AI-AIF: artificial intelligence-based arterial input function for quantitative stress perfusion cardiac magnetic resonance

Aims:One of the major challenges in the quantification of myocardial blood flow (MBF) from stress perfusion cardiac magnetic resonance (CMR) is the estimation of the arterial input function (AIF). This is due to the non-linear relationship between the concentration of gadolinium and the MR signal, which leads to signal saturation. In this work, we show that a deep learning model can be trained to predict the unsaturated AIF from standard images, using the reference dual-sequence acquisition AIFs (DS-AIFs) for training.Methods and results:A 1D U-Net was trained, to take the saturated AIF from the standard images as input and predict the unsaturated AIF, using the data from 201 patients from centre 1 and a test set comprised of both an independent cohort of consecutive patients from centre 1 and an external cohort of patients from centre 2 (n = 44). Fully-automated MBF was compared between the DS-AIF and AI-AIF methods using the Mann–Whitney U test and Bland–Altman analysis. There was no statistical difference between the MBF quantified with the DS-AIF [2.77 mL/min/g (1.08)] and predicted with the AI-AIF (2.79 mL/min/g (1.08), P = 0.33. Bland–Altman analysis shows minimal bias between the DS-AIF and AI-AIF methods for quantitative MBF (bias of −0.11 mL/min/g). Additionally, the MBF diagnosis classification of the AI-AIF matched the DS-AIF in 669/704 (95%) of myocardial segments.Conclusion:Quantification of stress perfusion CMR is feasible with a single-sequence acquisition and a single contrast injection using an AI-based correction of the AIF

Cardiac q-space trajectory imaging by motion-compensated tensor-valued diffusion encoding in human heart in vivo

PURPOSE: Tensor-valued diffusion encoding can probe more specific features of tissue microstructure than what is available by conventional diffusion weighting. In this work, we investigate the technical feasibility of tensor-valued diffusion encoding at high b-values with q-space trajectory imaging (QTI) analysis, in the human heart in vivo. METHODS: Ten healthy volunteers were scanned on a 3T scanner. We designed time-optimal gradient waveforms for tensor-valued diffusion encoding (linear and planar) with second-order motion compensation. Data were analyzed with QTI. Normal values and repeatability were investigated for the mean diffusivity (MD), fractional anisotropy (FA), microscopic FA (μFA), isotropic, anisotropic and total mean kurtosis (MKi, MKa, and MKt), and orientation coherence (Cc ). A phantom, consisting of two fiber blocks at adjustable angles, was used to evaluate sensitivity of parameters to orientation dispersion and diffusion time. RESULTS: QTI data in the left ventricular myocardium were MD = 1.62 ± 0.07 μm2 /ms, FA = 0.31 ± 0.03, μFA = 0.43 ± 0.07, MKa = 0.20 ± 0.07, MKi = 0.13 ± 0.03, MKt = 0.33 ± 0.09, and Cc  = 0.56 ± 0.22 (mean ± SD across subjects). Phantom experiments showed that FA depends on orientation dispersion, whereas μFA was insensitive to this effect. CONCLUSION: We demonstrated the first tensor-valued diffusion encoding and QTI analysis in the heart in vivo, along with first measurements of myocardial μFA, MKi, MKa, and Cc . The methodology is technically feasible and provides promising novel biomarkers for myocardial tissue characterization

Cardiac q-space trajectory imaging by motion-compensated tensor-valued diffusion encoding in human heart in vivo

Purpose: Tensor-valued diffusion encoding can probe more specific features of tissue microstructure than what is available by conventional diffusion weighting. In this work, we investigate the technical feasibility of tensor-valued diffusion encoding at high b-values with q-space trajectory imaging (QTI) analysis, in the human heart in vivo. Methods: Ten healthy volunteers were scanned on a 3T scanner. We designed time-optimal gradient waveforms for tensor-valued diffusion encoding (linear and planar) with second-order motion compensation. Data were analyzed with QTI. Normal values and repeatability were investigated for the mean diffusivity (MD), fractional anisotropy (FA), microscopic FA (μFA), isotropic, anisotropic and total mean kurtosis (MKi, MKa, and MKt), and orientation coherence (Cc). A phantom, consisting of two fiber blocks at adjustable angles, was used to evaluate sensitivity of parameters to orientation dispersion and diffusion time. Results: QTI data in the left ventricular myocardium were MD = 1.62 ± 0.07 μm2/ms, FA = 0.31 ± 0.03, μFA = 0.43 ± 0.07, MKa = 0.20 ± 0.07, MKi = 0.13 ± 0.03, MKt = 0.33 ± 0.09, and Cc = 0.56 ± 0.22 (mean ± SD across subjects). Phantom experiments showed that FA depends on orientation dispersion, whereas μFA was insensitive to this effect. Conclusion: We demonstrated the first tensor-valued diffusion encoding and QTI analysis in the heart in vivo, along with first measurements of myocardial μFA, MKi, MKa, and Cc. The methodology is technically feasible and provides promising novel biomarkers for myocardial tissue characterization.</p

Pathophysiology of LV Remodeling Following STEMI: A Longitudinal Diffusion Tensor CMR Study

Background: Adverse LV remodeling post–ST-segment elevation myocardial infarction (STEMI) is associated with a poor prognosis, but the underlying mechanisms are not fully understood. Diffusion tensor (DT)-cardiac magnetic resonance (CMR) allows in vivo characterization of myocardial architecture and provides unique mechanistic insight into pathophysiologic changes following myocardial infarction. Objectives: This study evaluated the potential associations between DT-CMR performed soon after STEMI and long-term adverse left ventricular (LV) remodeling following STEMI. Methods: A total of 100 patients with STEMI underwent CMR at 5 days and 12 months post-reperfusion. The protocol included DT-CMR for assessing fractional anisotropy (FA), secondary eigenvector angle (E2A) and helix angle (HA), cine imaging for assessing LV volumes, and late gadolinium enhancement for calculating infarct and microvascular obstruction size. Adverse remodeling was defined as a 20% increase in LV end-diastolic volume at 12 months. Results: A total of 32 patients experienced adverse remodeling at 12 months. Compared with patients without adverse remodeling, they had lower FA (0.23 ± 0.03 vs 0.27 ± 0.04; P < 0.001), lower E2A (37 ± 6° vs 51 ± 7°; P < 0.001), and, on HA maps, a lower proportion of myocytes with right-handed orientation (RHM) (8% ± 5% vs 17% ± 9%; P < 0.001) in their acutely infarcted myocardium. On multivariable logistic regression analysis, infarct FA (odds ratio [OR]: <0.01; P = 0.014) and E2A (OR: 0.77; P = 0.001) were independent predictors of adverse LV remodeling after adjusting for left ventricular ejection fraction (LVEF) and infarct size. There were no significant changes in infarct FA, E2A, or RHM between the 2 scans. Conclusions: Extensive cardiomyocyte disorganization (evidenced by low FA), acute loss of sheetlet angularity (evidenced by low E2A), and a greater loss of organization among cardiomyocytes with RHM, corresponding to the subendocardium, can be detected within 5 days post-STEMI. These changes persist post-injury, and low FA and E2A are independently associated with long-term adverse remodeling.ISSN:1936-878XISSN:1876-759

The relationship between myocardial microstructure and strain in chronic infarction using cardiovascular magnetic resonance diffusion tensor imaging and feature tracking

Background: Cardiac diffusion tensor imaging (cDTI) using cardiovascular magnetic resonance (CMR) is a novel technique for the non-invasive assessment of myocardial microstructure. Previous studies have shown myocardial infarction to result in loss of sheetlet angularity, derived by reduced secondary eigenvector (E2A) and reduction in subendocardial cardiomyocytes, evidenced by loss of myocytes with right-handed orientation (RHM) on helix angle (HA) maps. Myocardial strain assessed using feature tracking-CMR (FT-CMR) is a sensitive marker of sub-clinical myocardial dysfunction. We sought to explore the relationship between these two techniques (strain and cDTI) in patients at 3 months following ST-elevation MI (STEMI). Methods: 32 patients (F = 28, 60 ± 10 years) underwent 3T CMR three months after STEMI (mean interval 105 ± 17 days) with second order motion compensated (M2), free-breathing spin echo cDTI, cine gradient echo and late gadolinium enhancement (LGE) imaging. HA maps divided into left-handed HA (LHM, − 90 < HA < − 30), circumferential HA (CM, − 30° < HA < 30°), and right-handed HA (RHM, 30° < HA < 90°) were reported as relative proportions. Global and segmental analysis was undertaken. Results: Mean left ventricular ejection fraction (LVEF) was 44 ± 10% with a mean infarct size of 18 ± 12 g and a mean infarct segment LGE enhancement of 66 ± 21%. Mean global radial strain was 19 ± 6, mean global circumferential strain was − 13 ± − 3 and mean global longitudinal strain was − 10 ± − 3. Global and segmental radial strain correlated significantly with E2A in infarcted segments (p = 0.002, p = 0.011). Both global and segmental longitudinal strain correlated with RHM of infarcted segments on HA maps (p < 0.001, p = 0.003). Mean Diffusivity (MD) correlated significantly with the global infarct size (p < 0.008). When patients were categorised according to LVEF (reduced, mid-range and preserved), all cDTI parameters differed significantly between the three groups. Conclusion: Change in sheetlet orientation assessed using E2A from cDTI correlates with impaired radial strain. Segments with fewer subendocardial cardiomyocytes, evidenced by a lower proportion of myocytes with right-handed orientation on HA maps, show impaired longitudinal strain. Infarct segment enhancement correlates significantly with E2A and RHM. Our data has demonstrated a link between myocardial microstructure and contractility following myocardial infarction, suggesting a potential role for CMR cDTI to clinically relevant functional impact.ISSN:1097-6647ISSN:1532-429

Cardiac q-space trajectory imaging by motion-compensated tensor-valued diffusion encoding in human heart in vivo

Purpose: Tensor-valued diffusion encoding can probe more specific features of tissue microstructure than what is available by conventional diffusion weighting. In this work, we investigate the technical feasibility of tensor-valued diffusion encoding at high b-values with q-space trajectory imaging (QTI) analysis, in the human heart in vivo. Methods: Ten healthy volunteers were scanned on a 3T scanner. We designed time-optimal gradient waveforms for tensor-valued diffusion encoding (linear and planar) with second-order motion compensation. Data were analyzed with QTI. Normal values and repeatability were investigated for the mean diffusivity (MD), fractional anisotropy (FA), microscopic FA (μFA), isotropic, anisotropic and total mean kurtosis (MKi, MKa, and MKt), and orientation coherence (Cc). A phantom, consisting of two fiber blocks at adjustable angles, was used to evaluate sensitivity of parameters to orientation dispersion and diffusion time. Results: QTI data in the left ventricular myocardium were MD = 1.62 ± 0.07 μm2/ms, FA = 0.31 ± 0.03, μFA = 0.43 ± 0.07, MKa = 0.20 ± 0.07, MKi = 0.13 ± 0.03, MKt = 0.33 ± 0.09, and Cc = 0.56 ± 0.22 (mean ± SD across subjects). Phantom experiments showed that FA depends on orientation dispersion, whereas μFA was insensitive to this effect. Conclusion: We demonstrated the first tensor-valued diffusion encoding and QTI analysis in the heart in vivo, along with first measurements of myocardial μFA, MKi, MKa, and Cc. The methodology is technically feasible and provides promising novel biomarkers for myocardial tissue characterization

Cardiovascular magnetic resonance imaging and spectroscopy in clinical long-COVID-19 syndrome: a prospective case–control study

Background The underlying pathophysiology of post-coronavirus disease 2019 (long-COVID-19) syndrome remains unknown, but increased cardiometabolic demand and state of mitochondrial dysfunction have emerged as candidate mechanisms. Cardiovascular magnetic resonance (CMR) provides insight into pathophysiological mechanisms underlying cardiovascular disease and 31-phosphorus CMR spectroscopy (31P-CMRS) allows non-invasive assessment of the myocardial energetic state. The main aim of the study was to assess whether long COVID-19 syndrome is associated with abnormalities of myocardial structure, function, perfusion and energy metabolism. Methods Prospective case–control study. A total of 20 patients with a clinical diagnosis of long COVID-19 syndrome (seropositive) and no prior underlying cardiovascular disease (CVD) and 10 matching healthy controls underwent 31P-CMRS and CMR at 3T at a single time point. All patients had been symptomatic with acute COVID-19, but none required hospital admission. Results Between the long COVID-19 syndrome patients and matched contemporary healthy controls there were no differences in myocardial energetics (phosphocreatine to ATP ratio), in cardiac structure (biventricular volumes), function (biventricular ejection fractions, global longitudinal strain), tissue characterization (T1 mapping and late gadolinium enhancement) or perfusion (myocardial rest and stress blood flow, myocardial perfusion reserve). One patient with long COVID-19 syndrome showed subepicardial hyperenhancement on late gadolinium enhancement imaging compatible with prior myocarditis, but no accompanying abnormality in cardiac size, function, perfusion, extracellular volume fraction, native T1, T2 or cardiac energetics. Conclusions In this prospective case–control study, the overwhelming majority of patients with a clinical long COVID-19 syndrome with no prior CVD did not exhibit any abnormalities in myocardial energetics, structure, function, blood flow or tissue characteristics