Frontiers in public health · 2025
Predictive modeling of eye lens dose in interventional radiology: a polynomial regression approach to cumulative fluoroscopy dose.
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Wu Mengyun, Yuan Fang, Gu Yeqing, Wang Jinhan, Lu Lin, Zeng Zhi
Аннотация
OBJECTIVES: This study aimed to investigate the relationship between cumulative fluoroscopy dose and eye lens radiation dose among interventional radiologists, and to develop a predictive model to enhance occupational radiation safety.
METHODS: We collected data from interventional radiologists, focusing on cumulative fluoroscopy dose during procedures and corresponding eye lens doses. A quadratic polynomial regression model was developed to assess the non-linear relationship between cumulative fluoroscopy dose and eye lens dose. The study involved the use of machine-generated cumulative dose data and personal eye lens dosimeters.
RESULTS: The quadratic polynomial regression model effectively captured the non-linear relationship for cumulative doses >20 Gy, enabling precise dose prediction at higher exposure levels where cataract risks escalate. However, the model showed limited accuracy for doses ≤ 20 Gy. This model allowed for more precise prediction of eye lens dose, particularly at higher exposure levels where the risks of radiation-induced cataracts increase significantly.
CONCLUSIONS: The quadratic polynomial regression model serves as a potentially valuable tool for real-time monitoring in high-exposure scenarios (>20 Gy), supporting radiation safety protocols in clinical practice. Integration into routine hospital systems may enhance radiation protection protocols and inform policy development, aligning occupational dose monitoring practices with international safety standards.
METHODS: We collected data from interventional radiologists, focusing on cumulative fluoroscopy dose during procedures and corresponding eye lens doses. A quadratic polynomial regression model was developed to assess the non-linear relationship between cumulative fluoroscopy dose and eye lens dose. The study involved the use of machine-generated cumulative dose data and personal eye lens dosimeters.
RESULTS: The quadratic polynomial regression model effectively captured the non-linear relationship for cumulative doses >20 Gy, enabling precise dose prediction at higher exposure levels where cataract risks escalate. However, the model showed limited accuracy for doses ≤ 20 Gy. This model allowed for more precise prediction of eye lens dose, particularly at higher exposure levels where the risks of radiation-induced cataracts increase significantly.
CONCLUSIONS: The quadratic polynomial regression model serves as a potentially valuable tool for real-time monitoring in high-exposure scenarios (>20 Gy), supporting radiation safety protocols in clinical practice. Integration into routine hospital systems may enhance radiation protection protocols and inform policy development, aligning occupational dose monitoring practices with international safety standards.