BACKGROUND AND AIMS: Risk stratification of sudden cardiac death after myocardial infarction and prevention by defibrillator rely on left ventricular ejection fraction (LVEF). Improved risk stratification across the whole LVEF range is required for decision-making on defibrillator implantation. METHODS: The analysis pooled 20 data sets with 140 204 post-myocardial infarction patients containing information on demographics, medical history, clinical characteristics, biomarkers, electrocardiography, echocardiography, and cardiac magnetic resonance imaging. Separate analyses were performed in patients (i) carrying a primary prevention cardioverter-defibrillator with LVEF ≤ 35% [implantable cardioverter-defibrillator (ICD) patients], (ii) without cardioverter-defibrillator with LVEF ≤ 35% (non-ICD patients ≤ 35%), and (iii) without cardioverter-defibrillator with LVEF > 35% (non-ICD patients >35%). Primary outcome was sudden cardiac death or, in defibrillator carriers, appropriate defibrillator therapy. Using a competing risk framework and systematic internal-external cross-validation, a model using LVEF only, a multivariable flexible parametric survival model, and a multivariable random forest survival model were developed and externally validated. Predictive performance was assessed by random effect meta-analysis. RESULTS: There were 1326 primary outcomes in 7543 ICD patients, 1193 in 25 058 non-ICD patients ≤35%, and 1567 in 107 603 non-ICD patients >35% during mean follow-up of 30.0, 46.5, and 57.6 months, respectively. In these three subgroups, LVEF poorly predicted sudden cardiac death (c-statistics between 0.50 and 0.56). Considering additional parameters did not improve calibration and discrimination, and model generalizability was poor. CONCLUSIONS: More accurate risk stratification for sudden cardiac death and identification of low-risk individuals with severely reduced LVEF or of high-risk individuals with preserved LVEF was not feasible, neither using LVEF nor using other predictors.
- MeSH
- defibrilátory implantabilní * MeSH
- elektrokardiografie MeSH
- hodnocení rizik metody MeSH
- infarkt myokardu * mortalita komplikace MeSH
- lidé MeSH
- náhlá srdeční smrt * prevence a kontrola epidemiologie etiologie MeSH
- tepový objem * fyziologie MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- metaanalýza MeSH
BACKGROUND: Electroanatomical voltage mapping (EAVM) has been compared with late gadolinium enhancement cardiovascular magnetic resonance (LGE-CMR), which cannot delineate diffuse fibrosis. T1-mapping CMR overcomes the limitations of LGE-CMR, but it has not been directly compared against EAVM. OBJECTIVES: This study aims to assess the relationship between left ventricular (LV) endocardial voltage obtained by EAVM and extracellular volume (ECV) obtained by T1 mapping. METHODS: The study investigated patients who underwent endocardial EAVM for ventricular arrhythmias (CARTO 3, Biosense Webster) together with preprocedural contrast-enhanced T1 mapping (Ingenia 3T, Philips Healthcare). After image integration, EAVM datapoints were projected onto LGE-CMR and ECV-encoded images. Average values of unipolar voltage (UV), bipolar voltage (BV), LGE transmurality, and ECV were merged from corresponding cardiac segments (6 per slice) and pooled for analysis. RESULTS: The analysis included data from 628 segments from 18 patients (57 ± 13 years of age, 17% females, LV ejection fraction 48% ± 14%, nonischemic/ischemic cardiomyopathy/controls: 8/6/4 patients). Based on the 95th and 5th percentile values obtained from the controls, ECV >33%, BV <2.9 mV, and UV <6.7 mV were considered abnormal. There was a significant inverse association between voltage and ECV, but only in segments with abnormal ECV. Increased ECV could predict abnormal BV and UV with acceptable accuracy (area under the curve of 0.78 [95% CI: 0.74-0.83] and 0.84 [95% CI: 0.79-0.88]). CONCLUSIONS: This study found a significant inverse relationship between LV endocardial voltage and ECV. Real-time integration of T1 mapping may guide catheter mapping and may allow identification of areas of diffuse fibrosis potentially related to ventricular arrhythmias.
Purpose To develop a deep learning-based method for fully automated quantification of left ventricular (LV) function from short-axis cine MR images and to evaluate its performance in a multivendor and multicenter setting. Materials and Methods This retrospective study included cine MRI data sets obtained from three major MRI vendors in four medical centers from 2008 to 2016. Three convolutional neural networks (CNNs) with the U-NET architecture were trained on data sets of increasing variability: (a) a single-vendor, single-center, homogeneous cohort of 100 patients (CNN1); (b) a single-vendor, multicenter, heterogeneous cohort of 200 patients (CNN2); and (c) a multivendor, multicenter, heterogeneous cohort of 400 patients (CNN3). All CNNs were tested on an independent multivendor, multicenter data set of 196 patients. CNN performance was evaluated with respect to the manual annotations from three experienced observers in terms of (a) LV detection accuracy, (b) LV segmentation accuracy, and (c) LV functional parameter accuracy. Automatic and manual results were compared with the paired Wilcoxon test, Pearson correlation, and Bland-Altman analysis. Results CNN3 achieved the highest performance on the independent testing data set. The average perpendicular distance compared with manual analysis was 1.1 mm ± 0.3 for CNN3, compared with 1.5 mm ± 1.0 for CNN1 (P < .05) and 1.3 mm ± 0.6 for CNN2 (P < .05). The LV function parameters derived from CNN3 showed a high correlation (r2 ≥ 0.98) and agreement with those obtained by experts for data sets from different vendors and centers. Conclusion A deep learning-based method trained on a data set with high variability can achieve fully automated and accurate cine MRI analysis on multivendor, multicenter cine MRI data. © RSNA, 2018 See also the editorial by Colletti in this issue.
- MeSH
- deep learning * MeSH
- interpretace obrazu počítačem metody MeSH
- lidé MeSH
- magnetická rezonance kinematografická metody MeSH
- retrospektivní studie MeSH
- srdce - funkce komor fyziologie MeSH
- srdeční komory diagnostické zobrazování MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
OBJECTIVES: This study sought to determine new reference cutoffs for normal unipolar voltage (UV) and bipolar voltage (BV) that would be adjusted for the LV remodeling. BACKGROUND: The definition of "normal" left ventricular (LV) endocardial voltage in patients with post-infarct scar is still lacking. The reference voltage of the noninfarcted myocardium (NIM) may differ between patients depending on LV structural remodeling and the ensuing interstitial fibrosis. METHODS: Electroanatomic voltage mapping was integrated with isotropic late gadolinium-enhanced cardiac magnetic resonance in 15 patients with nonremodeled LV and 12 patients with remodeled LV (end-systolic volume index >50 ml/m2 with ejection fraction <47% assessed by cardiac magnetic resonance). Reference voltages (fifth percentile values) were determined from pooled NIM segments without late gadolinium enhancement. RESULTS: The cutoffs for normal BV and UV were ≥3.0 and ≥6.7 mV for nonremodeled LV and ≥2.1 and ≥6.4 mV for remodeled LV. Endocardial low-voltage area (LVA) defined by the adjusted cutoffs corresponded better to late gadolinium enhancement-detected scar than did LVA defined by uniform cutoffs. In 15 patients who underwent successful ablation of ventricular tachycardia, the LVA contained >97% of targeted evoked delayed potentials. Insights from whole-heart T1 mapping revealed more fibrotic NIM in patients with remodeled LV compared with nonremodeled LV. CONCLUSIONS: This study found substantial differences in endocardial voltage of NIM in post-infarct patients with remodeled versus nonremodeled LV. The new adjusted cutoffs for "normal" BV and UV enable a patient-tailored approach to electroanatomic voltage mapping of LV.
- MeSH
- elektrofyziologické techniky kardiologické * MeSH
- endokard diagnostické zobrazování fyziologie patofyziologie MeSH
- infarkt myokardu komplikace patofyziologie MeSH
- jizva diagnostické zobrazování etiologie patofyziologie MeSH
- katetrizační ablace MeSH
- komorová tachykardie etiologie patofyziologie chirurgie MeSH
- lidé středního věku MeSH
- lidé MeSH
- magnetická rezonance kinematografická MeSH
- magnetická rezonanční tomografie MeSH
- referenční hodnoty MeSH
- remodelace komor fyziologie MeSH
- senioři MeSH
- studie případů a kontrol MeSH
- Check Tag
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
