Takotsubo Cardiomyopathy Mimicking Obstructive Hypertrophic Cardiomyopathy.

Takotsubo cardiomyopathy (TCM) is characterized by transient left ventricular dysfunction, diagnosed via echocardiography or left ventriculography. In most cases, TCM involves an emotional, physical, or combined trigger. Acute coronary syndrome is one of the most frequent misdiagnoses in TCM patients due to electrocardiogram (ECG) abnormalities and elevated cardiac biomarkers. Typically, coronary angiography reveals no stenosis or occlusion of the coronary arteries. Hypertrophic cardiomyopathy (HCM) is a distinct pathology characterized by a hypertrophied left ventricle with various phenotypes. However, some reports have described TCM cases mimicking obstructive-type HCM in some patients. We present a case of a female patient diagnosed with TCM based on clinical, laboratory, and imaging tests. Differentiating TCM from HCM was challenging due to ventriculography and echocardiography findings, as hyperdynamic contraction of the basal segments of the left ventricle caused an increased left ventricular outflow tract (LVOT) gradient and severe mitral valve regurgitation. Detailed evaluation and close echocardiographic follow-up are essential in such rare cases.

Measurements of the Interventricular Septum and Mitral Leaflet Length in Hypertrophic Cardiomyopathy Patients Who Underwent Surgical Myectomy: A Prospective Comparative Multimodality Imaging Study.

Transesophageal echocardiography (TEE) plays an important role for real-time procedural guidance during surgical smyectomy (SM) for hypertrophic obstructive cardiomyopathy (HOCM). We aimed to compare (1) interventricular septum (IVS) thickness using 2- (2D) and 3-dimensional (3D) intraoperative TEE and preoperative cardiac magnetic resonance (CMR) and (2) mitral valve (MV) leaflet length using 2D, 3D TEE, automatic quantification of mitral valve (AMVQ) and preoperative CMR. We prospectively studied 50 patients with HOCM (age 59 ± 12 years, 44% men) who underwent SM during 2018 to 2019. The maximal basal, mid, and distal anteroseptum (AS) and inferoseptum (IS) were measured by multiplanar 3D reconstruction on TEE and by short-axis imaging on preoperative CMR and classified as mild (≤18 mm), moderate (18 to 25 mm), or severe (≥25 mm) groups based on AS and IS thickness on CMR. MV leaflet lengths were evaluated by preoperative CMR and intraprocedural 2D TEE, zoom 3D TEE, and AMVQ (EchoPAC, General Electric, Wisconsin). There was a moderate correlation between AS and IS thickness on 3D TEE and CMR (R2 = 0.46, p <0.01 and R2 = 0.41, p <0.01, respectively), with 3D TEE showing an average overestimation of 3.8 and 4.7 mm versus CMR. The 3D TEE overestimated 14 patients (56%) with mild thickness as moderate and 5 patients (22%) with moderate thickness as severe. Assuming 3D TEE as the gold standard, the closest correlation for anterior mitral leaflet length was with CMR (average overestimation by CMR of 0.5 mm [root mean square deviation (RMSE%) 17]), intermediate correlation with 2D TEE (average deviation of 0.6 mm [RMSE% 21]) and no correlation with AMVQ (average deviation of 0.7 mm [RMSE% 24]). In conclusion, 3D TEE overestimates IVS thickness versus CMR in patients with HOCM who underwent SM, with greater discrepancy in those with thinner IVS. There are significant differences in MV lengths measured using different imaging techniques.

Echocardiographic Strain Abnormalities Precede Left Ventricular Hypertrophy Development in Hypertrophic Cardiomyopathy Mutation Carriers.

Hypertrophic cardiomyopathy (HCM) is a genetic disease characterized by unexplained left ventricular hypertrophy (LVH), diastolic dysfunction, and increased sudden-death risk. Early detection of the phenotypic expression of the disease in genetic carriers without LVH (Gen+/Phen-) is crucial for emerging therapies. This clinical study aims to identify echocardiographic predictors of phenotypic development in Gen+/Phen-. Sixteen Gen+/Phen- (one subject with troponin T, six with myosin heavy chain-7, and nine with myosin-binding protein C3 mutations), represented the study population. At first and last visit we performed comprehensive 2D speckle-tracking strain echocardiography. During a follow-up of 8 ± 5 years, five carriers developed LVH (LVH+). At baseline, these patients were older than those who did not develop LVH (LVH-) (30 ± 8 vs. 15 ± 8 years, p = 0.005). LVH+ had reduced peak global strain rate during the isovolumic relaxation period (SRIVR) (0.28 ± 0.05 vs. 0.40 ± 0.11 1/s, p = 0.048) and lower global longitudinal strain (GLS) (-19.8 ± 0.4 vs. -22.3 ± 1.1%; p < 0.0001) than LVH- at baseline. SRIVR and GLS were not correlated with age (overall, p > 0.08). This is the first HCM study investigating subjects before they manifest clinically significant or relevant disease burden or symptomatology, comparing at baseline HCM Gen+/Phen- subjects who will develop LVH with those who will not. Furthermore, we identified highly sensitive, easily obtainable, age- and load-independent echocardiographic predictors of phenotype development in HCM gene carriers who may undergo early preventive treatment.

The impact of diabetes mellitus on cardiac function assessed by magnetic resonance imaging in patients with hypertrophic cardiomyopathy.

BACKGROUND: The adverse prognostic impact of diabetes on hypertrophic cardiomyopathy (HCM) is poorly understood. We sought to explore the underlying mechanisms in terms of structural and functional remodelling in HCM patients with coexisting diabetes (HCM-DM). METHODS: A total of 45 HCM-DM patients were retrospectively included. Isolated HCM controls (HCM patients without diabetes) were matched to HCM-DM patients in terms of maximal wall thickness, age, and gender distribution. Left ventricular (LV) and atrial (LA) performance were evaluated using cardiac magnetic resonance feature tracking strain analyses. The associations between diabetes and LV/LA impairment were investigated by univariable and multivariable linear regression. RESULTS: Compared with the isolated HCM controls, the HCM-DM patients had smaller end-diastolic volume and stroke volume, lower ejection fraction, larger mass/volume ratio and impaired strains in all three directions (all P < 0.05). In terms of the LA parameters, HCM-DM patients presented impaired LA reservoir and conduit strain/strain rate (all P < 0.05). Among all HCM patients, comorbidity with diabetes was independently associated with a low LV ejection fraction (ß = - 6.05, P < 0.001) and impaired global longitudinal strain (ß = 1.40, P = 0.007). Moreover, compared with the isolated HCM controls, HCM-DM patients presented with more myocardial fibrosis according to late gadolinium enhancement, which was an independent predictor of impaired LV global radial strain (ß = - 45.81, P = 0.008), LV global circumferential strain (ß = 18.25, P = 0.003), LA reservoir strain (ß = - 59.20, P < 0.001) and strain rate (ß = - 2.90, P = 0.002). CONCLUSIONS: Diabetes has adverse effects on LV and LA function in HCM patients, which may be important contributors to severe manifestations and outcomes in those patients. The present study strengthened the evidence of the prevention and management of diabetes in HCM patients.

Machine Learning in Hypertrophic Cardiomyopathy: Nonlinear Model From Clinical and CMR Features Predicting Cardiovascular Events.

BACKGROUND: The cumulative burden of hypertrophic cardiomyopathy (HCM) is significant, with a noteworthy percentage (10%-15%) of patients with HCM per year experiencing major adverse cardiovascular events (MACEs). A current risk stratification scheme for HCM had only limited accuracy in predicting sudden cardiac death (SCD) and failed to account for a broader spectrum of adverse cardiovascular events and cardiac magnetic resonance (CMR) parameters. OBJECTIVES: This study sought to develop and evaluate a machine learning (ML) framework that integrates CMR imaging and clinical characteristics to predict MACEs in patients with HCM. METHODS: A total of 758 patients with HCM (67% male; age 49 ± 14 years) who were admitted between 2010 and 2017 from 4 medical centers were included. The ML model was built on the internal discovery cohort (533 patients with HCM, admitted to Fuwai Hospital, Beijing, China) by using the light gradient-boosting machine and internally evaluated using cross-validation. The external test cohort consisted of 225 patients with HCM from 3 medical centers. A total of 14 CMR imaging features (strain and late gadolinium enhancement [LGE]) and 23 clinical variables were evaluated and used to inform the ML model. MACEs included a composite of arrhythmic events, SCD, heart failure, and atrial fibrillation-related stroke. RESULTS: MACEs occurred in 191 (25%) patients over a median follow-up period of 109.0 months (Q1-Q3: 73.0-118.8 months). Our ML model achieved areas under the curve (AUCs) of 0.830 and 0.812 (internally and externally, respectively). The model outperformed the classic HCM Risk-SCD model, with significant improvement (P < 0.001) of 22.7% in the AUC. Using the cubic spline analysis, the study showed that the extent of LGE and the impairment of global radial strain (GRS) and global circumferential strain (GCS) were nonlinearly correlated with MACEs: an elevated risk of adverse cardiovascular events was observed when these parameters reached the high enough second tertiles (11.6% for LGE, 25.8% for GRS, -17.3% for GCS). CONCLUSIONS: ML-empowered risk stratification using CMR and clinical features enabled accurate MACE prediction beyond the classic HCM Risk-SCD model. In addition, the nonlinear correlation between CMR features (LGE and left ventricular pressure gradient) and MACEs uncovered in this study provides valuable insights for the clinical assessment and management of HCM.

Prognostic value of right ventricular involvement in hypertrophic cardiomyopathy: A systematic review and meta-analysis.

BACKGROUND: Right ventricular (RV) involvement has been reported in one out of three patients with hypertrophic cardiomyopathy (HCM), however its prognostic significance remains unknown. We aimed to assess the prognostic value of RV involvement in patients with HCM through a systematic review and meta-analysis. METHODS: A literature search was performed on PubMed, ClinicalTrials.gov and Cochrane Library databases from inception through November 15, 2023. Original articles enrolling HCM patients >18 years old and evaluating the association of RV parameters routinely assessed in clinical practice through trans-thoracic echocardiography or cardiac magnetic resonance (i.e., RV hypertrophy, volumes, systolic function, and late gadolinium enhancement) and the risk of a pre-defined composite endpoint including i) all cause death; ii) cardiac death; iii) heart transplantation; iv) heart failure-related hospitalization; v) atrial fibrillation; vi) ventricular tachycardia; and vii) stroke were retrieved. We pooled the effect of RV imaging variables on the combined clinical endpoint in terms of hazard ratio (HR) with 95% confidence interval (CI). RESULTS: The meta-analysis included 12 articles and 4634 patients. The pooled analysis demonstrated that the presence of RV systolic dysfunction conveyed an increased risk of adverse outcomes (HR 2.46; 95% CI 1.80-3.35; P < 0.001), whereas other RV imaging parameters were not significantly associated with patients' prognosis, except for RV-fractional area change analyzed as a continuous variable (HR 0.96 per % increase; 95% CI 0.93-0.995; P = 0.025). CONCLUSIONS: Our results pinpoint a prognostic role of RV dysfunction, independent of left ventricular involvement, in patients with HCM, and future longitudinal studies, including multi-parametric RV assessment, are encouraged to provide clinically-relevant data to refine risk stratification in patients with HCM.

[Bibliometrics Analysis of Studies on Hypertrophic Cardiomyopathy From 2018 to 2022].

Objective To analyze the research progress and hot topics in hypertrophic cardiomyopathy from 2018 to 2022.Methods The publications in the field of hypertrophic cardiomyopathy from January 1,2018 to December 31,2022 were retrieved from Web of Science core collection database and included for a bibliometric analysis.Results A total of 6355 publications were included,with an average citation frequency of 7 times.The year 2021 witnessed the most publications (1406).The analysis with VOSviewer showed that the research on sudden death related to hypertrophic cardiomyopathy,especially the predictive value of late gadolinium-enhanced cardiac MRI in sudden death,was a hot topic.In addition,gene detection and the new drug mavacamten became hot research topics.The United States was the country with the largest number of publications and the highest citation frequency in this field.Chinese scholars produced the second largest number of publications,which,however,included few high-quality research results.Conclusions Risk stratification and prevention of sudden death is still an important and hot research content in the field of hypertrophic cardiomyopathy.Chinese scholars should carry out multi-center cooperation in the future to improve the research results.

Ongoing assertion of two-dimensional measurements on differentiation type of left ventricular hypertrophy: Focus on inferior vena cava.

BACKGROUND: Left ventricular hypertrophy (LVH), including hypertensive LVH, hypertrophic cardiomyopathy (HCM) and cardiac amyloidosis (CA), is a commonly encountered condition in cardiology practice, presenting challenges in differential diagnosis. In this study, we aimed to investigate the importance of echocardiographic evaluation of the inferior vena cava (IVC) in distinguishing LVH subtypes including hypertensive LVH, HCM, and CA. METHODS: In this retrospective study, patients with common causes of LVH including hypertensive LVH, HCM, and CA were included. The role of echocardiographic evaluation of IVC diameter and collapsibility in distinguishing these causes of LVH was assessed in conjunction with other echocardiographic, clinical, and imaging methods. RESULTS: A total of 211 patients (45% HCM, 43% hypertensive heart disease, and 12% CA) were included in our study. Their mean age was 56.6 years and 62% of them were male. While mean IVC diameter was significantly dilated in CA patients (13.4 mm in hypertensive LVH, 16.0 mm in HCM, and 21.1 mm in CA, p < .001), its collapsibility was reduced (IVC collapsible in 95% of hypertensive patients, 72% of HCM patients, and 12% of CA patients, p < .001). In the analysis of diagnostic probabilities, the presence of both hypovoltage and IVC dilation is significant for CA patients. Although it is not statistically significant, the presence of IVC dilation along with atrial fibrillation supports the diagnosis of HCM. CONCLUSION: In conclusion, although advances in imaging techniques facilitate the diagnosis of LVH, simple echocardiographic methods should never be overlooked. Our study supports the notion that IVC assessment could play an important role in the differential diagnosis of LVH.

Microcirculatory dysfunction in hypertrophic cardiomyopathy with chest pain assessed by angiography-derived microcirculatory resistance.

Chest pain, a common initial symptom in hypertrophic cardiomyopathy (HCM) patients, is closely linked to myocardial ischemia, despite the absence of significant coronary artery stenosis. This study explored microvascular dysfunction in HCM patients by employing angiography-derived microcirculatory resistance (AMR) as a novel tool for comprehensive assessment. This retrospective analysis included HCM patients with chest pain as the primary symptom and control patients without cardiac hypertrophy during the same period. The AMR was computed through angiography, providing a wire-free and adenosine-free index for evaluating microcirculatory function. Propensity score matching ensured balanced demographics between groups. This study also investigated the correlation between the AMR and clinical outcomes by utilizing echocardiography and follow-up data. After matching, 76 HCM patients and 152 controls were analyzed. While there was no significant difference in the incidence of epicardial coronary stenosis, the AMR of three epicardial coronary arteries was markedly greater in HCM patients. The criterion of an AMR ≥ 250 mmHg*s/m was that 65.7% of HCM patients experienced coronary microvascular dysfunction (CMD). Independent risk factors for CMD included increased left ventricular (LV) wall thickness (OR = 1.209, 95% CI 1.013-1.443, p = 0.036). Furthermore, an AMR_LAD ≥ 250 mmHg*s/m had an increased cumulative risk of the endpoint (log-rank p = 0.023) and was an independent risk factor for the endpoint (HR = 11.64, 95% CI 1.13-120.03, p = 0.039), providing valuable prognostic insights.

Atypical left-ventricular hypertrophy with apical aneurysm in leopard syndrome.

Noonan Syndrome with Multiple Lentigines (NSML-formerly known as LEOPARD syndrome) is a rare autosomal dominant condition that usually exhibits cardiac involvement with hypertrophic cardiomyopathy (HCM). Here we present a case of a NSML patient with an unusual and patchy cardiac hypertrophy distribution.

Cardiac disease discrimination from 3D-convolutional kinematic patterns on cine-MRI sequences. / Discriminación de enfermedades cardiacas utilizando patrones cinemáticos codificados con convoluciones 3D en secuencias de cine-RM

INTRODUCTION: Cine-MRI (cine-magnetic resonance imaging) sequences are a key diagnostic tool to visualize anatomical information, allowing experts to localize and determine suspicious pathologies. Nonetheless, such analysis remains subjective and prone to diagnosis errors. OBJECTIVE: To develop a binary and multi-class classification considering various cardiac conditions using a spatiotemporal model that highlights kinematic movements to characterize each disease. MATERIALS AND METHODS: This research focuses on a 3D convolutional representation to characterize cardiac kinematic patterns during the cardiac cycle, which may be associated with pathologies. The kinematic maps are obtained from the apparent velocity maps computed from a dense optical flow strategy. Then, a 3D convolutional scheme learns to differentiate pathologies from kinematic maps. RESULTS: The proposed strategy was validated with respect to the capability to discriminate among myocardial infarction, dilated cardiomyopathy, hypertrophic cardiomyopathy, abnormal right ventricle, and normal cardiac sequences. The proposed method achieves an average accuracy of 78.00% and a F1 score of 75.55%. Likewise, the approach achieved 92.31% accuracy for binary classification between pathologies and control cases. CONCLUSION: The proposed method can support the identification of kinematically abnormal patterns associated with a pathological condition. The resultant descriptor, learned from the 3D convolutional net, preserves detailed spatiotemporal correlations and could emerge as possible digital biomarkers of cardiac diseases.

Introducción. Las secuencias del cine-resonancia magnética (cine-MRI, cine magnetic resonance imaging) son una herramienta diagnóstica clave para visualizar la información anatómica que les permite a los expertos localizar y determinar aquellas anomalías que resulten sospechosas. No obstante, este análisis sigue siendo subjetivo y propenso a errores de diagnóstico. Objetivo. Desarrollar una clasificación binaria y multiclase, considerando diferentes condiciones cardiacas, mediante un modelo espaciotemporal que permita resaltar los movimientos cinéticos para caracterizar cada enfermedad. Materiales y métodos. Este estudio se centra en el uso de una representación de convolución 3D para caracterizar los patrones cinéticos durante el ciclo cardiaco que puedan estar asociados con enfermedades. Para ello, se obtienen mapas cinéticos a partir de mapas de velocidad aparente, calculados mediante una estrategia de flujo óptico denso. A continuación, un esquema de convolución 3D "aprende" a diferenciar patologías a partir de mapas cinemáticos. Resultados. La estrategia propuesta se validó según la capacidad de discriminar entre infarto de miocardio, miocardiopatía dilatada, miocardiopatía hipertrófica, ventrículo derecho anormal y un examen normal. El método propuesto alcanza una precisión media del 78,0 % y una puntuación F1 score del 75,55 %. Asimismo, el enfoque alcanzó el 92,31 % de precisión para la clasificación binaria entre enfermedades y casos de control. Conclusiones. El método propuesto es capaz de apoyar la identificación de patrones cinéticos anormales asociados con una condición patológica. El descriptor resultante, aprendido de la red de convolución 3D, conserva correlaciones espaciotemporales detalladas y podría surgir como posible biomarcador digital de enfermedades cardiacas.

Rapidly Progressive Apical Hypertrophic Cardiomyopathy: Not Everything is What It Seems.

Apical hypertrophic cardiomyopathy (HCM) is a rare variant of HCM. A 43-year-old female with a past medical history significant for hypertension and kidney transplantation presented with recurrent syncopal episodes and dyspnea on exertion. Electrocardiogram showed characteristic diffuse giant T-waves inversion, and cardiac magnetic resonance showed HCM with circumferential apical thickening. This case highlights the rapid development of apical HCM and its challenging diagnostic characteristics.

Ventricular late gadolinium enhancement by cardiac MRI as a predictor of atrial fibrillation in hypertrophic cardiomyopathy.

BACKGROUND: Atrial fibrillation (AF) increases stroke and mortality in patients with hypertrophic cardiomyopathy (HCM). Cardiac MRI (CMR) is increasingly used to detect late gadolinium enhancement (LGE) as a reliable indicator of left ventricular fibrosis, a potential predisposing factor of AF. Our research explored the correlation between left ventricular LGE and AF prevalence in HCM. METHODS: This retrospective study involved 351 HCM patients who underwent CMR. LGE percentages (0%, 1-5%, 6-14%, ≥15%) on CMR were compared with AF prevalence in HCM patients. Demographic, comorbidity, and imaging data were analyzed using appropriate univariate and multivariate analyses assessing for significant differences in AF prevalence. The predetermined significance level was p < 0.05. RESULTS: CMR demonstrated increased LGE in those with AF (p = 0.004). Increased LGE correlated with increased AF rates: 27.6% (0% LGE), 38.5% (1-5% LGE), 44.4% (6-14% LGE), and 54.7% (≥15% LGE) (p = 0.101, p = 0.043, p = 0.002, respectively, vs. 0% LGE). Adjusted for age, differences persisted and were most evident for LGE >15% (p = 0.001). Multivariate analysis, factoring age, gender, BMI, RVSP, and LVEF, supported LGE (odds ratio of 1.20, p = 0.036) and LAVI (odds ratio 1.05, 1.02-1.07, p < 0.001) as predictive markers for AF prevalence. CONCLUSIONS: Our study suggests a correlation between ventricular LGE and AF in patients with HCM. LGE exceeding 15% was associated with a significant increase in AF prevalence. These patients may require more frequent AF monitoring.

Impaired longitudinal systolic-diastolic coupling and cardiac response to exercise in patients with hypertrophic cardiomyopathy.

BACKGROUND: In patients with hypertrophic cardiomyopathy (HCM), impaired augmentation of stroke volume and diastolic dysfunction contribute to exercise intolerance. Systolic-diastolic (S-D) coupling characterizes how systolic contraction of the left ventricle (LV) primes efficient elastic recoil during early diastole. Impaired S-D coupling may contribute to the impaired cardiac response to exercise in patients with HCM. METHODS: Patients with HCM (n = 25, age = 47 ± 9 years) and healthy adults (n = 115, age = 49 ± 10 years) underwent a cardiopulmonary exercise testing (CPET) and echocardiogram. S-D coupling was defined as the ratio of LV longitudinal excursion of the mitral annulus during early diastole (EDexc) and systole (Sexc) and compared between groups. Peak oxygen uptake (peak V̇O2) (Douglas bags), cardiac index (C2H2 rebreathe), and stroke volume index (SVi) were assessed during CPET. Linear regression was performed between S-D coupling and peak V̇O2, peak cardiac index, and peak SVi. RESULTS: S-D coupling was lower in HCM (Controls: 0.63 ± 0.08, HCM: 0.56 ± 0.10, p < 0.001). Peak V̇O2 and stroke volume reserve were lower in patients with HCM (Peak VO2 Controls: 28.5 ± 5.5, HCM: 23.7 ± 7.2 mL/kg/min, p < 0.001, SV reserve: Controls 39 ± 16, HCM 30 ± 18 mL, p = 0.008). In patients with HCM, S-D coupling was associated with peak V̇O2 (r = 0.47, p = 0.018), peak cardiac index (r = 0.60, p = 0.002), and peak SVi (r = 0.63, p < 0.001). CONCLUSION: Systolic-diastolic coupling was impaired in patients with HCM and was associated with fitness and the cardiac response to exercise. Inefficient S-D coupling may link insufficient stroke volume generation, diastolic dysfunction, and exercise intolerance in HCM.

Deriving phenotype-representative left ventricular flow patterns by reduced-order modeling and classification.

BACKGROUND: Extracting phenotype-representative flow patterns and their associated numerical metrics is a bottleneck in the clinical translation of advanced cardiac flow imaging modalities. We hypothesized that reduced-order models (ROMs) are a suitable strategy for deriving simple and interpretable clinical metrics of intraventricular flow suitable for further assessments. Combined with machine learning (ML) flow-based ROMs could provide new insight to help diagnose and risk-stratify patients. METHODS: We analyzed 2D color-Doppler echocardiograms of 81 non-ischemic dilated cardiomyopathy (DCM) patients, 51 hypertrophic cardiomyopathy (HCM) patients, and 77 normal volunteers (Control). We applied proper orthogonal decomposition (POD) to build patient-specific and cohort-specific ROMs of LV flow. Each ROM aggregates a low number of components representing a spatially dependent velocity map modulated along the cardiac cycle by a time-dependent coefficient. We tested three classifiers using deliberately simple ML analyses of these ROMs with varying supervision levels. In supervised models, hyperparameter grid search was used to derive the ROMs that maximize classification power. The classifiers were blinded to LV chamber geometry and function. We ran vector flow mapping on the color-Doppler sequences to help visualize flow patterns and interpret the ML results. RESULTS: POD-based ROMs stably represented each cohort through 10-fold cross-validation. The principal POD mode captured >80 % of the flow kinetic energy (KE) in all cohorts and represented the LV filling/emptying jets. Mode 2 represented the diastolic vortex and its KE contribution ranged from <1 % (HCM) to 13 % (DCM). Semi-unsupervised classification using patient-specific ROMs revealed that the KE ratio of these two principal modes, the vortex-to-jet (V2J) energy ratio, is a simple, interpretable metric that discriminates DCM, HCM, and Control patients. Receiver operating characteristic curves using V2J as classifier had areas under the curve of 0.81, 0.91, and 0.95 for distinguishing HCM vs. Control, DCM vs. Control, and DCM vs. HCM, respectively. CONCLUSIONS: Modal decomposition of cardiac flow can be used to create ROMs of normal and pathological flow patterns, uncovering simple interpretable flow metrics with power to discriminate disease states, and particularly suitable for further processing using ML.