Optimising image-guidance frequency for patients treated with volumetric-modulated arc therapy for pelvic cancer

Abstract

Aim: To determine the feasibility of non-daily image-guided radiotherapy (RT) with volumetric-modulated arc therapy for pelvic cancer. Methods: Daily cone beam computed tomography (CBCT) images data of 21 patients (542 fractions) with pelvic cancer were used to simulate 5 non-daily imaging (DL) protocols (Alternate day: AD, First 5 + Weekly: FF+WL, Weekly: WL, First 5 fractions: FF and Alternate week: AW protocol). The residual errors in the lateral (X), longitudinal (Y), and vertical (Z) directions and 3D vector shifts of each non-DL protocol were explored. The planning target volume (PTV) margins were calculated using the van Herk's formula according to population systematic and random error. Finally, the average time of each process from the start to stop of the treatment was used to calculate the number of patients treated per day to assess the treatment delivery capacity for different imaging protocols. Results: The 3D vector shift for the FF+WL protocol produced the greatest proportion of residual error ≤ 0·5 cm and showed the smallest random error in all three directions. However, the FF protocol produced the greatest proportion of residual error > 0·5 cm and revealed the largest magnitudes of systematic error in all three directions. Only the AD protocol can explore the PTV margin of less than 0·5 cm in all three directions. The AW protocol showed the maximum capacity of the treatment delivery, showed the highest number of patients treated per day. In contrast, the AW protocol also affects the treatment accuracy, showed the large residual error and PTV margin. Findings: Reducing the frequency of image-guided RT results in a high residual error. Non-daily image-guided RT strategies for pelvic irradiation should be applied for margins more than 0·5 cm. The number of patients treated per day, residual error and PTV margin are information to determine non-daily protocol applications that balance treatment delivery capacity and treatment accuracy.