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A mathematical model for predicting the changes of non-small cell lung cancer based on tumor mass during radiotherapy.

Abstract：

:This study aims to build a feasible mathematical model to analyze the mass evolution of NSCLC during standard fractionated radiotherapy. Seventy-three cases of NSCLC who were received radiotherapy with prescription dose of 2 Gy × 30 fx were selected retrospectively and divided into adenocarcinoma (ADC) group and squamous cell carcinoma (SCC) group according to the pathological type. A total of six sets of CT/CBCT images were collected. The tumor masses were measured according to each set of images. We build a mathematical model (Linear Quadratic_Repopulation&Reoxygenation& Dissolution model, LQ_RRD model), which was used to fit the first five sets of measured mass into a smooth curve. By adjusting the model parameters (λ, ν and µ), the optimal fitting results can be obtained. In order to verify the accuracy of model prediction, we measured the mass of the review images (MV, measured values), and found out the estimate point of the corresponding time (EV, estimated value) on the fitting curve. The difference and correlation between MV and EV were compared. It was found that the model could substantially simulate the tumor mass changes during radiotherapy, and it had a good fit to the clinical data (%RMSE-Median = 5.52, %RMSE-Range = [3.19, 10.73]). Comparing the differences of model parameters between ADC and SCC group, there was no significant difference in λ (t = 1.622, p = 0.109), but the difference was significant in ν and µ (z = -7.270, p = 0.000 and t = -10.205, p = 0.000). Moreover, linear correlation analysis showed that there was a linear correlation between MV and EV no matter mass or volume (r = 0.960, p = 0.000 versus r = 0.926, p = 0.000). Nevertheless, the deviation between MV and EV of volume was larger than that of mass (z = -1.897, p = 0.058 versus z = -3.387, p = 0.001), and the deviation was more pronounced in larger tumors. We suggest that this mathematical model is more suitable to predict the tumor mass than volume for NSCLC during radiotherapy.

journal_name

Phys Med Biol

journal_title

Physics in medicine and biology

authors

Chen J,Wang K,Jian J,Zhang W

doi

10.1088/1361-6560/ab47c0

subject

Has Abstract

pub_date

2019-11-26 00:00:00

pages

235006

issue

eissn

0031-9155

issn

1361-6560

journal_volume

pub_type

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A mathematical model for predicting the changes of non-small cell lung cancer based on tumor mass during radiotherapy.