Abstract
Purpose: The aim of our study is to investigate the ability of preoperative and follow-up multi-detector row CT angiography (MDCTA) in evaluating interrupted aortic arch (IAA).
Materials and Methods: MDCTA and echocardiography (ECHO) were performed preoperatively and postoperatively in nine patients (6 males and 3 females, average age: 4.7 years) with surgically confirmed IAA. The preoperative and follow-up images were analyzed retrospectively and compared with operative findings.
Results: Of the nine IAA cases, eight were type A, and one was type B. All cases were diagnosed correctly by MDCTA with 100% sensitivity. The MDCTA findings were highly concordant with the operative findings as well as with the various combined cardiac anomalies, including patent ductus arteriosus (PDA) (N=7); ventricular septal defect (VSD) (N=6); double outlet right ventricle and atrial septal defect (ASD) (N=1); aortopulmonary window and right pulmonary artery arising from the ascending aorta (N=1); and abnormal enlarged collateral vessels connecting with the descending aorta and enlarged internal mammary artery without PDA, ASD or VSD (N=2; ages 15 and 13 years old). Only five patients correctly diagnosed by ECHO with 56% sensitivity, two were misdiagnosed with coarctation of the aorta (CoA), and the remaining two were missed diagnoses. In the follow-up period, descending aorta saccular aneurysm combining thrombus at the distal end of the stoma was found in one case by MDCTA but missed by ECHO, and this MDCTA finding was further confirmed by operative findings. No postoperative complications were found in the other cases.
Conclusions: MDCTA can display the pathological anatomy of IAA and its combined malformations in a reliable manner. With an improved detection rate of malformations compared with that of ECHO, MDCTA may have high diagnostic value in detecting IAA and its postoperative complications.
Keywords: Echocardiography, interrupted aortic arch, multi-detector row CT angiography.
Graphical Abstract
Call for Papers in Thematic Issues
Intelligent Information Retrieval for Multispectral and Hyperspectral Imaging
Multispectral and hyperspectral imaging is an interdisciplinary research area, widely focuses on spectral, spatial, and temporal data. It offers a plethora of opportunities to efficiently analyze the vast area of the earth's surface. However, there are numerous factors such as dimensionality and size of the hyperspectral data, lesser training samples, ...read more
Machine and Deep Learning in Medical Image Diagnosis
Medical Image Processing regards a set of methodologies that have been developed over recent years with the purpose of improving medical image quality, improving medical data visualization, understanding, and assisting medical diagnosis, and so on. The application of machine and deep learning methods in sensing and imaging can potentially have ...read more
Quantum Machine Learning for Medical Data and Imaging
Quantum computing has promised a significant speedup in certain computationally intensive tasks that are intractable on classical computers. Researchers in quantum machine learning, such as those working in computer vision, image processing, biomedical analysis, and related topics, may play an important role in comprehending and working on complicated medical data, ...read more
20
4