Unifying gamma passing rates in patient-specific QA for VMAT lung cancer treatment based on data assimilation.

This study aimed to identify systematic errors in measurement-, calculation-, and prediction-based patient-specific quality assurance (PSQA) methods for volumetric modulated arc therapy (VMAT) on lung cancer and to standardize the gamma passing rate (GPR) by considering systematic errors during data assimilation. This study included 150 patients with lung cancer who underwent VMAT. VMAT plans were generated using a collapsed-cone algorithm. For measurement-based PSQA, ArcCHECK was employed. For calculation-based PSQA, Acuros XB was used to recalculate the plans. In prediction-based PSQA, GPR was forecasted using a previously developed GPR prediction model. The representative GPR value was estimated using the least-squares method from the three PSQA methods for each original plan. The unified GPR was computed by adjusting the original GPR to account for systematic errors. The range of limits of agreement (LoA) were assessed for the original and unified GPRs based on the representative GPR using Bland-Altman plots. For GPR (3%/2 mm), original GPRs were 94.4 ± 3.5%, 98.6 ± 2.2% and 93.3 ± 3.4% for measurement-, calculation-, and prediction-based PSQA methods and the representative GPR was 95.5 ± 2.0%. Unified GPRs were 95.3 ± 2.8%, 95.4 ± 3.5% and 95.4 ± 3.1% for measurement-, calculation-, and prediction-based PSQA methods, respectively. The range of LoA decreased from 12.8% for the original GPR to 9.5% for the unified GPR across all three PSQA methods. The study evaluated unified GPRs that corrected for systematic errors. Proposing unified criteria for PSQA can enhance safety regardless of the methods used.

Applications of artificial intelligence for machine- and patient-specific quality assurance in radiation therapy: current status and future directions.

Machine- and patient-specific quality assurance (QA) is essential to ensure the safety and accuracy of radiotherapy. QA methods have become complex, especially in high-precision radiotherapy such as intensity-modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT), and various recommendations have been reported by AAPM Task Groups. With the widespread use of IMRT and VMAT, there is an emerging demand for increased operational efficiency. Artificial intelligence (AI) technology is quickly growing in various fields owing to advancements in computers and technology. In the radiotherapy treatment process, AI has led to the development of various techniques for automated segmentation and planning, thereby significantly enhancing treatment efficiency. Many new applications using AI have been reported for machine- and patient-specific QA, such as predicting machine beam data or gamma passing rates for IMRT or VMAT plans. Additionally, these applied technologies are being developed for multicenter studies. In the current review article, AI application techniques in machine- and patient-specific QA have been organized and future directions are discussed. This review presents the learning process and the latest knowledge on machine- and patient-specific QA. Moreover, it contributes to the understanding of the current status and discusses the future directions of machine- and patient-specific QA.

Protocol of a phase II study to evaluate the efficacy and safety of deep-inspiration breath-hold daily online adaptive radiotherapy for centrally located lung tumours (PUDDING study).

BACKGROUND: Centrally located lung tumours present a challenge because of their tendency to exhibit symptoms such as airway obstruction, atelectasis, and bleeding. Surgical resection of these tumours often requires sacrificing the lungs, making definitive radiotherapy the preferred alternative to avoid pneumonectomy. However, the proximity of these tumours to mediastinal organs at risk increases the potential for severe adverse events. To mitigate this risk, we propose a dual-method approach: deep inspiration breath-hold (DIBH) radiotherapy combined with adaptive radiotherapy. The aim of this single-centre, single-arm phase II study is to investigate the efficacy and safety of DIBH daily online adaptive radiotherapy. METHODS: Patients diagnosed with centrally located lung tumours according to the International Association for the Study of Lung Cancer recommendations, are enrolled and subjected to DIBH daily online adaptive radiotherapy. The primary endpoint is the one-year cumulative incidence of grade 3 or more severe adverse events, as classified by the Common Terminology Criteria for Adverse Events (CTCAE v5.0). DISCUSSION: Delivering definitive radiotherapy for centrally located lung tumours presents a dilemma between ensuring optimal dose coverage for the planning target volume and the associated increased risk of adverse events. DIBH provides measurable dosimetric benefits by increasing the normal lung volume and distancing the tumour from critical mediastinal organs at risk, leading to reduced toxicity. DIBH adaptive radiotherapy has been proposed as an adjunct treatment option for abdominal and pelvic cancers. If the application of DIBH adaptive radiotherapy to centrally located lung tumours proves successful, this approach could shape future phase III trials and offer novel perspectives in lung tumour radiotherapy. TRIAL REGISTRATION: Registered at the Japan Registry of Clinical Trials (jRCT; https://jrct.niph.go.jp/ ); registration number: jRCT1052230085 ( https://jrct.niph.go.jp/en-latest-detail/jRCT1052230085 ).

Influence of dose calculation algorithms on the helical diode array using volumetric-modulated arc therapy for small targets.

BACKGROUND: For patient-specific quality assurance (PSQA) for small targets, the dose resolution can change depending on the characteristics of the dose calculation algorithms. PURPOSE: This study aimed to evaluate the influence of the dose calculation algorithms Acuros XB (AXB), anisotropic analytical algorithm (AAA), photon Monte Carlo (pMC), and collapsed cone (CC) on a helical diode array using volumetric-modulated arc therapy (VMAT) for small targets. MATERIALS AND METHODS: ArcCHECK detectors were inserted with a physical depth of 2.9 cm from the surface. To evaluate the influence of the dose calculation algorithms for small targets, rectangular fields of 2×100, 5×100, 10×100, 20×100, 50×100, and 100×100 mm2 were irradiated and measured using ArcCHECK with TrueBeam STx. A total of 20 VMAT plans for small targets, including the clinical sites of 19 brain metastases and one spine, were also evaluated. The gamma passing rates (GPRs) were evaluated for the rectangular fields and the 20 VMAT plans using AXB, AAA, pMC, and CC. RESULTS: For rectangular fields of 2×100 and 5×100 mm2 , the GPR at 3%/2 mm of AXB was < 50% because AXB resulted in a coarser dose resolution with narrow beams. For field sizes > 10×100 mm2, the GPR at 3%/2 mm was > 88.1% and comparable for all dose calculation algorithms. For the 20 VMAT plans, the GPRs at 3%/2 mm were 79.1 ± 15.7%, 93.2 ± 5.8%, 94.9 ± 4.1%, and 94.5 ± 4.1% for AXB, AAA, pMC, and CC, respectively. CONCLUSION: The behavior of the dose distribution on the helical diode array differed depending on the dose calculation algorithm for small targets. Measurements using ArcCHECK for VMAT with small targets can have lower GPRs owing to the coarse dose resolution of AXB around the detector area.

Dosimetric verification of four dose calculation algorithms for spine stereotactic body radiotherapy.

The applications of Type B [anisotropic analytical algorithm (AAA) and collapsed cone (CC)] and Type C [Acuros XB (AXB) and photon Monte Carlo (PMC)] dose calculation algorithms in spine stereotactic body radiotherapy (SBRT) were evaluated. Water- and bone-equivalent phantoms were combined to evaluate the percentage depth dose and dose profile. Subsequently, 48 consecutive patients with clinical spine SBRT plans were evaluated. All treatment plans were created using AXB in Eclipse. The prescription dose was 24 Gy in two fractions at a 10 MV FFF on TrueBeam. The doses were then recalculated with AAA, CC and PMC while maintaining the AXB-calculated monitor units and beam arrangement. The dose index values obtained using the four dose calculation algorithms were then compared. The AXB and PMC dose distributions agreed with the bone-equivalent phantom measurements (within ±2.0%); the AAA and CC values were higher than those in the bone-equivalent phantom region. For the spine SBRT plans, PMC, AAA and CC were overestimated compared with AXB in terms of the near minimum and maximum doses of the target and organ at risk, respectively; the mean dose difference was within 4.2%, which is equivalent with within 1 Gy. The phantom study showed that the results from AXB and PMC agreed with the measurements within ±2.0%. However, the mean dose difference ranged from 0.5 to 1 Gy in the spine SBRT planning study when the dose calculation algorithms changed. Users should incorporate a clinical introduction that includes an awareness of these differences.

Intraoperative Radiation Exposure from O-arm-based 3D Navigation in Spine Surgery.

Introduction: Intraoperative three-dimensional (3D) imaging guide technology, such as the O-arm surgical imaging system, is a beneficial tool in spinal surgery that provides real-time 3D images of a patient's spine. This study aims to determine the exposure dose from intraoperative O-arm imaging. Methods: A consecutive retrospective review of all patients undergoing spinal surgery was conducted between June 2019 and August 2022. Demographic and operative data were collected from electronic medical records. Results: Intraoperative O-arm imaging was conducted in 206 (12.9%) of 1599 patients, ranging from one to 4 scans per patient (1.17±0.43 scans). Single O-arm imaging enabled navigation of seven vertebrae in the cervical spine, seven in the thoracic spine, five in the thoracolumbar spine, and four in the lumbar spine on average. The number of O-arm shots per surgery was 1.15±0.36, 1.06±0.24, 1.61±0.7, and 1.07±0.25 for cervical, thoracic, thoracolumbar, and lumbar spinal cases, respectively. The exposure doses represented by dose length products in single O-arm imaging were 377±19 mGy-cm, 243±22 mGy-cm, 378±38 mGy-cm, and 258±11 mGy-cm for cervical, thoracic, thoracolumbar, and lumbar spine cases, respectively. We observed a weak positive correlation between the number of fused spinal levels and the exposure dose. Conclusions: Intraoperative radiation exposure from O-arm imaging was lower than the national diagnostic reference levels in Japan established based on the International Commission on Radiological Protection publication, demonstrating its safety from the standpoint of radiological protection in most cases. In surgeries with a large range of fixations, such as corrective deformity surgery, the number of imaging sessions and the amount of intraoperative radiation exposure would increase, leading surgeons to pay attention to the risk of radiation in spinal surgery.

Evaluation of generalization ability for deep learning-based auto-segmentation accuracy in limited field of view CBCT of male pelvic region.

PURPOSE: The aim of this study was to evaluate generalization ability of segmentation accuracy for limited FOV CBCT in the male pelvic region using a full-image CNN. Auto-segmentation accuracy was evaluated using various datasets with different intensity distributions and FOV sizes. METHODS: A total of 171 CBCT datasets from patients with prostate cancer were enrolled. There were 151, 10, and 10 CBCT datasets acquired from Vero4DRT, TrueBeam STx, and Clinac-iX, respectively. The FOV for Vero4DRT, TrueBeam STx, and Clinac-iX was 20, 26, and 25 cm, respectively. The ROIs, including the bladder, prostate, rectum, and seminal vesicles, were manually delineated. The U2 -Net CNN network architecture was used to train the segmentation model. A total of 131 limited FOV CBCT datasets from Vero4DRT were used for training (104 datasets) and validation (27 datasets); thereafter the rest were for testing. The training routine was set to save the best weight values when the DSC in the validation set was maximized. Segmentation accuracy was qualitatively and quantitatively evaluated between the ground truth and predicted ROIs in the different testing datasets. RESULTS: The mean scores ± standard deviation of visual evaluation for bladder, prostate, rectum, and seminal vesicle in all treatment machines were 1.0 ± 0.7, 1.5 ± 0.6, 1.4 ± 0.6, and 2.1 ± 0.8 points, respectively. The median DSC values for all imaging devices were ≥0.94 for the bladder, 0.84-0.87 for the prostate and rectum, and 0.48-0.69 for the seminal vesicles. Although the DSC values for the bladder and seminal vesicles were significantly different among the three imaging devices, the DSC value of the bladder changed by less than 1% point. The median MSD values for all imaging devices were ≤1.2 mm for the bladder and 1.4-2.2 mm for the prostate, rectum, and seminal vesicles. The MSD values for the seminal vesicles were significantly different between the three imaging devices. CONCLUSION: The proposed method is effective for testing datasets with different intensity distributions and FOV from training datasets.

Effect of angular dependence for small-field dosimetry using seven different detectors.

BACKGROUND: Small-field dosimetry is challenging for radiotherapy dosimetry because of the loss of lateral charged equilibrium, partial occlusion of the primary photon source by the collimating devices, perturbation effects caused by the detector materials and their design, and the detector size relative to the radiation field size, which leads to a volume averaging effect. Therefore, a suitable tool for small-field dosimetry requires high spatial resolution, tissue equivalence, angular independence, and energy and dose rate independence to achieve sufficient accuracy. Recently, with the increasing use of combinations of coplanar and non-coplanar beams for small-field dosimetry, there is a need to clarify angular dependence for dosimetry where the detector is oriented at various angles to the incident beam. However, the effect of angular dependence on small-field dosimetry with coplanar and non-coplanar beams has not been fully clarified. PURPOSE: This study clarified the effect of angular dependence on small-field dosimetry with coplanar and non-coplanar beams using various detectors. METHODS: Seven different detectors were used: CC01, RAZOR, RAZOR Nano, Pinpoint 3D, stereotactic field diode (SFD), microSilicon, and microDiamond. All measurements were taken using a TrueBeam STx with 6 MV and 10 MV flattening filter-free (FFF) energies using a water-equivalent spherical phantom with a source-to-axis distance of 100 cm. The detector was inserted in a perpendicular orientation, and the gantry was rotated at 15° increments from the incidence beam angle. A multi-leaf collimator (MLC) with four field sizes of 0.5 × 0.5, 1 × 1, 2 × 2, and 3 × 3 cm2 , and four couch angles from 0°, 30°, 60°, and 90° (coplanar and non-coplanar) were adopted. The angular dependence response (AR) was defined as the ratio of the detector response at a given irradiation gantry angle normalized to the detector response at 0°. The maximum AR differences were calculated between the maximum and minimum AR values for each detector, field size, energy, and couch angle. RESULTS: The maximum AR difference for the coplanar beam was within 3.3% for all conditions, excluding the maximum AR differences in 0.5 × 0.5 cm2 field for CC01 and RAZOR. The maximum AR difference for non-coplanar beams was within 2.5% for fields larger than 1 × 1 cm2 , excluding the maximum AR differences for RAZOR Nano, SFD, and microSilicon. The Pinpoint 3D demonstrated stable AR tendencies compared to other detectors. The maximum difference was within 2.0%, except for the 0.5 × 0.5 cm2 field and couch angle at 90°. The tendencies of AR values for each detector were similar when using different energies. CONCLUSION: This study clarified the inherent angular dependence of seven detectors that were suitable for small-field dosimetry. The Pinpoint 3D chamber had the smallest angular dependence of all detectors for the coplanar and non-coplanar beams. The findings of this study can contribute to the calculation of the AR correction factor, and it may be possible to adapt detectors with a large angular dependence on coplanar and non-coplanar beams. However, note that the gantry sag and detector-specific uncertainties increase as the field size decreases.

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 ß) were calculated. With r, θ, ß 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.

A case of a pregnant woman with locally advanced cervical esophageal cancer treated with definitive chemoradiotherapy.

The information of definitive radiotherapy for a pregnant woman with malignancy was limited; however, it was reported to be potentially feasible with minimal risks. We performed definitive chemoradiotherapy for a pregnant woman with locally advanced cervical esophageal cancer. Feasibility of radiotherapy and safety of fetus were confirmed by the phantom study estimating fetal dose, and monitoring it in each radiotherapy session. The planned chemoradiotherapy completely eradicated esophageal cancer while preserving her laryngopharyngeal function. A female infant was delivered by cesarian section after planned chemoradiotherapy, and she grew without any apparent disorders 2 years after chemoradiotherapy. Chemoradiotherapy might be one of the treatment options for a pregnant woman with cervical esophageal cancer especially wishing the preservation of laryngopharyngeal function.

Multi-Institutional Study of End-to-End Dose Delivery Quality Assurance Testing for Image-Guided Brachytherapy Using a Gel Dosimeter.

PURPOSE: To quantify dose delivery errors for high-dose-rate image-guided brachytherapy (HDR-IGBT) using an independent end-to-end dose delivery quality assurance test at multiple institutions. The novelty of our study is that this is the first multi-institutional end-to-end dose delivery study in the world. MATERIALS AND METHODS: The postal audit used a polymer gel dosimeter in a cylindrical acrylic container for the afterloading system. Image acquisition using computed tomography, treatment planning, and irradiation were performed at each institution. Dose distribution comparison between the plan and gel measurement was performed. The percentage of pixels satisfying the absolute-dose gamma criterion was reviewed. RESULTS: Thirty-five institutions participated in this study. The dose uncertainty was 3.6% ± 2.3% (mean ± 1.96σ). The geometric uncertainty with a coverage factor of k = 2 was 3.5 mm. The tolerance level was set to the gamma passing rate of 95% with the agreement criterion of 5% (global)/3 mm, which was determined from the uncertainty estimation. The percentage of pixels satisfying the gamma criterion was 90.4% ± 32.2% (mean ± 1.96σ). Sixty-six percent (23/35) of the institutions passed the verification. Of the institutions that failed the verification, 75% (9/12) had incorrect inputs of the offset between the catheter tip and indexer length in treatment planning and 17% (2/12) had incorrect catheter reconstruction in treatment planning. CONCLUSIONS: The methodology should be useful for comprehensively checking the accuracy of HDR-IGBT dose delivery and credentialing clinical studies. The results of our study highlight the high risk of large source positional errors while delivering dose for HDR-IGBT in clinical practices.

Evaluation of correlation between intrafractional residual setup errors and accumulation of delivered dose distributions in single isocenter volumetric modulated arc therapy for multiple brain metastases.

PURPOSE: To evaluate the displacement of gross tumor volume (GTV) positions caused by intrafractional residual setup errors (RSEs) and to accumulate delivered dose distributions considering intrafraction RSEs in fractionated-stereotactic radiotherapy (f-SRT) with single isocenter volumetric modulated arc therapy (SI-VMAT) for multiple brain metastases. METHODS: Overall, 72 consecutive patients who underwent f-SRT with SI-VMAT for multiple brain metastases were included. For all patients, 6D correction was performed using the ExacTrac X-ray (ETX) system. GTV displacement (ΔD) was calculated considering the intrafractional RSEs measured by the ETX system during irradiation. The correlation between ΔD and the distance from the isocenter to each GTV (d) was analyzed. Computed tomography (CT) images considering the intrafractional RSEs were generated for five patients with ΔD > 1 mm. The delivered dose distributions for all fractions were reconstructed on the corresponding CT, followed by their accumulation. RESULTS: The 95th percentile of ΔD from 7,270 resultant center positions of 417 GTVs was 0.92 mm. No correlation was observed between ΔD and d. For 53 GTVs from five patients with ΔD > 1 mm, the difference of GTV D99.5% and D0.5% between the planned and accumulated values was -0.4 ± 2.5% and -1.0 ± 0.8%, respectively. There was no correlation between d and the difference of GTV D99.5% and D0.5%. CONCLUSIONS: We found no significant difference in GTV D99.5% and D0.5%, despite the location of GTVs far from the isocenter. However, it should be noted that this result was because the intrafractional RSEs were reduced to a clinically acceptable level.

Dosiomic feature comparison between dose-calculation algorithms used for lung stereotactic body radiation therapy.

To evaluate the reproducibility of dose-based radiomic (dosiomic) features between dose-calculation algorithms for lung stereotactic body radiation therapy (SBRT). We analyzed 105 patients with early-stage non-small cell lung cancer who underwent lung SBRT between March 2011 and December 2017. Radiation doses of 48, 60, and 70 Gy were prescribed to the isocenter in 4-8 fractions. Dose calculations were performed using X-ray voxel Monte Carlo (XVMC) on the iPlan radiation treatment planning system (RTPS). Thereafter, the radiation doses were recalculated using the Acuros XB (AXB) and analytical anisotropic algorithm (AAA) on the Eclipse RTPS while maintaining the XVMC-calculated monitor units and beam arrangements. A total of 6808 dosiomic features were extracted without preprocessing (112 shape, 144 first-order, and 600 texture features) or with wavelet filters to eight decompositions (1152 first-order and 4800 texture features). Features with absolute pairwise concordance correlation coefficients-|CCcon|-values exceeding or equaling 0.85 were considered highly reproducible. Subgroup analyses were performed considering the wavelet filters and prescribed doses. The numbers of highly reproducible first-order and texture features were 34.8%, 26.9%, and 31.0% for the XVMC-AXB, XVMC-AAA, and AXB-AAA pairs, respectively. The maximum difference between the mean |CCcon| values was 0.70 and 0.11 for the subgroup analyses of wavelet filters and prescribed dose, respectively. The application of wavelet filter-based dosiomic analyses may be limited when using different types of dose-calculation algorithms for lung SBRT.

Chemoradiotherapy for fistula-related perianal squamous cell carcinoma with Crohn's disease.

The reports of chemoradiotherapy for anal squamous cell carcinoma with Crohn's disease are few. Severe toxicity related to radiotherapy is concerned in patients with inflammatory bowel disease. We report a case of chemoradiotherapy for locally advanced fistula-related perianal squamous cell carcinoma in a patient with long-standing Crohn's disease which was controlled by a maintenance therapy. The patient completed standard chemoradiotherapy using intensity-modulated radiotherapy without severe toxicity, and achieved complete remission. Standard chemoradiotherapy using intensity-modulated radiotherapy may be feasible and effective treatment for this population when Crohn's disease is controlled.

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.

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.

Geometric and dosimetric impact of 3D generative adversarial network-based metal artifact reduction algorithm on VMAT and IMPT for the head and neck region.

BACKGROUND: We investigated the geometric and dosimetric impact of three-dimensional (3D) generative adversarial network (GAN)-based metal artifact reduction (MAR) algorithms on volumetric-modulated arc therapy (VMAT) and intensity-modulated proton therapy (IMPT) for the head and neck region, based on artifact-free computed tomography (CT) volumes with dental fillings. METHODS: Thirteen metal-free CT volumes of the head and neck regions were obtained from The Cancer Imaging Archive. To simulate metal artifacts on CT volumes, we defined 3D regions of the teeth for pseudo-dental fillings from the metal-free CT volumes. HU values of 4000 HU were assigned to the selected teeth region of interest. Two different CT volumes, one with four (m4) and the other with eight (m8) pseudo-dental fillings, were generated for each case. These CT volumes were used as the Reference. CT volumes with metal artifacts were then generated from the Reference CT volumes (Artifacts). On the Artifacts CT volumes, metal artifacts were manually corrected for using the water density override method with a value of 1.0 g/cm3 (Water). By contrast, the CT volumes with reduced metal artifacts using 3D GAN model extension of CycleGAN were also generated (GAN-MAR). The structural similarity (SSIM) index within the planning target volume was calculated as quantitative error metric between the Reference CT volumes and the other volumes. After creating VMAT and IMPT plans on the Reference CT volumes, the reference plans were recalculated for the remaining CT volumes. RESULTS: The time required to generate a single GAN-MAR CT volume was approximately 30 s. The median SSIMs were lower in the m8 group than those in the m4 group, and ANOVA showed a significant difference in the SSIM for the m8 group (p < 0.05). Although the median differences in D98%, D50% and D2% were larger in the m8 group than the m4 group, those from the reference plans were within 3% for VMAT and 1% for IMPT. CONCLUSIONS: The GAN-MAR CT volumes generated in a short time were closer to the Reference CT volumes than the Water and Artifacts CT volumes. The observed dosimetric differences compared to the reference plan were clinically acceptable.

Evaluation of intrafractional head motion for intracranial stereotactic radiosurgery with a thermoplastic frameless mask and ceiling-floor-mounted image guidance device.

PURPOSE: To evaluate intrafractional head motion (IFM) in patients who underwent intracranial stereotactic radiosurgery with the ExacTrac X-ray system (ETX) and a frameless mask. METHODS: A total of 143 patients who completed a pre-treatment examination for IFM were eligible for this study. The frameless mask type B R408 (Klarity Medical & Equipment Co., Ltd., Guangzhou, China), which covers the back of the head, and the entire face, was used for patient immobilization. After the initial 6D correction and first X-ray verification (IFM1), X-ray verification was performed every 3 min for a duration of 15 min. The IFMp (2 ≤ p ≤ 6) was calculated as the positional difference from IFM1. In addition, the inter-phase IFM (IP-IFM) and IFMm were calculated. The IP-IFM was defined as |IFMp - IFMp-1|, and IFMm as the difference between the values after all patients were asked to move their heads intentionally with the frameless mask on. RESULTS: Both translational IFMp and IP-IFM exceeded 1 mm for a single patient, whereas, for all patients, the translational IFMm values were kept to within 1 mm in all directions. The proportions of the rotational IFMp, IP-IFM, and IFMm values within 0.5° were greater than 94.4%, 98.6%, and 90.2% for all of the rotational axes, respectively. CONCLUSIONS: A frameless mask achieved highly accurate patient positioning in combination with ETX and a 6°-of-freedom robotic couch; however, a deviation over 1 mm and 0.5° was observed with low frequency. Therefore, X-ray verification and correction are required during treatment.

Statistical shape model-based planning organ-at-risk volume: application to pancreatic cancer patients.

PURPOSE: To introduce the concept of statistical shape model (SSM)-based planning organ-at-risk volume (sPRV) for pancreatic cancer patients. METHODS: A total of 120 pancreatic cancer patients were enrolled in this study. After correcting inter-patient variations in the centroid position of the planning target volume (PTV), four different SSMs were constructed by registering a deformable template model to an individual model for the stomach and duodenum. The sPRV, which focused on the following different components of the inter-patient variations, was then created: Scenario A: shape, rotational angle, volume, and centroid position; Scenario B: shape, rotational angle, and volume; Scenario C: shape and rotational angle; and Scenario D: shape. The conventional PRV (cPRV) was created by adding an isotropic margin R (3-15 mm) to the mean shape model. The corresponding sPRV was created from the SSM until the volume difference between the cPRV and sPRV was less than 1%. Thereafter, we computed the overlapping volume between the PTV and cPRV (OLc) or sPRV (OLs) in each patient. OLs being larger than OLc implies that the local shape variations in the corresponding OAR close to the PTV were large. Therefore, OLs/OLc was calculated in each patient for each R-value, and the median value of OLs/OLc was regarded as a surrogate for plan quality for each R-value. RESULTS: For R = 3 and 5 mm, OLs/OLc exceeded 1 for the stomach and duodenum in all scenarios, with a maximum OLs/OLc of 1.21. This indicates that smaller isotropic margins did not sufficiently account for the local shape changes close to the PTV. CONCLUSIONS: Our results indicated that, in contrast to conventional PRV, SSM-based PRVs, which account for local shape changes, would result in better dose sparing for the stomach and duodenum in pancreatic cancer patients.

Validation of the clinical applicability of knowledge-based planning models in single-isocenter volumetric-modulated arc therapy for multiple brain metastases.

PURPOSE: To validate the clinical applicability of knowledge-based (KB) planning in single-isocenter volumetric-modulated arc therapy (VMAT) for multiple brain metastases using the k-fold cross-validation (CV) method. METHODS: This study comprised 60 consecutive patients with multiple brain metastases treated with single-isocenter VMAT (28 Gy in five fractions). The patients were divided randomly into five groups (Groups 1-5). The data of Groups 1-4 were used as the training and validation dataset and those of Group 5 were used as the testing dataset. Four KB models were created from three of the training and validation datasets and then applied to the remaining Groups as the fourfold CV phase. As the testing phase, the final KB model was applied to Group 5 and the dose distributions were calculated with a single optimization process. The dose-volume indices (DVIs), modified Ian Paddick Conformity Index (mIPCI), modulation complexity scores for VMAT plans (MCSv), and the total number of monitor units (MUs) of the final KB plan were compared to those of the clinical plan (CL) using a paired Wilcoxon signed-rank test. RESULTS: In the fourfold CV phase, no significant differences were observed in the DVIs among the four KB plans (KBPs). In the testing phase, the final KB plan was statistically equivalent to the CL, except for planning target volumes (PTVs) D2% and D50% . The differences between the CL and KBP in terms of the PTV D99.5% , normal brain, and Dmax to all organs at risk (OARs) were not significant. The KBP achieved a lower total number of MUs and higher MCSv than the CL with no significant difference. CONCLUSIONS: We demonstrated that a KB model in a single-isocenter VMAT for multiple brain metastases was equivalent in dose distribution, MCSv, and total number of MUs to a CL with a single optimization.