Substrate characterization of the right ventricle in repaired tetralogy of Fallot using late enhancement cardiac magnetic resonance

Rivas-Gándara, Núria; Dos‐Subirà, Laura; Francisco‐Pascual, Jaume; Rodríguez-García, Julián; Pijuan-Domenech, Antònia; Benito, Begoña; Valente, Filipa; Pascual-González, Gabriel; Santos‐Ortega, Alba; Miranda, Berta; Pérez-Rodón, Jordi; Ribera-Solé, Aida; Burcet-Rodriguez, Gemma; Rosés‐Noguer, Ferran; Gordon, Blanca; Palomares, José F. Rodríguez; Ferreira‐González, Ignacio

doi:10.1016/j.hrthm.2021.05.032

Cited by 8 publications

(2 citation statements)

References 17 publications

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“…A recent study used 3D CMR reconstruction to visualize AI in 10 patients with rTOF. 10 The best SI threshold was defined by a site-by-site visual comparison of CMR reconstruction color-coded for different SI thresholds, with the presence of AI on EAM (BV>1.5mV between boundaries), until the best match was achieved. The CMR reconstruction using 60% of maxSI for isthmus boundaries showed a good match with the number of AI on EAM in 9/10 patients, confirming that viable myocardium between anatomical boundaries can be identified by LGE-CMR in rTOF.…”

Section: Discussionmentioning

confidence: 99%

“…Compared to two-dimensional (2D) LGE-CMR, 3D LGE-CMR allows accurate visualization of morphologically complex parts of the heart such as the RV outflow tract (RVOT) with high-spatial resolution 9 and has been compared with voltage mapping in a small series of rTOF patients. 10 However, noninvasive identification of SCAI, as VT substrate in rTOF by LGE-CMR, has not been achieved but may significantly contribute to individualized risk stratification and non-invasive follow-up.…”

Section: Introductionmentioning

confidence: 99%

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Non-invasive identification of slow conducting anatomical isthmuses in patients with tetralogy of Fallot by 3D late gadolinium enhancement cardiovascular magnetic resonance imaging

Kimura

Wallet

Jongbloed

et al. 2023

Preprint

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Background: Patients with repaired tetralogy of Fallot (rTOF) remain at risk of sustained monomorphic ventricular tachycardia (SMVT) related to slow-conducting anatomical isthmuses (SCAI). Invasive electroanatomical mapping (EAM) is the only available method to identify SCAI (SCAIEAM). We aimed to determine rTOF-specific high signal intensity threshold values (HSIt) to identify abnormal myocardium by 3D late gadolinium enhancement cardiac magnetic resonance (LGE-CMR) and assess the performance of LGE-CMR to non-invasively identify SCAIEAM. Methods: Consecutive rTOF patients who underwent right ventricular EAM (RV-EAM) and 3D LGE-CMR were included (2012-2021). A SCAIEAM was defined as an anatomical isthmus (AI) with conduction velocity (CV) <0.5 m/s. LGE-CMR-derived 3D RV reconstructions were merged with 3D RV-EAM data. The HSIt was determined based on the comparison of local bipolar voltages (BV) and the corresponding local SI using ROC analysis. An abnormal AI on LGE-CMR (Abnormal AICMR) was defined as AI showing continuous high SI (>HSIt) between anatomical boundaries. Results Forty-eight rTOF patients (34{plus minus}16 years, 58% male) were included. Of 107 AIs on EAM (AI1 and 3 in all, AI2 in 11), 78 were normal-conducting AIEAM (NCAIEAM), 22 were SCAIEAM (SCAIEAM2 in 2 and SCAIEAM3 in 20), and 7 were blocked AIEAM3. All 14 induced SMVTs were related to SCAIEAM3. A total of 9240 EAM points were analyzed. HSIt was 42% of the maximal SI (AUC 0.80; sensitivity, 74%; specificity, 78%). On 3D-CMR RV construction, all 29 SCAIEAM or Blocked AIEAM were identified as abnormal AICMR. Among the 78 NCAIEAM, 70 were normal AICMR and 8 were abnormal AICMR. The sensitivity and specificity of 3D LGE-CMR for identifying SCAIEAM or blocked AIEAM were 100% and 90% (29/29 and 70/78), respectively. Among patients with NCAIEAM3 (n=28), those with abnormal AICMR3 (n=6) had significantly lower BV and slower CV compared with those with normal AICMR3 (n=22) (BV, 1.91 [1.62-2.60] vs. 3.45 mV [2.22-5.67]; CV, 0.69 [0.62-0.81] vs, 0.95 m/s [0.82-1.09]; both P<0.01). Conclusion: 3D LGE-CMR can identify SCAI with excellent sensitivity and specificity and may identify diseased AI3 even before critical conduction delay occurs, which may enable non-invasive risk stratification of VT and may refine patient selection for invasive EAM.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%