Purpose: To overcome the imaging artifacts and Hounsfield unit inaccuracy limitations of cone-beam computed tomography, a conditional generative adversarial network is proposed to synthesize high-quality computed tomography-like images from cone-beam computed tomography images. Methods: A total of 120 paired cone-beam computed tomography and computed tomography scans of patients with head and neck cancer who were treated during January 2019 and December 2020 retrospectively collected; the scans of 90 patients were assembled into training and validation datasets, and the scans of 30 patients were used in testing datasets. The proposed method integrates a U-Net backbone architecture with residual blocks into a conditional generative adversarial network framework to learn a mapping from cone-beam computed tomography images to pair planning computed tomography images. The mean absolute error, root-mean-square error, structural similarity index, and peak signal-to-noise ratio were used to assess the performance of this method compared with U-Net and CycleGAN. Results: The synthesized computed tomography images produced by the conditional generative adversarial network were visually similar to planning computed tomography images. The mean absolute error, root-mean-square error, structural similarity index, and peak signal-to-noise ratio calculated from test images generated by conditional generative adversarial network were all significantly different than CycleGAN and U-Net. The mean absolute error, root-mean-square error, structural similarity index, and peak signal-to-noise ratio values between the synthesized computed tomography and the reference computed tomography were 16.75 ± 11.07 Hounsfield unit, 58.15 ± 28.64 Hounsfield unit, 0.92 ± 0.04, and 30.58 ± 3.86 dB in conditional generative adversarial network, 20.66 ± 12.15 Hounsfield unit, 66.53 ± 29.73 Hounsfield unit, 0.90 ± 0.05, and 29.29 ± 3.49 dB in CycleGAN, and 16.82 ± 10.99 Hounsfield unit, 58.68 ± 28.34 Hounsfield unit, 0.92 ± 0.04, and 30.48 ± 3.83 dB in U-Net, respectively. Conclusions: The synthesized computed tomography generated from the cone-beam computed tomography-based conditional generative adversarial network method has accurate computed tomography numbers while keeping the same anatomical structure as cone-beam computed tomography. It can be used effectively for quantitative applications in radiotherapy.

This study aims to propose a novel treatment planning methodology for multi-isocenter volumetric modulated arc therapy (VMAT) craniospinal irradiation (CSI) using the special feasibility dose–volume histogram (FDVH)-guided auto-planning (AP) technique. Three different multi-isocenter VMAT -CSI plans were created, including manually based plans (MUPs), conventional AP plans (CAPs) and FDVH-guided AP plans (FAPs). The CAPs and FAPs were specially designed by combining multi-isocenter VMAT and AP techniques in the Pinnacle treatment planning system. Specially, the personalized optimization parameters for FAPs were generated using the FDVH function implemented in PlanIQ software, which provides the ideal organs at risk (OARs) sparing for the specific anatomical geometry based on the valuable assumption of the dose fall-off. Compared to MUPs, CAPs and FAPs significantly reduced the dose for most of the OARs. FAPs achieved the best homogeneity index (0.092 ± 0.013) and conformity index (0.980 ± 0.011), while CAPs were slightly inferior to the FAPs but superior to the MUPs. As opposed to MUPs, FAPs delivered a lower dose to OARs, whereas the difference between FAPs and CAPs was not statistically significant except for the optic chiasm and inner ear_L. The two AP approaches had similar MUs, which were significantly lower than the MUPs. The planning time of FAPs (145.00 ± 10.25 min) was slightly lower than that of CAPs (149.83 ± 14.37 min) and was substantially lower than that of MUPs (157.92 ± 16.11 min) with P < 0.0167. Overall, introducing the multi-isocenter AP technique into VMAT-CSI yielded positive outcomes and may play an important role in clinical CSI planning in the future.

Background: To compare the dosimetric normal tissue complication probability (NTCP), secondary cancer complication probabilities (SCCP), and excess absolute risk (EAR) differences of volumetric modulated arc therapy (VMAT) and intensity-modulated radiation therapy (IMRT) for left-sided breast cancer after mastectomy. Methods and materials: Thirty patients with left-sided breast cancer treated with post-mastectomy radiation therapy (PMRT) were randomly enrolled in this study. Both IMRT and VMAT treatment plans were created for each patient. Planning target volume (PTV) doses for the chest wall and internal mammary nodes, PTV1, and PTV of the supraclavicular nodes, PTV2, of 50 Gy were prescribed in 25 fractions. The plans were evaluated based on PTV1 and PTV2 coverage, homogeneity index (HI), conformity index, conformity number (CN), dose to organs at risk, NTCP, SCCP, EAR, number of monitors units, and beam delivery time. Results: VMAT resulted in more homogeneous chest wall coverage than did IMRT. The percent volume of PTV1 that received the prescribed dose of VMRT and IMRT was 95.9 ± 1.2% and 94.5 ± 1.6%, respectively (p < 0.001). The HI was 0.11 ± 0.01 for VMAT and 0.12 ± 0.02 for IMRT, respectively (p = 0.001). The VMAT plan had better conformity (CN: 0.84 ± 0.02 vs. 0.78 ± 0.04, p < 0.001) in PTV compared with IMRT. As opposed to IMRT plans, VMAT delivered a lower mean dose to the ipsilateral lung (11.5 Gy vs 12.6 Gy) and heart (5.2 Gy vs 6.0 Gy) and significantly reduced the V5, V10, V20, V30, and V40 of the ipsilateral lung and heart; only the differences in V5 of the ipsilateral lung did not reach statistical significance (p = 0.409). Although the volume of the ipsilateral lung and heart encompassed by the 2.5 Gy isodose line (V2.5) was increased by 6.7% and 7.7% (p < 0.001, p = 0.002), the NTCP was decreased by 0.8% and 0.6%, and SCCP and EAR were decreased by 1.9% and 0.1% for the ipsilateral lung. No significant differences were observed in the contralateral lung/breast V2.5, V5, V10, V20, mean dose, SCCP, and EAR. Finally, VMAT reduced the number of monitor units by 31.5% and the treatment time by 71.4%, as compared with IMRT. Conclusions: Compared with IMRT, VMAT is the optimal technique for PMRT patients with left-sided breast cancer due to better target coverage, a lower dose delivered, NTCP, SCCP, and EAR to the ipsilateral lung and heart, similar doses delivered to the contralateral lung and breast, fewer monitor units and a shorter delivery time.