Abstract

Stereotactic body radiotherapy (SBRT) currently adopts non-discriminative prescription regimen. This study attempts to investigate an individualized fraction regimen (IFR) method for SBRT patients with non-small cell lung cancer (NSCLC) based on Uncomplicated and Cancer-free Control Probability (UCFCP). Twenty patients with NSCLC were retrospectively prescribed with forty regimens, ranging from 8Gy×5f to 12Gy×5f in step of 0.1 Gy, and forty plans were correspondingly generated for each of the patients. The dose volume histograms (DVHs) of PTV, total lung, chest wall and rib were extracted from the treatment planning system (TPS) with the resolution of 1cGy. Taking into consideration of the age and the BMI index of each patient as well, the tumor control probability (TCP), the normal tissue complication probability (NTCP) of the total lung, chest wall and rib, and the secondary cancer probability (SCP) of the total lung were calculated for each plan of the patients. For the forty regimens, the UCFCP was calculated and the maximum value of UCFCP was the one corresponding to the IFR of the specified patient. In addition, IFR of UCP approach which only took account of the TCP and NTCP was also derived and to be compared with the IFR based on the UCFCP method. For all the patients, the UCFCP value showed a bell-shaped trend with the change of prescription dose. Among the 20 patients, the IFRs of 16 patients were different from the original fixed regimen. Of the 16 patients, the IFR of five patients exhibited slight changes between UCP and UCFCP methods. The patients with smaller target volume could be benefited from increased fractional dose to some extent, while patients with larger target or with target closer to the chest wall might be better off with properly reduced fractional dose. The method based on the maximum value of UCFCP function may be helpful to provide IFR for specific SBRT patients with NSCLC, differentiating the patient specific characteristics such as anatomical structures and locations, ages and BMI indexes. Further validation in clinical samples is required.

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