Assessment of the deep learning-based gamma passing rate prediction system for 1.5 T magnetic resonance-guided linear accelerator.

Measurement-based verification is impossible for the patient-specific quality assurance (QA) of online adaptive magnetic resonance imaging-guided radiotherapy (oMRgRT) because the patient remains on the couch throughout the session. We assessed a deep learning (DL) system for oMRgRT to predict the gamma passing rate (GPR). This study collected 125 verification plans [reference plan (RP), 100; adapted plan (AP), 25] from patients with prostate cancer treated using Elekta Unity. Based on our previous study, we employed a convolutional neural network that predicted the GPRs of nine pairs of gamma criteria from 1%/1 mm to 3%/3 mm. First, we trained and tested the DL model using RPs (n = 75 and n = 25 for training and testing, respectively) for its optimization. Second, we tested the GPR prediction accuracy using APs to determine whether the DL model could be applied to APs. The mean absolute error (MAE) and correlation coefficient (r) of the RPs were 1.22 ± 0.27% and 0.29 ± 0.10 in 3%/2 mm, 1.35 ± 0.16% and 0.37 ± 0.15 in 2%/2 mm, and 3.62 ± 0.55% and 0.32 ± 0.14 in 1%/1 mm, respectively. The MAE and r of the APs were 1.13 ± 0.33% and 0.35 ± 0.22 in 3%/2 mm, 1.68 ± 0.47% and 0.30 ± 0.11 in 2%/2 mm, and 5.08 ± 0.29% and 0.15 ± 0.10 in 1%/1 mm, respectively. The time cost was within 3 s for the prediction. The results suggest the DL-based model has the potential for rapid GPR prediction in Elekta Unity.

Beginning of clinical treatment using the 1.5 Tesla MR-Linac system in Japan: a narrative review.

Background and Objective: In the field of radiation therapy, image-guided radiotherapy (IGRT) technology has been gradually improving and highly accurate radiation treatment has been possible. Research on IGRT using 1.5 Tesla magnetic resonance imaging (MRI) began in 1999, and a radiation therapy device called 1.5 Tesla magnetic resonance linear accelerator (MR-Linac), which combines a linear accelerator with 1.5 Tesla MRI, was developed in Europe. The aim of this review is to present an overview of 1.5 Tesla MR-Linac with a review of the literature and our experience. Methods: Reports related to 1.5 Tesla MR-Linac were searched for in PubMed and are discussed in relation to our experience. Key Content and Findings: The 1.5 Tesla MR-Linac enables IGRT using 1.5 Tesla MRI, further enhancing the precision of radiation therapy. Position verification by cone-beam computed tomography (CBCT) is performed in many institutions, but soft tissue contrast is often unclear in CBCT images of the abdomen and mediastinal organs. Since the 1.5 Tesla MR-Linac allows position verification using MRI, position verification can be performed using clear MRI even in regions where CBCT is unclear. With the 1.5 Tesla MR-Linac, it is possible to perform online adaptive radiotherapy (ART) using 1.5 Tesla MRI. Online ART is a method in which images are acquired while the patient is on the treatment table. The method is based on the current condition of the organs in the body on that day and an optimal treatment field is recreated. Additionally, it allows monitoring of tumor motion using cine images obtained by 1.5 Tesla MRI during the delivery of X-ray radiation. A previous report showed that patients with prostate cancer who received radiotherapy by MR-Linac had fewer side effects than those in patients who received conventional CBCT radiation therapy. Conclusions: The 1.5 Tesla MR-Linac obtained CE-mark certification in Europe in August 2018 and it has been used for clinical treatment. In Japan, clinical treatment using this device started in 2021. By using 1.5 Tesla MR-Linac, patients can be provided with higher precision radiotherapy. In this review, we provide an overview of 1.5 Tesla MR-Linac.

Evaluation of Unity 1.5 T MR-linac plan quality in patients with prostate cancer.

The Unity magnetic resonance (MR) linear accelerator (MRL) with MR-guided adaptive radiotherapy (MRgART) is capable of online MRgART where images are acquired on the treatment day and the radiation treatment plan is immediately replanned and performed. We evaluated the MRgART plan quality and plan reproducibility of the Unity MRL in patients with prostate cancer. There were five low- or moderate-risk and five high-risk patients who received 36.25 Gy or 40 Gy, respectively in five fractions. All patients underwent simulation magnetic resonance imaging (MRI) and five online adaptive MRI. We created plans for 5, 7, 9, 16, and 20 beams and for 60, 100, and 150 segments. We evaluated the target and organ doses for different number of beams and segments, respectively. Variation in dose constraint between the simulation plan and online adaptive plan was measured for each patient to assess plan reproducibility. The plan quality improved with the increasing number of beams. However, the proportion of significantly improved dose constraints decreased as the number of beams increased. For some dose parameters, there were statistically significant differences between 60 and 100 segments, and 100 and 150 segments. The plan of five beams exhibited limited reproducibility. The number of segments had minimal impact on plan reproducibility, but 60 segments sometimes failed to meet dose constraints for online adaptive plan. The optimization and delivery time increased with the number of beams and segments. We do not recommend using five or fewer beams for a reproducible and high-quality plan in the Unity MRL. In addition, many number of segments and beams may help meet dose constraints during online adaptive plan. Treatment with the Unity MRL should be performed with the appropriate number of beams and segments to achieve a good balance among plan quality, delivery time, and optimization time.

Evaluation of deep learning-based deliverable VMAT plan generated by prototype software for automated planning for prostate cancer patients.

This study aims to evaluate the dosimetric accuracy of a deep learning (DL)-based deliverable volumetric arc radiation therapy (VMAT) plan generated using DL-based automated planning assistant system (AIVOT, prototype version) for patients with prostate cancer. The VMAT data (cliDose) of 68 patients with prostate cancer treated with VMAT treatment (70-74 Gy/28-37 fr) at our hospital were used (n = 55 for training and n = 13 for testing). First, a HD-U-net-based 3D dose prediction model implemented in AIVOT was customized using the VMAT data. Thus, a predictive VMAT plan (preDose) comprising AIVOT that predicted the 3D doses was generated. Second, deliverable VMAT plans (deliDose) were created using AIVOT, the radiation treatment planning system Eclipse (version 15.6) and its vender-supplied objective functions. Finally, we compared these two estimated DL-based VMAT treatment plans-i.e. preDose and deliDose-with cliDose. The average absolute dose difference of all DVH parameters for the target tissue between cliDose and deliDose across all patients was 1.32 ± 1.35% (range: 0.04-6.21%), while that for all the organs at risks was 2.08 ± 2.79% (range: 0.00-15.4%). The deliDose was superior to the cliDose in all DVH parameters for bladder and rectum. The blinded plan scoring of deliDose and cliDose was 4.54 ± 0.50 and 5.0 ± 0.0, respectively (All plans scored ≥4 points, P = 0.03.) This study demonstrated that DL-based deliverable plan for prostate cancer achieved the clinically acceptable level. Thus, the AIVOT software exhibited a potential for automated planning with no intervention for patients with prostate cancer.

[Evaluation of Accuracy of Deformable Image Registration with Newly Developed Treatment Planning Support Software for Thoracic Images].

This study evaluated accuracy of deformable image registration (DIR) with twelve parameter settings for thoracic images. We used peak-inhale and peak-exhale images for ten patients provided by DIR-lab. We used a prototype version of iCView software (ITEM Corporation) with DIR to perform intensity, structure, and hybrid-based DIR with the twelve parameter settings. DIR accuracy was evaluated by a target registration error (TRE) using 300 bronchial bifurcations and the Dice similarity coefficient (DSC) of the lungs. For twelve parameter settings, TRE ranged from 2.83 mm to 5.27 mm, whereas DSC ranged from 0.96 to 0.98. These results demonstrated that DIR accuracy differed among parameter settings and show that appropriate parameter settings are required for clinical practice.

Dosimetric effects of the ipsilateral shoulder position variations in the sitting-positioned boron neutron capture therapy for lower neck tumor.

We aimed to evaluate dosimetric effects of ipsilateral shoulder position variations (ISPVs) in sitting-positioned boron neutron capture therapy (BNCT) for lower neck tumor. The ISPVs were simulated using deformed shoulder images that can simulate arbitrary shape. The dose-volume parameters for the tumor in the rotated shoulder plans considerably varied compared with that for the mucosa. Even in a small number of cases, these differences were clearly observed among patients. The ISPVs in lower neck BNCT have great dosimetric effects.

Determining a methodology of dosimetric quality assurance for commercially available accelerator-based boron neutron capture therapy system.

The irradiation field of boron neutron capture therapy (BNCT) consists of multiple dose components including thermal, epithermal and fast neutron, and gamma. The objective of this work was to establish a methodology of dosimetric quality assurance (QA), using the most standard and reliable measurement methods, and to determine tolerance level for each QA measurement for a commercially available accelerator-based BNCT system. In order to establish a system of dosimetric QA suitable for BNCT, the following steps were taken. First, standard measurement points based on tissue-administered doses in BNCT for brain tumors were defined, and clinical tolerances of dosimetric QA measurements were derived from the contribution to total tissue relative biological effectiveness factor-weighted dose for each dose component. Next, a QA program was proposed based on TG-142 and TG-198, and confirmed that it could be assessed whether constancy of each dose component was assured within the limits of tolerances or not by measurements of the proposed QA program. Finally, the validity of the BNCT QA program as an evaluation system was confirmed in a demonstration experiment for long-term measurement over 1 year. These results offer an easy, reliable QA method that is clinically applicable with dosimetric validity for the mixed irradiation field of accelerator-based BNCT.

The impact of 4DCT-ventilation imaging-guided proton therapy on stereotactic body radiotherapy for lung cancer.

Functional lung avoidance during radiotherapy can help reduce pulmonary toxicity. This study assessed the potential impact of four-dimensional computed tomography (4DCT)-ventilation imaging-guided proton radiotherapy (PT) on stereotactic body radiotherapy (SBRT) by comparing it with three-dimensional conformal radiotherapy (3D-CRT) and volumetric modulated arc therapy (VMAT), which employ photon beams. Thirteen lung cancer patients who received SBRT with 3D-CRT were included in the study. 4DCT ventilation was calculated using the patients' 4DCT data, deformable image registration, and a density-change-based algorithm. Three functional treatment plans sparing the functional lung regions were developed for each patient using 3D-CRT, VMAT, and PT. The prescribed doses and dose constraints were based on the Radiation Therapy Oncology Group 0618 protocol. We evaluated the region of interest (ROI) and functional map-based dose-function metrics for 4DCT ventilation and the irradiated dose. Using 3D-CRT, VMAT, and PT, the percentages of the functional lung regions that received ≥ 5 Gy (fV5) were 26.0%, 21.9%, and 10.7%, respectively; the fV10 were 14.4%, 11.4%, and 9.0%, respectively; and fV20 were 6.5%, 6.4%, and 6.6%, respectively, and the functional mean lung doses (fMLD) were 5.6 Gy, 5.2 Gy, and 3.8 Gy, respectively. These results indicated that PT resulted in a significant reduction in fMLD, fV5, and fV10, but not fV20. The use of PT reduced the radiation to highly functional lung regions compared with those for 3D-CRT and VMAT while meeting all dose constraints.

Design and construction of an accelerator-based boron neutron capture therapy (AB-BNCT) facility with multiple treatment rooms at the Southern Tohoku BNCT Research Center.

Installation of an accelerator-based boron neutron capture therapy (AB-BNCT) system was started in April 2014 at the Southern Tohoku BNCT Research Center (STBRC), and clinical trials began in January 2016. There are two treatment rooms, which have same specifications, and the beam quality equivalency was confirmed both rooms. Here, we describe the design and construction of the first hospital-based AB-BNCT facility in the world with multiple treatment rooms.

[Influence and Countermeasure of Respiratory Motion on Matchline Profile of Field Matching Technique in Passive Scattering Proton Therapy for Esophageal Cancer].

This study aimed to evaluate the influence of change in respiratory motion on matchline (ML) and reduction of the effect by increasing ML levels of field matching technique in passive scattering proton therapy for esophageal cancer. To evaluate the influence of respiratory motion in terms of stability, we measured relative dose around ML using a respiratory motion phantom. The relative error was -0.5% when the respiratory motion phantom worked stable, whereas there was obvious change that the relative error was -25.5% when the difference of amplitude between upper field and lower field was one side 3 mm on each cranially and caudally direction. In clinical case of the seven esophageal cancer patients simulated by the treatment planning system, assuming the difference of amplitude was 3 mm, the relative error of maximum (minimum) dose in clinical target volume around ML against the original treatment plan were 5.8±1.2% (-6.0±2.7%), 3.3±0.9% (-3.8±1.0%), and 2.4±0.5% (2.6±0.8%) on average (±SD) when ML levels were 2, 4, and 6, respectively. Increasing ML levels can reduce the influence of respiratory motion.

Patient-specific quality assurance for proton depth dose distribution using a multi-layer ionization chamber in a single-ring wobbling method.

The use of a multi-layer ionization chamber, Zebra, in patient-specific quality assurance (QA) for proton depth dose distributions in a single-ring wobbling method is investigated. The depth dose distributions measured using Zebra are compared with those calculated using the treatment planning system (TPS), XiO-M, and measured using an ionization chamber with a motorized water phantom system. Because the TPS only provides point doses, the average doses are calculated using in-house software. The detector size-corrected depth dose distributions are obtained by determining the average of the dose distributions from the TPS over a cylindrical region similar to the size of the Zebra detectors. The calculated depth dose distributions from the cases with a simple compensator shape are in good agreement with those obtained from the TPS without performing volume averaging; however, a 15% difference was shown when compared with those from the cases with a complex compensator shape. Then, the measurements are compared with the detector size-corrected depth dose distributions, showing an improved agreement within 3% for the highly steep dose gradient regions. Although there are some field size limitations, the Zebra system is a useful device for the fast measurement of patient-specific QA for depth dose distributions in wobbled proton beams. However, careful consideration is required for complex dose distribution fields, because the measurements obtained using Zebra cannot be directly compared to the depth dose distributions from the TPS owing to the finite detector size of the Zebra chamber.

Effect of anatomical change on dose distribution during radiotherapy for maxillary sinus carcinoma: passive scattering proton therapy versus volumetric-modulated arc therapy.

OBJECTIVE:: Maxillary sinus carcinomas are anatomically situated next to many organs at risk (OARs), and anatomical change is often observed during radiotherapy. We analyzed the effect of anatomical change on dose distribution of passive scattering proton therapy (PSPT) and volumetric-modulated arc therapy (VMAT) for 20 patients. METHODS:: The first plans were generated based on the first CT images. The second CT images were acquired after 3 weeks, and the second plans were generated by copying the first plans to the second CT images. The effect of anatomical change was estimated by comparing both plans. RESULTS:: Target volume change was observed in all cases, however, the influence on dose coverage of clinical target volume tended to be small. Alternatively, the doses to almost all OARs were increased. In particular, the increase in the dose to brainstem (p < 0.001) and optic chiasm (p < 0.001) was significantly higher in the second PSPT plan than in the first PSPT plan. Although PSPT is sensitive to anatomical change, the dose to OARs remained significantly lower in PSPT plans than that in VMAT plans. CONCLUSION:: PSPT was confirmed to be more effective than VMAT even the effect of anatomical change was taken into account. Therefore, it is expected that the contralateral vision can be preserved reliably while optimal target coverage is provided. ADVANCES IN KNOWLEDGE:: PSPT allowed significant sparing of OARs even in the result of the second plans affected by the anatomical change. PSPT offers benefits over VMAT in reducing dose to several OARs.

Effect of DIR uncertainty on prostate passive-scattering proton therapy dose accumulation.

Deformable image registration (DIR) is important in dose accumulation. Currently, the impact of DIR-algorithm-associated uncertainties in proton therapy is unclear. Here, we quantify the effect of DIR uncertainties on prostate passive-scattering proton therapy (PSPT) dose accumulation. Ten patients with an intermediate risk for prostate cancer formerly treated by PSPT (PTV D95=78GyE) were studied. Dose distributions from all verification CT images (five images per patient) were warped and accumulated in the planning CT geometries with DIR. The dose-volume histogram parameters (Dmean, V40, and V70) for rectum and bladder were calculated. Two commercially available DIR software packages were employed: Velocity AI (Varian Medical Systems) and RayStation (RaySearch Laboratories). The dice similarity coefficient (DSC) and surface distance, which were calculated between planning CT contours and deformed contours, were used for DIR validation, with the relationship between the dose parameter and DIR uncertainty ultimately investigated. On average, when using RayStation, the DSC increased by 0.14 and surface distance decreased by 6.4mm, as compared to Velocity. For Dmean, V40, and V70 to the rectum, the average differences between the RayStation and Velocity were 3.9GyE, 5.5%, and 3.2%, respectively. For the bladder, the differences were 5.2GyE, 5.8%, and 5.4%, respectively. The maximum differences in V40 between RayStation and Velocity were 14.4% and 22.8% for the rectum and bladder, respectively, when the average DSC and surface distance differences were more than 0.14 and 6.4mm, respectively. Such results suggest that DIR uncertainties might significantly affect prostate PSPT dose accumulations.

Feasibility of CBCT-based proton dose calculation using a histogram-matching algorithm in proton beam therapy.

The aim of this study was to confirm On-Board Imager cone-beam computed tomography (CBCT) using the histogram-matching algorithm as a useful method for proton dose calculation. We studied one head and neck phantom, one pelvic phantom, and ten patients with head and neck cancer treated using intensity-modulated radiation therapy (IMRT) and proton beam therapy. We modified Hounsfield unit (HU) values of CBCT and generated two modified CBCTs (mCBCT-RR, mCBCT-DIR) using the histogram-matching algorithm: modified CBCT with rigid registration (mCBCT-RR) and that with deformable image registration (mCBCT-DIR). Rigid and deformable image registration were applied to match the CBCT to planning CT. To evaluate the accuracy of the proton dose calculation, we compared dose differences in the dosimetric parameters (D2% and D98%) for clinical target volume (CTV) and planning target volume (PTV). We also evaluated the accuracy of the dosimetric parameters (Dmean and D2%) for some organs at risk, and compared the proton ranges (PR) between planning CT (reference) and CBCT or mCBCTs, and the gamma passing rates of CBCT and mCBCTs. For patients, the average dose and PR differences of mCBCTs were smaller than those of CBCT. Additionally, the average gamma passing rates of mCBCTs were larger than those of CBCT (e.g., 94.1±3.5% in mCBCT-DIR vs. 87.8±7.4% in CBCT). We evaluated the accuracy of the proton dose calculation in CBCT and mCBCTs for two phantoms and ten patients. Our results showed that HU modification using the histogram-matching algorithm could improve the accuracy of the proton dose calculation.

Multi-institutional Validation Study of Commercially Available Deformable Image Registration Software for Thoracic Images.

PURPOSE: To assess the accuracy of the commercially available deformable image registration (DIR) software for thoracic images at multiple institutions. METHODS AND MATERIALS: Thoracic 4-dimensional (4D) CT images of 10 patients with esophageal or lung cancer were used. Datasets for these patients were provided by DIR-lab (dir-lab.com) and included a coordinate list of anatomic landmarks (300 bronchial bifurcations) that had been manually identified. Deformable image registration was performed between the peak-inhale and -exhale images. Deformable image registration error was determined by calculating the difference at each landmark point between the displacement calculated by DIR software and that calculated by the landmark. RESULTS: Eleven institutions participated in this study: 4 used RayStation (RaySearch Laboratories, Stockholm, Sweden), 5 used MIM Software (Cleveland, OH), and 3 used Velocity (Varian Medical Systems, Palo Alto, CA). The ranges of the average absolute registration errors over all cases were as follows: 0.48 to 1.51 mm (right-left), 0.53 to 2.86 mm (anterior-posterior), 0.85 to 4.46 mm (superior-inferior), and 1.26 to 6.20 mm (3-dimensional). For each DIR software package, the average 3-dimensional registration error (range) was as follows: RayStation, 3.28 mm (1.26-3.91 mm); MIM Software, 3.29 mm (2.17-3.61 mm); and Velocity, 5.01 mm (4.02-6.20 mm). These results demonstrate that there was moderate variation among institutions, although the DIR software was the same. CONCLUSIONS: We evaluated the commercially available DIR software using thoracic 4D-CT images from multiple centers. Our results demonstrated that DIR accuracy differed among institutions because it was dependent on both the DIR software and procedure. Our results could be helpful for establishing prospective clinical trials and for the widespread use of DIR software. In addition, for clinical care, we should try to find the optimal DIR procedure using thoracic 4D-CT data.

Evaluation of on-board kV cone beam computed tomography-based dose calculation with deformable image registration using Hounsfield unit modifications.

PURPOSE: The purpose of this study was to estimate the accuracy of the dose calculation of On-Board Imager (Varian, Palo Alto, CA) cone beam computed tomography (CBCT) with deformable image registration (DIR), using the multilevel-threshold (MLT) algorithm and histogram matching (HM) algorithm in pelvic radiation therapy. METHODS AND MATERIALS: One pelvis phantom and 10 patients with prostate cancer treated with intensity modulated radiation therapy were studied. To minimize the effect of organ deformation and different Hounsfield unit values between planning CT (PCT) and CBCT, we modified CBCT (mCBCT) with DIR by using the MLT (mCBCT(MLT)) and HM (mCBCT(HM)) algorithms. To evaluate the accuracy of the dose calculation, we compared dose differences in dosimetric parameters (mean dose [D(mean)], minimum dose [D(min)], and maximum dose [D(max)]) for planning target volume, rectum, and bladder between PCT (reference) and CBCTs or mCBCTs. Furthermore, we investigated the effect of organ deformation compared with DIR and rigid registration (RR). We determined whether dose differences between PCT and mCBCTs were significantly lower than in CBCT by using Student t test. RESULTS: For patients, the average dose differences in all dosimetric parameters of CBCT with DIR were smaller than those of CBCT with RR (eg, rectum; 0.54% for DIR vs 1.24% for RR). For the mCBCTs with DIR, the average dose differences in all dosimetric parameters were less than 1.0%. CONCLUSIONS: We evaluated the accuracy of the dose calculation in CBCT, mCBCT(MLT), and mCBCT(HM) with DIR for 10 patients. The results showed that dose differences in D(mean), D(min), and D(max) in mCBCTs were within 1%, which were significantly better than those in CBCT, especially for the rectum (P<.05). Our results indicate that the mCBCT(MLT) and mCBCT(HM) can be useful for improving the dose calculation for adaptive radiation therapy.