Purpose: To test interactive semiautomated methods (ISAM) vs. manual contouring (MC) in segmenting cardiac cine MR images. Materials and Methods:Short-axis images of 10 consecutive patients (1.5-81.5 years of age) were evaluated by a trained radiologist (R1) and a low-trained engineer (R2). Each of them performed four independent reading sessions: two using ISAM and two using MC. Left ventricle (LV) myocardial mass (LVMM), LV ejection fraction (LVEF), and right ventricle (RV) ejection fraction (RVEF) were obtained. Bland-Altman analysis and Wilcoxon test were used. Results:The bias Ϯ 2 standard deviations (SD) of ISAM vs. MC for LVMM (g) was -5.7 Ϯ 13.4 (R1) and -5.5 Ϯ 26.3 (R2); for LVEF (%) it was -1.4 Ϯ 13.0 and -2.9 Ϯ and 6.8; for RVEF (%) it was 2.6 Ϯ 17.0 and 1.0 Ϯ 16.7. Considering both readers/methods, intraobserver bias Ϯ 2 SD ranged from 0.3 Ϯ 25.3 to -6.8 Ϯ 23.0, from 0.2 Ϯ 8.0 to -4.4 Ϯ 15.8, and from -0.0 Ϯ 26.4 to -4.6 Ϯ 27.8, respectively. Interobserver bias Ϯ 2 SD was -25.9 Ϯ 46.0 (ISAM) and 26.1 Ϯ 36.4 (MC), -1.4 Ϯ 8.6 (ISAM) and 0.1 Ϯ 17.9 (MC), and 0.7 Ϯ 23.3 and 2.3 Ϯ 29.8, respectively. Larger SDs were systematically found for RVEF vs. LVEF. Segmentation times: five minutes for LV with ISAM (both readers); for LV with MC, six (R1) vs. nine minutes (R2) (P Ͻ 0.001); five to six minutes for RV (both methods /readers). R2 significantly reduced LV segmentation times from nine (MC) to five minutes (ISAM) (P Ͻ 0.001). Conclusion:A highly reproducible LV segmentation was performed in a short time by R1. The advantage of ISAM vs. MC for LV segmentation was a time saving only for R2. For RVEF, a lower reproducibility was observed for both methods and readers.

Morphological changes that may arise through a treatment course are probably one of the most significant sources of range uncertainty in proton therapy. Non-invasive in-vivo treatment monitoring is useful to increase treatment quality. The INSIDE in-beam Positron Emission Tomography (PET) scanner performs in-vivo range monitoring in proton and carbon therapy treatments at the National Center of Oncological Hadrontherapy (CNAO). It is currently in a clinical trial (ID: NCT03662373) and has acquired in-beam PET data during the treatment of various patients. In this work we analyze the in-beam PET (IB-PET) data of eight patients treated with proton therapy at CNAO. The goal of the analysis is twofold. First, we assess the level of experimental fluctuations in inter-fractional range differences (sensitivity) of the INSIDE PET system by studying patients without morphological changes. Second, we use the obtained results to see whether we can observe anomalously large range variations in patients where morphological changes have occurred. The sensitivity of the INSIDE IB-PET scanner was quantified as the standard deviation of the range difference distributions observed for six patients that did not show morphological changes. Inter-fractional range variations with respect to a reference distribution were estimated using the Most-Likely-Shift (MLS) method. To establish the efficacy of this method, we made a comparison with the Beam’s Eye View (BEV) method. For patients showing no morphological changes in the control CT the average range variation standard deviation was found to be 2.5 mm with the MLS method and 2.3 mm with the BEV method. On the other hand, for patients where some small anatomical changes occurred, we found larger standard deviation values. In these patients we evaluated where anomalous range differences were found and compared them with the CT. We found that the identified regions were mostly in agreement with the morphological changes seen in the CT scan.

Objective Verification of delivered proton therapy treatments is essential for reaping the many benefits of the modality, with the most widely proposed in vivo verification technique being the imaging of positron emitting isotopes generated in the patient during treatment using positron emission tomography (PET). The purpose of this work is to reduce the computational resources and time required for simulation of patient activation during proton therapy using the GPU accelerated Monte Carlo code FRED, and to validate the predicted activity against the widely used Monte Carlo code GATE. Approach We implement a continuous scoring approach for the production of positron emitting isotopes within FRED version 5.59.9. We simulate treatment plans delivered to 95 head and neck patients at Centrum Cyklotronowe Bronowice using this GPU implementation, and verify the accuracy using the Monte Carlo toolkit GATE version 9.0. Main results We report an average reduction in computational time by a factor of 50 when using a local system with 2 GPUs as opposed to a large compute cluster utilising between 200 to 700 CPU threads, enabling simulation of patient activity within an average of 2.9 minutes as opposed to 146 minutes. All simulated plans are in good agreement across the two Monte Carlo codes. The two codes agree within a maximum of 0.95σ on a voxel-by-voxel basis for the prediction of 7 different isotopes across 472 simulated fields delivered to 95 patients, with the average deviation over all fields being 6.4·10-3σ. Significance The implementation of activation calculations in the GPU accelerated Monte Carlo code FRED provides fast and reliable simulation of patient activation following proton therapy, allowing for research and clinical applications of range verification for this treatment modality using PET to proceed at a rapid pace.