The future of CMR: All-in-one vs. real-time CMR (Part 2).

Cardiac Magnetic Resonance (CMR) protocols can be lengthy and complex, which has driven the research community to develop new technologies to make these protocols more efficient and patient-friendly. Two different approaches to improving CMR have been proposed, specifically "all-in-one" CMR, where several contrasts and/or motion states are acquired simultaneously, and "real-time" CMR, in which the examination is accelerated to avoid the need for breathholding and/or cardiac gating. The goal of this two-part manuscript is to describe these two different types of emerging rapid CMR protocols. To this end, the vision of all-in-one and real-time imaging are described, along with techniques which have been devised and tested along the pathway of clinical implementation. The pros and cons of the different methods are presented, and the remaining open needs of each are detailed. Part 1 tackles the "All-in-One" approaches, and Part 2 focuses on the "Real-Time" approaches along with an overall summary of these emerging methods.

Volumetric segmentation-free method for rapid visualization of vascular wall shear stress using 4D flow MRI.

PURPOSE: To develop a rapid segmentation-free method to visualize and compute wall shear stress (WSS) throughout the aorta using 4D Flow MRI data. WSS is the drag force-per-area the vessel endothelium exerts on luminal blood; abnormal levels of WSS are associated with cardiovascular pathologies. Previous methods for computing WSS are bottlenecked by labor-intensive manual segmentation of vessel boundaries. A rapid automated segmentation-free method for computing WSS is presented. THEORY AND METHODS: Shear stress is the dot-product of the viscous stress tensor and the inward normal vector. The inward normal vectors are approximated as the gradient of fluid speed at every voxel. Subsequently, a 4D map of shear stress is computed as the partial derivatives of velocity with respect to the inward normal vectors. We highlight the shear stress near the wall by fusing visualization with edge-emphasized anatomical data. RESULTS: As a proof-of-concept, four cases with aortic pathologies are presented. Visualization allows for rapid localization of pathologic WSS. Subsequent analysis of these pathological regions enables quantification of WSS. Average WSS during peak systole measures approximately 50-60 cPa in nonpathological regions of the aorta and is elevated in regions of stenosis, coarctation, and dissection. WSS is reduced in regions of aneurysm. CONCLUSION: A volumetric technique for calculation and visualization of WSS from 4D Flow MRI data is presented. Traditional labor-intensive methods for WSS rely on explicit manual segmentation of vessel boundaries before visualization. This automated volumetric strategy for visualization and quantification of WSS may facilitate its clinical translation.

Self-gated MRI of multiple beat morphologies in the presence of arrhythmias.

PURPOSE: Develop self-gated MRI for distinct heartbeat morphologies in subjects with arrhythmias. METHODS: Golden angle radial data was obtained in seven sinus and eight arrhythmias subjects. An image-based cardiac navigator was derived from single-shot images, distinct beat types were identified, and images were reconstructed for repeated morphologies. Image sharpness, contrast, and volume variation were quantified and compared with self-gated MRI. Images were scored for image quality and artifacts. Hemodynamic parameters were computed for each distinct beat morphology in bigeminy and trigeminy subjects and for sinus beats in patients with infrequent premature ventricular contractions. RESULTS: Images of distinct beat types were reconstructed except for two patients with infrequent premature ventricular contractions. Image contrast and sharpness were similar to sinus self-gated images (contrast = 0.45 ± 0.13 and 0.43 ± 0.15; sharpness = 0.21 ± 0.11 and 0.20 ± 0.05). Visual scoring was highest in self-gated images (4.1 ± 0.3) compared with real-time (3.9 ± 0.4) and ECG-gated cine (3.4 ± 1.5). ECG-gated cine had less artifacts than self-gating (2.3 ± 0.7 and 2.1 ± 0.2), but was affected by misgating in two subjects. Among arrhythmia subjects, post-extrasystole/sinus (58.1 ± 8.6 mL) and interrupted sinus (61.4 ± 5.9 mL) stroke volume was higher than extrasystole (32.0 ± 16.5 mL; P < 0.02). CONCLUSION: Self-gated imaging can reconstruct images during ectopy and allowed for quantification of hemodynamic function of different beat morphologies. Magn Reson Med 78:678-688, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Assessment of myocardial injury after reperfused infarction by T1ρ cardiovascular magnetic resonance.

BACKGROUND: The evolution of T1ρ and of other endogenous contrast methods (T2, T1) in the first month after reperfused myocardial infarction (MI) is uncertain. We conducted a study of reperfused MI in pigs to serially monitor T1ρ, T2 and T1 relaxation, scar size and transmurality at 1 and 4 weeks post-MI. METHODS: Ten Yorkshire swine underwent 90 min of occlusion of the circumflex artery and reperfusion. T1ρ, T2 and native T1 maps and late gadolinium enhanced (LGE) cardiovascular magnetic resonance (CMR) data were collected at 1 week (n = 10) and 4 weeks (n = 5). Semi-automatic FWHM (full width half maximum) thresholding was used to assess scar size and transmurality and compared to histology. Relaxation times and contrast-to-noise ratio were compared in healthy and remote myocardium at 1 and 4 weeks. Linear regression and Bland-Altman was performed to compare infarct size and transmurality. RESULTS: Relaxation time differences between infarcted and remote myocardial tissue were ∆T1 (infarct-remote) = 421.3 ± 108.8 (1 week) and 480.0 ± 33.2 ms (4 week), ∆T1ρ = 68.1 ± 11.6 and 74.3 ± 14.2, and ∆T2 = 51.0 ± 10.1 and 59.2 ± 11.4 ms. Contrast-to-noise ratio was CNRT1 = 7.0 ± 3.5 (1 week) and 6.9 ± 2.4 (4 week), CNRT1ρ = 12.0 ± 6.2 and 12.3 ± 3.2, and CNRT2 = 8.0 ± 3.6 and 10.3 ± 5.8. Infarct size was not significantly different for T1ρ, T1 and T2 compared to LGE (p = 0.14) and significantly decreased from 1 to 4 weeks (p < 0.01). Individual infarct size changes were ∆T1ρ = -3.8%, ∆T1 = -3.5% and ∆LGE = -2.8% from 1 - 4 weeks, but there was no observed change in infarct size for T2 or histologically. CONCLUSIONS: T1ρ was highly correlated with alterations left ventricle (LV) pathology at 1 and 4 weeks post-MI and therefore it may be a useful method endogenous contrast imaging of infarction.

Impact of end-diastolic and end-systolic phase selection in the volumetric evaluation of cardiac MRI.

PURPOSE: To evaluate the impact of end-diastolic (ED) and end-systolic (ES) cardiac phase selection methods, since task force recommendations have neither provided quantitative evidence nor explored errors introduced by clinical shortcuts. MATERIALS AND METHODS: Multislice, short-axis cine images were collected in 60 clinical patients on a 1.5T scanner. User-initialized active contour segmentation software quantified global left ventricular (LV) volume across all cardiac phases. Different approaches for selection of ED and ES phase were evaluated by quantification of temporal and volumetric errors. RESULTS: For diastole, the mid-ventricular maximum slice volume coincided with maximum global volume in 82.1% of patients with ejection fraction (EF) ≥55% (P = 0.66) and 71.9% of patients with EF <55% (P = 0.28) and is an accurate approximation of maximum global volume while the first and last phases in a retrospectively electrocardiogram (ECG)-gated acquisition introduced differences in cardiac phase selection (P < 0.001) which led to large errors in measured volume in some patients (12.7 and 10.1 mL, respectively). For systole, post-systolic shortening occurred in a significantly higher number of patients with EF <55% (18.9%) compared to 3.6% of patients with EF ≥55% (P = 0.001), which differentially impacted end-systolic volume estimation. CONCLUSION: For end-diastolic phase selection, our results indicated that the use of the mid-ventricular slice volume maximum provided accurate volume estimates, while selection of the first or last cardiac phase introduced differences in measured volume. For end-systolic phase, patients with EF <55% had a higher prevalence of post-systolic shortening, which suggests aortic valve closure should be used to estimate end-systolic volume.

User-initialized active contour segmentation and golden-angle real-time cardiovascular magnetic resonance enable accurate assessment of LV function in patients with sinus rhythm and arrhythmias.

BACKGROUND: Data obtained during arrhythmia is retained in real-time cardiovascular magnetic resonance (rt-CMR), but there is limited and inconsistent evidence to show that rt-CMR can accurately assess beat-to-beat variation in left ventricular (LV) function or during an arrhythmia. METHODS: Multi-slice, short axis cine and real-time golden-angle radial CMR data was collected in 22 clinical patients (18 in sinus rhythm and 4 patients with arrhythmia). A user-initialized active contour segmentation (ACS) software was validated via comparison to manual segmentation on clinically accepted software. For each image in the 2D acquisitions, slice volume was calculated and global LV volumes were estimated via summation across the LV using multiple slices. Real-time imaging data was reconstructed using different image exposure times and frame rates to evaluate the effect of temporal resolution on measured function in each slice via ACS. Finally, global volumetric function of ectopic and non-ectopic beats was measured using ACS in patients with arrhythmias. RESULTS: ACS provides global LV volume measurements that are not significantly different from manual quantification of retrospectively gated cine images in sinus rhythm patients. With an exposure time of 95.2 ms and a frame rate of > 89 frames per second, golden-angle real-time imaging accurately captures hemodynamic function over a range of patient heart rates. In four patients with frequent ectopic contractions, initial quantification of the impact of ectopic beats on hemodynamic function was demonstrated. CONCLUSION: User-initialized active contours and golden-angle real-time radial CMR can be used to determine time-varying LV function in patients. These methods will be very useful for the assessment of LV function in patients with frequent arrhythmias.

Regional Strain of Right Ventricle From Computed Tomography Improves Risk Stratification of Right Ventricle Failure.

Patients who undergo implantation of a left ventricular assist device (LVAD) are at a high risk for right ventricular failure (RVF), presumably due to poor right ventricular (RV) function before surgery. Cine computerized tomography (cineCT) can be used to evaluate RV size, function, and endocardial strain. However, CT-based strain measures in patients undergoing workup for LVAD implantation have not been evaluated. We quantified RV strain in the free wall (FW) and septal wall (SW) in patients with end-stage heart failure using cineCT. Compared to controls, both FW and SW strains were significantly impaired in heart failure patients. The difference between FW and SW strains predicted RV failure after LVAD implantation (area-under-the curve [AUC] = 0.82). Cine CT strain can be combined with RV volumetry to risk-stratify patients. In our study, patients with preserved RV volumes and poor strain had a higher rate of RV failure (57%), than those with preserved volume and preserved strain (0%). This suggests that CT could improve risk stratification of patients receiving LVADs and that strain metrics were particularly useful in risk-stratifying patients with preserved RV volumes.

Successful Cardiac Resynchronization Therapy Reduces Negative Septal Work in Patient-Specific Models of Dyssynchronous Heart Failure.

In patients with dyssynchronous heart failure (DHF), cardiac conduction abnormalities cause the regional distribution of myocardial work to be non-homogeneous. Cardiac resynchronization therapy (CRT) using an implantable, programmed biventricular pacemaker/defibrillator, can improve the synchrony of contraction between the right and left ventricles in DHF, resulting in reduced morbidity and mortality and increased quality of life. Since regional work depends on wall stress, which cannot be measured in patients, we used computational methods to investigate regional work distributions and their changes after CRT. We used three-dimensional multi-scale patient-specific computational models parameterized by anatomic, functional, hemodynamic, and electrophysiological measurements in eight patients with heart failure and left bundle branch block (LBBB) who received CRT. To increase clinical translatability, we also explored whether streamlined computational methods provide accurate estimates of regional myocardial work. We found that CRT increased global myocardial work efficiency with significant improvements in non-responders. Reverse ventricular remodeling after CRT was greatest in patients with the highest heterogeneity of regional work at baseline, however the efficacy of CRT was not related to the decrease in overall work heterogeneity or to the reduction in late-activated regions of high myocardial work. Rather, decreases in early-activated regions of myocardium performing negative myocardial work following CRT best explained patient variations in reverse remodeling. These findings were also observed when regional myocardial work was estimated using ventricular pressure as a surrogate for myocardial stress and changes in endocardial surface area as a surrogate for strain. These new findings suggest that CRT promotes reverse ventricular remodeling in human dyssynchronous heart failure by increasing regional myocardial work in early-activated regions of the ventricles, where dyssynchrony is specifically associated with hypoperfusion, late systolic stretch, and altered metabolic activity and that measurement of these changes can be performed using streamlined approaches.

DiFiR-CT: Distance field representation to resolve motion artifacts in computed tomography.

BACKGROUND: Motion during data acquisition leads to artifacts in computed tomography (CT) reconstructions. In cases such as cardiac imaging, not only is motion unavoidable, but evaluating the motion of the object is of clinical interest. Reducing motion artifacts has typically been achieved by developing systems with faster gantry rotation or via algorithms which measure and/or estimate the displacement. However, these approaches have had limited success due to both physical constraints as well as the challenge of estimating non-rigid, temporally varying, and patient-specific motion fields. PURPOSE: To develop a novel reconstruction method which generates time-resolved, artifact-free images without estimation or explicit modeling of the motion. METHODS: We describe an analysis-by-synthesis approach which progressively regresses a solution consistent with the acquired sinogram. In our method, we focus on the movement of object boundaries. Not only are the boundaries the source of image artifacts, but object boundaries can simultaneously be used to represent both the object as well as its motion over time without the need for an explicit motion model. We represent the object boundaries via a signed distance function (SDF) which can be efficiently modeled using neural networks. As a result, optimization can be performed under spatial and temporal smoothness constraints without the need for explicit motion estimation. RESULTS: We illustrate the utility of DiFiR-CT in three imaging scenarios with increasing motion complexity: translation of a small circle, heart-like change in an ellipse's diameter, and a complex topological deformation. Compared to filtered backprojection, DiFiR-CT provides high quality image reconstruction for all three motions without hyperparameter tuning or change to the architecture. We also evaluate DiFiR-CT's robustness to noise in the acquired sinogram and found its reconstruction to be accurate across a wide range of noise levels. Lastly, we demonstrate how the approach could be used for multi-intensity scenes and illustrate the importance of the initial segmentation providing a realistic initialization. Code and supplemental movies are available at https://kunalmgupta.github.io/projects/DiFiR-CT.html. CONCLUSIONS: Projection data can be used to accurately estimate a temporally-evolving scene without the need for explicit motion estimation using a neural implicit representation and analysis-by-synthesis approach.

Quantitative analysis of small coronary artery calcium detectability with an accurate simulation and validation on a clinical CT scanner.

BACKGROUND: The absence of coronary artery calcium (CAC) measured via CT is associated with very favorable prognosis, and current guidelines recommend low-density lipoprotein cholesterol (LDL-c) lowering therapy for individuals with any CAC. This motivates early detection of small granules of CAC; however, calcium scan sensitivity for detecting very low levels of calcium has not been quantified. PURPOSE: In this work, the size limit of detectability of small calcium hydroxyapatite (CaHA) granules with clinical CAC scanning was assessed using validated simulations. METHODS: CT projections of digital 3D mathematical phantoms containing small CaHA granules were simulated analytically; images were reconstructed using a filter designed to reproduce the point spread function of a specific commercial scanner, and a relationship of HU number versus diameter was derived. These simulation results were validated with experimental measurements of HU versus diameter from phantoms containing small granules of CaHA on a GE Revolution CT scanner in the clinic; ground truth measurements of the CaHA granule diameters were obtained using a Zeiss Xradia 510 Versa high-resolution 3D micro-CT imaging system. Using experimental measurements on the clinical CT scanner, detectability was quantified with a detectability index (d') using a non-prewhitened matched filter. The effect of changes to reconstruction slice thickness and reconstruction kernel on granule detectability was evaluated. RESULTS: Under typical clinical calcium scanning and reconstruction conditions, the minimum detectable diameter of a simulated spherical calcium granule with a clinically relevant CaHA density was 0.76 mm. The minimum detectable volume was 2.4 times smaller on images reconstructed at a slice thickness of 0.625 mm compared to 2.5 mm. The detectability index d' increased by a factor of 1.7 when images were reconstructed with 0.625 mm slices compared to 2.5 mm slices. d' did not change when images were reconstructed with the high-resolution BONE filter compared to the less sharp STANDARD resolution filter on the GE Revolution CT. CONCLUSIONS: We have quantified detectability versus size of small calcium granules at the resolution limit of a widely available clinical CT scanner. Detectability increased significantly with reduced slice thickness and did not change with a sharper reconstruction kernel. The simulation can be used to calculate the trade-off between dose and CAC detectability.

Myocardial Regional Shortening from 4D Cardiac CT Angiography for the Detection of Left Ventricular Segmental Wall Motion Abnormality.

Purpose: To investigate whether endocardial regional shortening computed from four-dimensional (4D) CT angiography (RSCT) can be used as a decision classifier to detect the presence of left ventricular (LV) wall motion abnormalities (WMAs). Materials and Methods: One hundred electrocardiographically gated cardiac 4D CT studies (mean age, 59 years ± 14 [SD]; 61 male patients) conducted between April 2018 and December 2020 were retrospectively evaluated. Three experts labeled LV wall motion in each of the 16 American Heart Association (AHA) segments as normal or abnormal; they also measured peak RSCT across one heartbeat in each segment. The data set was split evenly into training and validation groups. During training, interchangeability of RSCT thresholding with experts to detect WMA was assessed using the individual equivalence index (γ), and an optimal threshold of the peak RSCT (RSCT*) that achieved maximum agreement was identified. RSCT* was then validated using the validation group, and the effect of AHA segment-specific thresholds was evaluated. Agreement was assessed using κ statistics. Results: The optimal threshold, RSCT* of -0.19, when applied to all AHA segments, led to high agreement (agreement rate = 92.17%, κ = 0.82) and interchangeability with experts (γ = -2.58%). The same RSCT* also achieved high agreement in the validation group (agreement rate = 90.29%, κ = 0.76, γ = -0.38%). The use of AHA segment-specific thresholds (range: 0.16 to -0.23 across AHA segments) slightly improved agreement (1.79% increase). Conclusion: RSCT thresholding was interchangeable with expert visual analysis in detecting segmental WMA from 4D CT and may be used as an objective decision classifier.Keywords: CT, Left Ventricle, Regional Endocardial Shortening, Wall Motion Abnormality Supplemental material is available for this article. © RSNA, 2023.

Pressure Volume Loop Analysis of the Right Ventricle in Heart Failure With Computed Tomography.

Right ventricular (RV) function is an important marker of mortality in chronic left-sided heart failure. Right ventricular function is particularly important for patients receiving left ventricular assist devices as it is a predictor of postoperative RV failure. RV stroke work index (RVSWI), the area enclosed by a pressure-volume (PV) loop, is prognostic of RV failure. However, clinical RVSWI approximates RVSWI as the product of thermodilution-derived stroke volume and the pulmonary pressure gradient. This ignores the energetic contribution of regurgitant flow and does not allow for advanced energetic measures, such as pressure-volume area and efficiency. Estimating RVSWI from forward flow may underestimate the underlying RV function. We created single-beat PV loops by combining data from cine computed tomography (CT) and right heart catheterization in 44 heart failure patients, tested the approximations made by clinical RVSWI and found it to underestimate PV loop RVSWI, primarily due to regurgitant flow in tricuspid regurgitation. The ability of RVSWI to predict post-operative RV failure improved when the single-beat approach was used. Further, RV pressure-volume area and efficiency measures were obtained and show broad agreement with other functional measures. Future work is needed to investigate the utility of these PV metrics in a clinical setting.

Preoperative Computed Tomography Assessment of Risk of Right Ventricle Failure After Left Ventricular Assist Device Placement.

Identification of patients who are at a high risk for right ventricular failure (RVF) after left ventricular assist device (LVAD) implantation is of critical importance. Conventional tools for predicting RVF, including two-dimensional echocardiography, right heart catheterization (RHC), and clinical parameters, generally have limited sensitivity and specificity. We retrospectively examined the ability of computed tomography (CT) ventricular volume measures to identify patients who experienced RVF after LVAD implantation. Between September 2017 and November 2021, 92 patients underwent LVAD surgery at our institution. Preoperative CT-derived ventricular volumes were obtained in 20 patients. Patients who underwent CT evaluation had a similar demographics and rate of RVF after LVAD as patients who did not undergo cardiac CT imaging. In the study cohort, seven of 20 (35%) patients experienced RVF (2 unplanned biventricular assist device, 5 prolonged inotropic support). Computed tomography-derived right ventricular end-diastolic and end-systolic volume indices were the strongest predictors of RVF compared with demographic, echocardiographic, and RHC data with areas under the receiver operating curve of 0.79 and 0.76, respectively. Computed tomography volumetric assessment of RV size can be performed in patients evaluated for LVAD treatment. RV measures of size provide a promising means of pre-LVAD assessment for postoperative RV failure.

Mapping the Spatial Extent of Hypoperfusion in Chronic Thromboembolic Pulmonary Hypertension Using Multienergy CT.

Purpose: To assess if a novel automated method to spatially delineate and quantify the extent of hypoperfusion on multienergy CT angiograms can aid the evaluation of chronic thromboembolic pulmonary hypertension (CTEPH) disease severity. Materials and Methods: Multienergy CT angiograms obtained between January 2018 and December 2020 in 51 patients with CTEPH (mean age, 47 years ± 17 [SD]; 27 women) were retrospectively compared with those in 110 controls with no imaging findings suggestive of pulmonary vascular abnormalities (mean age, 51 years ± 16; 81 women). Parenchymal iodine values were automatically isolated using deep learning lobar lung segmentations. Low iodine concentration was used to delineate areas of hypoperfusion and calculate hypoperfused lung volume (HLV). Receiver operating characteristic curves, correlations with preoperative and postoperative changes in invasive hemodynamics, and comparison with visual assessment of lobar hypoperfusion by two expert readers were evaluated. Results: Global HLV correctly separated patients with CTEPH from controls (area under the receiver operating characteristic curve = 0.84; 10% HLV cutoff: 90% sensitivity, 72% accuracy, and 64% specificity) and correlated moderately with hemodynamic severity at time of imaging (pulmonary vascular resistance [PVR], ρ = 0.67; P < .001) and change after surgical treatment (∆PVR, ρ = -0.61; P < .001). In patients surgically classified as having segmental disease, global HLV correlated with preoperative PVR (ρ = 0.81) and postoperative ∆PVR (ρ = -0.70). Lobar HLV correlated moderately with expert reader lobar assessment (ρHLV = 0.71 for reader 1; ρHLV = 0.67 for reader 2). Conclusion: Automated quantification of hypoperfused areas in patients with CTEPH can be performed from clinical multienergy CT examinations and may aid clinical evaluation, particularly in patients with segmental-level disease.Keywords: CT-Spectral Imaging (Multienergy), Pulmonary, Pulmonary Arteries, Embolism/Thrombosis, Chronic Thromboembolic Pulmonary Hypertension, Multienergy CT, Hypoperfusion© RSNA, 2023.

Intravascularly infused extracellular matrix as a biomaterial for targeting and treating inflamed tissues.

Decellularized extracellular matrix in the form of patches and locally injected hydrogels has long been used as therapies in animal models of disease. Here we report the safety and feasibility of an intravascularly infused extracellular matrix as a biomaterial for the repair of tissue in animal models of acute myocardial infarction, traumatic brain injury and pulmonary arterial hypertension. The biomaterial consists of decellularized, enzymatically digested and fractionated ventricular myocardium, localizes to injured tissues by binding to leaky microvasculature, and is largely degraded in about 3 d. In rats and pigs with induced acute myocardial infarction followed by intracoronary infusion of the biomaterial, we observed substantially reduced left ventricular volumes and improved wall-motion scores, as well as differential expression of genes associated with tissue repair and inflammation. Delivering pro-healing extracellular matrix by intravascular infusion post injury may provide translational advantages for the healing of inflamed tissues 'from the inside out'.

In vivo chronic myocardial infarction characterization by spin locked cardiovascular magnetic resonance.

BACKGROUND: Late gadolinium enhanced (LGE) cardiovascular magnetic resonance (CMR) is frequently used to evaluate myocardial viability, estimate total infarct size and transmurality, but is not always straightforward is and contraindicated in patients with renal failure because of the risk of nephrogenic systemic fibrosis. T2- and T1-weighted CMR alone is however relatively insensitive to chronic myocardial infarction (MI) in the absence of a contrast agent. The objective of this manuscript is to explore T1ρ-weighted rotating frame CMR techniques for infarct characterization without contrast agents. We hypothesize that T1ρ CMR accurately measures infarct size in chronic MI on account of a large change in T1ρ relaxation time between scar and myocardium. METHODS: 7Yorkshire swine underwent CMR at 8 weeks post-surgical induction of apical or posterolateral myocardial infarction. Late gadolinium enhanced and T1ρ CMR were performed at high resolution to visualize MI. T1ρ-weighted imaging was performed with a B1 = 500 Hz spin lock pulse on a 3 T clinical MR scanner. Following sacrifice, the heart was excised and infarct size was calculated by optical planimetry. Infarct size was calculated for all three methods (LGE, T1ρ and planimetry) and statistical analysis was performed. T1ρ relaxation time maps were computed from multiple T1ρ-weighted images at varying spin lock duration. RESULTS: Mean infarct contrast-to-noise ratio (CNR) in LGE and T1ρ CMR was 2.8 ± 0.1 and 2.7 ± 0.1. The variation in signal intensity of tissues was found to be, in order of decreasing signal intensity, LV blood, fat and edema, infarct and healthy myocardium. Infarct size measured by T1ρ CMR (21.1% ± 1.4%) was not significantly different from LGE CMR (22.2% ± 1.5%) or planimetry (21.1% ± 2.7%; p < 0.05).T1ρ relaxation times were T1ρinfarct = 91.7 ms in the infarct and T1ρremote = 47.2 ms in the remote myocardium. CONCLUSIONS: T1ρ-weighted imaging using long spin locking pulses enables high discrimination between infarct and myocardium. T1ρ CMR may be useful to visualizing MI without the need for exogenous contrast agents for a wide range of clinical cardiac applications such as to distinguish edema and scar tissue and tissue characterization of myocarditis and ventricular fibrosis.

Right Ventricular and Pulmonary Computed Tomography Assessments in Paradoxical Low-Flow Low-Gradient Aortic Stenosis Undergoing Transcatheter Aortic Valve Replacement.

Background: Patients with paradoxical low-flow low-gradient aortic stenosis (pLFLG-AS) have high mortality and high degree of TAVR futility. Computed tomography (CT) enables accurate simultaneous right ventricular (RV) and parenchymal lung disease evaluation which may provide useful objective markers of AS severity, concomitant pulmonary comorbidities, and transcatheter aortic valve replacement (TAVR) improvement. However, the prevalence of RV dysfunction and its association with pulmonary disease in pLFLG-AS is unknown. The study objective was to test the hypothesis that pLFLG-AS patients undergoing TAVR have decreased RV function without significant parenchymal lung disease. Methods: Between August 2016 and March 2020, 194 consecutive AS patients completed high-resolution computed tomography (CT) imaging for TAVR evaluation. Subjects were stratified based on echocardiographic criteria as the study group, pLFLG (n=27), and two consecutive control groups: classic severe, normal-flow, high-gradient (n=27) and normal-flow, low-gradient (NFLG) (n=27) AS. Blinded biventricular function and lung parenchymal disease assessments were obtained by high-resolution CT imaging. Results: Patient demographics were similar between groups. pLFLG-AS had lower RV ejection fraction (49±10%) compared to both classic severe (58±7%, p<0.001) and NFLG AS (55±65%, p=0.02). There were no significant differences on lung emphysema (p=0.19), air fraction (p=0.58), and pulmonary disease presence (p=0.94) and severity (p=0.67) between groups. Conclusion: pLFLG-AS patients have lower RV ejection fraction, than classic severe and normal-flow low-gradient AS patients in the absence of significant parenchymal lung disease on CT imaging. These findings support the direct importance of RV function in the pathophysiology of aortic valve disease.

Deep learning automates detection of wall motion abnormalities via measurement of longitudinal strain from ECG-gated CT images.

Introduction: 4D cardiac CT (cineCT) is increasingly used to evaluate cardiac dynamics. While echocardiography and CMR have demonstrated the utility of longitudinal strain (LS) measures, measuring LS from cineCT currently requires reformatting the 4D dataset into long-axis imaging planes and delineating the endocardial boundary across time. In this work, we demonstrate the ability of a recently published deep learning framework to automatically and accurately measure LS for detection of wall motion abnormalities (WMA). Methods: One hundred clinical cineCT studies were evaluated by three experienced cardiac CT readers to identify whether each AHA segment had a WMA. Fifty cases were used for method development and an independent group of 50 were used for testing. A previously developed convolutional neural network was used to automatically segment the LV bloodpool and to define the 2, 3, and 4 CH long-axis imaging planes. LS was measured as the perimeter of the bloodpool for each long-axis plane. Two smoothing approaches were developed to avoid artifacts due to papillary muscle insertion and texture of the endocardial surface. The impact of the smoothing was evaluated by comparison of LS estimates to LV ejection fraction and the fractional area change of the corresponding view. Results: The automated, DL approach successfully analyzed 48/50 patients in the training cohort and 47/50 in the testing cohort. The optimal LS cutoff for identification of WMA was -21.8, -15.4, and -16.6% for the 2-, 3-, and 4-CH views in the training cohort. This led to correct labeling of 85, 85, and 83% of 2-, 3-, and 4-CH views, respectively, in the testing cohort. Per-study accuracy was 83% (84% sensitivity and 82% specificity). Smoothing significantly improved agreement between LS and fractional area change (R 2: 2 CH = 0.38 vs. 0.89 vs. 0.92). Conclusion: Automated LV blood pool segmentation and long-axis plane delineation via deep learning enables automatic LS assessment. LS values accurately identify regional wall motion abnormalities and may be used to complement standard visual assessments.