What is the best angiographic view for detection of coronary artery abnormality in Tetralogy of Fallot? A retrospective study

Abstract

Background The definite treatment of tetralogy of Fallot (TOF) as the most common cyanotic congenital heart disease is open heart surgery and the operation technique depends on the coronary artery anatomy. We aimed to evaluate the sensitivity and specificity of various root Aortogram views to detect abnormal coronary artery configuration and course in these patients.Methods In this retrospective study, the reports of coronary anatomy in angiography and operation notes of TOF patients since 2005 to 2017 were evaluated. The sensitivity and specificity of the two common root Aortogram views including the left anterior oblique/cranial (LAO/CRA) and left anterior oblique/caudal (LAO/CAU) were determined.Results 451 patients with the median age of 28 months (3-432 months) were included. All patients had LAO/CRA views and 199 patients had both LAO/CRA and LAO/CAU views. The rate of coronary abnormalities reported by surgery was 8%, and abnormal origin of the left anterior descending artery from the right coronary artery was the most common reported anomaly (4.4%). The sensitivity of the LAO/CAU view was 100%, but LAO/CRA view was about 75% in detecting abnormal coronary configuration. Both of them had excellent specificity (~100%). No significant sex difference was seen between different coronary anatomy abnormalities.Conclusion The Caudal root angiogram is an essential view to evaluate coronary artery anatomy in TOF patients and it seems that there is no need for other views like lateral view, but relying on LAO/CRA view alone may lead to significant misdiagnosis of the coronary arteries, crossing the right ventricular outflow tract (RVOT).

A novel model for predicting intravenous immunoglobulin-resistance in Kawasaki disease: a large cohort study

“…At present, researchers in many countries and regions have established region-specific predictive scoring systems based on the clinical data of children with KD. However, owing to the small sample size in these studies, the choice of modeling methods, and the lack of internal and external validation, the sensitivity and specificity of prediction models either do not meet clinical expectations or cannot be applied in different populations (5)(6)(7)(8)(9). Therefore, establishing a scoring model with a large sample size, reasonable modeling approach and strong predictive ability based on internal and external validation is essential.…”