Radiomics Analysis Derived From LGE-MRI Predict Sudden Cardiac Death in Participants With Hypertrophic Cardiomyopathy.
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SUBMITTER: Wang J
PROVIDER: S-EPMC8702805 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundHypertrophic cardiomyopathy is the leading cause of sudden cardiac death (SCD) in children and young adults. Our objective was to develop and validate a SCD risk prediction model in pediatric hypertrophic cardiomyopathy to guide SCD prevention strategies.MethodsIn an international multicenter observational cohort study, phenotype-positive patients with isolated hypertrophic cardiomyopathy <18 years of age at diagnosis were eligible. The primary outcome variable was the time from diagnosis to a composite of SCD events at 5-year follow-up: SCD, resuscitated sudden cardiac arrest, and aborted SCD, that is, appropriate shock following primary prevention implantable cardioverter defibrillators. Competing risk models with cause-specific hazard regression were used to identify and quantify clinical and genetic factors associated with SCD. The cause-specific regression model was implemented using boosting, and tuned with 10 repeated 4-fold cross-validations. The final model was fitted using all data with the tuned hyperparameter value that maximizes the c-statistic, and its performance was characterized by using the c-statistic for competing risk models. The final model was validated in an independent external cohort (SHaRe [Sarcomeric Human Cardiomyopathy Registry], n=285).ResultsOverall, 572 patients met eligibility criteria with 2855 patient-years of follow-up. The 5-year cumulative proportion of SCD events was 9.1% (14 SCD, 25 resuscitated sudden cardiac arrests, and 14 aborted SCD). Risk predictors included age at diagnosis, documented nonsustained ventricular tachycardia, unexplained syncope, septal diameter z-score, left ventricular posterior wall diameter z score, left atrial diameter z score, peak left ventricular outflow tract gradient, and presence of a pathogenic variant. Unlike in adults, left ventricular outflow tract gradient had an inverse association, and family history of SCD had no association with SCD. Clinical and clinical/genetic models were developed to predict 5-year freedom from SCD. Both models adequately discriminated between patients with and without SCD events with a c-statistic of 0.75 and 0.76, respectively, and demonstrated good agreement between predicted and observed events in the primary and validation cohorts (validation c-statistic 0.71 and 0.72, respectively).ConclusionOur study provides a validated SCD risk prediction model with >70% prediction accuracy and incorporates risk factors that are unique to pediatric hypertrophic cardiomyopathy. An individualized risk prediction model has the potential to improve the application of clinical practice guidelines and shared decision making for implantable cardioverter defibrillator insertion. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT0403679.
| S-EPMC7365676 | biostudies-literature
Project description:AimsSudden cardiac death (SCD) is an appalling complication of hypertrophic cardiomyopathy (HCM). There is an ongoing discussion about the optimal SCD risk stratification strategy since established SCD risk models have suboptimal discriminative power. The aim of this study was to evaluate the prognostic value of late gadolinium enhancement (LGE) cardiac magnetic resonance (CMR) for SCD risk stratification compared to the European Society of Cardiology (ESC) SCD risk score and traditional risk factors in an >10-year follow-up.Methods and resultsTwo hundred and twenty consecutive patients with HCM and LGE-CMR were enrolled. Follow-up data were available in 203 patients (median age 58 years, 61% male) after a median follow-up period of 10.4 years. LGE was present in 70% of patients with a median LGE amount of 1.6%, the median ESC 5-year SCD risk score was 1.84. In the overall cohort, SCD rates were 2.3% at 5 years, 4.8% at 10 years, and 15.7% at 15 years, independent from established risk models. An LGE amount of >5% left ventricular (LV) mass portends the highest risk for SCD with SCD prevalences of 5.5% at 5 years, 13.0% at 10 years, and 33.3% at 15 years. Conversely, patients with no or ≤5% LGE of LV mass have favourable prognosis.ConclusionsLGE-CMR in HCM patients allows effective 10-year SCD risk stratification beyond established risk factors. LGE amount might be added to established risk models to improve its discriminatory power. Specifically, patients with >5% LGE should be carefully monitored and might be adequate candidates for primary prevention implantable cardioverter-defibrillator during the clinical long-term course.
| S-EPMC8219365 | biostudies-literature
Project description:In hypertrophic cardiomyopathy (HCM) patients, left ventricular (LV) maximal wall thickness (MWT) is one of the most important factors determining sudden cardiac death (SCD) risk. In a large unselected sample of HCM patients, we aimed to simulate what changes would occur in the calculated SCD risk according to the European HCM Risk-SCD calculator when MWT measured using echocardiography was changed to MWT measured using MRI. All consecutive patients with HCM who underwent cardiac MRI were included. MWT measured with echocardiography and MRI were compared, and 5-year SCD risk according to the HCM Risk-SCD calculator was computed using four different models. The final population included 673 patients [389 (57.8%) males, median age 50 years, interquartile range (36-60)]. The median MWT was lower measured by echocardiography than by MRI [20 (17-24) mm vs 21 (18-24) mm; p < 0.0001]. There was agreement between echocardiography and MRI in the measurement of maximal LV wall thickness in 96 patients (14.3%). The largest differences between echo and MRI were - 13 mm and + 9 mm. The differences in MWT by echocardiography and MRI translated to a maximal difference of 8.33% in the absolute 5-year risk of SCD, i.e., the echocardiography-based risk was 8.33% lower than the MRI-based estimates. Interestingly, 13.7% of patients would have been reclassified into different SCD risk categories if MRI had been used to measure MWT instead of echocardiography. In conclusion, although there was high general intermodality agreement between echocardiography and MRI in the MWT measurements, the differences in MWT translated to significant differences in the 5-year risk of SCD.
| S-EPMC8009882 | biostudies-literature
Project description:In search of improved risk stratification in hypertrophic cardiomyopathy (HCM), CMR imaging has been implicated as a potential tool for prediction of sudden cardiac death (SCD). In follow-up of the promising results with extensive late gadolinium enhancement (LGE), high signal-intensity on T2-weighted imaging (HighT2) has become subject of interest given its association with markers of adverse disease progression, such as LGE, elevated troponin and non-sustained ventricular tachycardia. In lack of follow-up cohorts, we initiated an exploratory study on the association between HighT2 and the internationally defined risk categories of SCD. In a cohort of 109 HCM patients from a multicenter study on CMR imaging and biomarkers, we estimated the 5-year SCD risk (HCM Risk-SCD model). Patients were categorized as low (<?4%), intermediate (??4-<6%) or high (??6%) risk. In addition, risk categorization according to the ACC/AHA guidelines was performed. HighT2 was present in 27% (29/109). Patients with HighT2 were more often at an intermediate-high risk of SCD according to the European (28 vs. 10%, p?=?.032) and American guidelines (41 vs. 18%, p?=?.010) compared to those without HighT2. The estimated 5-year SCD risk of our cohort was 1.9% (IQR 1.3-2.9%), and projected SCD rates were higher in patients with than without HighT2 (2.8 vs. 1.8%, p?=?.002). In conclusion, HCM patients with HighT2 were more likely to be intermediate-high risk, with projected SCD rates that were 1.5 fold higher than in patients without HighT2. These pilot findings call for corroborative studies with more intermediate-high risk HCM patients and clinical follow-up to assess whether HighT2 may have additional value to current risk stratification.
| S-EPMC5797557 | biostudies-literature
Project description: Not available
| S-EPMC1767009 | biostudies-literature
Project description:BackgroundMaximal left ventricular wall thickness (MLVWT) is a risk factor for sudden cardiac death (SCD) in hypertrophic cardiomyopathy (HCM). In adults, the severity of left ventricular hypertrophy has a nonlinear relationship with SCD, but it is not known whether the same complex relationship is seen in childhood. The aim of this study was to describe the relationship between left ventricular hypertrophy and SCD risk in a large international pediatric HCM cohort.MethodsThe study cohort comprised 1075 children (mean age, 10.2 years [±4.4]) diagnosed with HCM (1-16 years) from the International Paediatric Hypertrophic Cardiomyopathy Consortium. Anonymized, noninvasive clinical data were collected from baseline evaluation and follow-up, and 5-year estimated SCD risk was calculated (HCM Risk-Kids).ResultsMLVWT Z score was <10 in 598 (58.1%), ≥10 to <20 in 334 (31.1%), and ≥20 in 143 (13.3%). Higher MLVWT Z scores were associated with heart failure symptoms, unexplained syncope, left ventricular outflow tract obstruction, left atrial dilatation, and nonsustained ventricular tachycardia. One hundred twenty-two patients (71.3%) with MLVWT Z score ≥20 had coexisting risk factors for SCD. Over a median follow-up of 4.9 years (interquartile range, 2.3-9.3), 115 (10.7%) had an SCD event. Freedom from SCD event at 5 years for those with MLVWT Z scores <10, ≥10 to <20, and ≥20 was 95.6%, 87.4%, and 86.0, respectively. The estimated SCD risk at 5 years had a nonlinear, inverted U-shaped relationship with MLVWT Z score, peaking at Z score +23. The presence of coexisting risk factors had a summative effect on risk.ConclusionsIn children with HCM, an inverted U-shaped relationship exists between left ventricular hypertrophy and estimated SCD risk. The presence of additional risk factors has a summative effect on risk. While MLVWT is important for risk stratification, it should not be used either as a binary variable or in isolation to guide implantable cardioverter defibrillator implantation decisions in children with HCM.
| S-EPMC7612749 | biostudies-literature
Project description:Hypertrophic cardiomyopathy (HCM) is associated with risk of sudden cardiac death (SCD) due to ventricular arrhythmias (VAs) arising from the proliferation of fibrosis in the heart. Current clinical risk stratification criteria inadequately identify at-risk patients in need of primary prevention of VA. Here, we use mechanistic computational modeling of the heart to analyze how HCM-specific remodeling promotes arrhythmogenesis and to develop a personalized strategy to forecast risk of VAs in these patients. We combine contrast-enhanced cardiac magnetic resonance imaging and T1 mapping data to construct digital replicas of HCM patient hearts that represent the patient-specific distribution of focal and diffuse fibrosis and evaluate the substrate propensity to VA. Our analysis indicates that the presence of diffuse fibrosis, which is rarely assessed in these patients, increases arrhythmogenic propensity. In forecasting future VA events in HCM patients, the imaging-based computational heart approach achieved 84.6%, 76.9%, and 80.1% sensitivity, specificity, and accuracy, respectively, and significantly outperformed current clinical risk predictors. This novel VA risk assessment may have the potential to prevent SCD and help deploy primary prevention appropriately in HCM patients.
| S-EPMC8789259 | biostudies-literature
Project description:RationaleSusceptibility to VT/VF (ventricular tachycardia/fibrillation) is difficult to predict in patients with ischemic cardiomyopathy either by clinical tools or by attempting to translate cellular mechanisms to the bedside.ObjectiveTo develop computational phenotypes of patients with ischemic cardiomyopathy, by training then interpreting machine learning of ventricular monophasic action potentials (MAPs) to reveal phenotypes that predict long-term outcomes.Methods and resultsWe recorded 5706 ventricular MAPs in 42 patients with coronary artery disease and left ventricular ejection fraction ≤40% during steady-state pacing. Patients were randomly allocated to independent training and testing cohorts in a 70:30 ratio, repeated K=10-fold. Support vector machines and convolutional neural networks were trained to 2 end points: (1) sustained VT/VF or (2) mortality at 3 years. Support vector machines provided superior classification. For patient-level predictions, we computed personalized MAP scores as the proportion of MAP beats predicting each end point. Patient-level predictions in independent test cohorts yielded c-statistics of 0.90 for sustained VT/VF (95% CI, 0.76-1.00) and 0.91 for mortality (95% CI, 0.83-1.00) and were the most significant multivariate predictors. Interpreting trained support vector machine revealed MAP morphologies that, using in silico modeling, revealed higher L-type calcium current or sodium-calcium exchanger as predominant phenotypes for VT/VF.ConclusionsMachine learning of action potential recordings in patients revealed novel phenotypes for long-term outcomes in ischemic cardiomyopathy. Such computational phenotypes provide an approach which may reveal cellular mechanisms for clinical outcomes and could be applied to other conditions.
| S-EPMC7855939 | biostudies-literature
Project description:ImportanceSudden cardiac death (SCD) is the most common mode of death in childhood hypertrophic cardiomyopathy (HCM), but there is no validated algorithm to identify those at highest risk.ObjectiveTo develop and validate an SCD risk prediction model that provides individualized risk estimates.Design, setting, and participantsA prognostic model was developed from a retrospective, multicenter, longitudinal cohort study of 1024 consecutively evaluated patients aged 16 years or younger with HCM. The study was conducted from January 1, 1970, to December 31, 2017.ExposuresThe model was developed using preselected predictor variables (unexplained syncope, maximal left-ventricular wall thickness, left atrial diameter, left-ventricular outflow tract gradient, and nonsustained ventricular tachycardia) identified from the literature and internally validated using bootstrapping.Main outcomes and measuresA composite outcome of SCD or an equivalent event (aborted cardiac arrest, appropriate implantable cardioverter defibrillator therapy, or sustained ventricular tachycardia associated with hemodynamic compromise).ResultsOf the 1024 patients included in the study, 699 were boys (68.3%); mean (interquartile range [IQR]) age was 11 (7-14) years. Over a median follow-up of 5.3 years (IQR, 2.6-8.3; total patient years, 5984), 89 patients (8.7%) died suddenly or had an equivalent event (annual event rate, 1.49; 95% CI, 1.15-1.92). The pediatric model was developed using preselected variables to predict the risk of SCD. The model's ability to predict risk at 5 years was validated; the C statistic was 0.69 (95% CI, 0.66-0.72), and the calibration slope was 0.98 (95% CI, 0.59-1.38). For every 10 implantable cardioverter defibrillators implanted in patients with 6% or more of a 5-year SCD risk, 1 patient may potentially be saved from SCD at 5 years.Conclusions and relevanceThis new, validated risk stratification model for SCD in childhood HCM may provide individualized estimates of risk at 5 years using readily obtained clinical risk factors. External validation studies are required to demonstrate the accuracy of this model's predictions in diverse patient populations.
| S-EPMC6694401 | biostudies-literature
Project description:AimsAssessment of ECG-features as predictors of sudden death in adults with hypertrophic cardiomyopathy (HCM).Methods and resultsECG-amplitude sums were measured in 44 normals, 34 athletes, a hospital-cohort of 87 HCM-patients, and 29 HCM-patients with sudden death or cardiac arrest (HCM-CA). HCM-patients with sudden death or cardiac arrest had substantially higher ECG-amplitudes than the HCM-cohort for limb-lead and 12-lead QRS-amplitude sums, and amplitude-duration products (P = 0.00003-P = 0.000002). Separation of HCM-CA from the HCM-cohort is obtained by limb-lead QRS-amplitude sum >or=7.7 mV (odds ratio 18.8, sensitivity 87%, negative predictive value (NPV) 94%, P < 0.0001), 12-lead amplitude-duration product >or=2.2 mV s (odds ratio 31.0, sensitivity 92%, NPV 97%, P < 0.0001), and limb-lead amplitude-duration product >or=0.70 mV s (odds ratio 31.5, sensitivity 93%, NPV 96%, P < 0.0001). Sensitivity in HCM-patients <40 years is 90, 100, and 100% for those ECG-variables, respectively. Qualitative analysis showed correlation with cardiac arrest for pathological T-wave-inversion (P = 0.0003), ST-depression (P = 0.0010), and dominant S-wave in V(4) (P = 0.0048). A risk score is proposed; a score >or=6 gives a sensitivity of 85% but a higher positive predictive value than above measures. Optimal separation between HCM-CA <40 years and athletes is obtained by a risk score >or=6 (odds ratio 345, sensitivity 85%, specificity 100%, P < 0.0001).ConclusionTwelve-lead ECG is a powerful instrument for risk-stratification in HCM.
| S-EPMC2821628 | biostudies-literature