BackgroundThe development of a dose-volume-histogram (DVH) estimation model for knowledge-based planning is very time-consuming and it could be inefficient if it was only used for similar upcoming cases as supposed. It is clinically desirable to explore and validate other potential applications for a configured model. This study tests the hypothesis that a supine volumetric modulated arc therapy (VMAT) model can optimize intensity modulated radiotherapy (IMRT) plans of other patient setup orientations.MethodsBased on RapidPlan, a DVH estimation model was trained using 81 supine VMAT rectal plans and validated on 10 similar cases to ensure the robustness of its designed purpose. Attempts were then made to apply the model to re-optimize the dynamic MLC-sequences of the duplicated IMRT plans from 30 historical patients (20 prone and 10 supine) that were treated with the same prescription as for the model (50.6 and 41.8 Gy to 95 % of PGTV and PTV simultaneously/22 fractions). The performance of knowledge-based re-optimization and the impact of setup orientations were evaluated dosimetrically.ResultsThe VMAT model validation on similar cases showed comparable target dose distribution and significantly improved organ sparing (by 10.77 ~ 18.65 %) than the original plans. IMRT plans of either setup can be re-optimized using the supine VMAT model, which significantly reduced the dose to the bladder (by 25.88 % from 33.85 ± 2.96 to 25.09 ± 1.32 Gy for D50 %; by 22.77 % from 33.99 ± 2.77 to 26.25 ± 1.22 Gy for mean dose) and femoral head (by 12.27 % from 15.65 ± 3.33 to 13.73 ± 1.43 Gy for D50 %; by 10.09 % from 16.26 ± 2.74 to 14.62 ± 1.10 Gy for mean dose), all P < 0.01. Although the dose homogeneity and PGTV conformity index (CI_PGTV) changed slightly (≤0.01), CI_PTV of IMRT plans was significantly increased (Δ = 0.17, P < 0.01) by the manually defined target-objectives in the VMAT optimizer. The semi-automated IMRT planning increased the global maximum dose and V107 % due to the missing of hot spot suppression by specific manual optimizing or fluence map editing.ConclusionsThe Varian RapidPlan model trained on a technique and orientation can be used for another. Knowledge-based planning improves organ sparing and quality consistency, yet the target-objectives defined for VMAT-optimizer should be readapted to IMRT planning, followed by manual hot spot processing.

A kinetic modeling analysis was performed on hepatocellular carcinoma (HCC) as well as healthy liver tissue regions from dynamic FDG positron emission tomographys/computer tomography (PET/CT) cans. On basis of image derived input function from hepatic artery and portal vein, various kinetic models were compared among each other in order to check whether HCC can be classified and differ from healthy tissue within the kinetic parameters. 14 HCC and 10 healthy liver regions from FDG PET/CT scans of ten patients were analyzed from their time activity curves (TACs) were extracted from the PET dynamic images. Also the hepatic artery and the portal vein were delineated in the fused PET/CT images, which were used as input functions. Four kinetic models were applied to the TACs, using both or only one input function. Results were analyzed with several information criteria according to Akaike and Schwartz as well as be the F-Test. The paired student’s t-test was used to determine the differences between HCC and healthy regions. All applied models revealed significant differences of p   <  0.01 of k3 between HCC and healthy liver and three out of four models produced almost identical values for k3  =  0.03 min−1 and Ki  =  0.03 min−1. According to the information criteria tests, a simple two-tissue model with only a venous input function is clearly preferred in case of HCC TACs. After dividing all HCC regions into two groups having a low and a high HCC-to-healthy ratio, respectively, this model also showed significant differences of k3 between these two groups. In conclusion, results indicate that the portal vein is sufficient to describe kinetic FDG processes in HCC and healthy liver regions.

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BackgroundPoleStar m660 is a newly developed clinical PET/CT system with time-of-flight (TOF) capability. The aim of this study is to characterize the performance of the new system. Spatial resolution, sensitivity, scatter fraction, and noise equivalent count rate (NECR) were measured on the scanner according to the NEMA NU 2-2012 protocol. The timing resolution was measured using a rotating line source that orbited around the center of field of view (CFOV) at a radius of 20 cm. The image quality phantom was also imaged to quantify the percent contrast, percent background variability, and residual error. The impacts of data acquisition time and bed overlap on the PET image quality were also evaluated using phantom and patient studies.ResultsThe transverse (axial) spatial resolutions were 3.59 mm (3.67), 4.08 mm (4.65), and 5.32 mm (6.48) full width at half maximum (FWHM) at 1 cm, 10 cm, and 20 cm, respectively, off the CFOV. The measured sensitivity was 10.7 cps/kBq at the CFOV and 10.4 cps/kBq at 10 cm off the CFOV. The peak NECR was 216.7 kcps at an activity concentration of 29.1 kBq/ml, and the scatter fraction was 38.2%. An average of 435 ps FWHM timing resolution was measured. For the image quality phantom, the contrast recovery ratios ranged from 33.9 to 76.4%, while the background variability ranged from 4.7 to 2.0%. In the preliminary clinical study, no noticeable difference in the image quality was observed when the scan time for the whole body and brain was reduced to 1 min/bed and 3 min, respectively. The tested 21% bed overlap showed no significant difference in the image quality compared with the default 38% bed overlap setting.ConclusionsThe physical performances of the PoleStar m660 PET/CT system showed good sensitivity, count rate performance, and timing resolution. The improved performance could help to reduce the acquisition time and bed overlap in the clinical application without detectable compromise in the image quality.

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