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The key goal and main challenge of radiation therapy is the elimination of tumors without any concurring damages of the surrounding healthy tissues and organs. Radiation doses required to achieve sufficient cancer‐cell kill exceed in most clinical situations the dose that can be tolerated by the healthy tissues, especially when large parts of the affected organ are irradiated. High‐precision radiation oncology aims at optimizing tumor coverage, while sparing normal tissues. Medical imaging during the preparation phase, as well as in the treatment room for localization of the tumor and directing the beam, referred to as image‐guided radiotherapy (IGRT), is the cornerstone of precision radiation oncology. Sophisticated high‐resolution real‐time IGRT using X‐rays, computer tomography, magnetic resonance imaging, or ultrasound, enables delivery of high radiation doses to tumors without significant damage of healthy organs. IGRT is the most convincing success story of radiation oncology over the last decades, and it remains a major driving force of innovation, contributing to the development of personalized oncology, for example, through the use of real‐time imaging biomarkers for individualized dose delivery. Sophisticated, high‐resolution, real‐time image‐guided radiotherapy (IGRT) using X‐rays, computer tomography, magnetic resonance imaging, or ultrasound, enables delivery of high radiation doses to tumors without significant damage of healthy organs. Here, we review IGRT research and applications and discuss how they contribute to the development of personalized oncology, for example, through the use of real‐time imaging biomarkers for individualized dose delivery.

Purpose This study aims to investigate a star shot analysis using a three‐dimensional (3D) gel dosimeter for the imaging and radiation isocenter verification of a magnetic resonance linear accelerator (MR‐Linac). Methods A mixture of methacrylic acid, gelatin, and tetrakis (hydroxymethyl) phosphonium chloride, called MAGAT gel, was fabricated. One MAGAT gel for each Linac and MR‐Linac was irradiated under six gantry angles. A 6 MV photon beam of Linac and a 6 MV flattening filter free beam of MR‐Linac were delivered to two MAGAT gels and EBT3 films. MR images were acquired by MR‐Linac with a clinical sequence (i.e., TrueFISP). The 3D star shot analysis for seven consecutive slices of the MR images with TrueFISP was performed. The 2D star shot analysis for the central plane of the gel was compared to the results from the EBT3 films. The radius of isocircle (ICr) and the distance between the center of the circle and the center marked on the image (ICd) were evaluated. Results For MR‐Linac with MAGAT gel measurements, ICd at the central plane was 0.46 mm for TrueFISP. Compared to EBT3 film measurements, the differences in ICd and ICr for both Linac and MR‐Linac were within 0.11 and 0.13 mm, respectively. For the 3D analysis, seven consecutive slices of TrueFISP images were analyzed and the maximum radii of isocircles (ICr_max) were 0.18 mm for Linac and 0.73 mm for MR‐Linac. The tilting angles of radiation axis were 0.31° for Linac and 0.10° for MR‐Linac. Conclusion The accuracy of 3D star shot analysis using MAGAT gel was comparable to that of EBT3 film, having a capability for integrated analysis for imaging isocenter and radiation isocenter. 3D star shot analysis using MAGAT gel can provide 3D information of radiation isocenter, suggesting a quantitative extent of gantry‐tilting.

Purpose This work describes a single institution experience of commissioning a real‐time target tracking and beam control system, known as comprehensive motion management, for a 1.5 T Elekta MR‐Linac. Methods Anatomical tracking and radiation beam control were tested using the MRI4D Quasar motion phantom. Multiple respiratory breathing traces were modeled across a range of realistic regular and irregular breathing patterns ranging between 10 and 18 breaths per minute. Each of the breathing traces was used to characterize the anatomical position monitoring (APM) accuracy, and beam latency, and to quantify the dosimetric impact of both parameters during a respiratory‐gated delivery using EBT3 film dosimetry. Additional commissioning tasks were performed to verify the dosimetric constancy during beam gating and to expand our existing quality assurance program. Results It was determined that APM correctly predicted the 3D position of a dynamically moving tracking target to within 1.5 mm for 95% of the imaging frames with no deviation exceeding 2 mm. Among the breathing traces investigated, the mean latency ranged between −21.7 and 7.9 ms with 95% of all observed latencies within 188.3 ms. No discernable differences were observed in the relative profiles or cumulative output for a gated beam relative to an ungated beam with minimal dosimetric impact observed due to system latency. Measured dose profiles for all gated scenarios retained a gamma pass rate of 97% or higher for a 3%/2 mm criteria relative to a theoretical gated dose profile without latency or tracking inaccuracies. Conclusion MRI‐guided target tracking and automated beam delivery control were successfully commissioned for the Elekta Unity MR‐Linac. These gating features were shown to be highly accurate with an effectively small beam latency for a range of regular and irregular respiratory breathing traces.

Purpose The aim of this study was to assess the use of magnetic resonance guided adaptive radiotherapy (MRgART) in the post‐prostatectomy setting; comparing dose accumulation for our initial seven patients treated with fully adaptive workflow on the Unity MR‐Linac (MRL) and with non‐adaptive plans generated offline. Additionally, we analyzed toxicity in patients receiving treatment. Methods Seven patients were treated with MRgART. The prescription was 70–72 Gy in 35–36 fractions. Patients were treated with an adapt to shape (ATS) technique. For each clinically delivered plan, a non‐adaptive plan based upon the reference plan was generated and compared to the associated clinically delivered plan. A total of 468 plans were analyzed. Concordance Index of target and Organs at Risk (OARs) for each fraction with reference contours was analyzed. Acute toxicity was then assessed at six‐months following completion of treatment with Common Terminology for Adverse Events (CTCAE) Toxicity Criteria. Results A total of 246 fractions were clinically delivered to seven patients; 234 fractions were delivered via MRgART and 12 fractions delivered via a traditional linear accelerator due to machine issues. Pre‐treatment reference plans met CTV and OAR criteria. PTV coverage satisfaction was higher in the clinically delivered adaptive plans than non‐adaptive comparison plans; 42.93% versus 7.27% respectively. Six‐month CTCAE genitourinary and gastrointestinal toxicity was absent in most patients, and mild‐to‐moderate in a minority of patients (Grade 1 GU toxicity in one patient and Grade 2 GI toxicity in one patient). Conclusions Daily MRgART treatment consistently met planning criteria. Target volume variability in prostate bed treatment can be mitigated by using MRgART and deliver satisfactory coverage of CTV whilst minimizing dose to adjacent OARs and reducing toxicity

Purpose Magnetic Resonance (MR)‐guided online adaptive radiation therapy (MRgOART), enabled with MR‐Linac, has potential to revolutionize radiation therapy. MRgOART is a complex process. This work is to introduce a comprehensive end‐to‐end quality assurance (QA) workflow in routine clinic for MRgOART with a high‐magnetic‐field MR‐Linac. Materials and Method The major components in MRgOART with a high‐magnetic field MR‐Linac (Unity, Elekta) include: (1) a patient record and verification (R&V) system (e.g., Mosaiq, Elekta), (2) a treatment session manager, (3) an offline treatment planning system (TPS), (4) an online adaptive TPS, (5) a 1.5T MRI scanner, (6) an 7MV Linac, (7) an MV imaging controller (MVIC), and (8) ArtQA: software for plan data consistency checking and secondary dose calculation. Our end‐to‐end QA workflow was designed to test the performance and connectivity of all these components by transferring, adapting and delivering a specifically designed five‐beam plan on a phantom. Beams 1–4 were designed to check Multi‐Leaves Collimator (MLC) position shift based on rigid image registration in TPS, while beam 5 was used to check daily radiation output based on image pixel factor of MV image of the field. The workflow is initiated in the R&V system and followed by acquiring and registering daily MRI of the phantom, checking isocenter shift, performing online adaptive replanning, checking plan integrity and secondary 3D dose calculation, delivering the plan while acquiring MV imaging using MVIC, acquiring real‐time images of the phantom, and checking the delivering parameters with ArtQA. Results It takes 10 min to finish the entire end‐to‐end QA workflow. The workflow has detected communication problems, permitted resolution prior to setting up patients for MRgOART. Up to 0.9 mm discrepancies in isocenter shift based on the image registration were detected. ArtQA performed the secondary 3D dose calculation, verified the plan integrity as well as the MR‐MV isocenter alignment values in TPS. The MLC shapes of beam 1–4 in all adaptive plans were conformal to the target and agreed with MV images. The variation of daily output was within ±2.0%. Conclusions The comprehensive end‐to‐end QA workflow can efficiently check the performance and communication between different components in MRgOART and has been successfully implemented for daily clinical practice.

Purpose To describe and report longitudinal quality assurance (QA) measurements for the magnetic resonance imaging (MRI) component of the Elekta Unity MR‐linac during the first year of clinical use in our institution. Materials and methods The performance of the MRI component of Unity was evaluated with daily, weekly, monthly, and annual QA testing. The measurements monitor image uniformity, signal‐to‐noise ratio (SNR), resolution/detectability, slice position/thickness, linearity, central frequency, and geometric accuracy. In anticipation of routine use of quantitative imaging (qMRI), we characterize B0/B1 uniformity and the bias/reproducibility of longitudinal/transverse relaxation times (T1/T2) and apparent diffusion coefficient (ADC). Tolerance levels for QA measurements of qMRI biomarkers are derived from weekly monitoring of T1, T2, and ADC. Results The 1‐year assessment of QA measurements shows that daily variations in each MR quality metric are well below the threshold for failure. Routine testing procedures can reproducibly identify machine issues. The longitudinal three‐dimensional (3D) geometric analysis reveals that the maximum distortion in a diameter of spherical volume (DSV) of 20, 30, 40, and 50 cm is 0.4, 0.6, 1.0, and 3.1 mm, respectively. The main source of distortion is gradient nonlinearity. Maximum peak‐to‐peak B0 inhomogeneity is 3.05 ppm, with gantry induced B0 inhomogeneities an order of magnitude smaller. The average deviation from the nominal B1 is within 2%, with minimal dependence on gantry angle. Mean ADC, T1, and T2 values are measured with high reproducibility. The median coefficient of variation for ADC, T1, and T2 is 1.3%, 1.1%, and 0.5%, respectively. The median bias for ADC, T1, and T2 is −0.8%, −0.1%, and 3.9%, respectively. Conclusion The MRI component of Unity operates within the guidelines and recommendations for scanner performance and stability. Our findings support the recently published guidance in establishing clinically acceptable tolerance levels for image quality. Highly reproducible qMRI measurements are feasible in Unity.

This study aimed to investigate the necessity of measurement‐based patient‐specific quality assurance (PSQA) for online adaptive radiotherapy by analyzing measurement‐based PSQA results and calculation‐based 3D independent dose verification results with Elekta Unity MR‐Linac. There are two workflows for Elekta Unity enabled in the treatment planning system: adapt to position (ATP) and adapt to shape (ATS). ATP plans are those which have relatively slighter shifts from reference plans by adjusting beam shapes or weights, whereas ATS plans are the new plans optimized from the beginning with probable re‐contouring targets and organs‐at‐risk. PSQA gamma passing rates were measured using an MR‐compatible ArcCHECK diode array for 78 reference plans and corresponding 208 adaptive plans (129 ATP plans and 79 ATS plans) of Elekta Unity. Subsequently, the relationships between ATP, or ATS plans and reference plans were evaluated separately. The Pearson's r correlation coefficients between ATP or ATS adaptive plans and corresponding reference plans were also characterized using regression analysis. Moreover, the Bland–Altman plot method was used to describe the agreement of PSQA results between ATP or ATS adaptive plans and reference plans. Additionally, Monte Carlo‐based independent dose verification software ArcherQA was used to perform secondary dose check for adaptive plans. For ArcCHECK measurements, the average gamma passing rates (ArcCHECK vs. TPS) of PSQA (3%/2 mm criterion) were 99.51% ± 0.88% and 99.43% ± 0.54% for ATP and ATS plans, respectively, which were higher than the corresponding reference plans 99.34% ± 1.04% (p < 0.05) and 99.20% ± 0.71% (p < 0.05), respectively. The Pearson's r correlation coefficients were 0.720 between ATP and reference plans and 0.300 between ATS and reference plans with ArcCHECK, respectively. Furthermore, >95% of data points of differences between both ATP and ATS plans and reference plans were within ±2σ (standard deviation) of the mean difference between adaptive and reference plans with ArcCHECK measurements. With ArcherQA calculation, the average gamma passing rates (ArcherQA vs. TPS) were 98.23% ± 1.64% and 98.15% ± 1.07% for ATP and ATS adaptive plans, separately. It might be unnecessary to perform measurement‐based PSQA for both ATP and ATS adaptive plans for Unity if the gamma passing rates of both measurements of corresponding reference plans and independent dose verification of adaptive plans have high gamma passing rates. Periodic machine QA and verification of adaptive plans were recommended to ensure treatment safety.

Purpose In this study, a bias field correction workflow was proposed to improve the flexibility and generalizability of the generative adversarial network (GAN) model for abdominal cancer patients treated with a 0.35T magnetic resonance imaging linear accelerator (MR‐LINAC) system. Methods Model training was performed using brain MR images acquired on a 3T diagnostic scanner, while model testing was performed using abdominal MR images obtained using a 0.35T MR‐LINAC system. The performance of the proposed workflow was first compared with the GAN model using root‐mean‐square error (RMSE), peak signal‐to‐noise ratio (PSNR), and structural similarity index measure (SSIM). To assess the impact of the workflow on image segmentation, it was also compared with the N4ITK algorithm. Segmentation was performed using the k‐means clustering algorithm with three clusters corresponding to air, fat, and soft tissue. Segmentation accuracy was then evaluated using the Dice similarity coefficient (DSC). Results The RMSE values were 30.59, 12.06, 10.37 for the bias field‐corrupted images (IIN), GAN‐corrected images (IGAN), and images corrected with the proposed workflow (IOUT), respectively. Corresponding PSNR values were 42.34, 46.04, 47.04 dB, and SSIM values were 0.84, 0.96, 0.98. For segmentation accuracy, the mean DSC for air masks was 0.95, 0.97, and 0.97; for fat masks, 0.61, 0.71, and 0.74; and for soft tissue masks, 0.60, 0.68, and 0.69, corresponding to IIN, N4ITK‐corrected images (IN4ITK), and IOUT, respectively Conclusion By effectively mitigating bias field artifacts, the proposed workflow has the potential to strengthen the clinical utility of MRI‐guided adaptive radiotherapy for abdominal cancers, ensuring safer and more accurate radiation delivery.

Background Plastic scintillation detectors (PSD) are widely used for detecting and measuring ionizing radiation. These detectors are versatile, with high efficiency, fast response and the ability to provide real‐time measurements. Purpose Evaluate the suitability of Blue Physics PSD (BP‐PSD) for performing ultra‐fast dosimetric commissioning measurements with high accuracy and precision in a very short time. Methods Ultra‐fast measurements were performed in water using a BP‐PSD on an Elekta Unity MR‐linac. Percentage depth doses (PDD) and profiles at different depths were measured at two movement velocities, 10 mm/s and 20 mm/s, for field sizes ranging from 10 × 10 cm2 to 1 × 1 cm2. Gamma analysis was conducted to compare these measurements with those obtained during machine commissioning using a PTW Semiflex 3D ionization chamber (for PDD) and a PTW micro‐Diamond detector (for PDD and profiles). Gamma criteria of 2%/2 mm and 1%/1 mm dose difference/distance to agreement were studied, alongside field size, penumbra, and measurement time. Results All PDD and profile gamma passing rates were 100% at 2%/2 mm. At the stricter 1%/1 mm criteria, all PDD showed a passing rate above 96.97% for both velocities, with most of the profiles exceeding 95% at 10 mm/s and 90% at 20 mm/s. Gamma analysis results were superior for smaller fields (1 × 1 cm2 and 2 × 2 cm2) and generally better at 10 mm/s. On average, the penumbra measurements obtained with the PSD were greater than those achieved with the micro‐Diamond detector. Measurement times were found to be between 7 and 14 times shorter for PDD, and between 5 and 9 times shorter for profiles at speeds of 10 mm/s and 20 mm/s, respectively. Conclusions Ultra‐fast measurements using the Blue Physics PSD are suitable for acquiring dosimetric commissioning data with high accuracy and precision, and can be performed in a much shorter timeframe than with commonly used detectors.

Background MR‐guided adaptive radiotherapy (ART) allows for daily plan optimization based on patient‐specific anatomy. Accumulated doses, driven by deformable image registration (DIR), of daily fractions can provide cumulative dose metrics and insights into toxicity and tumor control. In prostate ART, inter‐ and intra‐factional deformations, particularly due to bladder and rectum, pose a challenge to accurate DIR generation. Purpose To quantify geometric and dosimetric accuracy of a proposed prostate MR‐to‐MR DIR approach to support MR‐guided ART dose accumulation. Methods We evaluated DIR accuracy in 25 patients treated with 30 Gy in five fractions on a 1.5 T MR‐linac using an adaptive workflow. For all patients, a reference MR was used for planning, with three images collected at each fraction: adapt MR for adaptive planning, verify MR for pretreatment position verification and beam‐on for capturing anatomy during radiation delivery. We assessed three DIR approaches: intensity‐based, intensity‐based with controlling structures (CS), and intensity‐based with controlling structures and points of interest (CS + P). DIRs were performed between the reference and fraction images and within fractions (adapt‐to‐verify and adapt‐to‐beam‐on). For the evaluation, we propagated CTV, bladder, and rectum contours using the DIRs and compared each to manually delineated contours using Dice similarity coefficient, mean distance to agreement, and dose–volume metrics. Results CS and CS + P improved geometric agreement between manual and propagated contours over intensity‐only DIR. For example, mean distance to agreement (DTAmean) for reference‐to‐beam‐on intensity‐only DIR was 0.131 ± 0.009 cm (CTV), 0.46 ± 0.08 cm (bladder), and 0.154 ± 0.013 cm (rectum). For the CS, the DTAmean values were 0.018 ± 0.002, 0.388 ± 0.14, and 0.036 ± 0.013 cm. Finally, for CS + P, these values were 0.015 ± 0.001, 0.025 ± 0.004, and 0.021 ± 0.002 cm. Dosimetrically, comparing CS and CS + P for reference to beam‐on DIRs resulted in a change of CTV D98% from [−29 cGy, 19 cGy] to [−18 cGy, 26 cGy], bladder D5cc from [−51 cGy, 544 cGy] to [−79 cGy, 36 cGy], and rectum D1cc from [−106 cGy, 72 cGy] to [−52 cGy, 74 cGy]. Conclusion CS improved geometric and dosimetric accuracy over intensity‐only DIR, with CS + P providing further performance improvement, particularly for bladder. However, session image segmentation remains a challenge, which may be addressed with automated contouring.