Cardiovascular Magnetic Resonance Myocardial Perfusion Mapping for the Assessment of Coronary Artery Disease

Pixelwise myocardial perfusion mapping is a novel cardiovascular magnetic resonance (CMR) technique enables quantitative measurement of myocardial blood flow (MBF) at a pixel level. This could improve the accuracy of detection of obstructive coronary artery disease (CAD) and may also have a role in the diagnosis and assessment of coronary microvascular dysfunction (CMD). In this thesis, I explore the use of this novel technique in cohorts of clinical patients and controls with suspected CAD or CMD. Firstly, I demonstrate that stress MBF measured using perfusion mapping is accurate for the detection of CAD using invasive fractional flow reserve (FFR) as the reference standard, and that global stress MBF can be used as a marker of CMD using invasive index of microcirculatory resistance (IMR) as the reference standard. One limitation of adenosine stress testing is the confirmation of adequate hyperaemia with lack of gold standard non-invasive marker. Here, I demonstrate that regional stress MBF can be utilised as a non-invasive marker of adequate stress response. Another limitation of stress MBF is the relatively poor performance for the detection of multivessel disease. In a cohort of patients with confirmed two- and three-vessel disease I demonstrate that perfusion mapping is superior to visual analysis for the correct identification of disease severity. Perfusion mapping provides a host of options for quantitative image analysis. I show that the most reliable method for detection of coronary disease at a patient level is the presence of reduced MBF in two adjacent myocardial segments. In summary, in this thesis I performed a series of studies investigating the clinical utilisation of CMR perfusion mapping that can be translated to clinical practice to enhance the performance of stress perfusion CMR

Automated Detection of Left Ventricle in Arterial Input Function Images for Inline Perfusion Mapping using Deep Learning: A study of 15,000 Patients

Quantification of myocardial perfusion has the potential to improve detection of regional and global flow reduction. Significant effort has been made to automate the workflow, where one essential step is the arterial input function (AIF) extraction. Since failure here invalidates quantification, high accuracy is required. For this purpose, this study presents a robust AIF detection method using the convolutional neural net (CNN) model. CNN models were trained by assembling 25,027 scans (N=12,984 patients) from three hospitals, seven scanners. A test set of 5,721 scans (N=2,805 patients) evaluated model performance. The 2D+T AIF time series was inputted into CNN. Two variations were investigated: a) Two Classes (2CS) for background and foreground (LV mask); b) Three Classes (3CS) for background, foreground LV and RV. Final model was deployed on MR scanners via the Gadgetron InlineAI. Model loading time on MR scanner was ~340ms and applying it took ~180ms. The 3CS model successfully detect LV for 99.98% of all test cases (1 failed out of 5,721 cases). The mean Dice ratio for 3CS was 0.87+/-0.08 with 92.0% of all test cases having Dice ratio >0.75, while the 2CS model gave lower Dice of 0.82+/-0.22 (P<1e-5). Extracted AIF signals using CNN were further compared to manual ground-truth for foot-time, peak-time, first-pass duration, peak value and area-under-curve. No significant differences were found for all features (P>0.2). This study proposed, validated, and deployed a robust CNN solution to detect the LV for the extraction of the AIF signal used in fully automated perfusion flow mapping. A very large data cohort was assembled and resulting models were deployed to MR scanners for fully inline AI in clinical hospitals.Comment: Accepted by Magnetic Resonance in Medicine on March 30, 202

Automated Inline Analysis of Myocardial Perfusion MRI with Deep Learning

Recent development of quantitative myocardial blood flow (MBF) mapping allows direct evaluation of absolute myocardial perfusion, by computing pixel-wise flow maps. Clinical studies suggest quantitative evaluation would be more desirable for objectivity and efficiency. Objective assessment can be further facilitated by segmenting the myocardium and automatically generating reports following the AHA model. This will free user interaction for analysis and lead to a 'one-click' solution to improve workflow. This paper proposes a deep neural network based computational workflow for inline myocardial perfusion analysis. Adenosine stress and rest perfusion scans were acquired from three hospitals. Training set included N=1,825 perfusion series from 1,034 patients. Independent test set included 200 scans from 105 patients. Data were consecutively acquired at each site. A convolution neural net (CNN) model was trained to provide segmentation for LV cavity, myocardium and right ventricular by processing incoming 2D+T perfusion Gd series. Model outputs were compared to manual ground-truth for accuracy of segmentation and flow measures derived on global and per-sector basis. The trained models were integrated onto MR scanners for effective inference. Segmentation accuracy and myocardial flow measures were compared between CNN models and manual ground-truth. The mean Dice ratio of CNN derived myocardium was 0.93 +/- 0.04. Both global flow and per-sector values showed no significant difference, compared to manual results. The AHA 16 segment model was automatically generated and reported on the MR scanner. As a result, the fully automated analysis of perfusion flow mapping was achieved. This solution was integrated on the MR scanner, enabling 'one-click' analysis and reporting of myocardial blood flow.Comment: This work has been submitted to Radiology: Artificial Intelligence for possible publicatio

Ongoing Exercise Intolerance Following COVID‐19: A Magnetic Resonance–Augmented Cardiopulmonary Exercise Test Study

Background: Ongoing exercise intolerance of unclear cause following COVID‐19 infection is well recognized but poorly understood. We investigated exercise capacity in patients previously hospitalized with COVID‐19 with and without self‐reported exercise intolerance using magnetic resonance–augmented cardiopulmonary exercise testing. / Methods and Results: Sixty subjects were enrolled in this single‐center prospective observational case‐control study, split into 3 equally sized groups: 2 groups of age‐, sex‐, and comorbidity‐matched previously hospitalized patients following COVID‐19 without clearly identifiable postviral complications and with either self‐reported reduced (COVIDreduced) or fully recovered (COVIDnormal) exercise capacity; a group of age‐ and sex‐matched healthy controls. The COVIDreducedgroup had the lowest peak workload (79W [Interquartile range (IQR), 65–100] versus controls 104W [IQR, 86–148]; P=0.01) and shortest exercise duration (13.3±2.8 minutes versus controls 16.6±3.5 minutes; P=0.008), with no differences in these parameters between COVIDnormal patients and controls. The COVIDreduced group had: (1) the lowest peak indexed oxygen uptake (14.9 mL/minper kg [IQR, 13.1–16.2]) versus controls (22.3 mL/min per kg [IQR, 16.9–27.6]; P=0.003) and COVIDnormal patients (19.1 mL/min per kg [IQR, 15.4–23.7]; P=0.04); (2) the lowest peak indexed cardiac output (4.7±1.2 L/min per m2) versus controls (6.0±1.2 L/min per m2; P=0.004) and COVIDnormal patients (5.7±1.5 L/min per m2; P=0.02), associated with lower indexed stroke volume (SVi:COVIDreduced 39±10 mL/min per m2 versus COVIDnormal 43±7 mL/min per m2 versus controls 48±10 mL/min per m2; P=0.02). There were no differences in peak tissue oxygen extraction or biventricular ejection fractions between groups. There were no associations between COVID‐19 illness severity and peak magnetic resonance–augmented cardiopulmonary exercise testing metrics. Peak indexed oxygen uptake, indexed cardiac output, and indexed stroke volume all correlated with duration from discharge to magnetic resonance–augmented cardiopulmonary exercise testing (P<0.05). / Conclusions: Magnetic resonance–augmented cardiopulmonary exercise testing suggests failure to augment stroke volume as a potential mechanism of exercise intolerance in previously hospitalized patients with COVID‐19. This is unrelated to disease severity and, reassuringly, improves with time from acute illness

Multi-Imaging Characterization of Cardiac Phenotype in Different Types of Amyloidosis

BACKGROUND: Bone scintigraphy is extremely valuable when assessing patients with suspected cardiac amyloidosis (CA), but the clinical significance and associated phenotype of different degrees of cardiac uptake across different types is yet to be defined. OBJECTIVES: This study sought to define the phenotypes of patients with varying degrees of cardiac uptake on bone scintigraphy, across multiple types of systemic amyloidosis, using extensive characterization comprising biomarkers as well as echocardiographic and cardiac magnetic resonance (CMR) imaging. METHODS: A total of 296 patients (117 with immunoglobulin light-chain amyloidosis [AL], 165 with transthyretin (TTR) amyloidosis [ATTR], 7 with apolipoprotein AI amyloidosis [AApoAI], and 7 with apolipoprotein AIV amyloidosis [AApoAIV]) underwent deep characterization of their cardiac phenotype. RESULTS: AL patients with grade 0 myocardial radiotracer uptake spanned the spectrum of CMR findings from no CA to characteristic CA, whereas AL patients with grades 1 to 3 always produced characteristic CMR features. In ATTR, the CA burden strongly correlated with myocardial tracer uptake, except in Ser77Tyr. AApoAI presented with grade 0 or 1 and disproportionate right-sided involvement. AApoAIV always presented with grade 0 and characteristic CA. AL grade 1 patients (n = 48; 100%) had characteristic CA, whereas only ATTR grade 1 patients with Ser77Tyr had characteristic CA on CMR (n = 5; 11.4%). After exclusion of Ser77Tyr, AApoAI, and AApoAIV, CMR showing characteristic CA or an extracellular volume of >0.40 in patients with grade 0 to 1 cardiac uptake had a sensitivity and specificity of 100% for AL. CONCLUSIONS: There is a wide variation in cardiac phenotype between different amyloidosis types across different degrees of cardiac uptake. The combination of CMR and bone scintigraphy can help to define the diagnostic differentials and the clinical phenotype in each individual patient

Tracking Treatment Response in Cardiac Light-Chain Amyloidosis With Native T1 Mapping

IMPORTANCE: Cardiac magnetic resonance (CMR) imaging-derived extracellular volume (ECV) mapping, generated from precontrast and postcontrast T1, accurately determines treatment response in cardiac light-chain amyloidosis. Native T1 mapping, which can be derived without the need for contrast, has demonstrated accuracy in diagnosis and prognostication, but it is unclear whether serial native T1 measurements could also track the cardiac treatment response. OBJECTIVE: To assess whether native T1 mapping can measure the cardiac treatment response and the association between changes in native T1 and prognosis. DESIGN, SETTING, AND PARTICIPANTS: This single-center cohort study evaluated patients diagnosed with cardiac light-chain amyloidosis (January 2016 to December 2020) who underwent CMR scans at diagnosis and a repeat scan following chemotherapy. Analysis took place between January 2016 and October 2022. MAIN OUTCOMES AND MEASURES: Comparison of biomarkers and cardiac imaging parameters between patients with a reduced, stable, or increased native T1 and association between changes in native T1 and mortality. RESULTS: The study comprised 221 patients (mean [SD] age, 64.7 [10.6] years; 130 male [59%]). At 6 months, 183 patients (mean [SD] age, 64.8 [10.5] years; 110 male [60%]) underwent repeat CMR imaging. Reduced native T1 of 50 milliseconds or more occurred in 8 patients (4%), all of whom had a good hematological response; by contrast, an increased native T1 of 50 milliseconds or more occurred in 42 patients (23%), most of whom had a poor hematological response (27 [68%]). At 12 months, 160 patients (mean [SD] age, 63.8 [11.1] years; 94 male [59%]) had a repeat CMR scan. A reduced native T1 occurred in 24 patients (15%), all of whom had a good hematological response, and was associated with a reduction in N-terminal pro-brain natriuretic peptide (median [IQR], 2638 [913-5767] vs 423 [128-1777] ng/L; P < .001), maximal wall thickness (mean [SD], 14.8 [3.6] vs 13.6 [3.9] mm; P = .009), and E/e' (mean [SD], 14.9 [6.8] vs 12.0 [4.0]; P = .007), improved longitudinal strain (mean [SD], -14.8% [4.0%] vs -16.7% [4.0%]; P = .004), and reduction in both myocardial T2 (mean [SD], 52.3 [2.9] vs 49.4 [2.0] milliseconds; P < .001) and ECV (mean [SD], 0.47 [0.07] vs 0.42 [0.08]; P < .001). At 12 months, an increased native T1 occurred in 24 patients (15%), most of whom had a poor hematological response (17 [71%]), and was associated with an increased N-terminal pro-brain natriuretic peptide (median [IQR], 1622 [554-5487] vs 3150 [1161-8745] ng/L; P = .007), reduced left ventricular ejection fraction (mean [SD], 65.8% [11.4%] vs 61.5% [12.4%]; P = .009), and an increase in both myocardial T2 (mean [SD], 52.5 [2.7] vs 55.3 [4.2] milliseconds; P < .001) and ECV (mean [SD], 0.48 [0.09] vs 0.56 [0.09]; P < .001). Change in myocardial native T1 at 6 months was independently associated with mortality (hazard ratio, 2.41 [95% CI, 1.36-4.27]; P = .003). CONCLUSIONS AND RELEVANCE: Changes in native T1 in response to treatment, reflecting a composite of changes in T2 and ECV, are associated with in changes in traditional markers of cardiac response and associated with mortality. However, as a single-center study, these results require external validation in a larger cohort

Tracking Multiorgan Treatment Response in Systemic AL-Amyloidosis With Cardiac Magnetic Resonance Derived Extracellular Volume Mapping

Background: Systemic light chain amyloidosis is a multisystem disorder that commonly involves the heart, liver, and spleen. Cardiac magnetic resonance with extracellular volume (ECV) mapping provides a surrogate measure of the myocardial, liver, and spleen amyloid burden. Objectives: The purpose of this study was to assess multiorgan response to treatment using ECV mapping, and assess the association between multiorgan treatment response and prognosis. Methods: The authors identified 351 patients who underwent baseline serum amyloid-P-component (SAP) scintigraphy and cardiac magnetic resonance at diagnosis, of which 171 had follow-up imaging. Results: At diagnosis, ECV mapping demonstrated that 304 (87%) had cardiac involvement, 114 (33%) significant hepatic involvement, and 147 (42%) significant splenic involvement. Baseline myocardial and liver ECV independently predict mortality (myocardial HR: 1.03 [95% CI: 1.01-1.06]; P = 0.009; liver HR: 1.03; [95% CI: 1.01-1.05]; P = 0.001). Liver and spleen ECV correlated with amyloid load assessed by SAP scintigraphy (R = 0.751; P < 0.001; R = 0.765; P < 0.001, respectively). Serial measurements demonstrated ECV correctly identified changes in liver and spleen amyloid load derived from SAP scintigraphy in 85% and 82% of cases, respectively. At 6 months, more patients with a good hematologic response had liver (30%) and spleen (36%) ECV regression than myocardial regression (5%). By 12 months, more patients with a good response demonstrated myocardial regression (heart 32%, liver 30%, spleen 36%). Myocardial regression was associated with reduced median N-terminal pro-brain natriuretic peptide (P < 0.001), and liver regression with reduced median alkaline phosphatase (P = 0.001). Changes in myocardial and liver ECV, 6 months after initiating chemotherapy, independently predict mortality (myocardial HR: 1.11 [95% CI: 1.02-1.20]; P = 0.011; liver HR: 1.07 [95% CI: 1.01-1.13]; P = 0.014). Conclusions: Multiorgan ECV quantification accurately tracks treatment response and demonstrates different rates of organ regression, with the liver and spleen regressing more rapidly than the heart. Baseline myocardial and liver ECV and changes at 6 months independently predict mortality, even after adjusting for traditional predictors of prognosis

Distinct cardiovascular phenotypes are associated with prognosis in systemic sclerosis: a cardiovascular magnetic resonance study

AIMS: Cardiovascular involvement in systemic sclerosis (SSc) is heterogeneous and ill-defined. This study aimed to: (i) discover cardiac phenotypes in SSc by cardiovascular magnetic resonance (CMR); (ii) provide a CMR-based algorithm for phenotypic classification; and (iii) examine for associations between phenotypes and mortality. METHODS AND RESULTS: A retrospective, single-centre, observational study of 260 SSc patients who underwent clinically indicated CMR including native myocardial T1 and T2 mapping from 2016 to 2019 was performed. Agglomerative hierarchical clustering using only CMR variables revealed five clusters of SSc patients with shared CMR characteristics: dilated right hearts with right ventricular failure (RVF); biventricular failure dilatation and dysfunction (BVF); and normal function with average cavity (NF-AC), normal function with small cavity (NF-SC), and normal function with large cavity (NF-LC) sizes. Phenotypes did not co-segregate with clinical or antibody classifications. A CMR-based decision tree for phenotype classification was created. Sixty-three (24%) patients died during a median follow-up period of 3.4 years. After adjustment for age and presence of pulmonary hypertension (PH), independent CMR predictors of all-cause mortality were native T1 (P  0.14). Hazard ratios (HR) were statistically significant for RVF (HR = 8.9, P < 0.001), BVF (HR = 5.2, P = 0.006), and NF-LC (HR = 4.9, P = 0.002) groups. The NF-LC group remained significantly predictive of mortality after adjusting for RVEF, native T1, and PH diagnosis (P = 0.0046). CONCLUSION: We identified five CMR-defined cardiac SSc phenotypes that did not co-segregate with clinical data and had distinct outcomes, offering opportunities for a more precision-medicine based management approach

Sex differences among patients with transthyretin amyloid cardiomyopathy – from diagnosis to prognosis

Aims: transthyretin amyloid cardiomyopathy (ATTR-CM) is predominantly diagnosed in men. The few available studies suggest affected women have a more favourable cardiac phenotype. We aimed to characterize sex differences among consecutive patients with non-hereditary and two prevalent forms of hereditary (h)ATTR-CM diagnosed over a 20-year period. Methods and results: analysis of deep phenotyping at presentation, changes on serial echocardiography and overall prognosis were evaluated. In total, 1732 consecutive patients were studied, comprising: 1095 with wild-type (wt)ATTR-CM; 206 with T60A-hATTR-CM; and 431 with V122I-hATTR-CM. Female prevalence was greater in T60A-hATTR-CM (29.6%) and V122I-hATTR-CM (27.8%) compared to wtATTR-CM (6%). At presentation, females were 3.3 years older than males (wtATTR-CM: 81.9 vs. 77.8 years; T60A-hATTR-CM: 68.7 vs. 65.1 years; V122I-hATTR-CM: 77.1 vs. 74.9 years). Body size significantly influenced measures of disease severity; when indexed, overall structural and functional phenotype was similar between sexes, the few significant differences suggested a mildly worse phenotype in females. No significant differences were observed in both disease progression on serial echocardiography and mortality across the overall population (p = 0.459) and when divided by genotype (wtATTR-CM: p = 0.730; T60A-hATTR-CM: p = 0.161; V122I-hATTR-CM: p = 0.056). Conclusion: this study of a well-characterized large cohort of ATTR-CM patients did not demonstrate overall differences between sexes in either clinical phenotype, when indexed, or with respect to disease progression and prognosis. Non-indexed wall thickness measurements may have contributed to both under-representation and delays in diagnosis for affected females and highlights the potential role of utilizing indexed echocardiographic parameters for a more accurate assessment of patients at diagnosis and for disease prognostication

Impact of Earlier Diagnosis in Cardiac ATTR Amyloidosis Over the Course of 20 Years

Diagnostic and therapeutic advances have led to much greater awareness of transthyretin cardiac amyloidosis (ATTR-CA). We aimed to characterize changes in the clinical phenotype of patients diagnosed with ATTR-CA over the past 20 years