BMC Medical Education (Oct 2024)

Dynamic sequential cross-sectional scanning increases detection rate of congenital heart disease in sonographers: a prenatal ultrasound training program

  • Yi Zhou,
  • Yuchen Xie,
  • Min Fan,
  • Jing Wu,
  • Yuanyuan Zhou,
  • Chaoxue Zhang

DOI
https://doi.org/10.1186/s12909-024-06154-y
Journal volume & issue
Vol. 24, no. 1
pp. 1 – 8

Abstract

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Abstract Background Prenatal ultrasound is the preferred modality for diagnosing fetal congenital heart disease. Given issues of physician proficiency and hospital distribution, we propose a dynamic sequential cross-sectional scanning (SCS) to explore the feasibility of cardiac screening by sonographers with less than 5 years of experience in ultrasound. Materials and methods Twenty residents were randomly divided into two groups, receiving training in the American Institute of Ultrasound in Medicine (AIUM) fetal echocardiography and the SCS method. According to the needs of training, the professional staff developed the theoretical knowledge question bank, the CHD ultrasonic video disease bank, and the assessment scale. Trainees completed the pre-training examination, theory and skill operation training, and post-training assessment. For the two groups, the theoretical knowledge, skill operation and disease diagnosis were analyzed statistically before and after training. Results After training, the trainees in both groups had significantly improved knowledge and diagnostic abilities, their diagnostic thinking about CHD was clear, and they could identify major or even all structural abnormalities and make a definite diagnosis. In terms of skill operation, both groups could complete all required scanning within the specified time. The scanning time of the SCS group was significantly lower than that of the AIUM group, and the effect of the receptor site in the AIUM group was significantly higher than that in the SCS group. Conclusion SCS can be used as a new rapid fetal cardiac scanning method and try to popularize among echocardiographer.

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