Computed Tomography Measurement of the Aorta in Midaortic Syndrome in Children and Adolescents and Their Clinical Manifestations and Outcomes.
Seung Min BaekYoon Seong LeeMi Kyoung SongSang-Yun LeeEun Jung BaeGi-Beom KimPublished in: Pediatric cardiology (2024)
Midaortic syndrome (MAS) presents challenges in diagnosis due to the absence of well-defined diagnostic criteria in pediatric patients. This retrospective study aimed to aid in the diagnosis of MAS by employing computed tomography (CT) to measure the z-score of the aorta as well as to identify and understand its clinical features. CT images, echocardiography findings, and medical records of 17 patients diagnosed with MAS between 1997 and 2023 were reviewed, and z-scores were calculated. Aortic size on follow-up CT, blood pressure, and left ventricular function and hypertrophy at the last follow-up were analyzed, and possible prognostic factors were examined. Except for one patient, all individuals exhibited a z-score below - 2 at the level corresponding to stenosis. Left ventricular dysfunction occurred more frequently in patients aged < 5 years (p = 0.024). Patients with idiopathic MAS showed a better prognosis in terms of blood pressure and follow-up aortic size (p = 0.051 and 0.048, respectively). CT-measured aortic z-scores may be useful for the diagnosis and follow-up of MAS.
Keyphrases
- computed tomography
- left ventricular
- prognostic factors
- dual energy
- image quality
- blood pressure
- aortic valve
- positron emission tomography
- contrast enhanced
- end stage renal disease
- ejection fraction
- pulmonary artery
- magnetic resonance imaging
- heart failure
- chronic kidney disease
- newly diagnosed
- peritoneal dialysis
- hypertrophic cardiomyopathy
- aortic stenosis
- mitral valve
- case report
- pulmonary hypertension
- acute myocardial infarction
- coronary artery
- left atrial
- machine learning
- hypertensive patients
- transcatheter aortic valve replacement
- heart rate
- blood glucose
- metabolic syndrome
- percutaneous coronary intervention
- convolutional neural network
- weight loss
- atrial fibrillation
- adipose tissue