Medical Education Management ›› 2025, Vol. 11 ›› Issue (6): 689-695.doi: 10. 3969/j. issn. 2096-045X. 2025. 06. 011

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Application of AI-assisted reconstruction in head and neck CT angiography in medicalimaging technology professional practice teaching

Zhao Cheng, Zheng Chong, Li Ruili, Lu Jie*   

  1. Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing100053, China
  • Received:2025-06-20 Revised:2025-09-23 Online:2025-12-20 Published:2026-01-15

Abstract: Objective To explore the application value of the artificial intelligence (AI) -assisted reconstruction teachingmode in head and neck Computed angiography (CTA) in improving the teaching of CT angiography scanning andreconstruction techniques for students majoring in imaging technology. Methods A total of 15 medical imaging technologystudents who interned in tomography from January 2022 to March 2023 were included in the control group and trained usingtraditional teaching methods, while 17 medical imaging technology students who interned in tomography from January 2024to March 2025 were included in the experimental group and were first self-taught with AI and then received standardized teaching training. The teaching effects of the two groups were evaluated through theoretical tests, practical scanningoperation tests, vascular reconstruction skills tests, and satisfaction surveys. Results Overall, the experimental groupscored significantly higher than the control group in theoretical assessment, practical scanning operation, and vascular postprocessing reconstruction skills (P<0. 001), and the post-processing reconstruction time was shorter than that of the controlgroup (P<0. 01). In the detailed post-processing skill assessment items such as head and neck vessel localization,anatomical structure identification, specific lesion description, stenosis degree evaluation, artifact recognition and analysis,and vascular reconstruction time, the scores of the experimental group were also significantly higher than those of the controlgroup (P<0. 01). Meanwhile, the satisfaction score of the experimental group was significantly higher than that of thecontrol group (96. 35±1. 17 vs. 81. 60±1. 50, P<0. 001). Students in the experimental group also provided feedback thatthis teaching model was helpful in improving the anatomical understanding of blood uessels in the head and neck region,enhancing learning interest, improving learning efficiency, and enhancing professional skills. Conclusion The AI-assistedteaching mode can effectively enhance students' mastery of head and neck CTA operation and vascular reconstruction skills,but it cannot replace traditional teaching methods. Only by effective combination of the two can provide favorable supportfor the teaching practice of medical imaging technology.

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