Han Haegin, Streitmatter Seth W, Kitahara Cari M, Lee Choonsik
Radiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Rockville, Maryland, USA.
Medical Imaging Physics and Radiation Safety, Department of Radiology and Imaging Sciences, University of Utah Health, Salt Lake City, Utah, USA.
Med Phys. 2025 Apr;52(4):2551-2559. doi: 10.1002/mp.17667. Epub 2025 Feb 5.
In fluoroscopy, particularly fluoroscopically guided interventions (FGIs), accurate estimation of peak skin dose (PSD) is crucial for identifying potential radiation-induced skin injuries. Most current methodologies for PSD calculation methods rely on analytical methods, which may introduce uncertainty due to their limited consideration of the complexities of x-ray beam conditions, patient geometry, and positioning. Methods based on full Monte Carlo (MC) simulations can enhance accuracy, but their practical application is limited due to the intensive requirement of computational resources and time.
We aimed to develop a novel method that combines MC simulation with a noise reduction technique to calculate PSD, as well as skin dose distributions, more efficiently and accurately. The goal was to overcome the limitations of current methods, providing a more practical solution for clinical and academic use.
Our method to calculate the PSD and skin dose distributions consists of two steps of rough MC simulation and iterative noise reduction. The performance of the methodology was demonstrated for six fluoroscopy scenarios, with results compared against those from full MC simulation with high particle history, which is considered a gold standard for radiation dosimetry relative to conventional analytical methods.
Our method was demonstrated for various fluoroscopy scenarios, and the result showed that the iterative noise reduction procedure successfully estimates PSD and skin dose distribution for rough MC simulations with a maximum dose statistical error of up to 20%. For successful dose estimations, PSD discrepancies from the values obtained by full MC simulation were within 3%, and voxel-wise dose differences in skin dose distributions were less than 10% of the average skin dose. The computation time of our method was on the order of a few seconds on a personal computer, which is estimated to be at least 10 times faster than full MC simulation when using the same computing resources.
Our method rapidly and accurately calculates PSD and skin dose distribution, making it a useful tool for research and clinical applications. The planned integration of our method into the National Cancer Institute Dosimetry System for Radiography and Fluoroscopy (NCIRF) will enhance accessibility. Additionally, future upgrades of NCIRF will include a comprehensive phantom library and pregnant phantoms that will enable our method to account for patient-specific body shapes, further improving the accuracy and personalization in dose assessments.
在荧光透视检查中,尤其是在荧光透视引导下的介入操作(FGIs)中,准确估算皮肤峰值剂量(PSD)对于识别潜在的辐射性皮肤损伤至关重要。当前大多数PSD计算方法依赖于解析方法,由于这些方法对X射线束条件、患者体型和体位的复杂性考虑有限,可能会引入不确定性。基于全蒙特卡罗(MC)模拟的方法可以提高准确性,但由于对计算资源和时间的强烈需求,其实际应用受到限制。
我们旨在开发一种将MC模拟与降噪技术相结合的新方法,以更高效、准确地计算PSD以及皮肤剂量分布。目标是克服现有方法的局限性,为临床和学术应用提供更实用的解决方案。
我们计算PSD和皮肤剂量分布的方法包括粗略MC模拟和迭代降噪两个步骤。该方法在六种荧光透视场景下进行了性能验证,并将结果与具有高粒子历史的全MC模拟结果进行了比较,相对于传统解析方法,全MC模拟被认为是辐射剂量测定的金标准。
我们的方法在各种荧光透视场景下得到了验证,结果表明,迭代降噪程序成功地估算了粗略MC模拟的PSD和皮肤剂量分布,最大剂量统计误差高达20%。对于成功的剂量估算,与全MC模拟获得的值相比,PSD差异在3%以内,皮肤剂量分布中的体素剂量差异小于平均皮肤剂量的10%。我们方法的计算时间在个人计算机上约为几秒,估计在使用相同计算资源时比全MC模拟快至少10倍。
我们的方法能够快速、准确地计算PSD和皮肤剂量分布,使其成为研究和临床应用的有用工具。计划将我们的方法集成到美国国家癌症研究所放射摄影和荧光透视剂量测定系统(NCIRF)中将提高其可及性。此外,NCIRF未来的升级将包括一个综合体模库和孕妇体模,这将使我们的方法能够考虑患者特定的体型,进一步提高剂量评估的准确性和个性化程度。