Purpose To evaluate a method for generating virtual four‐dimensional computed tomography (4DCT) from four‐dimensional magnetic resonance imaging (4DMRI) data in carbon ion radiotherapy with pencil beam scanning for abdominal tumors. Methods Deformable image registration is used to: (a) register each respiratory phase of the 4DMRI to the end‐exhale MRI; (b) register the reference end‐exhale CT to the end‐exhale MRI volume; (c) generate the virtual 4DCT by warping the registered CT according to the obtained deformation fields. A respiratory‐gated carbon ion treatment plan is optimized on the planning 4DCT and the corresponding dose distribution is recalculated on the virtual 4DCT. The method was validated on a digital anthropomorphic phantom and tested on eight patients (18 acquisitions). For the phantom, a ground truth dataset was available to assess the method performances from the geometrical and dosimetric standpoints. For the patients, the virtual 4DCT was compared with the planning 4DCT. Results In the phantom, the method exhibits a geometrical accuracy within the voxel size and Dose Volume Histograms deviations up to 3.3% for target V95% (mean dose difference ≤ 0.2% of the prescription dose, gamma pass rate > 98%). For patients, the virtual and the planning 4DCTs show good agreement at end‐exhale (3% median D95% difference), whereas other respiratory phases exhibit moderate motion variability with consequent dose discrepancies, confirming the need for motion mitigation strategies during treatment. Conclusions The virtual 4DCT approach is feasible to evaluate treatment plan robustness against intra‐ and interfraction motion in carbon ion therapy delivered at the abdominal site.

The assessment of left ventricular function, wall motion and myocardial viability using electrocardiogram (ECG)-gated [(18)F]-FDG positron emission tomography (PET) is widely accepted in human and in preclinical small animal studies. The nonterminal and noninvasive approach permits repeated in vivo evaluations of the same animal, facilitating the assessment of temporal changes in disease or therapy response. Although well established, gated small animal PET studies can contain erroneous gating information, which may yield to blurred images and false estimation of functional parameters. In this work, we present quantitative and visual quality control (QC) methods to evaluate the accuracy of trigger events in PET list-mode and physiological data. Left ventricular functional analysis is performed to quantify the effect of gating errors on the end-systolic and end-diastolic volumes, and on the ejection fraction (EF). We aim to recover the cardiac functional parameters by the application of the commonly established heart rate filter approach using fixed ranges based on a standardized population. In addition, we propose a fully reprocessing approach which retrospectively replaces the gating information of the PET list-mode file with appropriate list-mode decoding and encoding software. The signal of a simultaneously acquired ECG is processed using standard MATLAB vector functions, which can be individually adapted to reliably detect the R-peaks. Finally, the new trigger events are inserted into the PET list-mode file. A population of 30 mice with various health statuses was analyzed and standard cardiac parameters such as mean heart rate (119 ms ± 11.8 ms) and mean heart rate variability (1.7 ms ± 3.4 ms) derived. These standard parameter ranges were taken into account in the QC methods to select a group of nine optimal gated and a group of eight sub-optimal gated [(18)F]-FDG PET scans of mice from our archive. From the list-mode files of the optimal gated group, we randomly deleted various fractions (5% to 60%) of contained trigger events to generate a corrupted group. The filter approach was capable to correct the corrupted group and yield functional parameters with no significant difference to the optimal gated group. We successfully demonstrated the potential of the fully reprocessing approach by applying it to the sub-optimal group, where the functional parameters were significantly improved after reprocessing (mean EF from 41% ± 16% to 60% ± 13%). When applied to the optimal gated group the fully reprocessing approach did not alter the functional parameters significantly (mean EF from 64% ± 8% to 64 ± 7%). This work presents methods to determine and quantify erroneous gating in small animal gated [(18)F]-FDG PET scans. We demonstrate the importance of a quality check for cardiac triggering contained in PET list-mode data and the benefit of optionally reprocessing the fully recorded physiological information to retrospectively modify or fully replace the cardiac triggering in PET list-mode data. We aim to provide ...

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Background/Aim: Definitive radiotherapy for bone and soft tissues sarcomas benefits patients deemed unfit for surgery; poor outcomes have been reported with conventional photons, while interesting preliminary results have been described with particle in single-Institution experiences. The aim of the study was to retrospectively evaluate preliminary results of carbon ion radiotherapy (CIRT) in patients with axial bone and soft tissue sarcomas (BSTS) treated with curative intent at the National Center for Oncological Hadrontherapy (CNAO). Patients and Methods: From January 2013 to September 2018, 54 patients with axial BSTS were treated with CIRT at CNAO. Their median age was 50 years (range=19-79 years), males/females=1.4:1. Tumor site was the pelvis in 50% of cases (n=27), thoracic region in 24% (n=13), cervical spine in 15% (n=8) and lumbar in 11% (n=6). A total of 76% (n=41) of patients had primary disease, while 24% (n=13) had recurrent disease. Before CIRT, surgery was performed in 47% of cases, including positive margins (R1) in 8 patients, and macroscopic residual disease (R2) in 17. Histological subtypes were mainly represented by chondrosarcomas in 39% (n=21) of patients and osteosarcomas in 24% (n=13). Pre-treatment chemotherapy was administered in 40% of cases (n=22); no patient received previous radiotherapy. All treatments were performed with active scanning CIRT for a median total dose of , in 16 fractions (4 fractions per week). Results: Median follow-up was 24 months (range=4-61 months). Four patients were lost to follow-up. Acute toxicities were mild, no >G2 event was reported and no

To estimate the impact of dose calculation approaches adopted in different treatment planning systems (TPSs) on proton therapy dose delivered with pencil beam scanning (PBS). Treatment plans for six regular volumes in water and 15 clinical cases were optimized with Syngo-VC13 and exported for forward recalculation with Raystation-V7.0 pencil beam (RS-PBA) and Monte Carlo (RS-MC) algorithms and with the independent Fluka-MC engine. To verify clinical consistency between the two TPS dosimetric outcomes, the average percentage variations of clinical target volume (CTV) D98%, D50% and D2%, adopted for plan prescription and evaluation, were considered. Ionization chamber measurements served as a further reference for comparison in homogeneous conditions. CTV dose volume histogram (DVH) analysis and gamma evaluation with 3 mm—3% agreement criteria quantified the dose deviation of TPS calculation algorithms, in heterogeneous conditions, against the Fluka-MC code. CTV D50%, representing the plan dose prescription goal, was higher on average over H&N cases of (3.9  ±  0.9)% and (2.3  ±  0.6)% as calculated with RS-PBA and RS-MC, respectively, compared to Syngo. For tumors located in the pelvis district, average D50% variations of (1.6  ±  0.7)% and (1.2  ±  0.7)% were found. Syngo underestimated target near maximum doses with respect to all computation systems. Calculation accuracy in heterogeneous conditions of RS-PBA H&N plans resulted poor when a range shifter was required. Target DVH and γ-analysis showed excellent agreement between RS-MC and Fluka-MC, with γ-pass rates  >98% for all patient groups. Different TPS dose calculation approaches mainly affected dose delivered in H&N proton treatments, while minor deviations were found for pelvic tumors. RS-MC proved to be the most accurate TPS dose calculation algorithm when compared to an independent MC simulation code.