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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., (© The Author(s) 2024. Published by Oxford University Press on behalf of The Japanese Radiation Research Society and Japanese Society for Radiation Oncology.)

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., (© The Author(s) 2022. Published by Oxford University Press on behalf of The Japanese Radiation Research Society and Japanese Society for Radiation Oncology.)

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 A; it 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., (© The Author(s) 2019. Published by Oxford University Press on behalf of The Japan Radiation Research Society and Japanese Society for Radiation Oncology.)

We evaluated two dual-energy cone-beam computed tomography (DE-CBCT) methodologies for a bench-top micro-CBCT system to reduce metal artifacts on reconstructed images. Two filter-based DE-CBCT methodologies were tested: (i) alternative spectral switching and (ii) simultaneous beam splitting. We employed filters of 0.6-mm-thick tin and 0.1-mm-thick tungsten to generate high- and low-energy spectra from 120 kVp X-rays, respectively. The spectral switching method was imitated by two half scans with different filters (pseudo-switching). Filters were placed and between the X-ray tube and a phantom ('1-u,' '2-u'), a phantom and a flat panel detector ('1-d,' '2-d'), and compared with (iii) two half scans at 80 and 140 kVp [pseudo-(80,140)]. For the splitting method, two half-width filters were aligned along a rotating axis. Projections were separated into halves and merged with corresponding areas of opposed projections after one full rotation. A solid 30-mm-diameter acrylic phantom and an acrylic phantom with four 5-mm-diameter titanium rods were used. DE images were generated by weighted summation of the high- and low-energy images. The blending factor was changed from 0 to +5 in increments of 0.01. Relative errors (REs) of the linear attenuation coefficients of the two phantoms and the contrast-to-noise ratios (CNRs) between the titanium and acrylic regions were compared. All methods showed zero REs except for the method (2-d). CNRs for pseudo-switching with upstream placement were 1.4-fold larger than CNRs for the pseudo-(80,140) method. CNRs for the downstream placements were small. It was concluded that the pseudo-switching method with upstream placement is appropriate for reducing metal artifacts.

Knowledge of the imaging doses delivered to patients and accurate dosimetry of the radiation to organs from various imaging procedures is becoming increasingly important for clinicians. The purposes of this study were to calculate imaging doses delivered to the organs of lung cancer patients during real-time tumor tracking (RTTT) with three-dimensional (3D), and four-dimensional (4D) cone-beam computed tomography (CBCT), using Monte Carlo techniques to simulate kV X-ray dose distributions delivered using the Vero4DRT. Imaging doses from RTTT, 3D-CBCT and 4D-CBCT were calculated with the planning CT images for nine lung cancer patients who underwent stereotactic body radiotherapy (SBRT) with RTTT. With RTTT, imaging doses from correlation modeling and from monitoring of imaging during beam delivery were calculated. With CBCT, doses from 3D-CBCT and 4D-CBCT were also simulated. The doses covering 2-cc volumes (D2cc) in correlation modeling were up to 9.3 cGy for soft tissues and 48.4 cGy for bone. The values from correlation modeling and monitoring were up to 11.0 cGy for soft tissues and 59.8 cGy for bone. Imaging doses in correlation modeling were larger with RTTT. On a single 4D-CBCT, the skin and bone D2cc values were in the ranges of 7.4-10.5 cGy and 33.5-58.1 cGy, respectively. The D2cc from 4D-CBCT was approximately double that from 3D-CBCT. Clinicians should Figure that the imaging dose increases the cumulative doses to organs.