BACKGROUND: The distribution of late gadolinium enhancement (LGE) on the cardiac MRI (CMR) indicates myocardial fibrosis and provides information of possible reentry substrates. QT dynamicity reflecting repolarization abnormalities has gained attention as a potential prognostic predictive factor. OBJECTIVE: To clarify the correlation between the LGE distribution on CMR and QT dynamicity represented by the QT/RR relationship. METHODS: CMR and QT/RR analyses using Holter monitoring were performed in 34 patients (24 males, 60 ± 11 years) with ventricular tachycardia (VT) and/or ventricular fibrillation (VF). The LGE on CMR was scored using a 4-point score in 17 left ventricular segments. The sum of the LGE scores was calculated for each patient. The QT/RR slope and daytime/nighttime QT/RR ratio (day/night ratio) were calculated. The correlation between the slope or the day/night QT/RR ratio and late enhancement findings was analyzed. RESULTS: All patients were divided into 23 LGE positive (LGE(+)) and 11 LGE negative (LGE(-)) patients. The slopes of the QTe/RR and QTa /RR were significantly steeper in the LGE(+) than in LGE(-) patients (0.21 ± 0.03 vs 0.13 ± 0.02; P < 0.001, 0.19 ± 0.03 vs 0.13 ± 0.02; P < 0.001, respectively), and both slopes were significantly correlated with the total LGE scores (r = 0.83, P < 0.001; r = 0.71, P < 0.001, respectively). In the LGE(+) patients, the QTe day/night (1.37 ± 0.38 vs 0.91 ± 0.33; P = 0.002) and QTa day/night ratios (1.33 ± 0.26 vs 1.06 ± 0.30; P = 0.011) were significantly greater than those in the LGE(-) patients. CONCLUSION: The LGE distribution was closely related to the QT dynamicity, suggesting that a combination of these markers can be a powerful tool for understanding the background pathophysiology.
BACKGROUND: The distribution of late gadolinium enhancement (LGE) on the cardiac MRI (CMR) indicates myocardial fibrosis and provides information of possible reentry substrates. QT dynamicity reflecting repolarization abnormalities has gained attention as a potential prognostic predictive factor. OBJECTIVE: To clarify the correlation between the LGE distribution on CMR and QT dynamicity represented by the QT/RR relationship. METHODS: CMR and QT/RR analyses using Holter monitoring were performed in 34 patients (24 males, 60 ± 11 years) with ventricular tachycardia (VT) and/or ventricular fibrillation (VF). The LGE on CMR was scored using a 4-point score in 17 left ventricular segments. The sum of the LGE scores was calculated for each patient. The QT/RR slope and daytime/nighttime QT/RR ratio (day/night ratio) were calculated. The correlation between the slope or the day/night QT/RR ratio and late enhancement findings was analyzed. RESULTS: All patients were divided into 23 LGE positive (LGE(+)) and 11 LGE negative (LGE(-)) patients. The slopes of the QTe/RR and QTa /RR were significantly steeper in the LGE(+) than in LGE(-) patients (0.21 ± 0.03 vs 0.13 ± 0.02; P < 0.001, 0.19 ± 0.03 vs 0.13 ± 0.02; P < 0.001, respectively), and both slopes were significantly correlated with the total LGE scores (r = 0.83, P < 0.001; r = 0.71, P < 0.001, respectively). In the LGE(+) patients, the QTe day/night (1.37 ± 0.38 vs 0.91 ± 0.33; P = 0.002) and QTa day/night ratios (1.33 ± 0.26 vs 1.06 ± 0.30; P = 0.011) were significantly greater than those in the LGE(-) patients. CONCLUSION: The LGE distribution was closely related to the QT dynamicity, suggesting that a combination of these markers can be a powerful tool for understanding the background pathophysiology.
Authors: Charles Antzelevitch; Guido D Pollevick; Jonathan M Cordeiro; Oscar Casis; Michael C Sanguinetti; Yoshiyasu Aizawa; Alejandra Guerchicoff; Ryan Pfeiffer; Antonio Oliva; Bernd Wollnik; Philip Gelber; Elias P Bonaros; Elena Burashnikov; Yuesheng Wu; John D Sargent; Stefan Schickel; Ralf Oberheiden; Atul Bhatia; Li-Fern Hsu; Michel Haïssaguerre; Rainer Schimpf; Martin Borggrefe; Christian Wolpert Journal: Circulation Date: 2007-01-15 Impact factor: 29.690
Authors: Sujith Kuruvilla; Nebiyu Adenaw; Arabindra B Katwal; Michael J Lipinski; Christopher M Kramer; Michael Salerno Journal: Circ Cardiovasc Imaging Date: 2013-12-20 Impact factor: 7.792
Authors: Olivier Xhaët; Jean-Francois Argacha; Atul Pathak; Marko Gujic; Anne Houssiere; Boutaïna Najem; Jean-Paul Degaute; Philippe Van de Borne Journal: J Cardiovasc Electrophysiol Date: 2007-12-12