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立体定向体部放射治疗中肿瘤体积计算的数学模型与微剂量动力学模型的结合。

Mathematical model combined with microdosimetric kinetic model for tumor volume calculation in stereotactic body radiation therapy.

机构信息

Department of Radiation Oncology, Niigata University Medical and Dental Hospital, 1-757 Asahimachi-dori, Chuo-ku, Niigata-shi, Niigata, Japan.

Department of Medical Physics and Engineering, Osaka University Graduate School of Medicine, 1-7 Yamadaoka, Suita-shi, Osaka, Japan.

出版信息

Sci Rep. 2023 Jul 6;13(1):10981. doi: 10.1038/s41598-023-38232-4.

DOI:10.1038/s41598-023-38232-4
PMID:37414844
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10326039/
Abstract

We proposed a new mathematical model that combines an ordinary differential equation (ODE) and microdosimetric kinetic model (MKM) to predict the tumor-cell lethal effect of Stereotactic body radiation therapy (SBRT) applied to non-small cell lung cancer (NSCLC). The tumor growth volume was calculated by the ODE in the multi-component mathematical model (MCM) for the cell lines NSCLC A549 and NCI-H460 (H460). The prescription doses 48 Gy/4 fr and 54 Gy/3 fr were used in the SBRT, and the effect of the SBRT on tumor cells was evaluated by the MKM. We also evaluated the effects of (1) linear quadratic model (LQM) and the MKM, (2) varying the ratio of active and quiescent tumors for the total tumor volume, and (3) the length of the dose-delivery time per fractionated dose (t) on the initial tumor volume. We used the ratio of the tumor volume at 1 day after the end of irradiation to the tumor volume before irradiation to define the radiation effectiveness value (REV). The combination of MKM and MCM significantly reduced REV at 48 Gy/4 fr compared to the combination of LQM and MCM. The ratio of active tumors and the prolonging of t affected the decrease in the REV for A549 and H460 cells. We evaluated the tumor volume considering a large fractionated dose and the dose-delivery time by combining the MKM with a mathematical model of tumor growth using an ODE in lung SBRT for NSCLC A549 and H460 cells.

摘要

我们提出了一个新的数学模型,将常微分方程(ODE)和微剂量动力学模型(MKM)结合起来,预测立体定向体放射治疗(SBRT)应用于非小细胞肺癌(NSCLC)的肿瘤细胞致死效应。多组分数学模型(MCM)中的 ODE 计算了细胞系 NSCLC A549 和 NCI-H460(H460)的肿瘤生长体积。SBRT 中使用了 48 Gy/4 fr 和 54 Gy/3 fr 的处方剂量,MKM 评估了 SBRT 对肿瘤细胞的影响。我们还评估了(1)线性二次模型(LQM)和 MKM,(2)总肿瘤体积中活跃肿瘤和静止肿瘤比例的变化,以及(3)每个分次剂量的剂量给予时间(t)的长短对初始肿瘤体积的影响。我们使用照射结束后 1 天的肿瘤体积与照射前的肿瘤体积之比来定义放射效能值(REV)。与 LQM 和 MCM 的组合相比,MKM 和 MCM 的组合使 48 Gy/4 fr 时的 REV 显著降低。活跃肿瘤的比例和 t 的延长影响了 A549 和 H460 细胞的 REV 降低。我们通过将 MKM 与使用 ODE 的肿瘤生长数学模型相结合,考虑了大的分次剂量和剂量给予时间,评估了 NSCLC A549 和 H460 细胞的肺 SBRT 中的肿瘤体积。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/508f/10326039/5e213475f54f/41598_2023_38232_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/508f/10326039/133b175a1c83/41598_2023_38232_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/508f/10326039/d63e01779a29/41598_2023_38232_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/508f/10326039/6e932a885f4e/41598_2023_38232_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/508f/10326039/3ddd706e6bb8/41598_2023_38232_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/508f/10326039/5fae0027712f/41598_2023_38232_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/508f/10326039/3019e87da235/41598_2023_38232_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/508f/10326039/3e3ebab8a6f9/41598_2023_38232_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/508f/10326039/5e213475f54f/41598_2023_38232_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/508f/10326039/133b175a1c83/41598_2023_38232_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/508f/10326039/d63e01779a29/41598_2023_38232_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/508f/10326039/6e932a885f4e/41598_2023_38232_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/508f/10326039/3ddd706e6bb8/41598_2023_38232_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/508f/10326039/5fae0027712f/41598_2023_38232_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/508f/10326039/3019e87da235/41598_2023_38232_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/508f/10326039/3e3ebab8a6f9/41598_2023_38232_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/508f/10326039/5e213475f54f/41598_2023_38232_Fig8_HTML.jpg

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