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Purpose: To evaluate customizing a knowledge-based planning (KBP) model using dosimetric analysis for volumetric modulated arc therapy for pancreatic cancer. Materials and Methods: The first model (M1) using 56 plans and the second model (M2) using 31 plans were created in the first 7 months of the study. The ratios of volume of both kidneys overlapping the expanded planning target volume to the total volume of both kidneys (Voverlap/Vwhole) were calculated in all cases to customize M1. Regression lines were derived from Voverlap/Vwhole and mean dose to both kidneys. The third model (M3) was created using 30 plans which data put them below the regression line. For validation, KBP was performed with the three models on 21 patients. Results: V18 of the left kidney for M1 plans was 7.3% greater than for clinical plans. Dmean of the left kidney for M2 plans was 2.2% greater than for clinical plans. There was no significant difference between all kidney doses in M3 and clinical plans. Dmean of the left kidney for M2 plans was 2.2% greater than for clinical plans. Dmean to both kidneys did not differ significantly between the three models in validation plans with Voverlap/Vwhole lower than average. In plans with larger than average volumes, the Dmean of validation plans created by M3 was significantly lower for both kidneys by 1.7 and 0.9 Gy than with M1 and M2, respectively. Conclusions: Selecting plans to register in a model by analyzing dosimetry and geometry is an effective means of improving the KBP model.

Background: The aim of this study was to investigate the performance of the RapidPlan knowledge-based treatment planning system using models including registered pseudo-structures, and to determine how many structures are required for automatic optimization of volumetric modulated arc therapy (VMAT) for postoperative uterine cervical cancer. Methods: Pseudo-structures were retrospectively contoured for patients who had completed treatment at one of five institutions. For 22 patients, RPs were generated with a single optimization for models with two (RP_2), four (RP_4), or five (RP_5) registered structures, and the dosimetric parameters of these models were compared with a clinical plan with several optimizations. The total times for pseudo-structure creation and optimization were also measured.Results: Most dosimetric parameters showed no major differences between each RP. In particular, the rectum Dmax, V50Gy, and V40Gy with RP_2, RP_4, and RP_5 were not significantly different, and were lower than those of the clinical plan. In addition, the average proportions of plans achieving acceptable criteria for all dosimetric parameters were 98%, 99%, 98%, and 98% for the clinical plan, RP_2, RP_4, and RP_5, respectively. The average times for the creation and optimization of pseudo-structures were 105, 17, 21, and 29 minutes, for the clinical plan, RP_2, RP_4, and RP_5, respectively. Conclusions: The RapidPlan model with two registered pseudo-structures could generate clinically acceptable plans while saving time. This modeling approach using pseudo-structures could possibility be used for the VMAT planning process.

Background: The aim of the study was to evaluate analysis criteria for the identification of the presence of rectal gas during volumetric modulated arc therapy (VMAT) for prostate cancer patients by using electronic portal imaging device (EPID)-based in vivo dosimetry (IVD). Materials and methods: All measurements were performed by determining the cumulative EPID images in an integrated acquisition mode and analyzed using PerFRACTION commercial software. Systematic setup errors were simulated by moving the anthropomorphic phantom in each translational and rotational direction. The inhomogeneity regions were also simulated by the I’mRT phantom attached to the Quasar phantom. The presence of small and large air cavities (12 and 48 cm 3 ) was controlled by moving the Quasar phantom in several timings during VMAT. Sixteen prostate cancer patients received EPID-based IVD during VMAT. Results: In the phantom study, no systematic setup error was detected in the range that can happen in clinical ( < 5-mm and < 3 degree). The pass rate of 2% dose difference (DD2%) in small and large air cavities was 98.74% and 79.05%, respectively, in the appearance of the air cavity after irradiation three quarter times. In the clinical study, some fractions caused a sharp decline in the DD2% pass rate. The proportion for DD2% < 90% was 13.4% of all fractions. Rectal gas was confirmed in 11.0% of fractions by acquiring kilo-voltage X-ray images after the treatment. Conclusions: Our results suggest that analysis criteria of 2% dose difference in EPID-based IVD was a suitable method for identification of rectal gas during VMAT for prostate cancer patients.

Purpose: The aim of this study is to compare the interfractional setup reproducibility of two types of patient immobilization devices for prostate cancer receiving image-guided radiation therapy (IGRT). Materials and Methods: The MOLDCARE (MC) involves hydraulic fixation, whereas the BlueBAG (BB) and Vac-Lock (VL) involve vacuum fixation. For 72 patients, each immobilization device was individually customized during computed tomography (CT) simulation. Before the treatment, bony registration was performed using orthogonal kV images and digitally reconstructed radiographs. The shift of the treatment couch was recorded as a benchmark in the first session. In subsequent sessions, the shifts from the benchmark were measured and analyzed. Soft-tissue registration was performed weekly by cone-beam CT and CT images, and the shifts were measured and analyzed. Results: In the superior-inferior and left-right directions, there were nearly no changes in the overall mean among the immobilization devices. In the anterior-posterior (AP) direction, the overall mean for the MC, BB, and VL were 0.34 ± 1.33, −0.47 ± 1.27, and −1.82 ± 1.65 mm, respectively. The mean shifts along the AP direction were approximately 1 mm more in patients immobilized on the BB and 2.5 mm more in those on the VL, compared to those on the MC, after the twentieth treatment. No significant changes were observed among the patients immobilized on those devices, respectively, in soft-tissue registration. Conclusion: It can be concluded that the settling of the vacuum fixation was caused by air leakage in the latter-half treatment, and the immobilization device type has no effect on the treatment-position reproducibility in IGRT.

Purpose To investigate whether a novel iterative cone-beam computed tomography (CBCT) reconstruction algorithm reduces metal artifacts in head and neck patient images. Method An anthropomorphic phantom and 35 patients with dental metal prostheses or implants were analyzed. All CBCT images were acquired using a TrueBeam linear accelerator and reconstructed with a Feldkamp–Davis–Kress algorithm-based CBCT (FDK-CBCT) and an iterative CBCT algorithm. The mean Hounsfield unit (HU) and standard deviation values were measured on the tongue near the metal materials and the unaffected region as reference values. The artifact index (AI) was calculated. For objective image analysis, the HU value and AI were compared between FDK-CBCT and iterative CBCT images in phantom and clinical studies. Subjective image analyses of metal artifact scores and soft tissue visualizations were conducted using a five-point scale by two reviewers in the clinical study. Results The HU value and AI showed significant artifact reduction for the iterative CBCT than for the FDK-CBCT images (phantom study: 389.8 vs.−10.3 for HU value, 322.9 vs. 96.2 for AI, FDK-CBCT vs. iterative CBCT, respectively; clinical study: 210.3 vs. 69.0 for HU value, 149.6 vs. 70.7 for AI). The subjective scores in the clinical patient study were improved in the iterative CBCT images (metal artifact score: 1.1 vs. 2.9, FDK-CBCT vs. iterative CBCT, respectively; soft tissue visualization: 1.8 vs. 3.6). Conclusions The iterative CBCT reconstruction algorithm substantially reduced metal artifacts caused by dental metal prostheses and improved soft tissue visualization compared to FDK-CBCT in phantom and clinical studies.

Objective: Determination of the optimal energy level of virtual monochromatic image (VMI) for brain metastases in contrast-enhanced dual-energy CT (DECT) for radiosurgery and assessment of the subjective and objective image quality of VMI at the optimal energy level. Methods: 20 patients (total of 42 metastases) underwent contrast-enhanced DECT. Spectral image analysis of VMIs at energy levels ranging from 40 to 140 keV in 1 keV increments was performed to determine the optimal VMI (VMIopt) as the one corresponding to the highest contrast-to-noise ratio (CNR) between brain parenchyma and the metastases. The objective and subjective values of VMIopt were compared to those of the VMI with 120 kVp equivalent, defined as reference VMI (VMIref, 77 keV). The objective measurement parameters included mean HU value and SD of tumor and brain parenchyma, absolute lesion contrast (LC), and CNR. The subjective measurements included five-point scale assessment of “overall image quality” and “tumor delineation” by three radiation oncologists. Results: The VMI at 63 keV was defined as VMIopt. The LC and CNR of VMIopt were significantly (p < 0.01) higher than those of VMIref (LC: 37.4 HU vs 24.7 HU; CNR: 1.1 vs 0.8, respectively). Subjective analysis rated VMIopt significantly (p < 0.01) superior to VMIref with respect to the overall image quality (3.2 vs 2.9, respectively) and tumor delineation (3.5 vs 2.9, respectively). Conclusion: The VMI at 63 keV derived from contrast-enhanced DECT yielded the highest CNR and improved the objective and subjective image quality for radiosurgery, compared to VMIref. Advances in knowledge: This paper investigated for the first time the optimal energy level of VMI in DECT for brain metastases. The findings will lead to improvement in tumor visibility with optimal VMI and consequently supplement accuracy delineation of brain metastases.

BACKGROUND AND PURPOSE The accurate delineation of pancreatic tumor with respiratory motion is challenging. This study demonstrates the application of contrast-enhanced four-dimensional dual-energy computed tomography (CE-4D-DECT) for tumor delineation and assesses the objective and subjective image quality. MATERIAL AND METHODS Twelve patients underwent CE-4D-DECT, and quantitative spectral analysis was performed on the resulting virtual monochromatic images (VMI) to determine the optimal VMI (O-VMI) with the highest contrast-to-noise ratio (CNR). The objective value of the CNR between pancreatic parenchyma and tumor, and the subjective measurement with five-point scale were compared between O-VMI, standard VMI (S-VMI, 77 keV) and single energy CT (SECT, 120 kVp). RESULTS The CNR was the highest in the VMI at 60 keV, and the corresponding CNR in the O-VMI (3.4) was significantly higher (p