The future of valvular heart disease assessment and therapy.

Valvular heart disease (VHD) is becoming more prevalent in an ageing population, leading to challenges in diagnosis and management. This two-part Series offers a comprehensive review of changing concepts in VHD, covering diagnosis, intervention timing, novel management strategies, and the current state of research. The first paper highlights the remarkable progress made in imaging and transcatheter techniques, effectively addressing the treatment paradox wherein populations at the highest risk of VHD often receive the least treatment. These advances have attracted the attention of clinicians, researchers, engineers, device manufacturers, and investors, leading to the exploration and proposal of treatment approaches grounded in pathophysiology and multidisciplinary strategies for VHD management. This Series paper focuses on innovations involving computational, pharmacological, and bioengineering approaches that are transforming the diagnosis and management of patients with VHD. Artificial intelligence and digital methods are enhancing screening, diagnosis, and planning procedures, and the integration of imaging and clinical data is improving the classification of VHD severity. The emergence of artificial intelligence techniques, including so-called digital twins-eg, computer-generated replicas of the heart-is aiding the development of new strategies for enhanced risk stratification, prognostication, and individualised therapeutic targeting. Various new molecular targets and novel pharmacological strategies are being developed, including multiomics-ie, analytical methods used to integrate complex biological big data to find novel pathways to halt the progression of VHD. In addition, efforts have been undertaken to engineer heart valve tissue and provide a living valve conduit capable of growth and biological integration. Overall, these advances emphasise the importance of early detection, personalised management, and cutting-edge interventions to optimise outcomes amid the evolving landscape of VHD. Although several challenges must be overcome, these breakthroughs represent opportunities to advance patient-centred investigations.

Age-related changes in left ventricular vortex and energy loss patterns: from newborns to adults.

Left ventricular vortex formation optimizes the effective transport of blood volume while minimizing energy loss (EL). Vector flow mapping (VFM)-derived EL patterns have not been described in children, especially in those less than 1 yr of age. A prospective cohort of 66 (0 days-22 yr, 14 patients ≤ 2 mo) cardiovascularly normal children was used to determine left ventricular (LV) vortex number, size (mm2), strength (m2/s), and energy loss (mW/m/m2) in systole and diastole and compared across age groups. One early diastolic (ED) vortex at the anterior mitral leaflet and one late diastolic (LD) vortex at the LV outflow tract (LVOT) were seen in all newborns ≤ 2 mo. At >2 mo, two ED vortices and one LD vortex were seen, with 95% of subjects > 2 yr demonstrating this vortex pattern. Peak and average diastolic EL acutely increased in the same 2 mo-2-yr period and then decreased within the adolescent and young adult age groups. Overall, these findings suggest that the growing heart undergoes a transition to adult vortex flow patterns over the first 2 yr of life with a corresponding acute increase in diastolic EL. These findings offer an initial insight into the dynamic changes of LV flow patterns in pediatric patients and can serve to expand our understanding of cardiac efficiency and physiology in children.NEW & NOTEWORTHY This research article demonstrates, for the first time, echocardiographic evidence of a transition in left ventricular vortex patterns from the newborn to the adult period, with an associated change in cardiac efficiency, marked by increased energy loss, during infancy.

Quantitative single photon emission computed tomography derived standardized uptake values on 99mTc-PYP scan in patients with suspected ATTR cardiac amyloidosis.

Technetium-99 pyrophosphate scintigraphy (99mTc-PYP) provides qualitative and semiquantitative diagnosis of ATTR cardiac amyloidosis (ATTR-CA) using the Perugini scoring system and heart/contralateral heart ratio (H/CL) on planar imaging. Standardized uptake values (SUV) with quantitative single photon emission computed tomography (xSPECT/CT) can offer superior diagnostic accuracy and quantification through precise myocardial contouring that enhances assessment of ATTR-CA burden. We examined the correlation of xSPECT/CT SUVs with Perugini score and H/CL ratio. We also assessed SUV correlation with cardiac magnetic resonance (CMR), echocardiographic, and baseline clinical characteristics. Retrospective review of 78 patients with suspected ATTR-CA that underwent 99mTc-PYP scintigraphy with xSPECT/CT. Patients were grouped off Perugini score (Grade 0-1 and Grade 2-3), H/CL ratio (≥ 1.5 and < 1.5). Two cohorts were also created: myocardium SUVmax > 1.88 and ≤ 1.88 at 1-hour based off an AUC curve with 1.88 showing the greatest sensitivity and specificity. Cardiac SUV retention index was calculated as [SUVmax myocardium/SUVmax vertebrae] × SUVmax paraspinal muscle. Primary outcome was myocardium SUVmax at 1-hour correlation with Perugini grades, H/CL ratio, CMR, and echocardiographic data. Higher Perugini Grades corresponded with higher myocardium SUVmax values, especially when comparing Perugini Grade 3 to Grade 2 and 1 (3.03 ± 2.1 vs 0.59 ± 0.97 and 0.09 ± 0.2, P < 0.001). Additionally, patients with H/CL ≥ 1.5 had significantly higher myocardium SUVmax compared to patients with H/CL ≤ 1.5 (2.92 ± 2.18 vs 0.35 ± 0.60, P < 0.01). Myocardium SUVmax at 1-hour strongly correlated with ECV (r = 0.91, P = 0.001), pre-contrast T1 map values (r = 0.66, P = 0.037), and left ventricle mass index (r = 0.80, P = 0.002) on CMR. SUVs derived from 99mTc-PYP scintigraphy with xSPECT/CT provides a discriminatory and quantitative method to diagnose and assess ATTR-CA burden. These findings strongly correlate with CMR.

Machine Learning in Cardiovascular Imaging.

The number of cardiovascular imaging studies is growing exponentially, and so is the demand to improve the efficacy of the imaging workflow. Over the past decade, studies have demonstrated that machine learning (ML) holds promise to revolutionize cardiovascular research and clinical care. ML may improve several aspects of cardiovascular imaging, such as image acquisition, segmentation, image interpretation, diagnostics, therapy planning, and prognostication. In this review, we discuss the most promising applications of ML in cardiovascular imaging and also highlight the several challenges to its widespread implementation in clinical practice.

Development and validation of optimal phenomapping methods to estimate long-term atherosclerotic cardiovascular disease risk in patients with type 2 diabetes.

AIMS/HYPOTHESIS: Type 2 diabetes is a heterogeneous disease process with variable trajectories of CVD risk. We aimed to evaluate four phenomapping strategies and their ability to stratify CVD risk in individuals with type 2 diabetes and to identify subgroups who may benefit from specific therapies. METHODS: Participants with type 2 diabetes and free of baseline CVD in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial were included in this study (N = 6466). Clustering using Gaussian mixture models, latent class analysis, finite mixture models (FMMs) and principal component analysis was compared. Clustering variables included demographics, medical and social history, laboratory values and diabetes complications. The interaction between the phenogroup and intensive glycaemic, combination lipid and intensive BP therapy for the risk of the primary outcome (composite of fatal myocardial infarction, non-fatal myocardial infarction or unstable angina) was evaluated using adjusted Cox models. The phenomapping strategies were independently assessed in an external validation cohort (Look Action for Health in Diabetes [Look AHEAD] trial: n = 4211; and Bypass Angioplasty Revascularisation Investigation 2 Diabetes [BARI 2D] trial: n = 1495). RESULTS: Over 9.1 years of follow-up, 789 (12.2%) participants had a primary outcome event. FMM phenomapping with three phenogroups was the best-performing clustering strategy in both the derivation and validation cohorts as determined by Bayesian information criterion, Dunn index and improvement in model discrimination. Phenogroup 1 (n = 663, 10.3%) had the highest burden of comorbidities and diabetes complications, phenogroup 2 (n = 2388, 36.9%) had an intermediate comorbidity burden and lowest diabetes complications, and phenogroup 3 (n = 3415, 52.8%) had the fewest comorbidities and intermediate burden of diabetes complications. Significant interactions were observed between phenogroups and treatment interventions including intensive glycaemic control (p-interaction = 0.042) and combination lipid therapy (p-interaction < 0.001) in the ACCORD, intensive lifestyle intervention (p-interaction = 0.002) in the Look AHEAD and early coronary revascularisation (p-interaction = 0.003) in the BARI 2D trial cohorts for the risk of the primary composite outcome. Favourable reduction in the risk of the primary composite outcome with these interventions was noted in low-risk participants of phenogroup 3 but not in other phenogroups. Compared with phenogroup 3, phenogroup 1 participants were more likely to have severe/symptomatic hypoglycaemic events and medication non-adherence on follow-up in the ACCORD and Look AHEAD trial cohorts. CONCLUSIONS/INTERPRETATION: Clustering using FMMs was the optimal phenomapping strategy to identify replicable subgroups of patients with type 2 diabetes with distinct clinical characteristics, CVD risk and response to therapies.

Cardiac mechanics in heart failure with preserved ejection fraction.

Heart failure with preserved ejection fraction (HFpEF) is a complex clinical entity associated with significant morbidity and mortality. Common comorbidities including hypertension, coronary artery disease, diabetes, chronic kidney disease, obesity, and increasing age predispose to preclinical diastolic dysfunction that often progresses to frank HFpEF. Clinical HFpEF is typically associated with some degree of diastolic dysfunction, but can occur in the absence of many conventional diastolic dysfunction indices. The exact biologic links between risk factors, structural changes, and clinical manifestations are not clearly apparent. Innovative approaches including deformation imaging have enabled deeper understanding of HFpEF cardiac mechanics beyond conventional metrics. Furthermore, predictive analytics through data-driven platforms have allowed for a deeper understanding of HFpEF phenotypes. This review focuses on the changes in cardiac mechanics that occur through preclinical myocardial dysfunction to clinically apparent HFpEF.

The Role of Artificial Intelligence in Echocardiography.

PURPOSE OF REVIEW: Echocardiography is an indispensable tool in diagnostic cardiology and is fundamental to clinical care. Significant advances in cardiovascular imaging technology paralleled by rapid growth in electronic medical records, miniaturized devices, real-time monitoring, and wearable devices using body sensor network technology have led to the development of complex data. RECENT FINDINGS: The intricate nature of these data can be overwhelming and exceed the capabilities of current statistical software. Machine learning (ML), a branch of artificial intelligence (AI), can help health care providers navigate through this complex labyrinth of information and unravel hidden discoveries. Furthermore, ML algorithms can help automate several tasks in echocardiography and clinical care. ML can serve as a valuable diagnostic tool for physicians in the field of echocardiography. In addition, it can help expand the capabilities of research and discover alternative pathways in medical management. In this review article, we describe the role of AI and ML in echocardiography.

Ticagrelor after pharmacological thrombolysis in patients with ST-segment elevation myocardial infarctions: insight from a trial sequential analysis.

Few randomized controlled trials (RCTs) have compared ticagrelor to clopidogrel after thrombolytic therapy in patients with ST-segment elevation myocardial infarction (STEMI). To assess the quality of the current evidence, a trial sequential analysis (TSA) of all the available RCTs was performed. A literature search through electronic databases for relevant RCTs was completed. Trial sequential boundaries were applied to the meta-analysis to guard against statistical error, calculate the information size (IS), and assess the quality of the currently available evidence. The safety outcome was bleeding at 30-days and the efficacy outcome was major adverse cardiovascular events at 30-days. There were 3 RCTs with a total of 3999 patients were included. For the safety and efficacy outcomes, there was no difference between the ticagrelor and clopidogrel groups (RR 0.94; 95% CI 0.56-1.60, p = 0.83) and (RR 0.87; 95% CI 0.49-1.52, p = 0.62), respectively. The corresponding TSA revealed an IS of 20,928 and 37,266 for safety and efficacy outcomes, respectively. The Z-curves for both outcomes failed to cross the conventional boundary of significance and TSA boundary, indicating no statistical difference between the ticagrelor and clopidogrel group and lack of firm evidence from the currently available RCTs to draw conclusion. Based on the current available RCTs, there is not enough evidence to support or refute better outcomes with ticagrelor in patients with STEMI treated with thrombolytics. Larger RCTs with enough power are needed before firm recommendations can be applied.

Handheld Echocardiography: Current State and Future Perspectives.

Echocardiography is the primary imaging modality for diagnosing cardiac conditions. Over the past 2 decades, technological advancements have resulted in the emergence of miniaturized handheld ultrasound equipment that is compact and battery operated, and handheld echocardiography can be readily performed at the point of care with reasonable image quality. The simplicity of use, availability at the patient's bedside, easy transportability, and relatively low cost have encouraged physicians to use these devices for prompt medical decision making. As a consequence, the use of handheld echocardiography is on the rise even among nonechocardiographers (intensivists, emergency care physicians, internists, and medical students). One of the real utilities of ultrasound-augmented clinical diagnosis is in evaluating patients efficiently and selecting patients for appropriate downstream diagnostic testing including comprehensive echocardiography. Although clinical evidence supports the use of handheld devices in various clinical settings and by different users, proficiency in point-of-care ultrasound requires dedicated training in both performance and interpretation. This review summarizes the existing literature on the use of handheld echocardiography in conducting focused cardiac examinations: its training requirements, challenges, opportunities, and future perspectives in the care of the cardiovascular patient.

Advances in Echocardiographic Imaging in Heart Failure With Reduced and Preserved Ejection Fraction.

Echocardiography, given its safety, easy availability, and the ability to permit a comprehensive assessment of cardiac structure and function, is an indispensable tool in the evaluation and management of patients with heart failure (HF). From initial phenotyping and risk stratification to providing vital data for guiding therapeutic decision-making and monitoring, echocardiography plays a pivotal role in the care of HF patients. The recent advent of multiparametric approaches for myocardial deformation imaging has provided valuable insights in the pathogenesis of HF, elucidating distinct patterns of myocardial dysfunction and events that are associated with progression from subclinical stage to overt HF. At the same time, miniaturization of echocardiography has further expanded clinical application of echocardiography, with the use of pocket cardiac ultrasound as an adjunct to physical examination demonstrated to improve diagnostic accuracy and risk stratification. Furthermore, ongoing advances in the field of big data analytics promise to create an exciting opportunity to operationalize precision medicine as the new approach to healthcare delivery that aims to individualize patient care by integrating data extracted from clinical, laboratory, echocardiographic, and genetic assessments. The present review summarizes the recent advances in the field of echocardiography, with emphasis on their role in HF phenotyping, risk stratification, and optimizing clinical outcomes.

Beamforming algorithms for endocardial border detection.

BACKGROUND: Software-based beamforming which utilizes delay and standard beamforming is a signal processing technique that temporarily stores data from each probe element to improve specular reflections to improve the image resolution. We compared a software algorithm which uses delay and standard beamforming with delay and sum beamforming in standard, hardware to evaluate endocardial borders and need for echo contrast. METHODS: In this prospective study, eligible participants were ≥18 years of age referred clinically for transthoracic echocardiograms. A limited study consisting of three views (apical 4, apical 3, and apical 2 chamber) was performed with the software-based beamforming and standard platform. Number and quality of segments visualized were evaluated using a 17-segment model. Quality of segments was graded as 0 = not visualized, 1 = incompletely visualized, or 2 = completely visualized. Overall quality score for each study (0 = poor, 1 = adequate, 2 = good) was reported. The need for contrast was determined by ASE guidelines. RESULTS: A total of 101 patients (mean age 61 ± 16 years, males 52%) were enrolled. Mean number of segments visualized in apical 4- (6.28 vs 5.65, P < .001), apical 3- (6.27 vs 5.54, P < .001), and apical 2-chamber views (6.26 vs 5.72 P < .001) was higher with the software vs standard platform. The average overall score for image quality was significantly better for the software platform vs standard (1.4 vs 0.9, P =< .001). With the software platform, 23% were judged as requiring contrast as compared with 45% for the standard platform (P < .001). CONCLUSIONS: Delay and standard beamforming in software platform identified more segments with better image quality when compared to the standard high-end platform, decreasing the need for contrast usage.

Sphingosine-1-Phosphate Receptor Agonist Fingolimod Increases Myocardial Salvage and Decreases Adverse Postinfarction Left Ventricular Remodeling in a Porcine Model of Ischemia/Reperfusion.

BACKGROUND: Fingolimod, a sphingosine-1-phosphate receptor agonist, is used for the treatment of multiple sclerosis and exerts antiapoptotic properties. We hypothesized that sphingosine-1-phosphate receptor activation with fingolimod during acute myocardial infarction (MI) inhibits apoptosis, leading to increased myocardial salvage, reduced infarct size, and mitigated left ventricular (LV) remodeling in a porcine model of ischemia/reperfusion. METHODS AND RESULTS: Ischemia/reperfusion was induced in pigs by balloon occlusion of the left anterior descending artery, followed by reperfusion. Animals randomly received fingolimod or saline (control). In short-term experiments, fingolimod treatment activated the cardioprotective reperfusion injury salvage kinase and survivor activating factor enhancement pathways in the infarct border zone 24 hours after MI, leading to decreased cardiomyocyte apoptosis and reduced myocardial oxidative stress. These effects were abolished by specific inhibitors of both pathways, demonstrating that fingolimod-induced cardioprotection was mediated by reperfusion injury salvage kinase and survivor activating factor enhancement pathways. In long-term experiments, fingolimod significantly improved myocardial salvage, reduced infarct size, and improved systolic LV function measured by cardiac magnetic resonance 1 week and 1 month after MI. Importantly, fingolimod mitigated the development of adverse post-MI LV remodeling 1 month after MI. Specifically, fingolimod treatment led to a significant reduction in LV mass, LV dilatation, and neurohormonal activation, and it preserved LV geometry. Furthermore, fingolimod decreased interstitial fibrosis, cardiomyocyte hypertrophy, and chronic activation of Akt and extracellular receptor kinase 1/2 in the remote noninfarcted myocardium. CONCLUSIONS: Sphingosine-1-phosphate receptor activation with fingolimod during acute MI reduced infarct size via the reperfusion injury salvage kinase and survivor activating factor enhancement pathways, improved systolic LV function, and mitigated post-MI LV remodeling. Our data strongly support a cardioprotective role for sphingosine-1-phosphate receptor activation during MI.

New Cardiac Imaging Algorithms to Diagnose Constrictive Pericarditis Versus Restrictive Cardiomyopathy.

PURPOSE OF REVIEW: Echocardiography is the mainstay in the diagnostic evaluation of constrictive pericarditis (CP) and restrictive cardiomyopathy (RCM), but no single echocardiographic parameter is sufficiently robust to accurately distinguish between the two conditions. The present review summarizes the recent advances in echocardiography that promise to improve its diagnostic performance for this purpose. The role of other imaging modalities such as cardiac computed tomography, magnetic resonance imaging, and invasive hemodynamic assessment in the overall diagnostic approach is also discussed briefly. RECENT FINDINGS: A recent study has demonstrated improved diagnostic accuracy of echocardiography with integration of multiple conventional echocardiographic parameters in to a step-wise algorithm. Concurrently, the studies using speckle-tracking echocardiography have revealed distinct and disparate patterns of myocardial mechanical abnormalities in CP and RCM with their ability to distinguish between the two conditions. The incorporation of machine-learning algorithms into echocardiography workflow permits easy integration of the wealth of the diagnostic data available and promises to further enhance the diagnostic accuracy of echocardiography. New imaging algorithms are continuously being evolved to permit accurate distinction between CP and RCM. Further research is needed to validate the accuracy of these newer algorithms and to define their place in the overall diagnostic approach for this purpose.

Mobile technology and the digitization of healthcare.

The convergence of science and technology in our dynamic digital era has resulted in the development of innovative digital health devices that allow easy and accurate characterization in health and disease. Technological advancements and the miniaturization of diagnostic instruments to modern smartphone-connected and mobile health (mHealth) devices such as the iECG, handheld ultrasound, and lab-on-a-chip technologies have led to increasing enthusiasm for patient care with promises to decrease healthcare costs and to improve outcomes. This 'hype' for mHealth has recently intersected with the 'real world' and is providing important insights into how patients and practitioners are utilizing digital health technologies. It is also raising important questions regarding the evidence supporting widespread device use. In this state-of-the-art review, we assess the current literature of mHealth and aim to provide a framework for the advances in mHealth by understanding the various device, patient, and clinical factors as they relate to digital health from device designs and patient engagement, to clinical workflow and device regulation. We also outline new strategies for generation and analysis of mHealth data at the individual and population-based levels.

Characterization and clinical significance of right ventricular mechanics in pulmonary hypertension evaluated with cardiovascular magnetic resonance feature tracking.

BACKGROUND: Prognosis in pulmonary hypertension (PH) is related to right ventricular (RV) function. Quantification of RV mechanics may offer additive value. The objective of our study is to determine the feasibility and clinical and prognostic value of RV strain analysis by cardiovascular magnetic resonance (CMR) based feature tracking (FT) in PH. METHODS: We retrospectively enrolled 116 patients (age 52.2 ± 12 years, 73.6 % women) referred to CMR for PH evaluation who underwent right heart catheterization within 1 month. Using dedicated FT software, peak global longitudinal and circumferential RV strain and strain rates (GLS, GCS, GLSR, and GCSR, respectively) were quantified from standard cine images. Using multivariate regression analysis, we evaluated the associations of strain with a composite endpoint of death, lung transplantation, or functional class deterioration. RESULTS: RV strain analysis was feasible in 110 (95 %) patients. Patients were classified into: Group A (no PH, normal right ventricular ejection fraction [RVEF]; n = 17), Group B (PH, normal RVEF; n = 26), or Group C (PH, abnormal RVEF; n = 67). All strain and strain rate values were reduced in Group C. Furthermore, GCSR was significantly reduced in Group B (-0.92 [-1.0/-0.7]; p < 0.001) compared to Group A (-1.12 [-1.3/-0.9]; p < 0.001). After adjustment for six clinically meaningful covariates, GLS (hazard ratio 1.06; p = 0.026), GLSR (hazard ratio 2.52; p = 0.04), and GCSR (hazard ratio 4.5; p = 0.01) were independently associated with the composite endpoint. GCSR successfully discriminated patients with and without events (p = 0.01). CONCLUSIONS: Quantification of RV strain with CMR-FT is feasible in the majority of patients, correlates with disease severity, and is independently associated with poor outcomes in PH.

Severity of cardiomyopathy associated with adenine nucleotide translocator-1 deficiency correlates with mtDNA haplogroup.

Mutations of both nuclear and mitochondrial DNA (mtDNA)-encoded mitochondrial proteins can cause cardiomyopathy associated with mitochondrial dysfunction. Hence, the cardiac phenotype of nuclear DNA mitochondrial mutations might be modulated by mtDNA variation. We studied a 13-generation Mennonite pedigree with autosomal recessive myopathy and cardiomyopathy due to an SLC25A4 frameshift null mutation (c.523delC, p.Q175RfsX38), which codes for the heart-muscle isoform of the adenine nucleotide translocator-1. Ten homozygous null (adenine nucleotide translocator-1(-/-)) patients monitored over a median of 6 years had a phenotype of progressive myocardial thickening, hyperalaninemia, lactic acidosis, exercise intolerance, and persistent adrenergic activation. Electrocardiography and echocardiography with velocity vector imaging revealed abnormal contractile mechanics, myocardial repolarization abnormalities, and impaired left ventricular relaxation. End-stage heart disease was characterized by massive, symmetric, concentric cardiac hypertrophy; widespread cardiomyocyte degeneration; overabundant and structurally abnormal mitochondria; extensive subendocardial interstitial fibrosis; and marked hypertrophy of arteriolar smooth muscle. Substantial variability in the progression and severity of heart disease segregated with maternal lineage, and sequencing of mtDNA from five maternal lineages revealed two major European haplogroups, U and H. Patients with the haplogroup U mtDNAs had more rapid and severe cardiomyopathy than those with haplogroup H.

Feature Tracking-Derived Peak Systolic Strain Compared to Late Gadolinium Enhancement in Troponin-Positive Myocarditis: A Case-Control Study.

Cardiac magnetic resonance (CMR) assesses myocardial involvement in myocarditis (MYO). Current techniques are qualitative, subjective, and prone to interpretation error. Feature tracking (FT) analyzes myocardial strain using CMR and has not been examined in MYO. We hypothesize that regional left ventricular (LV) strain is abnormal in MYO. Regional strain by FT was compared to late gadolinium enhancement (LGE) and troponin leak as measures of myocardial involvement. This single-center, retrospective CMR study reviewed patients with clinical MYO and structurally normal hearts who underwent CMR at our institution. Young adults with normal cardiac anatomy, function, and absent LGE served as controls. MYO patients with documented troponin leak and normal global ejection fraction (EF > 50 %) were included in comparison. FT determined regional myocardial peak systolic strain (pkS) in longitudinal and circumferential distributions. T tests compared strain values between cases and controls. Receiver operating characteristic curves determined pkS values with highest sensitivity and specificity for concurrent troponin leak and LGE. FT was performed on 57 patients: 37 MYO and 20 controls. Twenty-eight cases with normal EF, and 20 control patients were included in final analysis. Nearly all cases with normal function demonstrated abnormal regional pkS (27/28, 96 %). Cases had significantly diminished pkS when compared to controls in all regions except the longitudinal 2C distribution. FT-derived longitudinal and circumferential pkS is sensitive and specific in identifying myocardial involvement, namely the presence of troponin leak and LGE. FT may be a useful adjunctive, objective measure of myocardial involvement in patients with MYO and normal LV function.