| 吴梦云,李炜,张华东,等.人工智能识别60Co γ射线照射诱导人外周血微核的剂量-效应曲线建立[J].中华放射医学与防护杂志,2024,44(1):7-12.Wu Mengyun,Li Wei,Zhang Huadong,et al.Establishing a dose-response curve for 60Co γ-ray irradiation-induced micronuclei in human peripheral blood cells using artificial intelligence-based color recognition[J].Chin J Radiol Med Prot,2024,44(1):7-12 |
| 人工智能识别60Co γ射线照射诱导人外周血微核的剂量-效应曲线建立 |
| Establishing a dose-response curve for 60Co γ-ray irradiation-induced micronuclei in human peripheral blood cells using artificial intelligence-based color recognition |
| 投稿时间：2023-05-22 |
| DOI：10.3760/cma.j.cn112271-20230522-00156 |
| 中文关键词: 人工智能 剂量-效应曲线 松弛素B阻断微核法 人外周血 |
| 英文关键词:Artificial intelligence Dose-response curve Cytochalasin B blocking micronucleus method Human peripheral blood |
| 基金项目:重庆市自然科学基金(CSTB2022NSCQ-MSX1220);重庆市科卫联合医学科研项目(2022QNXM030,2022ZDXM034) |
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| 中文摘要: |
| 目的 根据扫描显微镜搭配玻片扫描软件(Metafer 4),在松弛素B(CB)阻断微核法试验中识别和鉴定微核,建立60Co γ射线照射剂量与人外周血淋巴细胞微核率的剂量-效应曲线。方法 采集4名健康人(2男2女)肘静脉血样品,用0、0.25、0.5、1、2、3、4和5 Gy 60Co γ射线(剂量率0.74 Gy/min)离体照射,胞质分裂阻断微核法培养、收获和制备标本玻片,人工智能彩色识别分析系统分析并记录双核细胞和微核数。应用CABAS 软件拟合基于微核率的剂量-效应曲线。2份照射后的盲样进行生物剂量估算验证。结果 在0~5 Gy 剂量范围内,拟合的微核剂量-效应曲线符合二次多项式模型,回归方程为y=0.0321D2+0.0237D+0.0127(R2=0.998,D为剂量)。用拟合曲线对验证样本的剂量估算结果与实际照射剂量基本接近。结论 成功建立基于人工智能识别微核的剂量-效应曲线,为估算辐射生物剂量提供了可行方法。 |
| 英文摘要: |
| Objective To identify micronuclei through the cytochalasin B blocking micronucleus method-based assay using scanning microscope, combined with the slide scanning software Metafer 4 and, accordingly, to establish a dose-response relationship between the dose of 60Co γ-rays and the frequency of micronuclei in human peripheral blood lymphocytes using artificial intelligence-based color recognition. Methods Blood samples were collected from four healthy individuals (two men and two women) and were then exposed to varying doses of 60Co γ-ray radiation (0, 0.25, 0.5, 1, 2, 3, 4, 5 Gy) at a dosage rate of 0.74 Gy/min. Micronucleus slides were prepared as per the GBZ 128-2023 standard. The numbers of binuclear cells and micronuclei were recorded using an artificial intelligence-based color recognition analysis system. The dose-response curve was determined through fitting using the CABAS software. Then, the doses to both independent samples were estimated based on the curve. Results Within a dose range of 0 to 5 Gy, the fitted micronucleus dose-response curve aligned with a quadratic polynomial model, with a regression equation of y= 0.0321D2+0.0237D+0.0127 (D denoting the dose, correlation coefficient R2=0.998). The dose estimations from the validation samples closely corresponded to the actual irradiation doses. Conclusions Establishing the micronucleus dose-response curve provides a feasible method and basis for the rapid and accurate estimation of radiation biological doses in laboratory automation. |
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