Development of in-house fully residual deep convolutional neural network-based segmentation software for the male pelvic CT

[Background] This study aimed to (1) develop a fully residual deep convolutional neural network (CNN)-based segmentation software for computed tomography image segmentation of the male pelvic region and (2) demonstrate its efficiency in the male pelvic region. [Methods] A total of 470 prostate cancer patients who had undergone intensity-modulated radiotherapy or volumetric-modulated arc therapy were enrolled. Our model was based on FusionNet, a fully residual deep CNN developed to semantically segment biological images. To develop the CNN-based segmentation software, 450 patients were randomly selected and separated into the training, validation and testing groups (270, 90, and 90 patients, respectively). In Experiment 1, to determine the optimal model, we first assessed the segmentation accuracy according to the size of the training dataset (90, 180, and 270 patients). In Experiment 2, the effect of varying the number of training labels on segmentation accuracy was evaluated. After determining the optimal model, in Experiment 3, the developed software was used on the remaining 20 datasets to assess the segmentation accuracy. The volumetric dice similarity coefficient (DSC) and the 95th-percentile Hausdorff distance (95%HD) were calculated to evaluate the segmentation accuracy for each organ in Experiment 3. [Results] In Experiment 1, the median DSC for the prostate were 0.61 for dataset 1 (90 patients), 0.86 for dataset 2 (180 patients), and 0.86 for dataset 3 (270 patients), respectively. The median DSCs for all the organs increased significantly when the number of training cases increased from 90 to 180 but did not improve upon further increase from 180 to 270. The number of labels applied during training had a little effect on the DSCs in Experiment 2. The optimal model was built by 270 patients and four organs. In Experiment 3, the median of the DSC and the 95%HD values were 0.82 and 3.23 mm for prostate; 0.71 and 3.82 mm for seminal vesicles; 0.89 and 2.65 mm for the rectum; 0.95 and 4.18 mm for the bladder, respectively. [Conclusions] We have developed a CNN-based segmentation software for the male pelvic region and demonstrated that the CNN-based segmentation software is efficient for the male pelvic region

Development of independent dose verification plugin using Eclipse scripting API for brachytherapy

In this study, an independent dose verification plugin (DVP) using the Eclipse Scripting Application Programming Interface (ESAPI) for brachytherapy was developed. The DVP was based on the general 2D formalism reported in AAPM-TG43U1. The coordinate and orientation of each source position were extracted from the translation matrix acquired from the treatment planning system (TPS), and the distance between the source and verification point (r) was calculated. Moreover, the angles subtended by the center-tip and tip-tip of the hypothetical line source with respect to the verification point (θ and β) were calculated. With r, θ, β and the active length of the source acquired from the TPS, the geometry function was calculated. As the TPS calculated the radial dose function, g(r), and 2D anisotropy function, F(r, θ), by interpolating and extrapolating the corresponding table stored in the TPS, the DVP calculated g(r) and F(r, θ) independently from equations fitted with the Monte Carlo data. The relative deviation of the fitted g(r) and F(r, θ) for the GammaMed Plus HDR 192Ir source was 0.5% and 0.9%, respectively. The acceptance range of the relative dose difference was set to ±1.03% based on the relative deviation between the fitted functions and Monte Carlo data, and the linear error propagation law. For 64 verification points from sixteen plans, the mean of absolute values of the relative dose difference was 0.19%. The standard deviation (SD) of the relative dose difference was 0.17%. The DVP maximizes efficiency and minimizes human error for the brachytherapy plan check

Reducing variability among treatment machines using knowledge‐based planning for head and neck, pancreatic, and rectal cancer

PURPOSE: This study aimed to assess dosimetric indices of RapidPlan model-based plans for different energies (6, 8, 10, and 15 MV; 6- and 10-MV flattening filter-free), multileaf collimator (MLC) types (Millennium 120, High Definition 120, dual-layer MLC), and disease sites (head and neck, pancreatic, and rectal cancer) and compare these parameters with those of clinical plans. METHODS: RapidPlan models in the Eclipse version 15.6 were used with the data of 28, 42, and 20 patients with head and neck, pancreatic, and rectal cancer, respectively. RapidPlan models of head and neck, pancreatic, and rectal cancer were created for TrueBeam STx (High Definition 120) with 6 MV, TrueBeam STx with 10-MV flattening filter-free, and Clinac iX (Millennium 120) with 15 MV, respectively. The models were used to create volumetric-modulated arc therapy plans for a 10-patient test dataset using all energy and MLC types at all disease sites. The Holm test was used to compare multiple dosimetric indices in different treatment machines and energy types. RESULTS: The dosimetric indices for planning target volume and organs at risk in RapidPlan model-based plans were comparable to those in the clinical plan. Furthermore, no dose difference was observed among the RapidPlan models. The variability among RapidPlan models was consistent regardless of the treatment machines, MLC types, and energy. CONCLUSIONS: Dosimetric indices of RapidPlan model-based plans appear to be comparable to the ones based on clinical plans regardless of energies, MLC types, and disease sites. The results suggest that the RapidPlan model can generate treatment plans independent of the type of treatment machine

Independent calculation-based verification of volumetric-modulated arc therapy–stereotactic body radiotherapy plans for lung cancer

This study aimed to investigate the feasibility of independent calculation‐based verification of volumetric‐modulated arc therapy (VMAT)–stereotactic body radiotherapy (SBRT) for patients with lung cancer using a secondary treatment planning system (sTPS). In all, 50 patients with lung cancer who underwent VMAT‐SBRT between April 2018 and May 2019 were included in this study. VMAT‐SBRT plans were devised using the Collapsed‐Cone Convolution in RayStation (primary TPS: pTPS). DICOM files were transferred to Eclipse software (sTPS), which utilized the Eclipse software, and the dose distribution was then recalculated using Acuros XB. For the verification of dose distribution in homogeneous phantoms, the differences among pTPS, sTPS, and measurements were evaluated using passing rates of a dose difference of 5% (DD5%) and gamma index of 3%/2 mm (γ3%/2 mm). The ArcCHECK cylindrical diode array was used for measurements. For independent verification of dose‐volume parameters per the patient’s geometry, dose‐volume indices for the planning target volume (PTV) including D95% and the isocenter dose were evaluated. The mean differences (± standard deviations) between the pTPS and sTPS were then calculated. The gamma passing rates of DD5% and γ3%/2 mm criteria were 99.2 ± 2.4% and 98.6 ± 3.2% for pTPS vs. sTPS, 92.9 ± 4.0% and 94.1 ± 3.3% for pTPS vs. measurement, and 93.0 ± 4.4% and 94.3 ± 4.1% for sTPS vs. measurement, respectively. The differences between pTPS and sTPS for the PTVs of D95% and the isocenter dose were −3.1 ± 2.0% and −2.3 ± 1.8%, respectively. Our investigation of VMAT‐SBRT plans for lung cancer revealed that independent calculation‐based verification is a time‐efficient method for patient‐specific quality assurance

Dosimetric Comparison between Dynamic Wave Arc and Co-Planar Volumetric Modulated Radiotherapy for Locally Advanced Pancreatic Cancer

Introduction: Dose reduction to the duodenum is important to decrease gastrointestinal toxicities in patients with locally advanced pancreatic cancer (LAPC) treated with definitive chemoradiotherapy. We aimed to compare dynamic wave arc (DWA), a volumetric-modulated beam delivery technique with simultaneous gantry/ring rotations passing the waved trajectories, with coplanar VMAT (co-VMAT) with respect to dose distributions in LAPC cases. Material and Methods: DWA and co-VMAT plans were created for 13 patients with LAPC. The prescribed dose was 45.6 or 48 Gy in 15 fractions. The dose volume indices (DVIs) for target volumes and organs at risk were compared between the corresponding plans. Gamma passing rate, monitor unit (MU), and beam-on time were also compared. Results: DWA significantly reduced the duodenal V39Gy, V42Gy, and V45Gy by 1.1, 0.8, and 0.2 cm3, and increased the liver mean dose and D2cm3 of the spinal cord planning volume by 1.0 and 1.5 Gy, respectively. Meanwhile, there was no significant difference in the target volumes except for D2% of PTV (111.5% in DWA vs. 110.5% in co-VMAT). Further, the gamma passing rate was similar in both plans. MU and beam-on time increased in DWA by 31 MUs and 15 seconds, respectively. Conclusion: DWA generated significantly lower duodenal doses in LAPC cases, albeit with slight increasing liver and spinal cord doses and increasing MU and the beam delivery time. Further evaluation is needed to know how the dose differences would affect the clinical outcomes in chemoradiotherapy for LAPC

先進的強度変調回転照射における機械及び患者個別品質管理法の確立

京都大学0048新制・課程博士博士(医学)甲第21619号医博第4425号新制||医||1033(附属図書館)京都大学大学院医学研究科医学専攻(主査)教授 増永 慎一郎, 教授 松村 由美, 教授 富樫 かおり学位規則第4条第1項該当Doctor of Medical ScienceKyoto UniversityDFA

Performance evaluation of a newly developed three-dimensional model-based global-to-local registration in prostate cancer

We evaluated the performance of a newly developed three-dimensional (3D) model-based global-to-local registration of multiple organs, by comparing it with a 3D model-based global registration in the prostate region. This study included 220 prostate cancer patients who underwent intensity-modulated radiotherapy or volumetric-modulated arc therapy. Our registration proceeded sequentially, i.e. global registration including affine and piece-wise affine transformation followed by local registration. As a local registration, Laplacian-based and finite element method-based registration was implemented in Algorithm A and B, respectively. Algorithm C was for global registration alone. The template models for the prostate, seminal vesicles, rectum and bladder were constructed from the first 20 patients, and then three different registrations were performed on these organs for the remaining 200 patients, to assess registration accuracy. The 75th percentile Hausdorff distance was 1 mm in Algorithm B, except for the prostate; and 3.9 mm for the prostate and >7.8 mm for other organs in Algorithm C. The median computation time to complete registration was <101, 30 and 16 s in Algorithms A, B and C, respectively. Analysis of variance revealed significant differences among Algorithms A–C in the Hausdorff distance and computation time. In addition, no significant difference was observed in the difference of Hausdorff distance between Algorithm A and B with Tukey’s multiple comparison test. The 3D model-based global-to-local registration, especially that implementing Laplacian-based registration, completed surface registration rapidly and provided sufficient registration accuracy in the prostate region

Quality assurance of non-coplanar, volumetric-modulated arc therapy employing a C-arm linear accelerator, featuring continuous patient couch rotation

Purpose: To perform quality assurance of non-coplanar, volumetric-modulated arc therapy featuring continuous couch rotation (CCR-VMAT) using a C-arm linear accelerator. Methods: We planned and delivered CCR-VMAT using the TrueBeam Developer Mode. Treatment plans were created for both a C-shaped phantom and five prostate cancer patients using seven CCR trajectories that lacked collisions; we used RayStation software (ver. 4.7) to this end. Subsequently, verification plans were generated. The mean absolute error (MAE) between the center of an MV-imaged steel ball and the radiation field was calculated using the Winston–Lutz test. The MAEs between planned and actual irradiation values were also calculated from trajectory logs. In addition, correlation coefficients (r values) among the MAEs of gantry angle, couch angle, and multi-leaf collimator (MLC) position, and mechanical parameters including gantry speed, couch speed, MLC speed, and beam output, were estimated. The dosimetric accuracies of planned and measured values were also assessed using ArcCHECK. Results: The MAEs ±2 standard deviations as revealed by the Winston–Lutz test for all trajectories were 0.3 ± 0.3 mm in two dimensions. The MAEs of the gantry, couch, and MLC positions calculated from all trajectory logs were within 0.04°, 0.08°, and 0.02 mm, respectively. Deviations in the couch angle (r = 0.98, p < 0.05) and MLC position (r = 0.86, p < 0.05) increased significantly with speed. The MAE of the beam output error was less than 0.01 MU. The mean gamma passing rate ± 2 SD (range) of the 3%/3 mm, 3%/1 mm, and 5%/1 mm was 98.1 ± 1.9% (95.7–99.6%), 87.2 ± 2.8% (80.2–96.7%), and 96.3 ± 2.8% (93.9–99.6%), respectively. Conclusions: CCR-VMAT delivered via the TrueBeam Developer Mode was associated with high-level geometric and mechanical accuracy, thus affording to high dosimetric accuracy. The CCR-VMAT performance was stable regardless of the trajectory chosen