identify missing basal and apical slices. To address this, a two-stage framework is proposed. First, the FDDI 3D CNN extracts high-level features in the common representation from different CMR datasets using adversarial approach; then these image features are used to detect missing basal and apical slices. Compared with the traditional 3D CNN strategy, the proposed FDDI 3D CNN can minimize the within-class scatter and maximize the between-class scatter, which can be adapted to other CMR image data for LV coverage assessment.

Cardiac segmentation on late gadolinium enhancement MRI: A benchmark study from multi-sequence cardiac MR segmentation challenge.

This paper presents a novel edge following technique for image segmentation designed to segment the left ventricle in cardiac magnetic resonance (MR) images. This is a required step to determine the volume of left ventricle in a cardiac MR image, which is an essential tool for cardiac diagnosis. The traditional method for extracting them from cardiac MR images is by human delineation. This method is accuracy but time consuming. So a new ventricular segmentation technique is proposed in order to reduce the analysis time with similar accuracy level compared to doctorspsila opinions. Our proposed technique can detect ventricle edges in MR images using the information from the vector image model and the edge map. We also compare the proposed segmentation technique with the active contour model (ACM) and the gradient vector flow (GVF) by using the opinions of two skilled doctors as the ground truth. The experimental results show that our technique is able to provide more accurate segmentation results than the classical contour models and visually close to the manual segmentation by the experts. The results evaluated using a numerical measure by mean of the probability of error in image segmentation also confirm the visual evaluation.

THU0342 DECLINE IN SUBCLINICAL SYSTEMIC SCLEROSIS PRIMARY HEART INVOLVEMENT ASSOCIATES WITH POOR PROGNOSTIC FACTORS AND ACTIVE INTERSTITIAL LUNG DISEASE

Objective. Cardiovascular disease (CVD) is a group of diseases affecting cardiac and blood vessels, and short-axis cardiac magnetic resonance (CMR) images are considered the gold standard for the diagnosis and assessment of CVD. In CMR images, accurate segmentation of cardiac structures (e.g. left ventricle) assists in the parametric quantification of cardiac function. However, the dynamic beating of the heart renders the location of the heart with respect to other tissues difficult to resolve, and the myocardium and its surrounding tissues are similar in grayscale. This makes it challenging to accurately segment the cardiac images. Our goal is to develop a more accurate CMR image segmentation approach. Approach. In this study, we propose a regional perception and multi-scale feature fusion network (RMFNet) for CMR image segmentation. We design two regional perception modules, a window selection transformer (WST) module and a grid extraction transformer (GET) module. The WST module introduces a window selection block to adaptively select the window of interest to perceive information, and a windowed transformer block to enhance global information extraction within each feature window. The WST module enhances the network performance by improving the window of interest. The GET module grids the feature maps to decrease the redundant information in the feature maps and enhances the extraction of latent feature information of the network. The RMFNet further introduces a novel multi-scale feature extraction module to improve the ability to retain detailed information. Main results. The RMFNet is validated with experiments on three cardiac data sets. The results show that the RMFNet outperforms other advanced methods in overall performance. The RMFNet is further validated for generalizability on a multi-organ data set. The results also show that the RMFNet surpasses other comparison methods. Significance. Accurate medical image segmentation can reduce the stress of radiologists and play an important role in image-guided clinical procedures.

BackgroundIn acute myocardial infarction (AMI), both tissue necrosis and edema are present and both might be implicated in the development of intraventricular dyssynchrony. However, their relative contribution to transient dyssynchrony is not known. Cardiovascular magnetic resonance (CMR) can detect necrosis and edema with high spatial resolution and it can quantify dyssynchrony by tagging techniques.MethodsPatients with a first AMI underwent percutaneous coronary interventions (PCI) of the infarct-related artery within 24 h of onset of chest pain. Within 5–7 days after the event and at 4 months, CMR was performed. The CMR protocol included the evaluation of intraventricular dyssynchrony by applying a novel 3D-tagging sequence to the left ventricle (LV) yielding the CURE index (circumferential uniformity ratio estimate; 1 = complete synchrony). On T2-weighted images, edema was measured as high-signal (>2 SD above remote tissue) along the LV mid-myocardial circumference on 3 short-axis images (% of circumference corresponding to the area-at-risk). In analogy, on late-gadolinium enhancement (LGE) images, necrosis was quantified manually as percentage of LV mid-myocardial circumference on 3 short-axis images. Necrosis was also quantified on LGE images covering the entire LV (expressed as %LV mass). Finally, salvaged myocardium was calculated as the area-at-risk minus necrosis (expressed as % of LV circumference).ResultsAfter successful PCI (n = 22, 2 female, mean age: 57 ± 12y), peak troponin T was 20 ± 36ug/l and the LV ejection fraction on CMR was 41 ± 8%. Necrosis mass was 30 ± 10% and CURE was 0.91 ± 0.05. Edema was measured as 58 ± 14% of the LV circumference. In the acute phase, the extent of edema correlated with dyssynchrony (r2 = −0.63, p < 0.01), while extent of necrosis showed borderline correlation (r2 = −0.19, p = 0.05). PCI resulted in salvaged myocardium of 27 ± 14%. LV dyssynchrony (=CURE) decreased at 4 months from 0.91 ± 0.05 to 0.94 ± 0.03 (p < 0.004, paired t-test). At 4 months, edema was absent and scar %LV slightly shrunk to 23.7 ± 10.0% (p < 0.002 vs baseline). Regression of LV dyssynchrony during the 4 months follow-up period was predicted by both, the extent of edema and its necrosis component in the acute phase.ConclusionsIn the acute phase of infarction, LV dyssynchrony is closely related to the extent of edema, while necrosis is a poor predictor of acute LV dyssynchrony. Conversely, regression of intraventricular LV dyssynchrony during infarct healing is predicted by the extent of necrosis in the acute phase.

Background Moderate intensity regular physical activity is a mainstay of cardiovascular prevention. However, it is under debate whether the cumulative effects of intensive endurance exercise induce chronic cardiac damage. It has been proposed that long-term endurance exercise may be associated with myocardial fibrosis detected by late gadolinium-enhancement (LGE) cardiac magnetic resonance (CMR), and/or with right ventricle contractile dysfunction, creating a potential substrate for ventricular arrythmia, but these aspects are not constantly found across studies. Extracellular volume (ECV) determined by CMR, circulating cardiac biomarkers, and longitudinal global 2D strain (LGS) assessed by cardiac echography are relevant tools to explore these potential adverse effects of exercise in senior athletes. Purpose To assess the presence of myocardial fibrosis detected by CMR (LGE and ECV) and biomarkers, and to evaluate ventricles function with LGS, in endurance senior competitive athletes. Methods Thirty-three asymptomatic endurance senior athletes (47±6 years old, 9,6±1,7 h of training per week for 26±6 years), were compared to 18 sedentary controls (49±7 years old). They underwent a CMR protocol including morphological and late gadolinium-enhancement (LGE) analysis, T1 mapping and calculation of ECV using a 1.5 T MRI scanner. A maximal exercise transthoracic echography with LGS analysis was performed. Cardiac biomarkers (N terminal pro brain natriuretic peptide, high-sensitivity troponin T and plasma markers of collagen biosynthesis and degradation procollagen type I N terminal propeptide and procollagen type III NT propeptide) were also analysed. Results Athletes had higher left (84,0±20,8 vs 67,62±12,4 ml/m2; p=0,00593) and right (41,3±9,5 vs 32,9±6,0 ml/m2; p=0,00228) ventricular volumes, higher total biventricular mass (109,61±14,18 vs 98,66±16,25 g/m2; p=0,02038), and higher stroke volume (50,7±12,6 vs 40,1±9,2 ml/m2; p=0,00441) assessed by CMR versus controls. Native T1 (left ventricle: 938±21 vs 940±34 ms; p=0,8098 - right ventricle: 1027±53 vs 1026±114 ms; p=0,92983) and ECV (21,5±1,6 vs 22,0±2,2%; p=0,40868) were not significantly different in athletes compared with controls. LGE was not found in athletes. Peak exercise LGS values were higher in athletes for left (23,19±2,86 vs 20,82±2,05%; p=0,00335) and right (29,25±3,47 vs 26,48±3,22%; p=0,00777) ventricles, compared with control. The levels of cardiac biomarkers were normal in all subjects. Conclusion Athletes showed signs of physiological cardiac remodelling, consistent with previous descriptions of athlete's heart. Despite this important remodelling, there was no evidence of myocardial fibrosis or exercise left or right ventricular dysfunction in athletes. Our results are not supporting the hypothesis of deleterious cardiac effects induced by long term and intensive endurance exercise training.

Automatic segmentation of left ventricle from cardiac MRI via deep learning and region constrained dynamic programming

PERIOPERATIVE myocardial complications after noncardiac surgery affect more than 1 million operations each year and are leading causes of morbidity and mortality, especially among patients undergoing vascular surgery. Myocardial complications such as perioperative myocardial infarction (MI) are common and are the most likely cause for perioperative death in all surgical populations.1In general surgery, the risk for perioperative MI is 0.8% in men older than 50 yr2and varies with the cardiovascular status, comorbidities, and the extent of the procedure, reaching more than 20% among patients undergoing vascular surgery.3As patients become older and sicker and procedures become more aggressive and extensive, physicians must find novel approaches to evaluate and prepare cardiac patients for noncardiac procedures and reduce perioperative myocardial events.The American Heart Association–American College of Cardiology guidelines for cardiac risk evaluation use the patient's history, physical examination, and functional capacity, and taking into account the expected surgery, one may recommend further assessment with noninvasive testing or coronary angiography.4The purpose of this review is to provide an overview of available imaging tools that could potentially be used for perioperative evaluation of cardiac patients before noncardiac surgery, in accord with recent guidelines and with focus on the recent progress made with cardiac computed tomography (CT).Traditionally, preoperative evaluation has relied on the patient's history, physical examination, and functional capacity. After preoperative evaluation, the physician should determine the clinical predictors as major, intermediate, or minor4and evaluate the functional capacity of the patient. New York Heart Association class II heart failure, which equals 4 metabolic equivalents,4has also been found to be an important predictor of perioperative cardiac complications after major noncardiac surgery. The cutoff value of 4 or more metabolic equivalents determines an adequate cardiac functional capacity and reserve and predicts perioperative cardiac events in patients treated with high-risk noncardiac surgery.5Finally, the extent and risk associated with the procedure should be categorized as major, intermediate, or minor. The cardiac risk is the combined incidence of cardiac death and nonfatal MI and is greater than 5% for high-risk procedures, whereas intermediate-risk procedures have less than 5% cardiac risk (1–5%), and low-risk procedures have less than 1% cardiac risk.4Indeed, based on these criteria, the flowchart of Eagle et al. 4suggests when a noninvasive test or coronary angiography may be appropriate to evaluate cardiac function, reserve, or ability to withstand surgical stress. Pertinent to the utility of evaluating cardiac structure and function, new imaging techniques for evaluation of the heart have emerged in the past couple of decades. These techniques may provide more comprehensive information regarding the structure and function of the heart and coronary arteries, and evaluate adequately patients who have mechanical restrictions to perform exercise-induced stress. Such developments in cardiac imaging may eventually provide an opportunity to revise and refine the steps involving the evaluation of cardiac patients.6,7This approach should be evaluated cautiously and should take into consideration recent recommendations and guidelines. For example, the current American Heart Association–American College of Cardiology guidelines recommend the use of perioperative β-blocker therapy as an alternative approach to decrease cardiovascular risk.8β-Blockers initiated at least 1 week before major vascular surgery and continued for 30 days postoperatively reduced significantly the perioperative incidence of nonfatal MI and death from cardiac causes in high-risk patients.9In addition to beta blockers, statins may reduce perioperative mortality in patients undergoing major vascular surgery and may have an additive effect to β-blockers.10,11The strategy of preoperative coronary artery revascularization before elective major vascular surgery to reduce perioperative cardiac morbidity and mortality was investigated in the Coronary Artery Revascularization Prophylaxis trial, a multicenter study involving patients with vascular disease and significant coronary artery disease (CAD), but no unstable angina. Cardiac revascularization did not result in increased survival, either perioperatively or in long-term follow-up, in patients who needed elective vascular surgery.12However, although the Coronary Artery Revascularization Prophylaxis study is a cornerstone trial in the perioperative care of cardiac patients for noncardiac surgery, it had some limitations. In particular, only 9% of the patients scheduled to undergo vascular operations were eligible for the study. The main reasons for exclusion were insufficient cardiac risk, an urgent vascular surgery, previous revascularization without ischemia, severe coexisting illnesses, left main coronary artery stenosis of at least 50%, left ventricular ejection fraction less than 20%, and severe aortic stenosis. The outcome of these patients has not been adequately evaluated.Indeed, taking into consideration the patient's perioperative cardiac risk according to clinical predictors, functional capacity, and the extent of the future surgery, the anesthesiologist must decide whether further cardiac assessment or perioperative medical management are indicated. Patients whose functional capacity is difficult to establish, who underwent previous coronary revascularization, who have unstable or changed cardiac status, or who have severe comorbidities may need further evaluation. Several imaging techniques are available for evaluation of cardiac patients, including cardiac CT, coronary angiography, stress echocardiography, cardiac magnetic resonance imaging (CMRI), and myocardial nuclear studies.Computed tomography is widely available in large medical centers and is routinely used in clinical practice. The basic principle of CT is that a fan-shaped, thin x-ray beam passes through the body at many angles to allow for cross-sectional images. After collimation of the beam (i.e. , achieving a definitive slice thickness using a collimator) to reduce scatter, the photons are recorded on a corresponding detector array, and the transmission data are digitized. A “filtered back projection” reconstruction algorithm, which takes into account the attenuation of the x-ray beam along its path, allows for reconstruction of the grayscale values of each picture element (pixel) with reference to the value for water and air, to depict cross-sectional images. Reconstruction algorithms and multirow detectors applied in current scanners enable three-dimensional volumetric imaging and multiple high-quality reconstructions of various volumes of interest.13Current clinical scanners used for cardiovascular imaging employ either a rotating x-ray source with a circular, stationary detector array (e.g. , helical CT) or electromagnetic deflection of an electron beam to replace mechanical motion (electron beam computed tomography [EBCT]).14Multidetector computed tomography (MDCT) is a helical CT with a large array of detectors, which allow it to acquire a large number of slices simultaneously (4–256) and greatly increase its resolution. However, to obtain quantitative measurements of tissue opacity within a specific cardiac phase (e.g. , for measurement of perfusion), the scanning time should generally be less than 100 ms.15Sufficiently high temporal resolution (the time required to acquire the data for one image) is currently offered only by the EBCT (50 ms/image) and the novel Dual-Source CT (SOMATOM® Defi-nition; Siemens Medical Systems, Forchheim, Germany) (83 ms/image), a recently released model of MDCT that has two x-ray tubes (rather than one) positioned at 90° to each other, thereby doubling temporal resolution.16However, this technique remains to be validated for such measurements.Electron beam computed tomography was developed in the 1980s and hailed as an ultimate cardiac scanner. It allows almost simultaneous data acquisition from up to eight parallel slices (7–8 mm thick) by rapid sweeping of an electron beam along target rings in as little as 50 ms per scan. Because it does not involve moving parts (and therefore decreases the need for cooling), the speed of acquisition (temporal resolution) with EBCT is faster than with MDCT (table 1) and usually does not require slowing the heart rate pharmacologically. The high speed of EBCT is offset by moderate image quality and relatively restricted power for acquisition of a large number of images, which decreased its popularity for comprehensive cardiac studies. Consequently, its availability is limited, resulting in declining use of this technology.Multidetector computed tomography is a relatively ubiquitous and newer scanner that has temporal resolution of 330–400 ms/image, which enables many studies of cardiac anatomy and global function (e.g. , ejection fraction and cardiac output). Spatial resolution can be achieved with 64-slice scanners using isotropic voxels (consistent three-dimensional image quality in any reconstruction plane) of 0.4 × 0.4 × 0.4 mm. The technique involves continuous rotation of the x-ray tube and detectors and simultaneous translation of the patient through the gantry opening, and can acquire multiple simultaneous sections of variable widths using prospective electrocardiographic triggering.17Alternatively, retrospective electrocardiographic gating enables reconstruction of images at any desired time in the cardiac cycle. Data can be used from multiple slices to reconstruct other imaging planes. The images are of best quality when the resting heart rate (HR) is less than 70 beats/min. At faster heart rates, motion artifacts may become more prominent, and therefore HR may need to be pharmacologically decreased before scanning. The temporal resolution of MDCT determines the overall scan time. As gantry rotation speeds increase, the minimum slice thickness decreases, with submillimeter sections throughout the heart acquired during a single breath hold. The overall CT scan time is approximately 12 s, and the mean total time for the examination is less than 13 min with 64-slice technology.The improvement in MDCT technology enabled the assessment of significant luminal stenosis and identification of nonstenotic atherosclerotic plaques. Virtual noninvasive angiography, with three-dimensional reconstruction of coronary anatomy from cardiac CT images, can provide information about coronary luminal obstruction, calcium scoring, and composition of the plaque.18Furthermore, it has the added benefit of offering fine details of the examined vessels (fig. 1).Excellent sensitivity and specificity were found for evaluation of proximal, middle and distal left anterior descending, first diagonal, proximal and distal circumflex, obtuse marginal and proximal mid and distal right coronary artery.19A meta-analysis of diagnostic performance of MDCT compared with invasive coronary angiography showed a sensitivity of 85% and a specificity of 95% for identification of CAD. On average, 87% of segments had diagnostic image quality, with a significant increase from 78% with 4-slice systems to 96% with the more recent 16-slice systems.6Multidetector computed tomography could provide a clinically useful tool in the workup of symptomatic patients before angiography.20A patient with chronic chest pain indicative of CAD could undergo CT angiography, and if low calcium score and no circumferential calcifications (or other test results indicative of ischemia) are found, invasive angiography may not be indicated, because MDCT has excellent negative predictive value to rule out CAD. By this approach, patients with primarily microvessel disease (which may cause angina and abnormal stress test results) may be identified and not required to go through unnecessary fluoroscopic angiography, and aggressive medical therapy would be indicated before surgery.20MDCT also has high diagnostic accuracy in detecting bypass graft stenosis and occlusions in symptomatic patients after coronary artery bypass grafting, which might potentially reduce dramatically the number of unnecessary invasive angiographies performed in these patients.21However, although the MDCT technique has been extensively evaluated for its accuracy for detection of CAD compared with standard coronary angiography,6,19,20,22it has not been applied for the routine evaluation of cardiac patients for noncardiac surgery and, to date, is not a recommended technique for perioperative risk stratification.The main technical limitations of cardiac CT for evaluation of the coronary arteries include the difficulty in handling cardiac motion, arrhythmia, severe calcifications, vessel size less than 1.5 mm, breathing, the presence of stents, and poor enhancement.22Lesions with extensive calcified components and implanted coronary stents compromise the accuracy of MDCT coronary angiography by causing artifacts.23Stent type and diameter influence evaluability of in-stent restenosis by MDCT, but in evaluable stents, sensitivity is still 86% and specificity is 98%.24When HR is reduced below 70 beats/min, image quality is improved, especially in terms of the visualization of the right coronary and left circumflex arteries, which are both significantly prone to motion artifacts (particularly at higher HR) because of their close proximity to the atrium, which is reactivated during the early diastolic phase.25For evaluation of coronary artery calcium volume with MDCT, thin-slice retrospective spiral electrocardiographic–gated scanning is desirable.26Most studies on coronary calcification have been performed using EBCT, which is still considered the “gold standard” (table 1). To image the coronary arteries with EBCT, 30–40 axial images are obtained with 3-mm slice thickness, using single-slice prospective electrocardiographic triggering in the craniocaudal direction along the full length of the heart. Rapid image acquisition at 100 ms allows accurate measurement of calcium deposits in the coronary arteries.27Quantification of coronary artery calcifications was found to be independently associated with cardiac events in a 3-yr follow-up of thousands of initially asymptomatic patients.28Noninvasive characterization and quantification of atherosclerotic plaque burden may also have important implications for the prevention of CAD progression and its complications.18For the past several years, CMRI has been considered the reference standard for assessment of left ventricular (LV) functions. However, cardiac CT is playing an increasingly important role in this evaluation. Both CT and CMRI surpass two-dimensional imaging techniques, such as standard two-dimensional echocardiography, for cardiac quantification because of their ability to generate contiguous short axis cine images, allowing for three-dimensional measurements without the use of geometric assumptions.29Postprocessing tools allow fast and semiautomatic determination of LV function parameters from MDCT data in analogy to known CMRI evaluation approaches.30Studies have demonstrated excellent correlation between cardiac CT and CMRI for LV ejection fraction, end-diastolic volume, end-systolic volume, stroke volume, and myocardial mass.30Furthermore, global and regional LV functions agree well with echocardiography, with correlation coefficients ranging from 0.91 to 0.97 for MDCT and from 0.93 to 0.98 for CMRI.7,30,31Although MDCT is not considered to be the first-line modality for assessment of LV function, it can provide a combined assessment of cardiac morphology and function without the need for additional radiation exposure in patients undergoing MDCT coronary angiography. The acquisition of images is performed according to the R–R interval. For MDCT, the image data are gated with the electrocardiogram to allow reconstruction at various times throughout the cardiac cycle. CT allows quantitative analysis of regional and global systolic function in normal and pathologic conditions by using short axis slices from the base to the apex of the heart. End-diastole and end-systole are defined as maximal and minimal LV volume, and LV ejection fraction is the difference between them.30Diastolic function can also be assessed from the rate of change of the LV volume during diastole.13Also, because temporal resolution for electrocardiographic-gated cardiac CT scans (down to 165 ms) is poorer in comparison to cine CMRI (30–40 ms), CT imaging may miss peak ejection rate or peak filling rate. However, advances in MDCT imaging that will improve temporal resolution may correct this problem.16Regional wall motion abnormalities, myocardial thinning, ventricular aneurysm, and mural thrombi in the infarcted area can all be detected by cardiac CT. Dual-phase contrast CT can detect acute MI characterized by an initial filling defect and late enhancement at the site of the damaged myocardium. Late enhancement may have the potential to distinguish viable from nonviable myocardium, and has significant prognostic value for the recovery of the myocardial wall motion and thickness after ischemia and in response to therapeutic revascularization.32In patients with previous MI, MDCT permits accurate, noninvasive assessment of coronary artery stenosis, LV function, and perfusion, assessed from a single data set.33If the myocardium supplied by the stenotic or occluded vessel is still viable, medical treatment or revascularization can be considered to reduce the risk of perioperative ischemia in the affected myocardium.Experimental studies in animals and humans demonstrated that cardiac CT could be used to assess microvascular function, although this technique is not used clinically, partially because of high radiation exposure. Evaluation of myocardial perfusion at rest and after infusion of vasodilators imposing cardiac challenge can reveal the presence of otherwise undetectable limited myocardial flow reserve, which might have a significant value for detection of borderline or very early alterations in cardiac microvascular function, as well as detecting increases in microvascular permeability that may reflect endothelial dysfunction or ischemic changes.34The use of CT scanning is limited by the need for contrast media and radiation exposure (table 2). The risks associated with contrast media administration include extravasation at the contrast injection site, allergic contrast reaction, and a decline in function, as well as and vascular In patients with administration of contrast media is media has been reduced and is than that used during angiography potential of alternative contrast such as might further decrease the various radiation are with MDCT, and scanning may allow a decrease in radiation of cardiac function and volumes may from to potentially any based on gated that data several cardiac limitations include the need to image quality in patients and the need for and physicians for acquisition and of cardiac CT data of the limitations of MDCT is the need to decrease heart rate at time of which may be in some It further the need for CT technology to acquisition time a greater volume of developed scanners such as the Dual-Source MDCT may this to temporal the number of that can be from axial CT images is limited only by gantry rotation speed and patient heart decreased ejection fraction in is associated with decreased overall postoperatively and with increased incidence of heart failure, but no has been found with main associated with cardiac events is the presence of wall motion has a low predictive is appropriate in patients who American Heart Association–American College of Cardiology clinical guidelines and who would require if no surgery were as well as in with aortic sensitivity of can be by the heart either or pharmacologically. stress test with administration of can provide information about cardiac function, ventricular and function, and a is in to 85% of maximal HR or or as wall motion abnormalities, whereas a in ejection fraction in response to administration is a of more severe CAD. has excellent negative predictive values and sensitivity but moderate specificity and is significantly and long-term cardiac risk using initial cardiac risk assessment and noninvasive testing with may the perioperative and long-term treatment of patients undergoing major vascular comparison with other noninvasive a diagnostic new of may improve cardiac risk compared with standard in patients undergoing noncardiac surgery whose functional capacity be evaluated by stress stress has a relatively low and can assess cardiac structure and function, wall thickness, aortic and the presence of However, has sensitivity for detection of single vessel disease and is to distinguish between microvascular and CAD (table because wall motion can be found in progress has been made during the past in which is used to evaluate a of heart and including CAD. CMRI is based on the of which and to an magnetic CMRI a causes deflection of the from the direction of the main magnetic The is during the of the back their in the magnetic are and data are used for image many image are for assessment of global ventricular and function, ejection fraction, stroke volume, and detection of and acute and chronic LV can be and using analysis of may find use in the clinical magnetic resonance imaging has higher temporal resolution but resolution (the ability to distinguish between two on the image) than cardiac resolution of 1.5 × 1.5 may have an CMRI for detection of because its overall accuracy in the detection of coronary artery stenosis is higher (table 2). The axial image of MDCT allows more vascular as compared with CMRI that may artifacts to sensitivity and specificity of CMRI for detection of coronary artery stenosis are and whereas of coronary segments are is noninvasive and high-quality images of the heart (table 2). However, CMRI examination be applied in patients who have a or and the presence of and stents can CMRI images and to is the of the test than an during which the patient must be CMRI is an important noninvasive tool and does not the use of potential contrast are needed to evaluate its use as a perioperative tool and its correlation with perioperative cardiac use of myocardial computed tomography and tomography has in the past two because of their in useful information about myocardial perfusion and function based on administration of an unstable with has been used for many for preoperative cardiac evaluation. the coronary response associated with testing not the HR and has been used in patients scheduled to undergo vascular surgery. However, has low and negative predictive and was not significantly associated with the incidence of perioperative MI, ischemia, or other the other the of this test was when used in patients undergoing aortic surgery whose risk could not have been on the of clinical value of imaging for preoperative cardiac assessment in high-risk has been demonstrated in patients before and vascular of myocardial with is important in patients with LV function to and the potential of revascularization can be These studies showed excellent correlation of with cardiac both perioperatively within 30 days and at long-term has high sensitivity in coronary disease but limited sensitivity for detecting significant disease and CAD (table 2). It also little functional data other than myocardial perfusion and has relatively low resolution that the quality of scanners have a maximal of approximately is required for before the performance of myocardial perfusion because the coronary effect of or is by with can be used to functional recovery of viable myocardium after coronary artery a is from a a in and with an results in of both the and the with to in the of electromagnetic radiation of two which in from each and are detected by a of radiation detectors at The difference in time the photons each radiation detector is used to detect the source of the of radiation detectors are in the gantry with million of per the imaging is useful in noninvasive quantification of myocardial flow and coronary flow reserve, and is also of detecting early disease in high-risk asymptomatic and the progression or of is to especially in patients and in undergoing remains a significant its high and limited availability currently its use as a technology of coronary angiography is well and involves injection of contrast media into the coronary artery by imaging in multiple planes. is by comparison of diameter at a stenotic site with that of a normal reference can evaluate coronary stenosis, LV function, and (table coronary angiography is an invasive technique and has a major rate of including mortality in of it may involve for the patient and is associated with other such as vascular complications for diagnostic and for complications and complications the risk of coronary angiography with that of MDCT, some risks are common to both procedures, such as an allergic contrast reaction, and exposure to whereas are to contrast media injection causes severe allergic in of risks of a of for MDCT angiography and for coronary angiography. However, the and risks and a overall risk of mortality from coronary that for MDCT angiography use of a power in a vascular with cardiac CT an additional risk of which in of the relatively significant number of negative invasive angiographies performed each the risks to this procedure by using noninvasive can greatly to the morbidity and mortality of coronary angiography. the number of negative angiographies might to significant because the of cardiac may be as as times that of cardiac evaluation of patients with or known cardiac disease for noncardiac surgery has been in the of of and The preoperative evaluation on assessment of clinical predictors, functional capacity, and the extent of the surgical The first-line to reduce perioperative morbidity and mortality include medical therapy with with HR and However, the strategy may also include of noninvasive imaging techniques that provide comprehensive and assessment of cardiac structure and In particular, in patients with restricted physical in assessment of the functional capacity is obtained using imaging with evaluation of the heart may potentially to treatment Cardiac CT is can provide coronary angiography for plaque assessment and scoring, and can assess LV function, and myocardial in a fast and relatively CT can in out significant CAD and determination of the need for invasive angiography. cardiac CT might potentially be the tool for overall evaluation of cardiac patients for noncardiac surgery. at this is no that preoperative cardiac CT scanning is to reduce perioperative studies are needed to assess the role of cardiac CT in the evaluation of patients at risk for cardiovascular disease before noncardiac surgery.

This prospective study aimed to evaluate whether radiation (RT)-induced myocardial damage by cardiac magnetic resonance (CMR) imaging could be a predictor of cardiac events after chemoradiotherapy (CRT) for esophageal cancer and determine the dose-volume histogram (DVH) parameters of the left ventricle (LV) in predicting cardiac events. CMR imaging was performed before and 6months after CRT in patients receiving definitive CRT. RT-induced myocardial damage was defined as abnormal CMR findings indicating myocardial fibrosis corresponding to an isodose line of ≥30Gy. The cutoff values of the LV DVH parameters were calculated using the receiver operating characteristic curve based on the presence of RT-induced myocardial damage. The prognostic factors related to cardiac events of Grade 3 or higher were examined. Twenty-three patients were enrolled in the study. RT-induced myocardial damage by late gadolinium enhancement and/or an increase of 100ms or higher in native T1 post-CRT was detected in 10 of the 23 patients. LV V45 was the best predictive factor for RT-induced myocardial damage with a cutoff value of 2.1% and an area under the curve of 0.75. The median follow-up period was 82.1months. The 5- and 7-year cumulative incidences of cardiac events of Grade 3 or higher were 14.7 and 22.4%, respectively. RT-induced myocardial damage and LV V45 were significant risk factors (P = 0.015 and P = 0.013, respectively). RT-induced myocardial damage is a significant predictor of cardiac events. LV V45 is associated with RT-induced myocardial damage and subsequent cardiac events.

The domain of deep learning stimulates medical image analysis, which is a catalyst of scientific research and an essential element of healthcare. Since semantic segmentation techniques empower image processing and quantitative determination in various applications, designing a dedicated solution is challenging and heavily reliant on input data characteristics and hardware constraints. Cardiac magnetic resonance imaging segmentation provides three essential heart structures, left ventricle (LV) cavity, myocardium (MYO), and right ventricle (RV) cavity. In clinical applications, manual contouring is frequently utilized to perform semantic segmentation. A fully automated cardiac magnetic resonance image (CMRI) segmentation technique is becoming more desirable as deep learning-based frameworks advance. Motivated by the power of U-Net, residual network, and deep supervision, this paper proposes a Deep Residual U-Net to achieve better LV, MYO, and RV segmentation in short-axis CMRI. The model is formed with residual connections and has a similar layout to U-Net. It provides three advantages: First, residual connections make deep network training easier. Second, the network's rich skip connections enable feature propagation, allowing for network creation with lower complexity but more remarkable performance. Third, Deep supervision facilitates the loss computation at every feature dimension except at least two, empowering gradients to be implanted more deeply in the network and improving each layer's training in Deep Residual U-Net. Automated Cardiac Diagnosis Challenge (ACDC) 2017 dataset has been used to assess the segmentation efficiency of proposed model. The proposed approach significantly outperformed all other methods, evidencing its supremacy over recent state-of-the-art U-Net-based techniques.