Predicting ventricular tachyarrhythmia in patients with systolic heart failure based on texture features of the gray zone from contrast-enhanced magnetic resonance imaging

Pham, Van Truong; Lin, Chen; Tran, Thi Thao; Su, Mao‐Yuan; Lin, Ying Kuang; Nien, Chun Tung; Tseng, Wen Yih I.; Lin, Jiunn Lee; Lo, Men Tzung; Lin, Lian Yu

doi:10.1016/j.jjcc.2020.06.020

Cited by 7 publications

(3 citation statements)

References 39 publications

(49 reference statements)

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“…The most notable use and development have been made in the field of neurooncology 1 – 4 . Application of radiomics has recently gained interest in cardiac MRI (CMRI) and few studies have evaluated its utility in patients with ventricular hypertrophy 5 – 7 , myocardial infarction 8 , tachyarrhythmia 9 , and myocarditis 10 , 11 .…”

Section: Introductionmentioning

confidence: 99%

Radiomics side experiments and DAFIT approach in identifying pulmonary hypertension using Cardiac MRI derived radiomics based machine learning models

Priya

Aggarwal

Ward

et al. 2021

Sci Rep

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Side experiments are performed on radiomics models to improve their reproducibility. We measure the impact of myocardial masks, radiomic side experiments and data augmentation for information transfer (DAFIT) approach to differentiate patients with and without pulmonary hypertension (PH) using cardiac MRI (CMRI) derived radiomics. Feature extraction was performed from the left ventricle (LV) and right ventricle (RV) myocardial masks using CMRI in 82 patients (42 PH and 40 controls). Various side study experiments were evaluated: Original data without and with intraclass correlation (ICC) feature-filtering and DAFIT approach (without and with ICC feature-filtering). Multiple machine learning and feature selection strategies were evaluated. Primary analysis included all PH patients with subgroup analysis including PH patients with preserved LVEF (≥ 50%). For both primary and subgroup analysis, DAFIT approach without feature-filtering was the highest performer (AUC 0.957–0.958). ICC approaches showed poor performance compared to DAFIT approach. The performance of combined LV and RV masks was superior to individual masks alone. There was variation in top performing models across all approaches (AUC 0.862–0.958). DAFIT approach with features from combined LV and RV masks provide superior performance with poor performance of feature filtering approaches. Model performance varies based upon the feature selection and model combination.

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Section: Introductionmentioning

confidence: 99%

Radiomics side experiments and DAFIT approach in identifying pulmonary hypertension using Cardiac MRI derived radiomics based machine learning models

Priya

Aggarwal

Ward

et al. 2021

Sci Rep

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“…The present study demonstrated that the assessment of both renal function and CSNA is useful for predicting lethal arrhythmic events in patients with CHF. Although late gadolinium enhancement on magnetic resonance imaging has become a gold standard method to identify patients at high risk of ventricular tachyarrhythmias, (Muser et al, 2021 ; Pham et al, 2020 ) the utility of this method is limited in patients with CKD or cardiac implantable electronic devices. On the other hand, risk assessment with cardiac 123 I‐MIBG scintigraphy is available and useful for even patients with CKD or cardiac implantable electronic devices.…”

Section: Discussionmentioning

confidence: 99%

“…Cox proportional hazard model of lethal arrhythmic events patients at high risk of ventricular tachyarrhythmias, (Muser et al, 2021;Pham et al, 2020) the utility of this method is limited in patients with CKD or cardiac implantable electronic devices. On the other hand, risk assessment with cardiac 123 I-MIBG scintigraphy is available and useful for even patients with CKD or cardiac implantable electronic devices.…”

Section: Ta B L Ementioning

confidence: 99%

Predictive impacts of chronic kidney disease and cardiac sympathetic nervous activity on lethal arrhythmic events in chronic heart failure

Amami

Yamada

Yoshihisa

et al. 2021

Noninvasive Electrocardiol

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Background The clinical implications of chronic kidney disease (CKD) and cardiac sympathetic nervous activity (CSNA) regarding lethal arrhythmic events have not yet been fully elucidated in patients with chronic heart failure (CHF). We hypothesized that the combination of CKD and abnormal CSNA, assessed by 123 I‐metaiodobenzylguanidine ( 123 I‐MIBG) scintigraphy, may provide useful prognostic information for lethal arrhythmic events. Methods We studied 165 consecutive hospitalized CHF patients without dialysis. Cardiac 123 I‐MIBG scintigraphy was performed in a clinically stable condition, and abnormal CSNA was defined as a late heart‐to‐mediastinum ratio of <1.6. CKD was defined as an estimated glomerular filtration rate of <60 ml/min/1.73 m 2 . We then investigated the incidence of lethal arrhythmic events (sustained ventricular tachyarrhythmia, appropriate implantable cardioverter‐defibrillator therapy, or sudden cardiac death). Results During a median follow‐up of 5.3 years, lethal arrhythmic events were observed in 40 patients (24.2%). The patients were divided into four groups according to the presence of CKD and CSNA abnormality: non‐CKD/normal CSNA ( n = 52), CKD/normal CSNA ( n = 39), non‐CKD/abnormal CSNA ( n = 33), and CKD/abnormal CSNA ( n = 41). Kaplan–Meier analysis showed that CKD/abnormal CSNA had the highest event rate (log‐rank p = .004). Additionally, the Cox proportional hazard analysis revealed that CKD/abnormal CSNA was a predictor for lethal arrhythmic events compared with non‐CKD/normal CSNA (hazard ratio, 5.368, p = .001). However, the other two groups did not show significant differences compared with the non‐CKD/normal CSNA group. Conclusions The combination of CKD and abnormal CSNA, assessed by 123 I‐MIBG scintigraphy, had a high predictive value for lethal arrhythmic events in patients with CHF.

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Quality of science and reporting for radiomics in cardiac magnetic resonance imaging studies: a systematic review

et al. 2022

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Predicting ventricular tachyarrhythmia in patients with systolic heart failure based on texture features of the gray zone from contrast-enhanced magnetic resonance imaging

Cited by 7 publications

References 39 publications

Radiomics side experiments and DAFIT approach in identifying pulmonary hypertension using Cardiac MRI derived radiomics based machine learning models

Radiomics side experiments and DAFIT approach in identifying pulmonary hypertension using Cardiac MRI derived radiomics based machine learning models

Predictive impacts of chronic kidney disease and cardiac sympathetic nervous activity on lethal arrhythmic events in chronic heart failure

Quality of science and reporting for radiomics in cardiac magnetic resonance imaging studies: a systematic review

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