Feasibility study on automatic dicentric chromosome detection and dose estimation using an artificial intelligence-based chromosome image scanning and processing system
10.13491/j.issn.1004-714X.2025.04.017
- VernacularTitle:人工智能染色体图像扫描处理系统自动检测dic估算剂量的可行性探讨
- Author:
Junchao FENG
1
;
Chang LIU
1
;
Yulong LIU
1
;
Jie LI
2
;
Yu GAO
2
Author Information
1. The Second Affiliated Hospital of Soochow University, Suzhou 215004, China.
2. The Third People’s Hospital of Henan Province, Henan Occupational Disease Hospital, Henan Key Laboratory of Medicine on Radiobiology and Epidemiology, Zhengzhou 450052, China.
- Publication Type:OriginalArticles
- Keywords:
Artificial intelligence;
Automatic chromosome aberration analysis;
High throughput;
Biological dose estimation
- From:
Chinese Journal of Radiological Health
2025;34(4):571-577
- CountryChina
- Language:Chinese
-
Abstract:
Objective To compare the results obtained from an artificial intelligence (AI)-based chromosome image scanning and processing system, the Metafer 4 chromosome scanning and analysis system, and manual analysis of dicentric chromosomes, and to explore the feasibility of applying AI technology for dicentric chromosome detection and biological dose estimation. Methods Healthy human elbow vein blood was collected and subjected to 60Co in vitro irradiation. Chromosome samples were prepared using conventional methods. The slides were scanned and automatically analyzed using the AI-based system and the Metafer 4 system. The results were manually analyzed and confirmed. Results The number of cells was comparable between the AI-based system and the Metafer 4 system. However, the scanning speed of the AI-based system was 4.5 seconds per image, which was significantly faster than the 7.3 seconds per image of the Metafer 4 system (t = −6.19, P < 0.05). At a confidence level of 0.7, the AI-based system demonstrated a true positive rate of 96.7% and a false positive rate of 6.5%, which were significantly better than the true positive rate (45.4%-54.5%) and false positive rate (22.2%-29.2%) of the Metafer 4 system (all P < 0.05). In the biological dose estimation, the deviation of the dose-response curve was ≤ ± 10% in the automatic analysis using the Metafer 4 system. Due to the use of the manual dose-response curve, the deviation of the AI-based System was ≤ ± 15%. However, there were no significant differences in the estimated doses when the two systems were compared with the manual analysis (P > 0.05). Conclusion Both the AI-based chromosome image scanning and processing system and the Metafer 4 chromosome scanning and analysis system greatly improved the analysis speed of chromosome aberrations. However, the scanning speed, true positive rate, and false positive rate of the AI-based system were superior to those of the Metafer 4 system. Therefore, the AI-based system is more suitable for rapid and high-throughput biological dose estimation in large-scale radiation accidents.
