Pattern recognition for prenatal sonographic diagnosis of most congenital heart disease: the “7×2” CHD algorithm
Year: 2024
Type: article
Study design: Observational Study
Abstract: Background: Congenital heart defects (CHD) are common anomalies and are commonly missed prenatally because of the difficult learning curve of fetal echocardiography. The aim study was to establish an algorithm to review most of the fetal CHD using a simple pattern recognition that will provide easy approach for their diagnosis. To our best knowledge this is the first algorithm that gather the salient sonographic features of most CHD. Methods: We had reviewed 66 cases of CHD that were gathered by one tertiary center from January 2020 till December 2023. We used an algorithmic path to allow easy deferential diagnosis of these anomalies by using certain sonographic features (we call them: altered key points). This work reviewed 14 fetal CHD. After exclusion of isolated ventricular septal defect (VSD). Results: Each 2 of these CHD has a common altered key point during echocardiography. These 7 key points are: right dominance, left dominance, absent crossover of great arteries, aorta override VSD, abnormal crux, abnormal area behind the heart and abnormal three vessels trachea view. These 14 anomalies were grouped in tables with their salient sonographic markers for easy mind mapping during echocardiography. Conclusions: The “7×2” CHD algorithm is a simple way that allow easy recognition of 14 fetal CHD by focusing on 7 altered key points that can be recognized on the common sonographic views where each of them has 2 main differential diagnosis. These 14 anomalies represents most of the CHD (78%) after exclusion of isolated VSD.
Author: Ahmed Elhabashy
Institution: Alexandria University
Language: English
Subfield: Epidemiology
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W4402068981