Tolerance limits and methodologies for IMRT measurement-based verification QA: Recommendations of AAPM Task Group No. 218

Clinical implementation of a secondary dose calculation system for patient-specific quality assurance of complex VMAT and SBRT treatments

PURPOSE

Advanced radiotherapy techniques require robust patient-specific quality assurance (PSQA). This study validated a secondary calculation software for plan dose verification, evaluating accuracy across different treatment sites, beam qualities, and plan complexities.

METHODS

Data from two beam-matched VersaHD linacs were used to commission RadCalc-V7.3.2.0. 33 end-to-end tests in homogeneous and anthropomorphic phantoms compared RadCalc Monte Carlo (RC-MC) and Collapsed Cone Convolution Superposition (RC-CCCS) algorithms with Pinnacle3 TPS, using gamma analysis (1.5 %/2mm) and ionization chamber measurements. 140 clinical VMAT plans of varying complexities, including 35 head and neck (H&N) and 65 SBRT treatments, were evaluated using gamma analysis (3 %/2mm) and relevant DVH metrics for PTV (D98%, D2%). RadCalc calculations were compared with pre-treatment Octavius 4D measurements.

RESULTS

Phantom studies showed excellent RadCalc-TPS agreement for homogeneous plans and lung SBRT with flattened beams (mean passing rates > 98 %, mean measured dose differences < 1 %). Larger discrepancies were observed in the anthropomorphic thorax phantom for FFF SBRT. For clinical plans, mean passing rates exceeded 98.5 %. Site-specific differences emerged: RC-MC performed better for H&N, RC-CCCS for other sites. RadCalc calculated slightly less homogeneous dose distributions than Pinnacle3, but averaging RC-MC and RC-CCCS results in reduced DVH discrepancies (mean ΔD98% -1.1 ± 1.1 %, mean ΔD2% +1.1 ± 1.5 %). Octavius measurements may underestimate calculation discrepancies due to tissue inhomogeneities.

CONCLUSIONS

RadCalc produced very consistent results with Pinnacle3 and can be integrated into our PSQA program for efficient 3D dose verification, reducing measurement workload while maintaining high standards of dosimetric accuracy. Using both RadCalc algorithms effectively reduced calculation uncertainties.

New index for quantitative comparison of dose distributions in radiotherapy

BACKGROUND

Delivery of intensity modulated radiotherapy (IMRT) requires patient specific quality assurance (QA) tests. These tests normally include a two-fold comparison of dose distributions: (a) comparison of planned dose created in the employed treatment planning system (TPS) and dose computed by using third-party software; (b) comparison of planned (predicted) and delivered doses.

PURPOSE

We describe a new approach to compare dose distributions in radiotherapy.

METHODS

The suggested approach employs a novel dose congruency index (DCI) to evaluate differences between compared dose distributions. The new index is dependent on dose and dose increment (δ D $\delta D$ ). The "pass" and "fail" criteria for dose congruency assessment are given by the conditionsD C I ≤ 1 $DCI \le 1$ andD C I > 1 $DCI > 1$ , respectively. The employment of DCI was demonstrated by comparing 3D dose distirbutions in stereotactic body radiation therapy (SBRT) and stereotactic intracranial radiosurgery (SRS). The DCI was also computed for predicted and measured portal doses.

RESULTS

For the compared SBRT dose distributions, the DCI computed withδ D $\delta D$  = 1%, 1.5%, and 2% of the prescribed dose resulted in passing rates (i.e., relative number of dose levels withD C I ≤ 1 $DCI \le 1$ ) of 34.1%, 61.5%, and 100%, respectively. For the compared SRS dose distributions, the DCI withδ D $\delta D$  = 1%, 1.5%, and 2% of the prescribed dose had passing rates of 25.3%, 33%, and 41.8%, respectively. For the compared 2D distributions, the DCI passing rates averaged over the two arcs employed in the studied case, were as follows: 14.5% forδ D $\delta D$  = 1%, 48.8% forδ D $\delta D$  = 1.5%, and 85.5% forδ D $\delta D$  = 2%.

CONCLUSIONS

It is demonstrated that the suggested index can be used to compare 2D and 3D dose distributions in radiotherapy.

Impact of iso-dose levels on pre-treatment quality assurance in volumetric modulated arc therapy

The current standard of modern radiotherapy pre-treatment evaluation of dose distributions measured using gamma pass percentage is the predominant metric for Patient-Specific Quality Assurance (PSQA). The aim of the study was to analyze the impact of the different dose levels for three different gamma criteria in various anatomical sites. Retrospectively selected 120 VMAT plans of the brain, head and neck, thorax, and pelvic sites were considered for this study. Quality assurance plans were created and measurements were done using PTW Octavius 4D phantom. Three different gamma criteria were used to evaluate different dose levels' volume gamma passing rates. The maximum gamma passing rate for all dose levels except 100% with a 3%/3 mm criterion was observed for the pelvis site. A significant variation in dose levels was observed with the 3%/2 mm gamma criteria for head and neck sites, particularly above the 85% dose level compared to other anatomical sites. Using 2%/2 mm gamma criteria, there was a rapid fall in the gamma passing rate and all the dose levels showed a significant variation among different sites. This study demonstrated significant variations in gamma passing rates across anatomical sites and dose levels, emphasizing the importance of tailored QA protocols. The findings underscore the need for site-specific action limits and highlight the sensitivity of stricter gamma criteria for detecting errors in complex treatment plans.

Experimental validation of a comprehensive fluoroscopy peak skin dose model using four different computational phantoms

BACKGROUND

Accurately determining the Peak Skin Dose (PSD) delivered to the patient during Fluoroscopically Guided Interventional Procedures (FGIP) is crucial for assessing potential radiation-induced skin injuries and determining the necessary follow-up care for exposed patients.

PURPOSE

This study evaluates the accuracy of PSD estimation model for FGIPs using mathematical and anthropomorphic computational phantoms that mimic the dimensions of the imaged patient and provides their description.

METHODS

The modeling of the FGIP and calculation of peak skin dose involved extracting geometric parameters like primary and secondary angulation, fields sizes, and table shifts, as well as dosimetric parameters such as tube voltage, Air Kerma, Kerma Area Product, and additional filtration of the FGIP stored in a dose tracking system. Computational phantoms were employed to represent the patient anatomy and their axes scaled to match the patient dimensions. The first, a hybrid computational human phantom (HCHP) was developed using Rhinoceros 6.0, generating a 3D surface skin model derived from an adult International Commission on Radiological Protection (ICRP) reference voxel-male-phantom. Three other computational (mathematical) phantoms with cylindrical, ellipsoidal, and semi-ellipsoidal geometries were created using MATLAB software and employed to calculate PSD. Dose-distribution mapping was performed on all phantoms using MATLAB software, following the guidelines outlined in the summary of a joint report by AAPM TG357 and EFOMP by Andersson et al. To improve the PSD model accuracy, measured Kerma correction factors (KCF) that account for backscatter and table attenuation were incorporated for all radiation fields. Two FGIPs were conducted utilizing a male anthropomorphic phantom. Thermoluminescent Dosimeters (TLD) were strategically positioned in a grid pattern on the posterior surface of the phantom to serve as reference measurements. Traditional methods, in which all fields overlap, intersect the table and phantom, were also used to calculate the PSD. The resulting skin doses, derived from the HCHP, mathematical phantoms, and traditional methodologies, were then compared against the corresponding reference measurements for a comprehensive evaluation.

RESULTS

The results showed that the PSD calculations obtained through the HCHP, cylindrical, ellipsoidal, and semi-ellipsoidal phantoms were 3.163, 3.085, 2.952, and 3.095 Gy, respectively, for the first FGIP and 3.728, 3.722, 3.598, 3.720 Gy, respectively, for the second FGIP. In comparison, the measured PSD using TLDs was 3.161 and 3.713 Gy for the first and second FGIP. The use of the HCHP-introduced PSD differences of 0.1% and 0.4%, and the mathematical phantoms yielded differences of -2.4% and 0.3%, 6.6% and -3.1%, and -2.1% and 0.2% for the cylindrical, ellipsoidal, and semi-ellipsoidal phantoms, respectively for each FGIP. The traditional approach yielded a difference of -19.1% and -6.4%.

CONCLUSIONS

Modeling the FGIP with the use of computational phantoms accurately reflects patient anatomy and can be useful in evaluating radiation PSD from FGIPs. The traditional methods yielded a greater difference against our fluoroscopy PSD measurements, while the use of the HCHP resulted in superior though practically comparable accuracy in calculating PSD to using computational phantoms, with added computational power and time needed to create a patient-based human model.

A novel dose calculation system implemented in image domain

PURPOSE

Modern intensity-modulated radiotherapy, aiming to deliver an accurate dose to the planning target volume while protecting the surrounding organs at risk, is regarded as the indispensable treatment for cancer in the clinic. An accurate and efficient dose calculation algorithm is essential to support and accelerate the treatment plan optimization process.

METHOD

To improve the effectiveness of the dose calculation, deep learning methods are widely adopted to compute dose distributions from several variables mimicking the physical features required for dose calculation. However, these methods employed similar concepts and neural network inputs, and had only limited improvements to traditional dose calculation methods. In this work, we propose a new computing process, named DeepBEVdose, which is essentially distinct to the previous deep learning-based dose calculation methods. We present a novel image-domain dose calculation algorithm to automatically compute dose distributions from the computer tomography images and radiation field fluence maps. Specifically, a novel beam's eye view calculation scheme is introduced to substitute the traditional trivial ray-tracing procedure that cannot be removed in the previously published dose calculation system. Under this new calculation scheme, a generic two-dimensional convolutional neural network with minimal input requirements is sufficient to perform accurate dose calculation.

RESULTS

We demonstrate the feasibility of this approach with datasets acquired from multi-institutions with two different tumor sites (nasopharynx and lung). The average pixel-wise difference between the ground truth and the predicted results across all testing cases (both internal and external) is within 2%. The average 3D gamma passing rate is above 95% for all testing cases.

CONCLUSIONS

We have developed a novel deep learning framework that effectively maps radiation fluences to dose distributions. The high accuracy and efficiency of the proposed approach indicate its potential for use in online adaptive plan optimization.

From 2D to 3D gamma passing rate tolerance and action limits for patient-specific quality assurance in volumetric-modulated arc therapy

BACKGROUND

Volumetric modulated arc therapy (VMAT) requires an accurate patient-specific quality assurance (PSQA) program. In clinical practice, this is usually performed using the γ-index and the two-dimensional gamma passing rate (2D %GP). A three-dimensional (3D) index incorporating the patient anatomy could be more useful for the 3D dose distribution verification.

PURPOSE

The current study demonstrates a thorough investigation of VMAT PSQA treatment plans by examining the correlation between 3D Gamma passing rate (%GP) and 2D %GP. The aim was to establish the tolerance limits (TL) and action limits (AL) that could be adopted in clinical practice.

MATERIALS AND METHODS

PSQA was performed for 67 head and neck (H&N) and 69 prostate treatment plans, using an appropriate phantom and the γ-index method. The 3%/2  mm acceptance criterion was used. Treatment plans' 2D% GP and 3D %GP values were collected and correlated with individual 3D %GP values of planning target volume (PTV) and organs at risk (OARs). Institutional TL and AL of both 2D %GP and 3D %GP were established using 30 prostate and 30 H&N treatment plans, as per recommendations proposed by AAPM TG-218.

RESULTS

A moderate correlation was observed between 2D %GP and 3D %GP of the treatment plans. Τhe correlations demonstrated a stronger association for the 3D %GP than for the 2D %GP with respect to the 3D %GP of the individual structures considered. The TL for the 3D %GP (both plan and individual) and the plans' 2D %GP were generally more stringent, while the AL showed a wider range compared to the corresponding limits suggested by the TG-218 protocol for plan 2D %GP.

CONCLUSIONS

Institution-specific 3D %GP as well as TL and AL for treatment plan, PTV and OARs could be incorporated in the PSQA procedure in synergy with the 2D evaluation, as they can provide a more-in-depth-view of the treatment quality.

Design and validation of a novel dosimetry phantom for motion management audits

BACKGROUND

We present a novel phantom design for conducting end-to-end dosimetry audits for respiratory motion management of two anatomical treatment sites. The design enables radiochromic film measurements of the dose administered to the target throughout the respiratory cycle (motion-included) and the dose delivered to the time-averaged motion of the phantom (motion-excluded) to be conducted simultaneously.

PURPOSE

To demonstrate the phantom's utility in a dosimetry audit and capacity to detect errors by quantifying spatial and dosimetric reproducibility.

METHODS

Spatial and dosimetric reproducibility was quantified by repeat exposures using a simple lateral beam. Five exposures per measurement configuration were used. In each series of five measurements, the median film was used as the series reference to quantify the reproducibility of the remaining "test films." Spatial reproducibility was quantified by comparing the position of isodose lines in two axes on the test films back to the series reference. Dosimetric reproducibility was quantified using gamma comparison between each test film and the series reference. Proof-of-concept of the motion-excluded measurement capability was also established by comparing all films to treatment planning system (TPS) calculated dose distributions.

RESULTS

Spatial reproducibility was better than 1 mm on all assessed metrics across all measurements. Film-to-film local gamma passing rates at 3%/0.6 mm were above 90% for all measurements. Film-to-TPS global gamma passing rates at 3%/1 mm were >95% in the motion-excluded measurement series', but <80% in the motion-included series, highlighting the utility of the motion-excluded measurements.

CONCLUSIONS

Measurements were highly reproducible and of sufficient accuracy/reproducibility to facilitate multiple avenues of analysis in a prospective dosimetry audit. Motion-excluded measurements were directly comparable to the TPS dose distribution. Motion-included measurements may yield more clinically-relevant information about the actual dose administered to the target. This promises greater sensitivity to motion management-related errors, detectable in the setting of a dosimetry audit for motion management.

Integration test of biaxially rotational dynamic-radiation therapy for nasopharyngeal carcinoma: Efficacy evaluation and dosimetric analysis

BACKGROUND AND PURPOSE

OXRAY is a new O-ring-shaped radiotherapy system delivering biaxially rotational dynamic-radiation therapy (BROAD-RT), a technique that enables non-coplanar volumetric-modulated arc therapy (VMAT) for large target volumes without requiring couch movement. The purpose of this study was to evaluate the benefits of BROAD-RT and to perform an integration test to confirm the plan deliverability and its accuracy from the treatment planning system to OXRAY for patients with nasopharyngeal carcinoma.

METHODS AND MATERIALS

We compared treatment plans for BROAD-RT and coplanar VMAT (COVMAT) created in RayStation for 15 patients with nasopharyngeal cancer using the Wilcoxon signed-rank test. P values less than 0.05 were considered statistically significant. Additionally, we confirmed the plan delivery accuracy of BROAD-RT from the treatment planning system to OXRAY; gamma passing rates (GPRs) and delivery time were evaluated. The criteria for pass and fail were ≥95 % at γ3%2 mm.

RESULTS

BROAD-RT significantly improved the homogeneity and conformity index of planning target volume and reduced dose volume indices compared with COVMAT in D0.03 cc for the brainstem, D0.03 cc for the left optic nerve, D0.03 cc for the brachial plexus, Dmean for each submandibular gland, Dmean for the oral cavity, and Dmean for each parotid gland. All plans for BROAD-RT passed the integration test; the mean GPR (3 %/2 mm) was above 95 % and the median delivery time was 209 s.

CONCLUSIONS

BROAD-RT delivered by OXRAY passed the integration test, and it demonstrated the potential benefit of improving the dose distribution compared with COVMAT for patients with nasopharyngeal carcinoma.

Commissioning of Halcyon enhanced leaf model in the Eclipse treatment planning system: Focus on simple slit fields and VMAT dose calculation

PURPOSE

The dual-layer multileaf collimator (MLC) in Halcyon adds complexities to the dose calculation process owing to the variability of dosimetric characteristics with leaf motion. Recently, an enhanced leaf model (ELM) was developed to refine the MLC model in the Eclipse treatment planning system. This study investigates the performance of the Halcyon ELM by verifying doses for simple slit fields and volumetric modulated arc therapy (VMAT) plans.

MATERIALS AND METHODS

Dose calculations were performed with Acuros XB using the ELM. To commission the leaf-tip model, the dosimetric leaf gap (DLG) was calculated (referred to as DLGELM) and compared with Halcyon measurements. The DLGs were assessed under conditions both with and without leaf trailing between the MLC layers. The tongue-and-groove (TG) model was evaluated by comparing leaf-edge profiles and the outputs of the asynchronous sweeping gap. Furthermore, eleven VMAT plans were validated against chamber doses and Delta4 measurements.

RESULTS

DLGELM demonstrated variation between layers, measuring 0.42 mm for the proximal layer and 0.23 mm for the distal layer, and showed a correspondence with the measured DLGs in 0.1 mm. Additionally, ELM reduced the discrepancy between calculated and measured DLGs when accounting for leaf trailing. In the TG model test, ELM calculations successfully mirrored the measured leaf-edge profiles. Moreover, the median dose difference between ELM calculations and chamber doses was -0.8% in asynchronous sweeping gaps. In the VMAT dose verification, the incorporation of ELM enhanced the target dose and resulted in a gamma pass rate (2%/2 mm) exceeding 95%.

CONCLUSION

Halcyon ELM considerably improved the accuracy of simulating actual leaf-tip transmission, both with and without leaf trailing, and it effectively accounted for the additional blocking caused by TG design. Furthermore, the introduction of ELM in Eclipse considerably enhanced the VMAT dose calculation. ELM addresses the limitations of traditional leaf models and reduces uncertainties in Halcyon dose calculations.

Real-time radiation beam imaging on an MR linear accelerator using quantitative T1 mapping

BACKGROUND

Direct three-dimensional imaging of radiation beams could enable more accurate radiation dosimetry. It has been previously reported that changes in T1-weighted magnetic resonance imaging (MRI) intensity could be observed during radiation due to radiochemical oxygen depletion. Quantitative T1 mapping could increase sensitivity for dosimetry applications.

PURPOSE

We use an MRI linear accelerator (MR-Linac) to visualize radiation delivery through the real-time effects of dose on the spin-lattice magnetic relaxation time (T1) of water. We quantify the relationships between dose, spin-lattice relaxation rates (R1) and dissolved oxygen concentration to further investigate the mechanisms of T1 change.

METHODS

An ultrapure water phantom and a 1% agarose gel phantom were irradiated and imaged on a 1.5 T Elekta Unity MR-Linac. Radiation plans were created using the Monaco treatment planning system. Images were acquired before, during and after radiation. A dual-echo Look-Locker inversion recovery pulse sequence was used for simultaneous dynamic T1/B0 mapping. The change in R1 with respect to dose (∆R1/∆Dose) and the radiochemical oxygen depletion (ROD = ∆O2/∆Dose) were measured. The relaxivity of oxygen (r1,O2 = ∆R1/∆O2) in water was also measured in a separate experiment with samples of various dissolved oxygen concentrations. The minimum measurable dose over a 20-min period was estimated using a single-tailed 99th quantile Student's t-distribution.

RESULTS

Changes to R1 were found to be spatiotemporally correlated to the predicted delivered radiation dose and persisted for at least 1 h after radiation. A complex dose plan could be imaged in the 1% agarose gel phantom, as the gel limits diffusion and convective mixing. In water, the ∆R1/∆Dose was found to be -1.0 × 10-4 s-1/Gy, the r1,O2 was found to be 5.4 × 10-3 s-1/(mg/L), and the ROD was found to be -0.010 (mg/L)/Gy. Both r1,O2 and ROD agree with published values. However, combining these two values yields a predicted ∆R1/∆Dose of -5.4 × 10-5 s-1/Gy, indicating that radiochemical oxygen depletion alone under-predicts the MRI effect. The detection limit of R1 was 1.1 × 10-3 s-1 which corresponded to a single-voxel minimum detectable dose of 11.1 Gy for this specific sequence.

CONCLUSION

Quantitative T1 mapping was used to image radiation dose patterns in real-time in water and agarose gel. Radiochemical oxygen depletion only partially explains the T1 changes measured. Agarose gel could be used as a simple system for three-dimensional patient-specific quality assurance. Future applications may include in vivo dosimetry for FLASH radiotherapy, though improvements in acquisition methods and hardware are likely needed.

A workflow to select local tolerance limits by combining statistical process control and error curve model

BACKGROUND

Patient-specific quality assurance (QA) is a complicated process specific to personnel, equipment, and procedure. The universal or commonly used tolerance limits may not be applicable to local situations. Therefore, it is a need for a medical physicist to establish appropriate local tolerance limits based on actual situations and quantitatively evaluate the error sensitivity of selected tolerance limits to determine their availability in clinical practice.

PURPOSE

This study aims to develop a comprehensive and scientifically sound methodology for determining appropriate local tolerance limits in patient-specific QA.

METHODS AND MATERIALS

A total of 214 RapidArc plans for cervical cancer were selected. Systematic multi-leaf collimator (MLC) positional errors were simulated across eighteen offsets ranging from ± 0.2 to ± 5 mm. Dose verification was conducted on 808 RapidArc plans, and a retrospective review was carried out. Firstly, six commonly used QA metrics in gamma and DVH analysis were extracted from the QA results of 196 error-free RapidArc plans. These QA metrics included GP10 (gamma passing rates [GPRs] at 3%/2mm, 10% dose threshold), GP50 (GPRs at 3%/2mm, 50% dose threshold), µGI50 (mean gamma index at 3%/2mm, 50% dose threshold), PTV95 (dose received by 95% of PTV), PTV5 (dose received by 5% of PTV) and PTVmean (mean dose received by PTV). Secondly, the statistical process control was used to establish the corresponding tolerance limits for each metric. Then, six error curve models were created based on 360 error-introduced plans to record changes in QA metrics under different magnitudes of MLC positional error. The error range of theoretical detection limits for systematic MLC positional errors was investigated to assess error sensitivity quantitatively using the error curve model. Finally, the process-based tolerance limits of six single QA metrics and four combined QA metrics were validated by using 252 sets of test data. The binary classification performance (error-free/error-introduced) was assessed based on detection rate, accuracy, precision, recall, and f1-score.

RESULTS

The theoretical detection limits for process-based tolerance limits of GP10, GP50, µGI50, PTV95, PTVmean, and PTV5 were 2.19 mm, 2.71 mm, 3.52 mm, 1.93 mm, 3.20 mm, and 2.15 mm, respectively. In the validation phase, the process-based tolerance limits for PTV95 effectively identified systematic MLC positional errors exceeding 0.6 mm with a detection rate of 76.19%, displaying superior performance in binary classification among six single metrics. Regarding combined metrics, the joint evaluation of process-based tolerance limits for GP10 and PTV95 showed a higher detection rate of 80.16% for systematic MLC positional errors exceeding 0.6 mm.

CONCLUSION

The proposed workflow integrates the establishment and validation of tolerance limits. It not only provides a practical tool for setting local tolerance limits based on actual clinical scenarios but also offers a quantitative method for medical physicists to understand the error sensitivity of the selected local tolerance limits.

Retrospective Study Evaluating the Outcome and Efficacy of Stereotactic Body Radiation Therapy for the Treatment of Metastatic Abdominal Lymph Nodes in Dogs With Apocrine Gland Anal Sac Adenocarcinoma

Local treatment for dogs with regional lymph node metastasis secondary to apocrine gland anal sac adenocarcinoma (AGASACA) includes nodal extirpation or radiotherapy. Stereotactic body radiation therapy (SBRT) may provide a definitive intent treatment option for macroscopic nodal disease when surgery is declined or the disease is deemed inoperable. Twenty-five dogs receiving SBRT to the metastatic sacroiliac lymph nodes were retrospectively evaluated. Dogs were staged according to the previously published TNM staging system with 3 stage IIIa, 14 stage 3b, and 8 stage IV. The overall median survival time (MST) was 451 days and the stage did not significantly impact survival (p = 0.31). The overall median event-free survival time was 246 days. Significant positive prognostic factors included male sex, higher dose per fraction, and higher total dose (p = 0.034, 0.0035, 0.0047). Dogs receiving 6-7.5 Gy per fraction with a total dose of 30-37.5 Gy outperformed dogs receiving other protocols. Twelve dogs experienced gait changes in the hind limbs during the late radiation effects period. Resolution of hypercalcemia in 5 dogs was inconsistent and transient. The best response was complete in 21%, partial in 58%, and stable disease in 17% at a median of 100 days. Three dogs (12%) developed progression of treated lymph nodes at 157, 498, and 644 day. Eight dogs (32%) had recurrence of their primary (untreated by radiation) anal sac masses. SBRT was determined to be an effective alternative to surgical excision; however, more investigation is needed to determine the cause of gait changes in the late toxicity period.

Using deep learning generated CBCT contours for online dose assessment of prostate SABR treatments

Prostate Stereotactic Ablative Body Radiotherapy (SABR) is an ultra-hypofractionated treatment where small setup errors can lead to higher doses to organs at risk (OARs). Although bowel and bladder preparation protocols reduce inter-fraction variability, inconsistent patient adherence still results in OAR variability. At many centers without online adaptive machines, radiation therapists use decision trees (DTs) to visually assess patient setup, yet their application varies. To evaluate our center's DTs, we employed deep learning-generated cone-beam computed tomography (CBCT) contours to estimate daily doses to the rectum and bladder, comparing these with planned dose-volume metrics to guide future personalized DT development. Two hundred pretreatment CBCT scans from 40 prostate SABR patients (each receiving 40 Gy in five fractions) were auto-contoured retrospectively, and daily rectum and bladder doses were estimated by overlaying the planned dose on the CBCT using online rigid registration data. Dose-volume metrics were classified as "no", "minor", or "major" violations based on meeting preferred or mandatory goals. Twenty-seven percent of fractions exhibited at least one major bladder violation (with an additional 34% minor), while 14% of fractions had a major rectum violation (10% minor). Across treatments, five patients had recurring bladder V37 Gy major violations and two had rectum V36 Gy major violations. Bowel and bladder preparation significantly influenced OAR position and volume, leading to unmet mandatory goals. Our retrospective analysis underscores the significant impact of patient preparation on dosimetric outcomes. Our findings highlight that DTs based solely on visual assessment miss dose metric violations due to human error; only 23 of 59 under-filled bladder fractions were flagged. In addition to the insensitivity of visual assessments, variability in DT application further compromises patient setup evaluation. These analyses confirm that reliance on visual inspection alone can overlook deviations, emphasizing the need for automated tools to ensure adherence to dosimetric constraints in prostate SABR.

Proton dose calculation with transformer: Transforming spot map to dose

BACKGROUND

Conventional proton dose calculation methods are either time- and resource-intensive, like Monte Carlo (MC) simulations, or they sacrifice accuracy, as seen with analytical methods. This trade-off between computational efficiency and accuracy highlights the need for improved dose calculation approaches in clinical settings.

PURPOSE

This study aims to develop a deep-learning-based model that calculates dose-to-water (DW) and dose-to-medium (DM) using patient anatomy and proton spot map (PSM), achieving approaching MC-level accuracy with significantly reduced computation time. Additionally, the study seeks to generalize the model to different treatment sites using transfer learning.

METHODS

A SwinUNetr model was developed using 259 four-field prostate proton stereotactic body radiation therapy (SBRT) plans to calculate patient-specific DW and DM distributions from CT and projected PSM (PPSM). The PPSM was created by projecting PSM into the CT scans using spot coordinates, stopping power ratio, beam divergence, and water-equivalent thickness. Fine-tuning was then performed for the central nervous system (CNS) site using 84 CNS plans. The model's accuracy was evaluated against MC simulation benchmarks using mean absolute error (MAE), gamma analysis (2% local dose difference, 2-mm distance-to-agreement, 10% low dose threshold), and relevant clinical indices on the test dataset.

RESULTS

The trained model achieved a single-field dose calculation time of 0.07 s on a Nvidia-A100 GPU, over 100 times faster than MC simulators. For the prostate site, the best-performing model showed an average MAE of 0.26 ± 0.17 Gy and a gamma index of 92.2% ± 3.1% in dose regions above 10% of the maximum dose for DW calculations, and an MAE of 0.30 ± 0.19 Gy with a gamma index of 89.7% ± 3.9% for DM calculations. After transfer learning for CNS plans, the model achieved an MAE of 0.49 ± 0.24 Gy and a gamma index of 90.1% ± 2.7% for DW computations, and an MAE of 0.47 ± 0.25 Gy with a gamma index of 85.4% ± 7.1% for DM computations.

CONCLUSIONS

The SwinUNetr model provides an efficient and accurate method for computing dose distributions in proton therapy. It also opens the possibility of reverse-engineering PSM from DW, potentially speeding up treatment planning while maintaining accuracy.

Recommendations for radiotherapy quality assurance in clinical trials

Robust quality assurance (QA) of clinical trials in radiotherapy (RT) is paramount for minimising uncertainties in treatment delivery, thereby strengthening the statistical power of the study and increasing the likelihood of accurately answering the research question. As RT techniques evolve and become more complex, establishing an appropriate QA program for a specific clinical trial becomes increasingly challenging, highlighting the importance of clear and standardised recommendations. This study provide such recommendations for Principal Investigators (PIs) to consider when planning and conducting RT Quality Assurance (RTQA) for clinical trials. They arise from experiences with RTQA in the clinical trials conducted in the Danish Multidisciplinary Cancer Groups (DMCGs). The recommendations include a checklist to guide PIs in developing an effective RTQA program.

STAR Locally Prolongs Effective Refractory Period and Increases Ventricular Tachycardia Cycle Length Without Short-Term Scar Formation or Functional Decline: Insights From a Translational Porcine Model Study

BACKGROUND

Stereotactic arrhythmia radiotherapy (STAR) has emerged as a potential therapy for treatment-refractory ventricular tachycardia (VT). However, the mechanisms underlying STAR efficacy, such as scar or other electromechanical changes, are still unclear. The goal of this study was to develop a translational porcine model of ischemic monomorphic VT treated with STAR to examine the physiological changes after a typical clinical STAR treatment.

METHODS

We treated a previously validated porcine model of monomorphic VT after myocardial infarction with a clinically derived STAR protocol. A dose of 25 Gy was prescribed to the planning target volume and 35 Gy to the clinical target volume (regions of scar), while controls underwent a sham STAR treatment. All investigators in the study were blinded except the treating investigator. The primary study outcome was VT inducibility at 6 weeks post-STAR. Animals underwent pre- and post-STAR cardiac magnetic resonance imaging to quantify myocardial scar and function, as well as body surface mapping. Six weeks post-STAR, animals underwent a VT induction study, and tissue was harvested for optical mapping and histological analysis.

RESULTS

Six animals completed the study, which ended before finishing enrollment because all animals had inducible VT. We found a significantly longer local effective refractory period in the left ventricular apex and longer VT cycle lengths in STAR-treated animals compared with controls (P<0.05). We found no difference in myocardial scar burden, mechanical function, or body surface recordings when comparing pre- and post-STAR.

CONCLUSIONS

Our data suggest a novel therapeutic mechanism of STAR driven by increasing the effective refractory period in locally treated areas, corresponding to increased tissue wavelength. Our results corroborate clinical case reports and anecdotal evidence that STAR increases VT cycle length. Importantly, these effects were not mediated by an increase in myocardial scar burden. However, our studies do not examine the long-term effects of STAR.

Beam model development and clinical experience with RadCalc for treatment plan quality assurance in online adaptive workflow with an MR-linac

PURPOSE

The aim of this work was to report on the optimization, commissioning, and validation of a beam model using a commercial independent dose verification software RadCalc version 7.2 (Lifeline Software Inc, Tyler, TX, USA), along with 4 years of experience employing RadCalc for offline and online monitor unit (MU) verification on the Elekta Unity MR-linac (MRL) for a range of clinical sites.

METHODS

Calculation settings and model parameters, including the Clarkson integration settings and radiation/light field offset, have been systematically examined and optimized, and pitfalls in the use of density inhomogeneity corrections and in off-axis calculations were investigated and addressed. The resulting model was commissioned by comparing RadCalc calculations to measurements for a variety of cases, selected following relevant recommendations, ranging from simple fields in a water tank to end-to-end point dose measurements in an anthropomorphic phantom.

RESULTS

For simple geometries, the agreement was within 2%, and for complex geometries, within 5%. When validating against the Monaco (Elekta AB, Stockholm, Sweden) treatment planning system (TPS), for 39 clinical commissioning plans, the mean total point dose difference was -0.3 ± 0.8% (-2.0%-1.1%). Finally, when applied retrospectively to 4085 clinical plan calculations, the agreement with the TPS was 0.3 ± 1.1% (-4.8%-4.2%), with fail rates of 0.1% for total point dose (discrepancy > 4%) and 0.3% for individual fields (discrepancy > 10%).

CONCLUSIONS

Improved calculation agreement with the TPS and therefore increased confidence in the online QA, opened the way for an automated and physics-light independent MU verification workflow within our MRL program.

Exploring the dosimetric advantages of a novel multi-modality radiotherapy platform in prostate cancer

The present research aims to explore the dosimetric advantages associated with a novel multi-modality radiotherapy platform TaiChiB, which integrates a medical linac and a focused 60Co γ-ray system. The primary focus of this investigation is to assess the efficacy of this platform in the treatment of prostate cancer. A retrospective study was conducted involving fifteen prostate patients. Each patient had two different treatment plans: a Varian linac x-ray plan (group A), and a TaiChiB plan combined with linac x rays and focused γ rays (group B). In both plan groups, the prescribed dose to the planning target volume (PTV) was 50 Gy, with a boost dose of 20 Gy to the gross tumor volume (GTV). In the TaiChiB plan, the primary plan was delivered using linac x rays and the boost dose plan was delivered using γ rays. Different criteria were used to evaluate the plan quality and results from the two plan groups were compared through statistical analysis (p < 0.05 as significantly different). All plans from these two groups met the clinical requirements for treatment, and Gamma passing rates were above 95% using the 3%/2 mm criterion suggested by TG-218. Regarding the dose coverage to targets, the TaiChiB plan group had a higher mean dose to the GTV (77.46 ± 1.04 Gy (B) vs. 71.40 ± 0.33 Gy (A), p < 0.01), whereas it maintained a comparable mean dose to the PTV (55.33 ± 1.76 Gy (B) vs. 55.23 ± 1.92 Gy (A), non-significant). In terms of dose to organs-at-risk (OARs), the TaiChiB plan group showed a lower or comparable mean value. In detail, bladder V45Gy (43.90 ± 6.34% (B) vs. 49.83 ± 6.31% (A), p < 0.01); rectum V45Gy (38.45 ± 14.38% (B) vs. 51.46 ± 17.18%(A), p < 0.01); intestine V45Gy (163.88 ± 18.85 cm3 (B) vs. 177.18 ± 18.20 cm3 (A), p < 0.01); left femoral head V30Gy (5.63 ± 1.97% (B) vs. 11.83 ± 2.56% (A), p < 0.01); and right femoral head V30Gy (4.64 ± 1.94% (B) vs. 10.38 ± 2.73% (A), p < 0.01). The comparison of plan evaluation results showed the superiority of the novel multi-modality radiotherapy platform TaiChiB in dosimetric characteristics by harnessing the physical advantages of γ rays as a supplement to x rays in radiotherapy.

Clinical validation of statistical predictive model for patient-specific quality assurance outcomes in stereotactic radiotherapy using secondary Monte Carlo dose calculations

PURPOSE

To evaluate Monte Carlo (MC) secondary dose verification for predicting ionization chamber (IC)-based patient-specific quality assurance (PSQA) measurements for stereotactic body radiotherapy (SBRT) plans.

METHODS

IC-based PSQA is a trusted method for verifying accurate delivery of absolute dose calculated by the treatment planning system (TPS). However, these measurements are often time-consuming and challenging to perform precisely, especially for small-volume SBRT targets. To investigate an MC-based method as a viable alternative, a logistic regression model was developed to predict measurement-based PSQA results utilizing 400 retrospectively collected IC PSQA measurements across our system. Each clinically approved plan was recalculated using a commercially available secondary MC-based dose calculation platform (Rad MonteCarlo, Radformation, NY). The dose to a contoured volume corresponding to the active IC volume was recorded. Additionally, measurement setup uncertainty was modeled by placing equivalent volumes +/- 2 mm in each cardinal direction. The TPS-calculated value was compared to the average MC-simulated values for all contours. Receiver Operating Characteristic (ROC) analysis was performed on an additional dataset of 328 prospective PSQA measurements to determine MC-based QA prediction thresholds for indicating when physical measurements can be safely avoided.

RESULTS

Of the 400 model plans, the percent differences between IC and TPS doses were [Median: -0.06 %, Range: -19.6 %-4.5 %]. The percent differences between IC and MC doses were [Median: 0.17 %, Range: -21.8 %-5.1 %]. When investigating MC against TPS dose for predicting likely PSQA failures, ROC analysis yielded an AUC of 0.76. Based on threshold analysis of the prospective validation dataset, a difference of 1 % between MC and TPS calculations resulted in zero false negatives, and would safely reduce the number of required IC measurements by 46 %.

CONCLUSION

This study demonstrates feasibility of and a workflow for implementing MC-based secondary dose calculations to reduce the number of physical measurements required for PSQA without compromising safety and quality.

Visualization and evaluation of the quality variations of EBT4 Gafchromic film using multidimensional scaling and Lie derivative image analysis

Film-specific uniformity variations in packages are known to significantly diminish the effectiveness of the one-scan protocol, a commonly used film dosimetry method. This method universally adopts the reference dose-response with rescaling linearly from the relationship of the known dose and the unexposed state. This study aims to visualize and quantify the variation in unexposed film-specific uniformity in a package to evaluate the suitability of the reference dose response using machine-learning method. Fourteen EBT4 films (#00-#13) were selected from two lot packages. Nine grid-spaced 100 × 100 pixel (72 dpi) patches were obtained from the color images of EBT4 film sheet using a single scanner with landscape (scan A) and portrait (scan B) scan orientations. The reference patch was set at the center of film #00. For this study, multidimensional scaling (MDS) and Lie derivative image analysis (LDIA) were applied to the patch data with respect to the red (R)/green (G)/blue (B) channels. MDS is a suitable method for analyzing non-linear data with similarity, which provides a map of data objects according to a distance metric. LDIA directly detects the deviation vector field between image gradients. The film-specific uniformity was measured at 1/10000 scaled pixel value as a scalar distribution. The image flow field was obtained as a negative gradient of the scalar distribution. Two similarity metrics were defined for comparison with the reference patch: (1) MDSr (the distance parameter in the MDS map from the origin) and (2) Stot (summed S-value in each patch, where S-value represents the vorticity of the deviation vector field obtained via the Lie derivative). MDSr highly correlated with the absolute pixel value difference from the reference patch except for the blue channel in which a favorable package was detected for the reference dose response. Stot quantified the film-uniformity variation from the reference, independent of the dataset, and detected the unfavorable film state as Stot < 0.8 in the blue channel. We visualized and quantified the variation in film-specific uniformity in a lot package using MDS and LDIA, thereby quantitatively determining the unfavorable condition for applying the reference dose-response.

Beam modeling and validation for a 1.5 T MR-linac in an alternative treatment planning system

Objective.MR-guided adaptive radiotherapy (MRgART) is ideally suited to adjust the treatment plan for anatomical changes. The online nature of MRgART involves multiple process steps during each treatment fraction, which may greatly benefit from automation. TheRayStationtreatment planning system incorporates automation features by design, but requires dose calculations in the presence of an external magnetic field and the modeling of the MRgART system. This study developed and commissioned a comprehensive model for the 1.5 T MR-guided linear accelerators (MR-linacs) inRayStation.Approach.MR-linac dose profiles and output factors were used to model the Unity MR-linac inRayStation. The MR cryostat was implemented in the Monte Carlo simulation as a multi-layer barrel, adjusted using simulations and in-air output measurements. The cryostat transmission variation with gantry angle was added as a fluence correction. Dose distributions of on-axis square, off-axis square, and 90 IMRT fields of ten prostate MR-linac treatment plans were evaluated with the PTW Octavius 1500MR detector array. The radiofrequency coils and couch were characterized with megavoltage imager transmission measurements. CT scans of the coils were used to model its geometry inRayStationand mass densities were assigned to match the measured attenuation.Results.Differences between measured and calculated depth dose showed aγ< 0.5 beyonddmax. For both the inline and crossline profiles, theγevaluation exhibited aγ< 1.0 for nearly all evaluated points. The maximum difference between the measured and calculated cryostat scatter was 0.6%. The averageγpass rate for the on-axis, off-axis, and IMRT fields was >98.3% (range: 91.2%-100%). The average coil transmissions were 0.6 (anterior) and 2.2% (posterior).Significance.We successfully modeled and commissioned the 1.5 T MR-linac inRayStationwell within tolerance limits as specified by the American Association of Physicists in Medicine TG-157 report.

Impact of log file source and data frequency on accuracy of log file-based patient specific quality assurance

Performing phantom measurements for patient-specific quality assurance (PSQA) adds a significant amount of time to the adaptive radiotherapy procedure. Log file based PSQA can be used to increase the efficiency of this process. This study compared the dosimetric accuracy of high-frequency linear accelerator (Linac) log files and low-frequency log data stored in the oncology information system (OIS). Thirty patients were included, that were recently treated in the head and neck (HN), brain, and prostate region with volumetric modulated arc therapy (VMAT) and an additional ten patients treated using stereotactic body radiation therapy (SBRT) with 3D-conformal radiotherapy (3D-CRT) technique. Log data containing a single fraction were used to calculate the dose distributions. The dosimetric differences between Linac log files and OIS logs were evaluated with a gamma analysis with 2%/2 mm criterion and dose threshold of 30%. The original treatment plan was used as a reference. Moreover, DVH parameters of D98%, D50%, and D2% of the planning-target volume (PTV) and dose to several organs at risk (OARs) were reported. Significant differences in dose distributions between the two log types and the original dose were observed for PTV D98% and D2% (r < 0.001) for HN cases, PTV D98% (r = 0.005) for brain cases, and PTV D50% (r = 0.015) for prostate cases. No significant differences were found between the two log types with respect to D50%. The root mean square (RMS) error of the leaf positions of the OIS log was approximately twice the RMS error of the Linac log file for VMAT plans, but identical for 3D-CRT plans. The relationship between the gamma pass rate and the RMS error showed a moderate correlation for the Linac log files (r = -0.58, p < 0.001) and strong correlation for OIS logs (r = -0.71, p < 0.001). Furthermore, all doses calculated using Linac log files and OIS log data had a GPR >90% for an RMS error < 3.3 mm. Based on these findings, a tolerance limit of RMS error of 3.3 mm for considering OIS log based PSQA was established. Nevertheless, the OIS log data quality should be improved to achieve adequate PSQA.

Assessing HyperSight iterative CBCT for dose calculation in online adaptive radiotherapy for pelvis and breast patients compared to synthetic CT

PURPOSE/OBJECTIVES

Recent technological advancements have increased efficiency for clinical deliverability of online-adaptive-radiotherapy (oART). Previous cone-beam-computed-tomography (CBCT) generations lacked the ability to provide reliable Hounsfield-units (HU), thus requiring oART workflows to rely on synthetic-CT (sCT) images derived through deformable-image-registration (DIR) between the planning CT (pCT) and the daily CBCT. These sCTs are prone to errors stemming from DIR, potentially contributing to dosimetric errors. This study aims to evaluate the capability of direct dose calculation using a novel CBCT platform, HyperSight (Varian-Medical-Systems), as an alternative for sCT.

METHODS/MATERIALS

To validate the HyperSight iterative CBCT (HS-iCBCT) HU accuracy, 125 kV and 140 kV HS-iCBCT calibration curves were benchmarked against a pCT calibration curve. To determine the clinical impact of HS-iCBCT compared to sCT, daily adaptive sessions from 47 oART fractions from 10 patients were analyzed. For these patients, HS-iCBCT was acquired for daily adaption, and sCT was generated as part of the standard adaptive workflow. After daily adaption, dose was recalculated directly using the HS-iCBCT, and the HS-iCBCT and sCT dose distributions were compared by γ-index and dose-volume-histogram (DVH) analysis.

RESULTS

The mean HU differences of pCT minus HS-iCBCT (140/125 kV) were -40.97/-57.79, 9.86/21.74, and 87.22/158.20 for lung, water, and bone. In the patient cohort, the median gamma passing rates between HS-iCBCT and sCT-based dose calculations for 3%/2 mm and 1%/1 mm were 99.57 and 96.45% with 10% threshold, and 99.92% and 86.15% with 80% threshold. Dosimetric deviations in high dose regions were concentrated in areas with larger deformation, that is, surface change and variable bladder/bowel filling. The median (min-max) D98%/V100% absolute deviations were 0.3(0.0-1.6)/0.0(0.0-13.7) and 0.4(0.0-1.4)/0.5(0.0-17.5) for CTVs and PTVs.

CONCLUSIONS

The HS-iCBCT platform with iterative reconstruction provides dose calculation comparable to sCT for pelvis and breast patients. However, acceptable, yet noticeable, dose discrepancies between HS-iCBCT and sCT exist, particularly in high-dose regions. Further investigations are needed to benchmark these methods against ground truth measurements.

Plan complexity and dosiomics signatures for gamma passing rate classification in volumetric modulated arc therapy: External validation across different LINACs

PURPOSE

This study aims to enhance gamma passing rate (GPR) classification by integrating plan complexity signature, dosiomics signature, and comprehensive plan parameters, and to validate this method using data from different linear accelerators (LINACs).

METHODS

This study included 235 volumetric modulated arc therapy (VMAT) treatment plans delivered using the TrueBeam LINAC as the primary dataset, along with 47 plans from the VitalBeam LINAC for external validation. The primary dataset was split into training (N = 166) and test (N = 69) subsets. Extracted features included 47 plan complexity metrics, 851 dosiomics features, and 20 plan parameters. Plan complexity score (PCscore) and dosiomics score (Doscore) were derived using the least absolute shrinkage and selection operator (LASSO). Four classification models were developed by combining PCscore, Doscore, and plan parameters according to a gamma criterion of 2 %/2 mm (γ2%/2 mm). A nomogram was constructed to combine these signatures with plan parameters. Model performance was evaluated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA).

RESULTS

The combined model incorporating PCscore, Doscore, and plan parameters exhibited high discriminative power, with areas under the curve (AUC) of 0.894, 0.899, and 0.904 for the training, test, and external datasets, respectively. At γ3%/2 mm, the model maintained robust performance with AUCs of 0.842 and 0.833 in the test and external datasets. Calibration curves and DCA validated the model's effectiveness.

CONCLUSIONS

Integrating plan complexity and dosiomics signatures with key plan parameters significantly improves GPR classification for VMAT treatment plans, offering a robust approach for patient-specific quality assurance (PSQA).

Commissioning of a reference beam model-based Monte Carlo dose calculation algorithm for cranial stereotactic radiosurgery

PURPOSE

In treatment planning system (TPS) commissioning for stereotactic radiosurgery (SRS), the required measurements and precision necessary to generate an accurate beam model make the process taxing and time-consuming. Recently, Brainlab AG released reference beam models available for use with the Elements TPS. In this work, we detail our implementation of reference beam model-based Monte Carlo dose calculations for our Elements 4.0 TPS.

METHODS

Depth dose, output factor, and beam profile measurements were used to select a reference beam model. 9 treatment plans encompassing the range of clinical use cases were created. Patient QA measurements were performed using a high-resolution detector array. Dose distributions were mapped to the QA array using the reference beam model with 1-2 mm grid resolution. Independent MU verifications were performed for each test plan. An end-to-end test was performed for final verification of system performance and data integrity.

RESULTS

Acceptable agreement was demonstrated between measured data and the reference beam model. All QA gamma pass rates exceeded 95 %. Measured peak dose differences were over 5 % for targets with diameter <7 mm when using a 1.0 mm Monte Carlo grid resolution. 1 of the 46 tested arcs had over a 5 % difference between MU verification and the TPS-calculated MU. End-to-end testing verified system performance.

CONCLUSION

Validation testing demonstrated good agreement between the reference beam dataset and machine performance for targets with diameters ≥7 mm. The use of a reference beam model may significantly reduce measurement burden while mitigating potential failure modes associated with TPS commissioning.

Effects of cardiac motion on dose distribution during stereotactic arrhythmia radioablation treatment: A simulation and phantom study

PURPOSE

Cardiac motion may degrade dose distribution during stereotactic arrhythmia radioablation using the CyberKnife system, a robotic radiosurgery system. This study evaluated the dose distribution changes using a self-made cardiac dynamic platform that mimics cardiac motion.

METHODS

The cardiac dynamic platform was operated with amplitudes of 5 and 3.5 mm along the superior-inferior (SI) and left-right (LR) directions, respectively. The respiratory motion tracking of the CyberKnife system was applied when respiratory motion, simulated using a commercial platform, was introduced. The accuracy of respiratory motion tracking was evaluated by the correlation error between infrared markers and a fiducial marker. The dose distribution was compared with and without cardiac motion. The evaluations included error in the centroid analysis of the irradiated dose distribution, dose profile analysis in the SI and LR directions, and dose distribution analysis comparing the irradiated and planned dose distributions.

RESULTS

Cardiac motion increased the correlation error in the direction of motion. Cardiac motion displaced the centroid by up to 0.23 and 0.19 mm in the SI and LR directions, respectively. Cardiac motion blurring caused the distance of the isodose lines to become smaller (bigger) at higher (lower) doses in the SI direction. The gamma pass rate was reduced by cardiac motion but exceeded 94.1% with 1 mm/3% for all conditions. Respiratory motion tracking was also effective under cardiac motion. The cardiac motion slightly varied the dose at the edges of the irradiation volume.

CONCLUSION

While cardiac motion increased respiratory tracking correlation errors, its effects on dose distribution were limited in this study. Further studies using motion phantoms that are close to a human or individual patient are necessary for a more detailed understanding of the effects of cardiac motion.

In vivo transit dosimetry methodology for whole breast intensity modulated radiation therapy

BACKGROUND

In vivo transit dosimetry using an electronic portal imaging device (EPID-IVTD) is an important tool for verifying the accuracy of radiation therapy treatments. Despite its potential, the implementation of EPID-IVTD in breast intensity modulated radiation therapy (IMRT) treatments has not yet been standardized, limiting its clinical adoption. A standardized EPID-IVTD method could enhance treatment accuracy and improve patient safety in routine clinical practice.

PURPOSE

This study aims to develop a method for EPID-IVTD for whole breast IMRT treatment.

METHODS

Gamma passing rates (GPRs) analysis was the basis of the work conducted on a dataset of 50 patients. The first phase of the work focused on the identification of the reference fraction. In the second phase a method for performing EPID-IVTD was implemented. Lower-tolerance and -action limits (l-TL and l-AL), as introduced by AAPM TG 218, were employed to determine the reference fraction and used as alert and alarm thresholds, respectively, in EPID-IVTD monitoring.

RESULTS

The first treatment fraction demonstrated the best dosimetric agreement with the theoretical plan and was therefore used as the reference in the second phase of the study. EPID-IVTD results showed that 75% of the GPRs ranged from 97.5% to 99.9%, 93.83% were above the l-TL, 4.31% fell between l-TL and l-AL, and 1.86% were below l-AL.

CONCLUSIONS

A method for the implementation of an effective EPID-IVTD in whole breast IMRT treatment was developed and is now routinely applied at our center, enabling efficient monitoring in clinical practice.

Validity of one-time phantomless patient-specific quality assurance in proton therapy with regard to the reproducibility of beam delivery

BACKGROUND

Patient-specific quality assurance (PSQA) is a crucial yet resource-intensive task in proton therapy, requiring special equipment, expertise and additional beam time. Machine delivery log files contain information about energy, position and monitor units (MU) of all delivered spots, allowing a reconstruction of the applied dose. This raises the prospect of phantomless, log file-based QA (LFQA) as an automated replacement of current phantom-based solutions, provided that such an approach guarantees a comparable level of safety.

PURPOSE

To retrieve a reliable LFQA conclusion from a one-time plan delivery before treatment initiation, deviations between planned and logged parameters must either be persistent over all following treatment fractions or, in case of random fluctuations, must not have a relevant impact on the reconstructed dose distribution. We therefore investigated the reproducibility of log file parameters over multiple patient treatment fractions and compared the reconstructed dose distributions.

METHODS

Log file variability was examined at both spot parameter and integral dose levels. The log files of 14 patient treatment plans were analyzed retrospectively for a total of 339 delivered fractions. From the recorded x/y position and MU parameters per spot, the respective mean difference to the planned value (accuracy) and the standard deviation (reproducibility) were calculated for 108,610 planned spots. The dose distributions reconstructed from the log files of each fraction were evaluated against the planned fraction dose using 3D gamma index analysis. The dose-based gamma pass rate Γ $\Gamma$ was correlated with a new spot-based log file pass rate Λ ${\Lambda}$ . Beam timing information from the log files was used to quantify the total plan/field delivery time stability after excluding machine interlocks.

RESULTS

The mean spot-wise accuracy with respect to distance from planned positions and MUs was (0.6 ± 0.3) mm and (0.0001 ± 0.0023) MU, respectively. The mean reproducibility of the observed single spot deviations was (0.2 ± 0.1) mm and (0.0004 ± 0.0004) MU (mean ± standard deviation). These variations resulted in minimal changes in the reconstructed fraction dose with Γ ${{\Gamma}}$ (2 mm/2%) > 99% for all studied fractions. Results for more sensitive criteria Γ ${{\Gamma}}$ (1 mm/1%) were plan-specific, but on average > 92.6% per plan and correlated with Λ ${{\Lambda}}$ (1 mm) pass rates (0.51 ≤ rPearson ≤ 0.99). Field delivery times were reproducible within ± 4 s (2σ) and no treatment interruptions were observed in 92.8% of cases.

CONCLUSIONS

The log file records of plan-relevant spot parameters are well-reproducible over multiple fractions and deviations have no dosimetrically relevant impact on the reconstructed fraction doses. Results of a one-time pre-treatment LFQA are considered as valid for the entire treatment course and there is no concern in this regard to replace state-of-the-art phantom measurements in the current PSQA workflow.

Impact of acceleration treatment on treatment plan and delivery qualities in tomotherapy for lung cancer

BACKGROUND

Acceleration treatment (AT) is a novel treatment planning parameter introduced in the tomotherapy-dedicated treatment planning system, Precision. This study explores the effects of AT on tomotherapy plans using helical (TomoHelical) and direct (TomoDirect) irradiation techniques.

METHODS

This study enrolled 20 patients with lung cancer. Initially, 10 TomoHelical and 10 TomoDirect treatment plans were created for each patient, utilizing patient-specific field width and pitch with an AT setting of 0. These original plans were subsequently reoptimized by changing only the AT values to 1, 4, 7, and 10 without changing other calculation parameters to assess the impact of AT on dosimetric and delivery parameters. Additionally, the deliverability of all plans was evaluated through patient-specific quality assurance using gamma analysis.

RESULTS

Increasing the AT from 0 to 10 led to a slight increase in maximum doses and a decrease in minimum doses within the target volume, thereby impairing dose homogeneity. Dose conformity to the target also deteriorated. Conversely, target coverage and delivery time improved considerably with higher AT values. Moreover, doses to organs at risk, including the lung, spinal cord, heart, and esophagus, remained clinically acceptable across all plans. Changes in these doses and the gamma pass rate in patient-specific quality assurance were negligible with variations in AT. This trend was consistent across both delivery techniques.

CONCLUSION

AT is a crucial parameter in tomotherapy planning for modulating plan and delivery qualities. Higher AT values can enhance target coverage and delivery time efficiency.

Evaluation of deliverable artificial intelligence-based automated volumetric arc radiation therapy planning for whole pelvic radiation in gynecologic cancer

This study aimed to develop a deep learning (DL)-based deliverable whole pelvic volumetric arc radiation therapy (VMAT) for patients with gynecologic cancer using a prototype DL-based automated planning support system, named RatoGuide, to evaluate its clinical validity. In our hospital, 110 patients with gynecologic cancer were registered. The prescribed dose was 50.4 Gy/28 fr. A DL-based three-dimensional dose prediction model was first trained by the dose distribution and structure data of whole pelvic VMAT (n = 100) created on the Monaco treatment planning system (TPS). The structure data of the test data (n = 10) were then input to RatoGuide, and RatoGuide predicted the dose distribution of the whole pelvic VMAT plan (PreDose). We established deliverable plans with Monaco and Eclipse TPS (DeliDose) based on PreDose and vendor-supplied optimization objectives. Medical physicists then manually developed plans (CliDose) for the test data. Finally, we evaluated and compared the dose distribution and dose constraints of PreDose, DeliDose, and CliDose. DeliDose, in both Eclipse and Monaco, was comparable to PreDose in most Dose constraints, planning target volume (PTV) coverage, and Dmax of the bladder, rectum, and bowel bag were better for DeliDose than for PreDose. Additionally, DeliDose demonstrated no significant difference from CliDose in most dose constraints. The blinded average scores of radiation oncologists for DeliDose and CliDose were 4.2 ± 0.4 and 4.3 ± 0.5, respectively, in Eclipse, and 4.0 ± 0.6 and 3.9 ± 0.5, respectively, in Monaco (5 is the max score and 3 is clinically acceptable). We indicated that RatoGuide can eliminate variations in plan quality between hospitals in whole pelvic VMAT irradiation and help develop VMAT plans in a short time.

IPEM topical report: guidance for the use of linac manufacturer integrated quality control

This report provides guidance for users of linear accelerator (linac) manufacturer integrated quality control (MIQC) tools. MIQC tools have been developed and introduced by radiotherapy linac vendors, and have the potential to improve both the quality and efficiency of linac quality control (QC). They usually utilise the Electronic Portal Imaging Device (EPID), but may acquire data from other sources, and automatically perform and analyse tests of various treatment machine QC parameters. The currently available systems meeting this definition are Varian machine performance check, CyberKnife automated quality assurance /end-to-end, TomoTherapy Quality Assurance, and Elekta machine QA (also known as AQUA). This guidance report covers the commissioning and implementation of MIQC. The guidance has been developed by a radiotherapy special interest group working party on behalf of the Institute of Physics and Engineering in Medicine. Recommendations within the report are derived from the experience of the working party members, existing guidance, literature, and a United Kingdom survey conducted in 2022 (Pearsonet al2023Phys. Med. Biol.68245018). Topics covered include developing an understanding of the QC system, independence review of MIQC, commissioning, implementation, ongoing QC and calibration, software upgrades and periodic review. The commissioning section covers detector commissioning, repeatability and reproducibility, baseline and tolerance setting, concordance with existing QC, sensitivity testing, cost-benefits analysis, and risk assessment methods. In order to offer practical guidance, case studies covering each aspect of commissioning are included. They are real-world examples or experiences from early adopters, each applied to a different example MIQC system. The examples will be directly applicable to users of that specific MIQC system, but also provide practical guidance on clinical implementation to users of the other systems.

Shielding disc backscatter calculations in intraoperative radiotherapy using a Monte Carlo simulation based on the method of energy spectra reconstruction

The study focuses on validating and applying a Monte Carlo (MC) simulation model to backscatter calculations from the shielding discs used during intraoperative electron radiotherapy (IOERT), particularly in breast cancer treatments. The MC model is developed based on dosimetric data collected under reference conditions and validated by measurements with EBT4 Gafchromic films in a water phantom. The study investigates the dose distributions for 6, 9, and 12 MeV electron beams formed by a mobile AQURE accelerator, comparing scenarios with and without a surgical stainless steel shielding disc. While the shielding disc effectively reduces radiation doses behind it, the backscatter significantly increases doses in tissues immediately in front of the disc. Specifically, the dose at 1 mm in front of the disc increases by 19.8%, 18.4%, and 17.5% were observed for 6, 9, and 12 MeV beams, respectively. The validated MC model provides an accurate tool for predicting dose distributions in complex geometries, enabling improved treatment planning and safety in IOERT applications. The findings underscore the need to consider backscatter effects when shielding discs are used in IOERT. The study suggests further optimization of shielding disc design, potentially incorporating biocompatible, low-Z materials to mitigate backscatter.

Portal dose image prediction using Monte Carlo generated transmission energy fluence maps of dynamic radiotherapy treatment plans: a deep learning approach

Aims.This work aims to develop and investigate the feasibility of a hybrid model combining Monte Carlo (MC) simulations and deep learning (DL) to predict electronic portal imaging device (EPID) images based on MC-generated exit phase space energy fluence maps from dynamic radiotherapy treatment plans. Such predicted images can be used as reference images duringin vivodosimetry.Materials and methods. MC simulations involving a Varian True Beam linear accelerator model were performed using the EGSnrc code package. Two custom variants of the U-Net architecture were employed. The MLC dynamic chair sequence and 17 clinical treatment plans, spanning various cancer types and delivery methods, were used to acquire experimental data, and in the MC simulations. The proposed method was tested through 2D gamma index analysis, comparing predicted and measured EPID images.Results. Results showed gamma passing rates of 38.65%, 74.16% and 96.17% (minimum, median, maximum) for a simpler model variant and 52.72%, 80.61% and 96.80% for the more complex model variant.Conclusion. The study highlights the feasibility of integrating MC and DL methodologies forin vivodosimetry quality assurance in complex radiotherapy delivery.

In Silico Evaluation of Direct-to-Unit, Single-Visit Celiac Plexus Pain Ablation Using Computed Tomography Guided Adaptive Radiation Therapy

PURPOSE

Celiac plexus stereotactic body radiation therapy (CP-SBRT) using 25 Gy in a single fraction is an effective method of palliative pain relief for patients suffering from celiac axis tumor invasion. Standard complex stereotactic body radiation therapy workflows for simulation and planning result in delays in pain relief during end-of-life care. We propose a simulation-free, direct-to-unit (DTU) adaptive radiation therapy (ART) approach, using a diagnostic computed tomography (CT) preplan and online adaptation for final plan construction to enable the same-day radiation oncology consult and CP-SBRT. We aimed to demonstrate that this advanced imaging has increased electron density accuracy which enables the test of this DTU, adaptive CP-SBRT workflow in silico.

METHODS AND MATERIALS

Ten patients with abdominal malignancies were imaged on a HyperSight Cone Beam Computed Tomography (CBCT) solution on a C-arm linear accelerator as part of a prospective imaging clinical trial (NCT05975619). These patients' existing diagnostic CT scans were used to generate CP-SBRT preplans. To simulate a simulation-free, DTU workflow, HyperSight CBCT images were injected into a CT guided ART treatment planning system environment as the primary data set, with target contours propagated from the registered diagnostic CT. Contours were updated as needed to reflect the treatment anatomy and positioning. A standard online ART workflow was used for the predicted and final adaptive plan calculation. Dose-volume values for each clinical goal were compared between predicted and final plans. Timing and measured quality assurance data were also collected.

RESULTS

DTU adaptive CP-SBRT plans were successfully created for all 10 patients and met all clinical goals. Without adaptation, predicted plans were infeasible for clinical use; 9 of 10 patients had nondeliverable predicted plans. The average time to complete ART contouring was 6 minutes. The average gamma passing rate for 3%/2 mm was 92.6%.

CONCLUSION

DTU ART for CP-SBRT is dosimetrically feasible. Adaptation is a critical component for DTU CP-SBRT to achieve deliverable plans. This approach could reduce treatment delay for cancer-related celiac pain.

Commissioning of a motion management system for a 1.5T Elekta Unity MR-Linac: A single institution experience

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.

AAPM-RSS Medical Physics Practice Guideline 9.b: SRS-SBRT

The purpose of this Medical Physics Practice Guideline (MPPG) is to describe the minimum level of medical physics support deemed prudent for the practice of linear-accelerator, photon-based (linac) stereotactic radiosurgery (SRS), and stereotactic body radiation therapy (SBRT) services. This report is an update of MPPG 9.a1 published in 2017. As SRS and SBRT services are rapidly adopted into the community-practice setting, this guideline has been developed to build on the work presented in MPPG 9.a and provide current appropriate minimum practice guidelines for such services.

Body contour adaptation for weight-loss and bolus for head and neck radiotherapy on Ethos version 2.0 and HyperSight: Synthetic CT versus direct calculation

PURPOSE

In radiotherapy, body contour inaccuracies may compromise the delineation of adjacent structures and affect calculated dose. Here, we evaluate the un-editable body contours auto-generated by Ethos versions 1.0 (v1) and 2.0 (v2) treatment planning softwares for two simulated cases: weight-loss and bolus application, particularly important for head and neck radiotherapy patients.

METHODS

A 3D-printed target structure was secured to the neck of an anthropomorphic phantom and sequentially covered with silicone boluses of uniform thickness, providing cases for bolus application (0.5 and 1 cm) and weight-loss (2.0, 1.5, 1.0, 0.5, and 0 cm). HyperSight CBCT images of the phantom were acquired to simulate the online adaptation process. Baseline body contours were manually produced and compared to those auto-generated in Ethos v1 (synthetic CTs) and Ethos v2 (synthetic CTs and direct calculation on HyperSight CBCTs). Additionally, the target volume D95% dose metric for weight-loss adapted plans generated by the Ethos v2 were analyzed as a function of surface layer thickness.

RESULTS

The Ethos v1 body contour did not adapt adequately for the weight-loss image set [mean absolute volume deviation from baseline (MAD) = 205 cm3]. The weight-loss synthetic CT and HyperSight CBCT volumes in Ethos v2 were comparable to manually generated contours (MAD = 34 and 46 cm3 , respectively); however, the bolus Hypersight CBCT body contour intersected the outer edge of the phantom (MAD = 157 cm3). The D95% deviation from the planned dose decreased by up to 10% when using the Ethos v2 adapted plan for the weight-loss scenario.

CONCLUSION

Contours in Ethos v1 rely on reference contours and deformable registration algorithms, whereas Ethos v2 does not. Hence, Ethos v2 is preferred for cases involving weight change. A tight-fitted air gap-free bolus is critical for achieving accurate body contours for Ethos v2 Hypersight CBCTs.

A feasibility study of deep learning prediction model for VMAT patient-specific QA

Purpose

This study introduces a deep learning (DL) model that leverages doses calculated from both a treatment planning system (TPS) and independent dose verification software using Monte Carlo (MC) simulations, aiming to predict the gamma passing rate (GPR) in VMAT patient-specific QA more accurately.

Materials and method

We utilized data from 710 clinical VMAT plans measured with an ArcCHECK phantom. These plans were recalculated on an ArcCHECK phantom image using Pinnacle TPS and MC algorithms, and the planar dose distributions corresponding to the detector element surfaces were utilized as input for the DL model. A convolutional neural network (CNN) comprising four layers was employed for model training. The model's performance was evaluated through multiple predictive error metrics and receiver operator characteristic (ROC) curves for various gamma criteria.

Results

The mean absolute errors (MAE) between measured GPR and predicted GPR are 1.1%, 1.9%, 1.7%, and 2.6% for the 3%/3mm, 3%/2mm, 2%/3mm, and 2%/2mm gamma criteria, respectively. The correlation coefficients between predicted GPR and measured GPR are 0.69, 0.72, 0.68, and 0.71 for each gamma criterion. The AUC (Area Under the Curve) values based on ROC curve for the four gamma criteria are 0.90, 0.92, 0.93, and 0.89, indicating high classification performance.

Conclusion

This DL-based approach showcases significant potential in enhancing the efficiency and accuracy of VMAT patient-specific QA. This approach promises to be a useful tool for reducing the workload of patient-specific quality assurance.

Measurement-guided therapeutic-dose prediction using multi-level gated modality-fusion model for volumetric-modulated arc radiotherapy

Objectives

Radiotherapy is a fundamental cancer treatment method, and pre-treatment patient-specific quality assurance (prePSQA) plays a crucial role in ensuring dose accuracy and patient safety. Artificial intelligence model for measurement-free prePSQA have been investigated over the last few years. While these models stack successive pooling layers to carry out sequential learning, directly splice together different modalities along channel dimensions and feed them into shared encoder-decoder network, which greatly reduces the anatomical features specific to different modalities. Furthermore, the existing models simply take advantage of low-dimensional dosimetry information, meaning that the spatial features about the complex dose distribution may be lost and limiting the predictive power of the models. The purpose of this study is to develop a novel deep learning model for measurement-guided therapeutic-dose (MDose) prediction from head and neck cancer radiotherapy data.

Methods

The enrolled 310 patients underwent volumetric-modulated arc radiotherapy (VMAT) were randomly divided into the training set (186 cases, 60%), validation set (62 cases, 20%), and test set (62 cases, 20%). The effective prediction model explicitly integrates the multi-scale features that are specific to CT and dose images, takes into account the useful spatial dose information and fully exploits the mutual promotion within the different modalities. It enables medical physicists to analyze the detailed locations of spatial dose differences and to simultaneously generate clinically applicable dose-volume histograms (DVHs) metrics and gamma passing rate (GPR) outcomes.

Results

The proposed model achieved better performance of MDose prediction, and dosimetric congruence of DVHs, GPR with the ground truth compared with several state-of-the-art models. Quantitative experimental predictions show that the proposed model achieved the lowest values for the mean absolute error (37.99) and root mean square error (4.916), and the highest values for the peak signal-to-noise ratio (52.622), structural similarity (0.986) and universal quality index (0.932). The predicted dose values of all voxels were within 6 Gy in the dose difference maps, except for the areas near the skin or thermoplastic mask indentation boundaries.

Conclusions

We have developed a feasible MDose prediction model that could potentially improve the efficiency and accuracy of prePSQA for head and neck cancer radiotherapy, providing a boost for clinical adaptive radiotherapy.

Radiotherapy quality assurance in the PROTECT trial - a European randomised phase III-trial comparing proton and photon therapy in the treatment of patients with oesophageal cancer

PURPOSE

To present results from the trial radiotherapy quality assurance (RTQA) programme of the centres involved in the randomised phase-III PROton versus photon Therapy for esophageal Cancer - a Trimodality strategy (PROTECT)-trial, investigating the clinical effect of proton therapy (PT) vs. photon therapy (XT) for patients with oesophageal cancer.

MATERIALS AND METHODS

The pre-trial RTQA programme consists of benchmark target and organ at risk (OAR) delineations as well as treatment planning cases, a facility questionnaire and beam output audits. Continuous on-trial RTQA with individual case review (ICR) of the first two patients and every fifth patient at each participating site is performed. Patient-specific QA is mandatory for all patients. On-site visits are scheduled after the inclusion of the first two patients at two associated PT and XT sites. Workshops are arranged annually for all PROTECT participants.

RESULTS

Fifteen PT/XT sites are enrolled in the trial RTQA programme. Of these, eight PT/XT sites have completed the entire pre-trial RTQA programme. Three sites are actively including patients in the trial. On-trial ICR was performed for 22 patients. For the delineation of targets and OARs, six major and 11 minor variations were reported, and for six patients, there were no remarks. One major and four minor variations were reported for the treatment plans. Three site visits and two annual workshops were completed.

INTERPRETATION

A comprehensive RTQA programme was implemented for the PROTECT phase III trial. All centres adhered to guidelines for pre-trial QA. For on-trial QA, major variations were primarily seen for target delineations (< 30%), and no treatment plans required re-optimisation.

AI-enhanced cancer radiotherapy quality assessment: utilizing daily linac performance, radiomics, dosimetrics, and planning complexity

Objective

This study aimed to develop and validate an Informer- Convolutional Neural Network (CNN) model to predict the gamma passing rate (GPR) for patient-specific quality assurance in volumetric modulated arc therapy (VMAT), enhancing treatment safety and efficacy by integrating multiple data sources.

Methods

Analyzing 465 VMAT treatment plans covering head & neck, chest, and abdomen, the study extracted data from 31 complexity indicators, 123 radiomics features, and 123 dosimetrics indices, along with daily linac performance data including 141 key performance indicators. A hybrid Informer-CNN architecture was used to handle both temporal and non-temporal data for predicting GPR.

Results

The Informer-CNN model demonstrated superior predictive performance over traditional models like Convolutional Neural Networks (CNN), Long Short-Term Memory(LSTM), and Informer. Specifically, in the validation set, the model achieved a mean absolute error (MAE) of 0.0273 and a root mean square error (RMSE) of 0.0360 using the 3%/3mm criterion. In the test set, the MAE was 0.0327 and the RMSE was 0.0468. The model also showed high classification performance with AUC scores of 0.97 and 0.95 in test and validation sets, respectively.

Conclusion

The developed Informer-CNN model significantly enhances the prediction accuracy and classification of gamma passing rates in VMAT treatment plans. It facilitates early integration of daily accelerator performance data, improving the assessment and verification of treatment plans for better patient-specific quality assurance.

Standardization of radiation therapy quality control system through mutual quality control based on failure mode and effects analysis

The advancement of irradiation technology has increased the demand for quality control of radiation therapy equipment. Consequently, the number of quality control items and required personnel have also increased. However, differences in the proportion of qualified personnel to irradiation techniques have caused bias in quality control systems among institutions. To standardize the quality across institutions, researchers should conduct mutual quality control by analyzing the quality control data of one institution at another institution and comparing the results with those of their own institutions. This study uses failure mode and effects analysis (FMEA) to identify potential risks in 12 radiation therapy institutions, compares the results before and after implementation of mutual quality control, and examines the utility of mutual quality control in risk reduction. Furthermore, a cost-effectiveness factor is introduced into FMEA to evaluate the utility of mutual quality control.

Feasibility study of structural similarity index for patient-specific quality assurance

BACKGROUND

The traditional gamma evaluation method combines dose difference (DD) and distance-to-agreement (DTA) to assess the agreement between two dose distributions. However, while gamma evaluation can identify the location of errors, it does not provide information about the type of errors.

PURPOSE

The purpose of this study is to optimize and apply the structural similarity (SSIM) index algorithm as a supplementary metric for the quality evaluation of radiation therapy plans alongside gamma evaluation. By addressing the limitations of gamma evaluation, this study aims to establish clinically meaningful SSIM criteria to enhance the accuracy of patient-specific quality assurance (PSQA).

METHODS

We analyzed the relationship between the gamma passing rate (GPR) and the SSIM index with respect to distance and dose errors. For SSIM analysis corresponding to gamma evaluation criteria of 3%/2 mm, we introduce the concept of SSIM passing rate (SPR). We determined a valid SSIM index that met the gamma evaluation criteria and applied it. Evaluations performed for 40 fields measured with an electronic portal imaging device (EPID) were analyzed using the GPR and the applied SPR.

RESULTS

The study results showed that distance errors significantly affected both the GPR and the SSIM index, whereas dose errors had some influence on the GPR but little impact on the SSIM index. The SPR was 100% for distance error of 2 mm but began to decrease for distance errors of 3 mm or more. An optimal SSIM index threshold of 0.65 was established, indicating that SPR fell below 100% when distance errors exceeded 2 mm.

CONCLUSIONS

This study demonstrates that the SSIM algorithm can be effectively applied for the quality evaluation of radiation therapy plans. The SPR can serve as a supplementary metric to gamma evaluation, offering a more precise identification of distance errors. Future research should further validate the efficacy of SSIM algorithm across a broader range of clinical cases.

Assessing the correlation between Gamma passing rate and clinical dosimetric variations in breast cancer IMRT plans with multi-leaf collimator errors: perspectives from the ArcCHECK QA system

This study aimed to comprehensively investigate the influence of multi-leaf collimator (MLC) position errors on both the clinical absolute dose distribution and Gamma passing rate (%GP) in intensity-modulated radiation therapy (IMRT) plans for breast cancer. Additionally, the correlation between %GP and the clinical absolute dose relative difference (%DE) caused by MLC position errors was analysed. Ten IMRT plans for breast cancer were randomly selected. Systematic and random MLC position errors were introduced into DICOM files representing the investigated treatment plans by modifying the plan files and adjusting the MLC positions. Systematic errors were categorized as MLC opening errors, closing errors, and shift errors. The %DE in the tumour planning target volume (PTV) and organs at risk (OARs) caused by MLC errors were statistically analyzed using dose-volume histogram (DVH) analysis. The ArcCHECK quality assurance (QA) system was used to detect the %GP differences between baseline plans and plans with MLC errors. The correlation between %GP and %DE was obtained using linear regression methods. The results of this study indicate that MLC opening and closing errors have a significant impact on %DE and %GP in IMRT plans for breast cancer. Opening and closing errors can be detected at a gamma level of 3%/2 mm, if error values are greater than or equal to 0.5 mm, and %GP can predict DVH dosimetric changes caused by MLC opening and closing errors. It is concluded that DVH-based verification of IMRT plans can serve as an adjunct method to Gamma analysis to improve QA accuracy for breast cancer cases. Additionally, it is concluded that greater attention should be given to MLC leaf opening and closing errors in clinical practice.

Working thresholds for in-vivo dosimetry in EPIGray based on a clinical, anatomically-stratified study

PURPOSE

To obtain tolerance levels for working with the EPID-based EPIgray in vivo dosimetry system.

METHODS

Dose differences between planned and delivered treatments in various anatomical areas, including the gastro-intestinal, urological, rectum and anal canal, gynecological, breast, head and neck, and lung regions, were analyzed across 5,791 fractions. Whether or not the dose differences at each location are symmetrical with respect to zero and adhere to a normal distribution is then checked. Linear regression analysis was applied to check for temporal drift in lung and head and neck treatments. A water equivalent phantom and another with a water-polystyrene interface is used to estimate the dose difference intrinsic to the measurement system. Furthermore, appropriate dose distribution in two treatments is verified using radiochoromic film.

RESULTS

Normal distribution was not observed in any region, and only two showed symmetry around zero. The mean dose differences were: (0.33 ± 6.32) % for the gastro-intestinal system, (-1.31 ± 3.16) % for the gynaecological area, (0.79 ± 4.55) % for VMAT-breast, (3.48 ± 4.00) % for 3DCRT-breast, (0.70 ± 3.20) % for head and neck, (5.63 ± 5.48)% for lung, (-1.36 ± 2.98) % for rectum and anal canal, and (0.13 ± 3.53) % for the urological system.

CONCLUSION

EPIgray should support tolerance levels asymmetric with respect to zero, given the positive deviation observed in mean dose for lung, breast, and head and neck regions. Additionally, the system's ability to detect dose variations during treatment could help identify changes in tumor volume.

Case report: Clinical workflow considerations for treating soft-tissue sarcoma on a 1.5-T MR-Linac

We present specific issues that arose when using a 1.5-Tesla MR-Linac to treat a series of 4 soft-tissue sarcoma (STS) patients. These issues arose from the combination of typical STS attributes (long, off-axis target) and MR-Linac design-specific limitations on field size and patient positioning. Despite the availability of on-line plan adaptation, STS patients were more efficiently treated after workflow changes to improve patient selection and immobilization. Other issues arising from off-axis STS target locations: geometric distortion of MR images and patient-specific QA, are discussed.

Quantification of uncertainties in reference and relative dose measurements, dose calculations, and patient setup in modern external beam radiotherapy

Uncertainties in the steps of external beam radiotherapy (EBRT) affect patient outcomes. However, few studies have investigated major contributors to these uncertainties. This study investigated factors contributing to reducing uncertainty in delivering a dose to a target volume. The EBRT process was classified into four steps: reference dosimetry, relative dosimetry [percentage depth doses (PDDs) and off-center ratios (OCRs)], dose calculations (PDDs and OCRs in a virtual water phantom), and patient setup using an image-guided radiation therapy system. We evaluated the uncertainties for these steps in conventionally fractionated EBRT for intracranial disease using 4-, 6-, and 10-MV flattened photon beams generated from clinical linear accelerators following the Guide to the Expression of Uncertainty in Measurement and an uncertainty evaluation method with uncorrected deflection. The following were the major contributors to these uncertainties: beam quality conversion factors for reference dosimetry; charge measurements, chamber depth, source-to-surface distance, water evaporation, and field size for relative dosimetry; dose calculation accuracy for the dose calculations; image registration, radiation-imaging isocenter coincidence, variation in radiation isocenter due to gantry and couch rotation, and intrafractional motion for the patient setup. Among the four steps, the relative dosimetry and dose calculation (namely, both penumbral OCRs) steps involved an uncertainty of more than 5% with a coverage factor of 1. In the EBRT process evaluated herein, the uncertainties in the relative dosimetry and dose calculations must be reduced.

Comparison of HDR-brachytherapy and tomotherapy for the treatment of non-melanoma skin cancers of the head and neck

PURPOSE

This study aims to investigate and compare High Dose Rate Brachytherapy (HDR-BT) with Helical Tomotherapy (HT) treatment plans. The focus is on small target volumes near radiation-sensitive organs in the ocular region, to evaluate the advantages of these techniques in treating skin cancer.

METHODS

This retrospective observational analysis included patients who underwent skin cancer HDR-BT Freiburg flap treatment between 2019 and 2023. An expert radiation oncologist contoured the planning target volumes (PTVs) and marked their visible extension with a radio-opaque tin wire. Each patient had two treatment plans: an individually shaped HDR-BT surface mold and an HT calculation used specifically for this study. Quality assurance of treatment plan was performed in both HDR-BT and HT. The plans were then compared using organ at risk (OAR) maximum doses and the conformity index CI. Radiation oncologists assessed their quality using their routine workflow evaluation plan.

RESULTS

Twelve patients were selected for the inclusion in this study. HT provided more consistent target coverage than HDR-BT, with a statistically significant difference (p < 0.05) at t-test. HT showed higher CIs and maximum dose for the optic nerve, optic chiasm, and lens in the homolateral part. Radiation oncologists preferred the overall quality of HT treatment due to its superior PTV coverage, especially for convex surfaces, while maintaining effective OAR sparing. HDR-BT is preferred when concave surfaces are present.

CONCLUSION

HT offers more conformal treatment, although some OAR parameters are statistically significantly better with HDR-BT, which may also be superior for complex geometries.

Evaluation of radiation treatment plan quality in head and neck cancer: a comparative analysis of RapidArc technique with flattening filter and flattening filter-free photon beams

AIM

This study aims to evaluate the treatment plan quality for oral cavity cancers in the head and neck region using the RapidArc (RA) technique with both flattening filter (FF) and flattening filter-free (FFF) photon beams.

MATERIALS AND METHODS

In this analytical study, treatment plans for 12 patients originally planned with a 6 MV FF photon beam were recreated using the RA technique with a 6 MV FFF photon beam. Identical beam parameters and planning objectives were maintained for both sets of plans to facilitate comparison. All plans were evaluated based on planning indices and doses to organs at risk (OAR).

RESULTS

A significant dose variation was found in the minimum (Dmin) and mean (Dmean) doses of the high-risk planning target volume between FF and FFF photon beam RA plans. However, the dose distribution for the low-risk planning target volume was equivalent between the two techniques. The FFF-RA plans demonstrated superior conformity and homogeneity indices compared to the FF plans, with these differences being statistically significant. In addition, the FF-RA plans showed higher doses to the parotid glands, eyes and lenses than the FFF plans. The FFF plans also showed significantly shorter beam-on treatment times and a higher gamma passing index rate compared to the FF plans.

CONCLUSION

In contrast to the FF photon beam, an FFF photon beam-oriented RA plan provides significant OAR sparing without losing the quality of the treatment plan. High monitor units and beam on time are major highlights of the RA plan with FFF beam.