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The Application of an Anatomical Database for Fetal Congenital Heart Disease
Li Yang, Qiu-Yan Pei1, Yun-Tao Li
1Department of Obstetrics and Gynecology, Peking University People's Hospital, Beijing 100044, China.
Insights
A new 3D fetal congenital heart disease (CHD) database aids in training for fetal echocardiography (FECG). This tool enhances learning of complex cardiac anatomy for improved prenatal diagnosis and physician education.
Area of Science:
- Medical Imaging
- Cardiology
- Medical Education
Background:
- Fetal congenital heart anomalies are the most common congenital anomalies.
- Fetal echocardiography (FECG) is crucial for prenatal diagnosis of congenital heart disease (CHD).
- Current FECG diagnosis rates vary due to challenges in mastering CHD anatomy.
Purpose of the Study:
- To investigate the application of a 3D fetal CHD anatomic database in FECG teaching and training.
- To enhance the accuracy and consistency of antenatal CHD diagnosis.
- To provide a standardized training resource for ultrasound physicians.
Main Methods:
- Evaluation of 60 transverse section databases of 27 fetal CHD types.
- Utilized 3D software (Amira 5.3.1) for database reconstruction and visualization.
- Analysis of database features for FECG continuing education and training applications.
Main Results:
- Successfully rebuilt a dynamic, rotatable 3D fetal CHD anatomy database.
- Database accurately reproduced anatomical structures and spatial relationships of fetal CHDs.
- Established standardized training databases for FECG, enabling centralized and distance education.
Conclusions:
- The 3D fetal CHD database effectively reproduces complex cardiac anatomy and spatial relationships.
- This database serves as a valuable tool for anatomy and FECG teaching and training.
- Facilitates improved understanding and diagnosis of fetal CHD.
Background:
Fetal congenital heart anomalies are the most common congenital anomalies in live births. Fetal echocardiography (FECG) is the only prenatal diagnostic approach used to detect fetal congenital heart disease (CHD). FECG is not widely used, and the antenatal diagnosis rate of CHD varies considerably. Thus, mastering the anatomical characteristics of different kinds of CHD is critical for ultrasound physicians to improve FECG technology. The aim of this study is to investigate the applications of a fetal CHD anatomic database in FECG teaching and training program.
Methods:
We evaluated 60 transverse section databases including 27 types of fetal CHD built in the Prenatal Diagnosis Center in Peking University People's Hospital. Each original database contained 400-700 cross-sectional digital images with a resolution of 3744 pixels × 5616 pixels. We imported the database into Amira 5.3.1 (Australia Visage Imaging Company, Australia) three-dimensional (3D) software. The database functions use a series of 3D software visual operations. The features of the fetal CHD anatomical database were analyzed to determine its applications in FECG continuing education and training.
Results:
The database was rebuilt using the 3D software. The original and rebuilt databases can be displayed dynamically, continuously, and synchronically and can be rotated at arbitrary angles. The sections from the dynamic displays and rotating angles are consistent with the sections in FECG. The database successfully reproduced the anatomic structures and spatial relationship features of different fetal CHDs. We established a fetal CHD anatomy training database and a standardized training database for FECG. Ultrasound physicians and students can learn the anatomical features of fetal CHD and FECG through either centralized training or distance education.
Conclusions:
The database of fetal CHD successfully reproduced the anatomic structures and spatial relationship of different kinds of fetal CHD. This database can be widely used in anatomy and FECG teaching and training.
