Feasibility of CBCT-based dose calculation: Comparative analysis of HU adjustment techniques

Systematic construction of composite radiation therapy dataset using automated data pipeline for prognosis prediction

BACKGROUND

Existing research on medical data has primarily focused on single time-points or single-modality data. This study aims to collect all data generated during radiotherapy comprehensively to improve the treatment and prognosis of patients with malignant tumors.

METHODS

The data collected from each medical institution were transmitted to the lead organization, where they underwent a file integrity check and were processed using a data pipeline. The key metadata of the collected data were compiled into a database, which were examined by data analysts to identify outliers based on theoretical and institution-specific characteristics. Appropriate filters were applied and the filtered data were subsequently reviewed by artificial intelligence (AI)-based models and researchers for radiotherapy organ slides. Finally, they were annotated by specialists.

RESULTS

The final dataset included 30,136 three-dimensional cone-beam computed tomography scans and 5,019 tabular data entries collected from 5,019 patients. It comprised 2,043,162 Digital Imaging and Communications in Medicine-format files with a total file size of 832 GB. Quality verification of the data using AI models revealed high classification performance for most organs, with relatively poor performance for the rectum. Overall, the macro AUROC value was 0.947.

CONCLUSIONS

This study implemented an automated data pipeline and AI-based verification to enhance the quality of collected radiotherapy data. The constructed dataset can be utilized for various types of future research and is expected to contribute to the improvement of radiotherapy efficiency.

Proof of concept of fully automated adaptive workflow for head and neck radiotherapy treatments with a conventional linear accelerator

Introduction

The objective of this study is to evaluate the performance of an automatic workflow for head-and-neck (H&N) radiotherapy using a multi-atlas based auto-contouring software and an a-priori multicriteria plan optimization algorithm and implement an adaptive online approach with CBCT images. Two different modalities are investigated, the fluence-to-position (FTP) and the adapt-to-shape (ATS) approach.

Materials and methods

Nine patients are used for the multi-atlas database. The organs at risk (OARs) of the H&N district and five additional structures (air, fat, tissue, bone and patient's exterior) subsequently used for the creation of the synthetic CT are auto-contoured with the Elekta ADMIRE® software. The mCycle algorithm is used for the a-priori multicriteria plan calculation. A total of twenty H&N patients are selected for this step. The automatic plans are compared to manual VMAT plans by assessing differences in planning time, dose delivered to targets and OARs, and calculating the plan quality indexes (PQIs). Two patients are chosen for the retrospective CBCT adaptive online feasibility analysis. To assess the differences for the two adaptive modalities, the clinical goals for targets and OARs and the number of passed constraints are explored. An analysis of the timing for the different steps is carried out to assess its clinical applicability.

Result

The dice of the five HU layer structures range between 0.66 and 0.99. The mCycle auto-planning significantly reduces planning time, from 2 hours to 10 minutes. The radiotherapist deems all plans clinically acceptable, and in the majority of cases the automatic plan is the preference choice. The automatic plans enhance OARs sparing and preserve a good target coverage, this is also confirmed by the PQIs result. Comparing FTP and ATS modes in adaptive radiotherapy, ATS exhibits superior outcomes, mostly in the target coverage. In the FTP techniques target coverage is inadequate and statistically different from the accepted values. In the ATS the results align with the initial approved values. Using the ATS mode the planning time takes around 14 minutes and approximately 20 minutes for the entire treatment.

Conclusion

This study contributes to the advancement of automatic and adaptive radiotherapy, demonstrating the potential of an automated workflow in H&N treatments.

Daily CBCT-based dose calculations for enhancing the safety of dose-escalation in lung cancer radiotherapy

PURPOSE

Dose-escalation in lung cancer comes with a high risk of severe toxicity. This study aimed to calculate the delivered dose in a Scandinavian phase-III dose-escalation trial.

METHODS

The delivered dose was evaluated for 21 locally-advanced non-small cell lung cancer (LA-NSCLC) patients treated as part of the NARLAL2 dose-escalation trial. The patients were randomized between standard and escalated heterogeneous dose-delivery. Both treatment plans were created and approved before randomization. Daily cone-beam CT (CBCT) for patient positioning, and adaptive radiotherapy were mandatory. Standard and escalated plans, including adaptive re-plans, were recalculated on each daily CBCT and accumulated on the planning CT for each patient. Dose to the clinical target volume (CTV), organs at risk (OAR), and the effects of plan adaptions were evaluated for the accumulated dose and on each treated fraction scaled to full treatment.

RESULTS

For the standard treatment, plan adaptations reduced the number of patients with CTV-T underdosage from six to one, and the total number of fractions with CTV-T underdosage from 161 to 56; while for the escalated treatment, the number of patients was reduced from five to zero and number of fractions from 81 to 11. For dose-escalation, three patients had fractions exceeding trial constraints for heart, bronchi, or esophagus, and one had an accumulated heart dose above the constraints.

CONCLUSION

Dose-escalation for LA-NSCLC patients, using daily image guidance and adaptive radiotherapy, is dosimetrically safe for the majority of patients. Dose calculation on daily CBCTs is an efficient tool to monitor target coverage and OAR doses.

Exploring dual energy CT synthesis in CBCT-based adaptive radiotherapy and proton therapy: application of denoising diffusion probabilistic models

Background.Adaptive radiotherapy (ART) requires precise tissue characterization to optimize treatment plans and enhance the efficacy of radiation delivery while minimizing exposure to organs at risk. Traditional imaging techniques such as cone beam computed tomography (CBCT) used in ART settings often lack the resolution and detail necessary for accurate dosimetry, especially in proton therapy.Purpose.This study aims to enhance ART by introducing an innovative approach that synthesizes dual-energy computed tomography (DECT) images from CBCT scans using a novel 3D conditional denoising diffusion probabilistic model (DDPM) multi-decoder. This method seeks to improve dose calculations in ART planning, enhancing tissue characterization.Methods.We utilized a paired CBCT-DECT dataset from 54 head and neck cancer patients to train and validate our DDPM model. The model employs a multi-decoder Swin-UNET architecture that synthesizes high-resolution DECT images by progressively reducing noise and artifacts in CBCT scans through a controlled diffusion process.Results.The proposed method demonstrated superior performance in synthesizing DECT images (High DECT MAE 39.582 ± 0.855 and Low DECT MAE 48.540± 1.833) with significantly enhanced signal-to-noise ratio and reduced artifacts compared to traditional GAN-based methods. It showed marked improvements in tissue characterization and anatomical structure similarity, critical for precise proton and radiation therapy planning.Conclusions.This research has opened a new avenue in CBCT-CT synthesis for ART/APT by generating DECT images using an enhanced DDPM approach. The demonstrated similarity between the synthesized DECT images and ground truth images suggests that these synthetic volumes can be used for accurate dose calculations, leading to better adaptation in treatment planning.

Supervised deep learning-based synthetic computed tomography from kilovoltage cone-beam computed tomography images for adaptive radiation therapy in head and neck cancer

PURPOSE

To generate and investigate a supervised deep learning algorithm for creating synthetic computed tomography (sCT) images from kilovoltage cone-beam computed tomography (kV-CBCT) images for adaptive radiation therapy (ART) in head and neck cancer (HNC).

MATERIALS AND METHODS

This study generated the supervised U-Net deep learning model using 3,491 image pairs from planning computed tomography (pCT) and kV-CBCT datasets obtained from 40 HNC patients. The dataset was split into 80% for training and 20% for testing. The evaluation of the sCT images compared to pCT images focused on three aspects: Hounsfield units accuracy, assessed using mean absolute error (MAE) and root mean square error (RMSE); image quality, evaluated using the peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM) between sCT and pCT images; and dosimetric accuracy, encompassing 3D gamma passing rates for dose distribution and percentage dose difference.

RESULTS

MAE, RMSE, PSNR, and SSIM showed improvements from their initial values of 53.15 ± 40.09, 153.99 ± 79.78, 47.91 ± 4.98 dB, and 0.97 ± 0.02 to 41.47 ± 30.59, 130.39 ± 78.06, 49.93 ± 6.00 dB, and 0.98 ± 0.02, respectively. Regarding dose evaluation, 3D gamma passing rates for dose distribution within sCT images under 2%/2 mm, 3%/2 mm, and 3%/3 mm criteria, yielded passing rates of 92.1% ± 3.8%, 93.8% ± 3.0%, and 96.9% ± 2.0%, respectively. The sCT images exhibited minor variations in the percentage dose distribution of the investigated target and structure volumes. However, it is worth noting that the sCT images exhibited anatomical variations when compared to the pCT images.

CONCLUSION

These findings highlight the potential of the supervised U-Net deep learningmodel in generating kV-CBCT-based sCT images for ART in patients with HNC.

Comparative analysis of delivered and planned doses in target volumes for lung stereotactic ablative radiotherapy

BACKGROUND

Adaptive therapy has been enormously improved based on the art of generating adaptive computed tomography (ACT) from planning CT (PCT) and the on-board image used for the patient setup. Exploiting the ACT, this study evaluated the dose delivered to patients with non-small-cell lung cancer (NSCLC) patients treated with stereotactic ablative radiotherapy (SABR) and derived relationship between the delivered dose and the parameters obtained through the evaluation procedure.

METHODS

SABR treatment records of 72 patients with NSCLC who were prescribed a dose of 60 Gy (Dprescribed) to the 95% volume of the planning target volume (PTV) in four fractions were analysed in this retrospective study; 288 ACTs were generated by rigid and deformable registration of a PCT to a cone-beam computed tomography (CBCT) per fraction. Each ACT was sent to the treatment planning system (TPS) and treated as an individual PCT to calculate the dose. Delivered dose to a patient was estimated by averaging four doses calculated from four ACTs per treatment. Through the process, each ACT provided the geometric parameters, such as mean displacement of the deformed PTV voxels (Warpmean) and Dice similarity coefficient (DSC) from deformation vector field, and dosimetric parameters, e.g. difference of homogeneity index (ΔHI, HI defined as (D2%-D98%)/Dprescribed*100) and mean delivered dose to the PTV (Dmean), obtained from the dose statistics in the TPS. Those parameters were analyzed using multiple linear regression and one-way-ANOVA of SPSS® (version 27).

RESULTS

The prescribed dose was confirmed to be fully delivered to internal target volume (ITV) within maximum difference of 1%, and the difference between the planned and delivered doses to the PTV was agreed within 6% for more than 95% of the ACT cases. Volume changes of the ITV during the treatment course were observed to be minor in comparison of their standard deviations. Multiple linear regression analysis between the obtained parameters and the dose delivered to 95% volume of the PTV (D95%) revealed four PTV parameters [Warpmean, DSC, ΔHI between the PCT and ACT, Dmean] and the PTV D95% to be significantly related with P-values < 0.05. The ACT cases of high ΔHI were caused by higher values of the Warpmean and DSC from the deformable image registration, resulting in lower PTV D95% delivered. The mean values of PTV D95% and Warpmean showed significant differences depending on the lung lobe where the tumour was located.

CONCLUSIONS

Evaluation of the dose delivered to patients with NSCLC treated with SABR using ACTs confirmed that the prescribed dose was accurately delivered to the ITV. However, for the PTV, certain ACT cases characterised by high HI deviations from the original plan demonstrated variations in the delivered dose. These variations may potentially arise from factors such as patient setup during treatment, as suggested by the statistical analyses of the parameters obtained from the dose evaluation process.

Stereotactic Body Radiation Therapy (SBRT) in prostate cancer in the presence of hip prosthesis - is it a contraindication? A narrative review

Hip replacement is a common orthopedic surgery in the aging population. With the rising incidence of prostate cancer, metallic hip prosthetics can cause considerable beam hardening and streak artifacts, leading to difficulty in identifying the target volumes and planning process for radiation treatment. The growing use of Stereotactic Body Radiation Therapy (SBRT) to treat prostate cancer is now well established. However, the use of this treatment modality in the presence of a hip prosthesis is poorly understood. There is enough literature on planning for external beam radiation treatment without any difficulties in the presence of hip prosthesis with conventional or Hypofractionated treatment. However, there is a shortage of literature on the impact of the prosthesis in SBRT planning, and there is a need for further understanding and measures to mitigate the obstacles in planning for SBRT in the presence of hip prosthesis. We present our review of the intricacies that need to be understood while considering SBRT in the presence of hip prostheses in prostate cancer treatment.

A treatment-site-specific evaluation of commercial synthetic computed tomography solutions for proton therapy

Background and purpose

Despite the superior dose conformity of proton therapy, the dose distribution is sensitive to daily anatomical changes, which can affect treatment accuracy. This study evaluated the dose recalculation accuracy of two synthetic computed tomography (sCT) generation algorithms in a commercial treatment planning system.

Materials and methods

The evaluation was conducted for head-and-neck, thorax-and-abdomen, and pelvis sites treated with proton therapy. Thirty patients with two cone-beam computed tomography (CBCT) scans each were selected. The sCT images were generated from CBCT scans using two algorithms, Corrected CBCT (corrCBCT) and Virtual CT (vCT). Dose recalculations were performed based on these images for comparison with "ground truth" deformed CTs.

Results

The choice of algorithm influenced dose recalculation accuracy, particularly in high dose regions. For head-and-neck cases, the corrCBCT method showed closer agreement with the "ground truth", while for thorax-and-abdomen and pelvis cases, the vCT algorithm yielded better results (mean percentage dose discrepancy of 0.6 %, 1.3 % and 0.5 % for the three sites, respectively, in the high dose region). Head-and-neck and pelvis cases exhibited excellent agreement in high dose regions (2 %/2 mm gamma passing rate >98 %), while thorax-and-abdomen cases exhibited the largest differences, suggesting caution in sCT algorithm usage for this site. Significant systematic differences were observed in the clinical target volume and organ-at-risk doses in head-and-neck and pelvis cases, highlighting the importance of using the correct algorithm.

Conclusions

This study provided treatment site-specific recommendations for sCT algorithm selection in proton therapy. The findings offered insights for proton beam centers implementing adaptive radiotherapy workflows.

2D antiscatter grid and scatter sampling based CBCT method for online dose calculations during CBCT guided radiation therapy of pelvis

BACKGROUND

Online dose calculations before the delivery of radiation treatments have applications in dose delivery verification, online adaptation of treatment plans, and simulation-free treatment planning. While dose calculations by directly utilizing CBCT images are desired, dosimetric accuracy can be compromised due to relatively lower HU accuracy in CBCT images.

PURPOSE

In this work, we propose a novel CBCT imaging pipeline to enhance the accuracy of CBCT-based dose calculations in the pelvis region. Our approach aims to improve the HU accuracy in CBCT images, thereby improving the overall accuracy of CBCT-based dose calculations prior to radiation treatment delivery.

METHODS

An in-house developed quantitative CBCT pipeline was implemented to address the CBCT raw data contamination problem. The pipeline combines algorithmic data correction strategies and 2D antiscatter grid-based scatter rejection to achieve high CT number accuracy. To evaluate the effect of the quantitative CBCT pipeline on CBCT-based dose calculations, phantoms mimicking pelvis anatomy were scanned using a linac-mounted CBCT system, and a gold standard multidetector CT used for treatment planning (pCT). A total of 20 intensity-modulated treatment plans were generated for five targets, using 6 and 10 MV flattening filter-free beams, and utilizing small and large pelvis phantom images. For each treatment plan, four different dose calculations were performed using pCT images and three CBCT imaging configurations: quantitative CBCT, clinical CBCT protocol, and a high-performance 1D antiscatter grid (1D ASG). Subsequently, dosimetric accuracy was evaluated for both targets and organs at risk as a function of patient size, target location, beam energy, and CBCT imaging configuration.

RESULTS

When compared to the gold-standard pCT, dosimetric errors in quantitative CBCT-based dose calculations were not significant across all phantom sizes, beam energies, and treatment sites. The largest error observed was 0.6% among all dose volume histogram metrics and evaluated dose calculations. In contrast, dosimetric errors reached up to 7% and 97% in clinical CBCT and high-performance ASG CBCT-based treatment plans, respectively. The largest dosimetric errors were observed in bony targets in the large phantom treated with 6 MV beams. The trends of dosimetric errors in organs at risk were similar to those observed in the targets.

CONCLUSIONS

The proposed quantitative CBCT pipeline has the potential to provide comparable dose calculation accuracy to the gold-standard planning CT in photon radiation therapy for the abdomen and pelvis. These robust dose calculations could eliminate the need for density overrides in CBCT images and enable direct utilization of CBCT images for dose delivery monitoring or online treatment plan adaptations before the delivery of radiation treatments.

Ultra-hypofractionated prostate cancer radiotherapy: Dosimetric impact of real-time intrafraction prostate motion and daily anatomical changes

PURPOSE

To retrospectively assess the differences between planned and delivered dose during ultra-hypofractionated (UHF) prostate cancer treatments, by evaluating the dosimetric impact of daily anatomical variations alone, and in combination with prostate intrafraction motion.

METHODS

Prostate intrafraction motion was recorded with a transperineal ultrasound probe in 15 patients treated by UHF radiotherapy (36.25 Gy/5 fractions). The dosimetric objective was to cover 99 % of the clinical target volume with the 100 % prescription isodose line. After treatment, planning CT (pCT) images were deformably registered onto daily Cone Beam CT to generate pseudo-CT for dose accumulation (accumulated CT, aCT). The interplay effect was accounted by synchronizing prostatic shifts and beam geometry. Finally, the shifted dose maps were accumulated (moved-accumulated CT, maCT).

RESULTS

No significant change in daily CTV volumes was observed. Conversely, CTV V100% was 98.2 ± 0.8 % and 94.7 ± 2.6 % on aCT and maCT, respectively, compared with 99.5 ± 0.2 % on pCT (p < 0.0001). Bladder volume was smaller than planned in 76 % of fractions and D5cc was 33.8 ± 3.2 Gy and 34.4 ± 3.4 Gy on aCT (p = 0.02) and maCT (p = 0.01) compared with the pCT (36.0 ± 1.1 Gy). The rectum was smaller than planned in 50.3 % of fractions, but the dosimetric differences were not statistically significant, except for D1cc, found smaller on the maCT (33.2 ± 3.2 Gy, p = 0.02) compared with the pCT (35.3 ± 0.7 Gy).

CONCLUSIONS

Anatomical variations and prostate movements had more important dosimetric impact than anatomical variations alone, although, in some cases, the two phenomena compensated. Therefore, an efficient IGRT protocol is required for treatment implementation to reduce setup errors and control intrafraction motion.

Evaluation of a cone-beam computed tomography system calibrated for accurate radiotherapy dose calculation

Background and purpose

Dose calculation on cone-beam computed tomography (CBCT) images has been less accurate than on computed tomography (CT) images due to lower image quality and discrepancies in CT numbers for CBCT. As increasing interest arises in offline and online re-planning, dose calculation accuracy was evaluated for a novel CBCT imager integrated into a ring gantry treatment machine.

Materials and methods

The new CBCT system allowed fast image acquisition (5.9 s) by using new hardware, including a large-size flat panel detector, and incorporated image-processing algorithms with iterative reconstruction techniques, leading to accurate CT numbers allowing dose calculation. In this study, CBCT- and CT-based dose calculations were compared based on three anthropomorphic phantoms, after CBCT-to-mass-density calibration was performed. Six plans were created on the CT scans covering various target locations and complexities, followed by CBCT to CT registrations, copying of contours, and re-calculation of the plans on the CBCT scans. Dose-volume histogram metrics for target volumes and organs-at-risk (OARs) were evaluated, and global gamma analyses were performed.

Results

Target coverage differences were consistently below 1.2 %, demonstrating the agreement between CT and re-calculated CBCT dose distributions. Differences in Dmean for OARs were below 0.5 Gy for all plans, except for three OARs, which were below 0.8 Gy (<1.1 %). All plans had a 3 %/1mm gamma pass rate > 97 %.

Conclusions

This study demonstrated comparable results between dose calculations performed on CBCT and CT acquisitions. The new CBCT system with enhanced image quality and CT number accuracy opens possibilities for off-line and on-line re-planning.

Evaluation of a novel CBCT conversion method implemented in a treatment planning system

BACKGROUND

To evaluate a novel CBCT conversion algorithm for dose calculation implemented in a research version of a treatment planning system (TPS).

METHODS

The algorithm was implemented in a research version of RayStation (v. 11B-DTK, RaySearch, Stockholm, Sweden). CBCTs acquired for each ten head and neck (HN), gynecology (GYN) and lung cancer (LNG) patients were collected and converted using the new algorithm (CBCTc). A bulk density overriding technique implemented in the same version of the TPS was used for comparison (CBCTb). A deformed CT (dCT) was created by using deformable image registration of the planning CT (pCT) to the CBCT to reduce anatomical changes. All treatment plans were recalculated on the pCT, dCT, CBCTc and the CBCTb. The resulting dose distributions were analyzed using the MICE toolkit (NONPIMedical AB Sweden, Umeå) with local gamma analysis, with 1% dose difference and 1 mm distance to agreement criteria. A Wilcoxon paired rank sum test was applied to test the differences in gamma pass rates (GPRs). A p value smaller than 0.05 considered statistically significant.

RESULTS

The GPRs for the CBCTb method were systematically lower compared to the CBCTc method. Using the 10% dose threshold and the dCT as reference the median GPRs were for the CBCTc method were 100% and 99.8% for the HN and GYN cases, respectively. Compared to that the GPRs of the CBCTb method were lower with values of 99.8% and 98.0%, for the HN and GYN cases, respectively. The GPRs of the LNG cases were 99.9% and 97.5% for the CBCTc and CBCTb method, respectively. These differences were statistically significant. The main differences between the dose calculated on the CBCTs and the pCTs were found in regions near air/tissue interfaces, which are also subject to anatomical variations.

CONCLUSION

The dose distribution calculated using the new CBCTc method showed excellent agreement with the dose calculated using dCT and pCT and was superior to the CBCTb method. The main reasons for deviations of the calculated dose distribution were caused by anatomical variations between the pCT and the corrected CBCT.

Evaluation of morphological changes based on cone beam CT for adaptive radiotherapy

BACKGROUND

During radiotherapy treatment, morphological changes can occur in patients (as weight loss). This can lead to significant dosimetric consequences on target volumes and/or organs at risk. The process of adaptive radiotherapy can compensate for these variations. Its deployment in the clinic is slowed by the considerable additional workload for the medical teams. The need for a tool facilitating the detection of patients whose treatment plans need adaptation has been clearly expressed in clinical practice, hence the usefulness of studying the impact of these morphological changes before the decision of adaptive radiotherapy.

METHODS

We considered the cases of 26 patients treated for pelvic cancer where CBCT (Cone Beam Computed Tomography) repositioning images were used. These images have undergone pre-processing to improve their quality and obtain a more precise registration using seven algorithms. We compared the results obtained in order to choose the most adequate algorithm allowing the calculation of external morphological differences using similarity metrics, such as DSC, NCC, MI and TC.

RESULTS

In this study, we showed that the "rigid body" algorithm, based on the rigid registration, gives the best results. The conservation of external contours allowed quantification of the variation in the external volumes of the patients. The obtained variations were on average (6.12±1.69)% and (4.36±1.22)% for rectum and prostate cancers, respectively.

CONCLUSION

Morphological changes evaluated in this study may influence the quality of patient treatment; hence the need for adaptive radiotherapy to take these variations into consideration. However, a rigorous evaluation of the dosimetric impact of these morphological variations is necessary to determine decision criteria for treatment plan adaptation.

Scatter correction of 4D cone beam computed tomography to detect dosimetric effects due to anatomical changes in proton therapy for lung cancer

BACKGROUND

The treatment of moving tumor entities is expected to have superior clinical outcomes, using image-guided adaptive intensity-modulated proton therapy (IMPT).

PURPOSE

For 21 lung cancer patients, IMPT dose calculations were performed on scatter-corrected 4D cone beam CTs (4DCBCTcor ) to evaluate their potential for triggering treatment adaptation. Additional dose calculations were performed on corresponding planning 4DCTs and day-of-treatment 4D virtual CTs (4DvCTs).

METHODS

A 4DCBCT correction workflow, previously validated on a phantom, generates 4DvCT (CT-to-CBCT deformable registration) and 4DCBCTcor images (projection-based correction using 4DvCT as a prior) with 10 phase bins, using day-of-treatment free-breathing CBCT projections and planning 4DCT images as input. Using a research planning system, robust IMPT plans administering eight fractions of 7.5 Gy were created on a free-breathing planning CT (pCT) contoured by a physician. The internal target volume (ITV) was overridden with muscle tissue. Robustness settings for range and setup uncertainties were 3% and 6 mm, and a Monte Carlo dose engine was used. On every phase of planning 4DCT, day-of-treatment 4DvCT, and 4DCBCTcor , the dose was recalculated. For evaluation, image analysis as well as dose analysis were performed using mean error (ME) and mean absolute error (MAE) analysis, dose-volume histogram (DVH) parameters, and 2%/2-mm gamma pass rate analysis. Action levels (1.6% ITV D98 and 90% gamma pass rate) based on our previous phantom validation study were set to determine which patients had a loss of dosimetric coverage.

RESULTS

Quality enhancements of 4DvCT and 4DCBCTcor over 4DCBCT were observed. ITV D98% and bronchi D2% had its largest agreement for 4DCBCTcor -4DvCT, and the largest gamma pass rates (>94%, median 98%) were found for 4DCBCTcor -4DvCT. Deviations were larger and gamma pass rates were smaller for 4DvCT-4DCT and 4DCBCTcor -4DCT. For five patients, deviations were larger than the action levels, suggesting substantial anatomical changes between pCT and CBCT projections acquisition.

CONCLUSIONS

This retrospective study shows the feasibility of daily proton dose calculation on 4DCBCTcor for lung tumor patients. The applied method is of clinical interest as it generates up-to-date in-room images, accounting for breathing motion and anatomical changes. This information could be used to trigger replanning.

AAPM Task Group Report 307: Use of EPIDs for Patient-Specific IMRT and VMAT QA

PURPOSE

Electronic portal imaging devices (EPIDs) have been widely utilized for patient-specific quality assurance (PSQA) and their use for transit dosimetry applications is emerging. Yet there are no specific guidelines on the potential uses, limitations, and correct utilization of EPIDs for these purposes. The American Association of Physicists in Medicine (AAPM) Task Group 307 (TG-307) provides a comprehensive review of the physics, modeling, algorithms and clinical experience with EPID-based pre-treatment and transit dosimetry techniques. This review also includes the limitations and challenges in the clinical implementation of EPIDs, including recommendations for commissioning, calibration and validation, routine QA, tolerance levels for gamma analysis and risk-based analysis.

METHODS

Characteristics of the currently available EPID systems and EPID-based PSQA techniques are reviewed. The details of the physics, modeling, and algorithms for both pre-treatment and transit dosimetry methods are discussed, including clinical experience with different EPID dosimetry systems. Commissioning, calibration, and validation, tolerance levels and recommended tests, are reviewed, and analyzed. Risk-based analysis for EPID dosimetry is also addressed.

RESULTS

Clinical experience, commissioning methods and tolerances for EPID-based PSQA system are described for pre-treatment and transit dosimetry applications. The sensitivity, specificity, and clinical results for EPID dosimetry techniques are presented as well as examples of patient-related and machine-related error detection by these dosimetry solutions. Limitations and challenges in clinical implementation of EPIDs for dosimetric purposes are discussed and acceptance and rejection criteria are outlined. Potential causes of and evaluations of pre-treatment and transit dosimetry failures are discussed. Guidelines and recommendations developed in this report are based on the extensive published data on EPID QA along with the clinical experience of the TG-307 members.

CONCLUSION

TG-307 focused on the commercially available EPID-based dosimetric tools and provides guidance for medical physicists in the clinical implementation of EPID-based patient-specific pre-treatment and transit dosimetry QA solutions including intensity modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT) treatments.

Evaluating synthetic computed tomography images for adaptive radiotherapy decision making in head and neck cancer

Background and purpose

Adaptive radiotherapy (ART) decision-making benefits from dosimetric information to supplement image inspection when assessing the significance of anatomical changes. This study evaluated a dosimetry-based clinical decision workflow for ART utilizing deformable registration of the original planning computed tomography (CT) image to the daily Cone Beam CT (CBCT) to replace the need for a replan CT for dose estimation.

Materials and methods

We used 12 retrospective Head & Neck patient cases having a ground truth - a replan CT (rCT) in response to anatomical changes apparent in the daily CBCT - to evaluate the accuracy of dosimetric assessment conducted on synthetic CTs (sCT) generated by deforming the original planning CT Hounsfield Units to the daily CBCT anatomy.The original plan was applied to the sCT and dosimetric accuracy of the sCT was assessed by analyzing plan objectives for targets and organs-at-risk compared to calculations on the ground-truth rCT. Three commercial DIR algorithms were compared.

Results

For the best-performing algorithms, the majority of dose metrics calculated on the sCTs differed by less than 4 Gy (5.7% of 70 Gy prescription dose). An uncertainty of ±2.5 Gy (3.6% of 70 Gy prescription) is recommended as a conservative tolerance when evaluating dose metrics on sCTs for head and neck.

Conclusions

Synthetic CTs present a valuable addition to the adaptive radiotherapy workflow, and synthetic CT dose estimates can be effectively used in addition to the current practice of visually inspecting the overlay of the planning CT and CBCT to assess the significance of anatomical change.

Evaluating on-board kVCT- and MVCT-based dose calculation accuracy using a thorax phantom for helical tomotherapy treatments

Purpose.To evaluate the impact of CT number calibration and imaging parameter selection on dose calculation accuracy relative to the CT planning process in thoracic treatments for on-board helical CT imaging systems used in helical tomotherapy.Methods and Materials.Direct CT number calibrations were performed with appropriate protocols for each imaging system using an electron density phantom. Large volume and SBRT treatment plans were simulated and optimized for planning CT scans of an anthropomorphic thorax phantom and transferred to registered kVCT and MVCT scans of the phantom as appropriate. Relevant DVH metrics and dose-difference maps were used to evaluate and compare dose calculation accuracy relative to the planning CT based on a variation in imaging parameters applied for the on-board systems.Results.For helical kVCT scans of the thorax phantom, median differences in DVH parameters for the large volume treatment plan were less than ±1% with dose to the target volume either over- or underestimated depending on the imaging parameters utilized for CT number calibration and thorax phantom acquisition. For the lung SBRT plan calculated on helical kVCT scans, median dose differences were up to -2.7% with a more noticeable dependence on parameter selection. For MVCT scans, median dose differences for the large volume plan were within +2% with dose to the target overestimated regardless of the imaging protocol.Conclusion.Accurate dose calculations (median errors of <±1%) using a thorax phantom simulating realistic patient geometry and scatter conditions can be achieved with images acquired with a helical kVCT system on a helical tomotherapy unit. This accuracy is considerably improved relative to that achieved with the MV-based approach. In a clinical setting, careful consideration should be made when selecting appropriate kVCT imaging parameters for this process as dose calculation accuracy was observed to vary with both parameter selection and treatment type.

Dosimetric Impact of Intrafraction Prostate Motion and Interfraction Anatomical Changes in Dose-Escalated Linac-Based SBRT

The dosimetric impact of intrafraction prostate motion and interfraction anatomical changes and the effect of beam gating and motion correction were investigated in dose-escalated linac-based SBRT. Fifty-six gated fractions were delivered using a novel electromagnetic tracking device with a 2 mm threshold. Real-time prostate motion data were incorporated into the patient's original plan with an isocenter shift method. Delivered dose distributions were obtained by recalculating these motion-encoded plans on deformed CTs reflecting the patient's CBCT daily anatomy. Non-gated treatments were simulated using the prostate motion data assuming that no treatment interruptions have occurred. The mean relative dose differences between delivered and planned treatments were -3.0% [-18.5-2.8] for CTV D99% and -2.6% [-17.8-1.0] for PTV D95%. The median cumulative CTV coverage with 93% of the prescribed dose was satisfactory. Urethra sparing was slightly degraded, with the maximum dose increased by only 1.0% on average, and a mean reduction in the rectum and bladder doses was seen in almost all dose metrics. Intrafraction prostate motion marginally contributed in gated treatments, while in non-gated treatments, further deteriorations in the minimum target coverage and bladder dose metrics would have occurred on average. The implemented motion management strategy and the strict patient preparation regimen, along with other treatment optimization strategies, ensured no significant degradations of dose metrics in delivered treatments.

Dosimetric impact of deformable image registration using radiophotoluminescent glass dosimeters with a physical geometric phantom

PURPOSE

To study the dosimetry impact of deformable image registration (DIR) using radiophotoluminescent glass dosimeter (RPLD) and custom developed phantom with various inserts.

METHODS

The phantom was developed to facilitate simultaneous evaluation of geometric and dosimetric accuracy of DIR. Four computed tomography (CT) images of the phantom were acquired with four different configurations. Four volumetric modulated arc therapy (VMAT) plans were computed for different phantom. Two different patterns were applied to combination of four phantom configurations. RPLD dose measurement was combined between corresponding two phantom configurations. DIR-based dose accumulation was calculated between corresponding two CT images with two commercial DIR software and various DIR parameter settings, and an open source software. Accumulated dose calculated using DIR was then compared with measured dose using RPLD.

RESULTS

The mean ± standard deviation (SD) of dose difference was 2.71 ± 0.23% (range, 2.22%-3.01%) for tumor-proxy and 3.74 ± 0.79% (range, 1.56%-4.83%) for rectum-proxy. The mean ± SD of target registration error (TRE) was 1.66 ± 1.36 mm (range, 0.03-4.43 mm) for tumor-proxy and 6.87 ± 5.49 mm (range, 0.54-17.47 mm) for rectum-proxy. These results suggested that DIR accuracy had wide range among DIR parameter setting.

CONCLUSIONS

The dose difference observed in our study was 3% for tumor-proxy and within 5% for rectum-proxy. The custom developed physical phantom with inserts showed potential for accurate evaluation of DIR-based dose accumulation. The prospect of simultaneous evaluation of geometric and dosimetric DIR accuracy in a single phantom may be useful for validation of DIR for clinical use.

Dosimetric comparison of deformable image registration and synthetic CT generation based on CBCT images for organs at risk in cervical cancer radiotherapy

OBJECTIVE

Anatomical variations existing in cervical cancer radiotherapy treatment can be monitored by cone-beam computed tomography (CBCT) images. Deformable image registration (DIR) from planning CT (pCT) to CBCT images and synthetic CT (sCT) image generation based on CBCT are two methods for improving the quality of CBCT images. This study aims to compare the accuracy of these two approaches geometrically and dosimetrically in cervical cancer radiotherapy.

METHODS

In this study, 40 paired pCT-CBCT images were collected to evaluate the accuracy of DIR and sCT generation. The DIR method was based on a 3D multistage registration network that was trained with 150 paired pCT-CBCT images, and the sCT generation method was performed based on a 2D cycle-consistent adversarial network (CycleGAN) with 6000 paired pCT-CBCT slices for training. Then, the doses were recalculated with the CBCT, pCT, deformed pCT (dpCT) and sCT images by a GPU-based Monte Carlo dose code, ArcherQA, to obtain Dose_CBCT, Dose_pCT, Dose_dpCT and Dose_sCT. Organs at risk (OARs) included small intestine, rectum, bladder, spinal cord, femoral heads and bone marrow, CBCT and pCT contours were delineated manually, dpCT contours were propagated through deformation vector fields, sCT contours were auto-segmented and corrected manually.

RESULTS

The global gamma pass rate of Dose_sCT and Dose_dpCT was 99.66% ± 0.34%, while that of Dose_CBCT and Dose_dpCT was 85.92% ± 7.56% at the 1%/1 mm criterion and a low-dose threshold of 10%. Based on Dose_dpCT as uniform dose distribution, there were comparable errors in femoral heads and bone marrow for the dpCT and sCT contours compared with CBCT contours, while sCT contours had lower errors in small intestine, rectum, bladder and spinal cord, especially for those with large volume difference of pCT and CBCT.

CONCLUSIONS

For cervical cancer radiotherapy, the DIR method and sCT generation could produce similar precise dose distributions, but sCT contours had higher accuracy when the difference in planning CT and CBCT was large.

Daily dose evaluation based on corrected CBCTs for breast cancer patients: accuracy of dose and complication risk assessment

OBJECTIVES

The goal of this study is to validate different CBCT correction methods to select the superior method that can be used for dose evaluation in breast cancer patients with large anatomical changes treated with photon irradiation.

MATERIALS AND METHOD

Seventy-six breast cancer patients treated with a partial VMAT photon technique (70% conformal, 30% VMAT) were included in this study. All patients showed at least a 5 mm variation (swelling or shrinkage) of the breast on the CBCT compared to the planning-CT (pCT) and had a repeat-CT (rCT) for dose evaluation acquired within 3 days of this CBCT. The original CBCT was corrected using four methods: (1) HU-override correction (CBCT_HU), (2) analytical correction and conversion (CBCT_CC), (3) deep learning (DL) correction (CT_DL) and (4) virtual correction (CT_V). Image quality evaluation consisted of calculating the mean absolute error (MAE) and mean error (ME) within the whole breast clinical target volume (CTV) and the field of view of the CBCT minus 2 cm (CBCT-ROI) with respect to the rCT. The dose was calculated on all image sets using the clinical treatment plan for dose and gamma passing rate analysis.

RESULTS

The MAE of the CBCT-ROI was below 66 HU for all corrected CBCTs, except for the CBCT_HU with a MAE of 142 HU. No significant dose differences were observed in the CTV regions in the CBCT_CC, CT_DL and CT_v. Only the CBCT_HU deviated significantly (p < 0.01) resulting in 1.7% (± 1.1%) average dose deviation. Gamma passing rates were > 95% for 2%/2 mm for all corrected CBCTs.

CONCLUSION

The analytical correction and conversion, deep learning correction and virtual correction methods can be applied for an accurate CBCT correction that can be used for dose evaluation during the course of photon radiotherapy of breast cancer patients.

Technical note: Characterization of novel iterative reconstructed cone beam CT images for dose tracking and adaptive radiotherapy on L-shape linacs

BACKGROUND

Cone-beam computed tomography (CBCT) allows for patient setup and positioning, and potentially dose verification or adaptive replanning prior to each treatment delivery. Poor CBCT image quality due to scatter artifacts and patient motion has been a major limiting factor. A new image reconstruction algorithm was recently clinically implemented for improving image quality through iterative reconstruction (iCBCT).

PURPOSE

This study aims to characterize iCBCT image quality, establish image value (HU)-to-relative electron density (RED) calibration curves for dose calculation, and assess the dosimetric accuracy for different anatomical sites.

MATERIAL AND METHODS

Both conventional CBCT and iCBCT scans were acquired from a Varian TrueBeam On-Board Imager system. A Catphan 604 phantom was scanned to compare image quality between the traditional Feldkamp-Davis-Kress (FDK) and novel iterative reconstruction techniques. Computerized Imaging Reference Systems (CIRS) electron density phantom was used to construct site-specific HU-RED curves corresponding to various scan settings. The CIRS Dynamic Thorax phantom, Rando pelvis phantom, and BrainLab head phantom were used for assessing dosimetric accuracy calculated on iCBCT images, compared to that on traditional FDK-based CBCT images. All phantoms were scanned on a computed tomography (CT) to obtain baseline HU values for comparison.

RESULTS

Test results obtained from Catphan showed statistically significant improvement with iCBCT, compared to FDK CBCT. Average HU differences from the baseline CT values were improved to within ±30 HU for iCBCT, compared to FDK CBCT for phantom studies. Dose calculated on iCBCT for both phantoms and patient cases directly using baseline HU-RED calibration from CT showed 0.5%-2.0% accuracy from the baseline dose calculated on CT, which is comparable to doses calculated using site-specific HU-RED calibration curves.

CONCLUSION

iCBCT provides improved image quality, improved HU accuracy compared to CT baseline, and has potential to provide online dose verification as part of the adaptive radiotherapy workflow directly using the baseline HU-RED calibration curve from CT.

Assessment of CBCT-based synthetic CT generation accuracy for adaptive radiotherapy planning

PURPOSE

Cone-beam CT (CBCT)-based synthetic CT (sCT) dose calculation has the potential to make the adaptive radiotherapy (ART) pathway more efficient while removing subjectivity. This study assessed four sCT generation methods using 15 head-and-neck rescanned ART patients. Each patient's planning CT (pCT), rescan CT (rCT), and CBCT post-rCT was acquired with the CBCT deformably registered to the rCT (dCBCT).

METHODS

The four methods investigated were as follows: method 1-deformably registering the pCT to the dCBCT. Method 2-assigning six mass density values to the dCBCT. Method 3-iteratively removing artifacts and correcting the dCBCT Hounsfield units (HU). Method 4-using a cycle general adversarial network machine learning model (trained with 45 paired pCT and CBCT). Treatment plans were created on the rCT and recalculated on each sCT. Planning target volume (PTV) and organ-at-risk (OAR) structures were contoured by clinicians on the rCT (high-dose PTV, low-dose PTV, spinal canal, larynx, brainstem, and parotids) to allow the assessment of dose-volume histogram statistics at clinically relevant points.

RESULTS

The HU mean absolute error (MAE) and minimum dose gamma index pass rate (2%/2 mm) were calculated, and the generation time was measured for 15 patients using the rCT as the comparator. For methods 1-4 the MAE, gamma index analysis, and generation time were as follows: 59.7 HU, 100.0%, and 143 s; 164.2 HU, 95.2%, and 232 s; 75.7 HU, 99.9%, and 153 s; and 79.4 HU, 99.8%, and 112 s, respectively. Dose differences for PTVs and OARs were all <0.3 Gy except for method 2 (<0.5 Gy).

CONCLUSION

All methods were considered clinically viable. The machine learning method was found to be most suitable for clinical implementation due to its high dosimetric accuracy and short generation time. Further investigation is required for larger anatomical changes between the CBCT and pCT and for other anatomical sites.

Dosimetric Accuracy of MR-Guided Online Adaptive Planning for Nasopharyngeal Carcinoma Radiotherapy on 1.5 T MR-Linac

Purpose

The aim of this study is to evaluate the dose accuracy of bulk relative electron density (rED) approach for application in 1.5 T MR-Linac and assess the reliability of this approach in the case of online adaptive MR-guided radiotherapy for nasopharyngeal carcinoma (NPC) patients.

Methods

Ten NPC patients formerly treated on conventional linac were included in this study, with their original planning CT and MRI collected. For each patient, structures such as the targets, organs at risk, bone, and air regions were delineated on the original CT in the Monaco system (v5.40.02). To simulate the online adaptive workflow, firstly all contours were transferred to MRI from the original CT using rigid registration in the Monaco system. Based on the structures, three different types of synthetic CT (sCT) were generated from MRI using the bulk rED assignment approach: the sCT_ICRU uses the rED values recommended by ICRU46, the sCT_tailor uses the patient-specific mean rED values, and the sCT_Homogeneity uses homogeneous water equivalent values. The same treatment plan was calculated on the three sCTs and the original CT. Dose calculation accuracy was investigated in terms of gamma analysis, point dose comparison, and dose volume histogram (DVH) parameters.

Results

Good agreement of dose distribution was observed between sCT_tailor and the original CT, with a gamma passing rate (3%/3 mm) of 97.81% ± 1.06%, higher than that of sCT_ICRU (94.27% ± 1.48%, p = 0.005) and sCT_Homogeneity (96.50% ± 1.02%, p = 0.005). For stricter criteria 1%/1 mm, gamma passing rates for plans on sCT_tailor, sCT_ICRU, and sCT_Homogeneity were 86.79% ± 4.31%, 79.81% ± 3.63%, and 77.56% ± 4.64%, respectively. The mean point dose difference in PTV_nx between sCT_tailor and planning CT was −0.14% ± 1.44%, much lower than that calculated on sCT_ICRU (−8.77% ± 2.33%) and sCT_Homogeneity (1.65% ± 2.57%), all with p < 0.05. The DVH differences for the plan based on sCT_tailor were much smaller than sCT_ICRU and sCT_Homogeneity.

Conclusions

The bulk rED-assigned sCT by adopting the patient-specific rED values can achieve a clinically acceptable level of dose calculation accuracy in the presence of a 1.5 T magnetic field, making it suitable for online adaptive MR-guided radiotherapy for NPC patients.

Please Place Your Seat in the Full Upright Position: A Technical Framework for Landing Upright Radiation Therapy in the 21st Century

Delivering radiotherapy to patients in an upright position can allow for increased patient comfort, reduction in normal tissue irradiation, or reduction of machine size and complexity. This paper gives an overview of the requirements for the delivery of contemporary arc and modulated radiation therapy to upright patients. We explore i) patient positioning and immobilization, ii) simulation imaging, iii) treatment planning and iv) online setup and image guidance. Treatment chairs have been designed to reproducibly position seated patients for treatment and can be augmented by several existing immobilisation systems or promising emerging technologies such as soft robotics. There are few solutions for acquiring CT images for upright patients, however, cone beam computed tomography (CBCT) scans of upright patients can be produced using the imaging capabilities of standard Linacs combined with an additional patient rotation device. While these images will require corrections to make them appropriate for treatment planning, several methods indicate the viability of this approach. Treatment planning is largely unchanged apart from translating gantry rotation to patient rotation, allowing for a fixed beam with a patient rotating relative to it. Rotation can be provided by a turntable during treatment delivery. Imaging the patient with the same machinery as used in treatment could be advantageous for online plan adaption. While the current focus is using clinical linacs in existing facilities, developments in this area could also extend to lower-cost and mobile linacs and heavy ion therapy.

Evaluation of kV-CBCT based 3D dose calculation accuracy and its validation using delivery fluence derived dose metrics in Head and Neck Cancer

PURPOSE

The purpose of this study is to evaluate the dosimetric impact of Hounsfield unit (HU) variations in kilovoltage cone-beam computed tomography (kV-CBCT) based 3D dose calculation accuracy in the treatment planning system and its validation using measured treatment delivery dose (MTDD) derived dose metrics for Volumetric Modulated Arc Therapy (VMAT) and Intensity Modulated Radiotherapy (IMRT) plans in Head and Neck (HN) Cancer.

METHODS

CBCT dose calculation accuracy was evaluated for 8 VMAT plans on inhomogeneous phantom and 40 VMAT and IMRT plans of HN Cancer patients and validated using ArcCHECK diode array MTDD derived 3D dose metric on CT and CBCT.

RESULTS

The mean percentage dose difference between CBCT and CT in TPS (ΔD(CBCT-CT)_TPS) and 3DVH (ΔD(CBCT-CT)_3DVH) were compared for the corresponding evaluation dose metrics (D_98%, D_95%, D_50%, D_2%, D_max, D_1cc, D_0.03cc, D_mean) of all PTVs and OARs in phantom and patients. ΔD(CBCT-CT)_TPS and ΔD(CBCT-CT)_3DVH for all evaluation dose points of all PTVs and OARs were less than 2.55% in phantom and 2.4% in HN patients. The Pearson correlation coefficient (r) between ΔD(CBCT-CT)_TPS and ΔD(CBCT-CT)_3DVH for all dose points in all PTVs and OARs showed a strong to moderate correlation in phantom and patients with p < 0.001.

CONCLUSIONS

This study evaluated and validated the potential feasibility of kV-CBCT for treatment plan 3D dose reconstruction in clinical decision making for Adaptive radiotherapy on CT in Head and Neck cancer.

Clinical suitability of deep learning based synthetic CTs for adaptive proton therapy of lung cancer

Purpose

Adaptive proton therapy (APT) of lung cancer patients requires frequent volumetric imaging of diagnostic quality. Cone‐beam CT (CBCT) can provide these daily images, but x‐ray scattering limits CBCT‐image quality and hampers dose calculation accuracy. The purpose of this study was to generate CBCT‐based synthetic CTs using a deep convolutional neural network (DCNN) and investigate image quality and clinical suitability for proton dose calculations in lung cancer patients.

Methods

A dataset of 33 thoracic cancer patients, containing CBCTs, same‐day repeat CTs (rCT), planning‐CTs (pCTs), and clinical proton treatment plans, was used to train and evaluate a DCNN with and without a pCT‐based correction method. Mean absolute error (MAE), mean error (ME), peak signal‐to‐noise ratio, and structural similarity were used to quantify image quality. The evaluation of clinical suitability was based on recalculation of clinical proton treatment plans. Gamma pass ratios, mean dose to target volumes and organs at risk, and normal tissue complication probabilities (NTCP) were calculated. Furthermore, proton radiography simulations were performed to assess the HU‐accuracy of sCTs in terms of range errors.

Results

On average, sCTs without correction resulted in a MAE of 34 ± 6 HU and ME of 4 ± 8 HU. The correction reduced the MAE to 31 ± 4HU (ME to 2 ± 4HU). Average 3%/3 mm gamma pass ratios increased from 93.7% to 96.8%, when the correction was applied. The patient specific correction reduced mean proton range errors from 1.5 to 1.1 mm. Relative mean target dose differences between sCTs and rCT were below ± 0.5% for all patients and both synthetic CTs (with/without correction). NTCP values showed high agreement between sCTs and rCT (<2%).

Conclusion

CBCT‐based sCTs can enable accurate proton dose calculations for APT of lung cancer patients. The patient specific correction method increased the image quality and dosimetric accuracy but had only a limited influence on clinically relevant parameters.

Møller D, Assenholt MS, Hansen R, Nyvang L, Ravkilde T, Thomsen MS, Hoffmann L. Density calibrated cone beam CT as a tool for adaptive radiotherapy

BACKGROUND

Visual inspections of anatomical changes observed on daily cone-beam CT (CBCT) images are often used as triggers for radiotherapy plan adaptation to avoid unacceptable dose levels to the target or OARs. Direct CBCT dose calculations would improve the ability to adapt only those plans where dosimetric changes are observed. This study investigates the accuracy of dose calculations on CBCTs.

MATERIALS AND METHODS

Calibration curves were obtained for CBCT imagers at nine identical accelerators. CBCT scans of a phantom with different density inserts were recorded for two scan modes (Head-Neck and Pelvis) and mean calibration curves were calculated. Subsequently, CBCT scans of the phantom with six different density inserts were recorded, the dose distributions on the CBCTs were calculated and compared to dose on the planning CT (pCT). The uncertainty was quantified by the dosimetric difference between the pCT and the CBCT. The two mean calibration curves were used to calculate the daily delivered CBCT dose for ten Head-Neck-, eleven Lung-, and ten pelvic patients. Additional patient calculations were performed using low-HU empirically corrected calibration curves. Patient doses were compared on target coverage and mean dose, and D1cc for OARs.

RESULTS

The dose differences between pCT and CBCT for phantom data were small for all DVH parameters, with mean deviations below ±0.6% for both CBCT modes. For patient data, it was found that low-HU corrected calibration curves performed the best. The mean deviations for the mean dose and coverage of the target were 0.2%±0.7% and 0.1%±0.6%, across all patient groups.

CONCLUSION

Dose calculation on CBCT images results in target coverage and mean dose with an accuracy of the order of 1%, which makes this acceptable for clinical use. The CBCT mode specific calibration curves can be used at all identical imaging devices and for all patient groups.

Effect of computed tomography value error on dose calculation in adaptive radiotherapy with Elekta X-ray volume imaging cone beam computed tomography

Purpose

We evaluated the effect of changing the scan mode of the Elekta X‐ray volume imaging cone beam computed tomography (CBCT) on the accuracy of dose calculation, which may be affected by computed tomography (CT) value errors in three dimensions.

Methods

We used the electron density phantom and measured the CT values in three dimensions. CT values were compared with planning computed tomography (pCT) values for various materials. The evaluated scan modes were for head and neck (S‐scan), chest (M‐scan), and pelvis (L‐scan) with various collimators and filter systems. To evaluate the effects of the CT value error of the CBCT on dose error, Monte Carlo calculations of dosimetry were performed using pCT and CBCT images.

Results

The L‐scan had a CT value error of approximately 800 HU at the isocenter compared with the pCT. Furthermore, inhomogeneity in the longitudinal CT value profile was observed in the bone material. The dose error for ±100 HU difference in CT values for the S‐scan and M‐scan was within ±2%. The center of the L‐scan had a CT error of approximately 800 HU and a dose error of approximately 6%. The dose error of the L‐scan occurred in the beam path in the case of both single field and two parallel opposed fields, and the maximum error occurred at the center of the phantom in the case of both the 4‐field box and single‐arc techniques.

Conclusions

We demonstrated the three‐dimensional CT value characteristics of the CBCT by evaluating the CT value error obtained under various imaging conditions. It was found that the L‐scan is considerably affected by not having a unique bowtie filter, and the S‐scan without the bowtie filter causes CT value errors in the longitudinal direction. Moreover, the CBCT dose errors for the 4‐field box and single‐arc irradiation techniques converge to the isocenter.

A Deep Unsupervised Learning Model for Artifact Correction of Pelvis Cone-Beam CT

Purpose

In recent years, cone-beam computed tomography (CBCT) is increasingly used in adaptive radiation therapy (ART). However, compared with planning computed tomography (PCT), CBCT image has much more noise and imaging artifacts. Therefore, it is necessary to improve the image quality and HU accuracy of CBCT. In this study, we developed an unsupervised deep learning network (CycleGAN) model to calibrate CBCT images for the pelvis to extend potential clinical applications in CBCT-guided ART.

Methods

To train CycleGAN to generate synthetic PCT (sPCT), we used CBCT and PCT images as inputs from 49 patients with unpaired data. Additional deformed PCT (dPCT) images attained as CBCT after deformable registration are utilized as the ground truth before evaluation. The trained uncorrected CBCT images are converted into sPCT images, and the obtained sPCT images have the characteristics of PCT images while keeping the anatomical structure of CBCT images unchanged. To demonstrate the effectiveness of the proposed CycleGAN, we use additional nine independent patients for testing.

Results

We compared the sPCT with dPCT images as the ground truth. The average mean absolute error (MAE) of the whole image on testing data decreased from 49.96 ± 7.21HU to 14.6 ± 2.39HU, the average MAE of fat and muscle ROIs decreased from 60.23 ± 7.3HU to 16.94 ± 7.5HU, and from 53.16 ± 9.1HU to 13.03 ± 2.63HU respectively.

Conclusion

We developed an unsupervised learning method to generate high-quality corrected CBCT images (sPCT). Through further evaluation and clinical implementation, it can replace CBCT in ART.

Cone beam CT based validation of neural network generated synthetic CTs for radiotherapy in the head region

PURPOSE

In the past years, many different neural network-based conversion techniques for synthesizing computed tomographys (sCTs) from MR images have been published. While the model's performance can be checked during the training against the test set, test datasets can never represent the whole population. Conversion errors can still occur for special cases, for example, for unusual anatomical situations. Therefore, the performance of sCT conversion needs to be verified on a patient specific level, especially in the absence of a planning CT (pCT). In this study, the capability of cone-beam CTs (CBCTs) for the validation of sCTs generated by a neural network was investigated.

METHODS

41 patients with tumors in the head region were selected. 20 of them were used for model training and 10 for validation. Different implementations of CycleGAN (with/without identity and feature loss) were used to generate sCTs. The pixel (MAE, RMSE, PSNR) and geometric error (DICE, Sensitivity, Specificity) values were reported to identify the best model. VMAT plans were created for the remaining 11 patients on the pCTs. These plans were re-calculated on sCTs and CBCTs. An automatic density overriding method ( C B C T RS ) and a population-based dose calculation method ( C B C T Pop ) were employed for CBCT-based dose calculation. The dose distributions were analysed using 3D global gamma analysis, applying a threshold of 10% with respect to the prescribed dose. Differences in DVH metrics for the PTV and the organs-at-risk were compared among the dose distributions based on pCTs, sCTs, and CBCTs.

RESULTS

The best model was the CycleGAN without identity and feature matching loss. Including the identity loss led to a metric decrease of 10% for DICE and a metric increase of 20-60 HU for MAE. Using the 2%/2 mm gamma criterion and pCT as reference, the mean gamma pass rates were 99.0  ±  0.4% for sCTs. Mean gamma pass rate values comparing pCT and CBCT were 99.0  ±  0.8% and 99.1  ±  0.8% for the C B C T RS and C B C T Pop , respectively. The mean gamma pass rates comparing sCT and CBCT resulted in 98.4  ±  1.6% and 99.2  ±  0.6% for C B C T RS and C B C T Pop , respectively. The differences between the gamma-pass-rates of the sCT and two CBCT-based methods were not significant. The majority of deviations of the investigated DVH metrices between sCTs and CBCTs were within 2%.

CONCLUSION

The dosimetric results demonstrate good agreement between sCT, CBCT, and pCT based calculations. A properly applied CBCT conversion method can serve as a tool for quality assurance procedures in an MR only radiotherapy workflow for head patients. Dosimetric deviations of DVH metrics between sCT and CBCTs of larger than 2% should be followed up. A systematic shift of approximately 1% should be taken into account when using the C B C T RS approach in an MR only workflow.

Accuracy of dose calculation on iterative CBCT for head and neck radiotherapy

PURPOSE

To evaluate the feasibility of the use of iterative cone-beam computed tomography (CBCT) for dose calculation in the head and neck region.

METHODS

This study includes phantom and clinical studies. All acquired CBCT images were reconstructed with Feldkamp-Davis-Kress algorithm-based CBCT (FDK-CBCT) and iterative CBCT (iCBCT) algorithm. The Hounsfield unit (HU) consistency between the head and body phantoms was determined in both reconstruction techniques. Volumetric modulated arc therapy (VMAT) plans were generated for 16 head and neck patients on a planning CT scan, and the doses were recalculated on FDK-CBCT and iCBCT with Anisotropic Analytical Algorithm (AAA) and Acuros XB (AXB). As a comparison of the accuracy of dose calculations, the absolute dosimetric difference and 1%/1 mm gamma passing rate analysis were analyzed.

RESULTS

The difference in the mean HU values between the head and body phantoms was larger for FDK-CBCT (max value: 449.1 HU) than iCBCT (260.0 HU). The median dosimetric difference from the planning CT were <1.0% for both FDK-CBCT and iCBCT but smaller differences were found with iCBCT (planning target volume D_50%: 0.38% (0.15-0.59%) for FDK-CBCT, 0.28% (0.13-0.49%) for iCBCT, AAA; 0.14% (0.04-0.19%) for FDK-CBCT, 0.07% (0.02-0.20%) for iCBCT). The mean gamma passing rate was significantly better in iCBCT than FDK-CBCT (AAA: 98.7% for FDK-CBCT, 99.4% for iCBCT; AXB: 96.8% for FDK_CBCT, 97.5% for iCBCT).

CONCLUSION

The iCBCT-based dose calculation in VMAT for head and neck cancer was accurate compared to FDK-CBCT.

Evaluation of scatter rejection and correction performance of 2D antiscatter grids in cone beam computed tomography

PURPOSE

We have been investigating two-dimensional (2D) antiscatter grids (2D ASGs) to reduce scatter fluence and improve image quality in cone beam computed tomography (CBCT). In this work, two different aspects of 2D ASGs, their scatter rejection and correction capability, were investigated in CBCT experiments. To correct residual scatter transmitted through the 2D ASG, it was used as a scatter measurement device with a novel method: grid-based scatter sampling.

METHODS

Three focused 2D ASG prototypes with grid ratios of 8, 12, and 16 were developed for linac-mounted offset detector CBCT geometry. In the first phase, 2D ASGs were used as a scatter rejection device, and the effect of grid ratio on CT number accuracy and contrast-to-noise ratio (CNR) evaluated in CBCT images. In the second phase, a grid-based scatter sampling method which exploits the signal modulation characteristics of the 2D ASG's septal shadows to measure and correct residual scatter transmitted through the grid was implemented. To evaluate CT number accuracy, the percent change in CT numbers was measured by changing the phantom from head to pelvis size and configuration.

RESULTS

When 2D ASG was used as a scatter rejection device, CT number accuracy increased and the CT number variation due to change in phantom dimensions was reduced from 23% to 2-6%. A grid ratio of 16 yielded the lowest CT number variation. All three 2D ASGs yielded improvement in CNR, up to a factor of two in pelvis-sized phantoms. When 2D ASG prototypes were used for both scatter rejection and correction, CT number variations were reduced further, to 1.3-2.6%. In comparisons with a clinical CBCT system and a high-performance radiographic ASG, 2D ASG provided higher CT number accuracy under the same imaging conditions.

CONCLUSIONS

When 2D ASG is used solely as a scatter rejection device, substantial improvement in CT number accuracy can be achieved by increasing the grid ratio. Two-dimensional ASGs also provided significant CNR improvement even at lower grid ratios. Two-dimensional ASGs used in conjunction with the grid-based scatter sampling method provided further improvement in CT number accuracy, irrespective of the grid ratio, while preserving 2D ASGs' capacity to improve CNR. The combined effect of scatter rejection and residual scatter correction by 2D ASG may accelerate implementation of new techniques in CBCT that require high quantitative accuracy, such as radiotherapy dose calculation and dual energy CBCT.

Cone beam computed tomography for dose calculation quality assurance for magnetic resonance-only radiotherapy

•

Clinical Magnetic Resonance (MR)-only radiotherapy requires a dose quality assurance method.

•

Doses calculated on Cone Beam Computed Tomography (CBCT) were within 2% of MR-only doses calculated using synthetic CT.

•

CBCT with asymmetric dose difference tolerances of [−2%,1%] appears clinically feasible for quality assurance of prostate MR-only radiotherapy.

Background and purpose

Magnetic Resonance (MR)-only prostate radiotherapy using synthetic Computed Tomography (sCT) algorithms with high dose accuracy has been clinically implemented. MR images can suffer from geometric distortions so Quality Assurance (QA) using an independent, geometrically accurate, image could be required. The first-fraction Cone Beam CT (CBCT) has demonstrated potential but has not been evaluated in a clinical MR-only pathway. This study evaluated the clinical use of CBCT for dose accuracy QA of MR-only radiotherapy.

Materials and methods

A total of 49 patients treated with MR-only prostate radiotherapy were divided into two cohorts. Cohort 1 (20 patients) received a back-up CT, whilst Cohort 2 (29 patients) did not. All patients were planned using the sCT and received daily CBCT imaging with MR-CBCT soft-tissue matching. Each CBCT was calibrated using a patient-specific stepwise Hounsfield Units-to-mass density curve. The treatment plan was recalculated on the first-fraction CBCT using the clinically applied soft-tissue match and the doses compared. For Cohort 1 the sCT was rigidly registered to the back-up CT, the plan recalculated and doses compared.

Results

Mean sCT-CBCT dose difference across both cohorts was -0.6±0.1% (standard error of the mean, range −2.3%,2.3%), with 47/49 patients within [-2%,1%]. The sCT-CBCT dose difference was systematically lower than the sCT-CT by -0.7±0.6% (±95% limits of agreement). The mean sCT-CBCT gamma pass rate (2%/2mm) was 96.1±0.4% (85.4%,99.7%).

Conclusions

CBCT-based dose accuracy QA for MR-only radiotherapy appears clinically feasible. There was a small systematic sCT-CBCT dose difference implying asymmetric tolerances of [-2%,1%] would be appropriate.

Evaluation of a cycle-generative adversarial network-based cone-beam CT to synthetic CT conversion algorithm for adaptive radiation therapy

PURPOSE

Image-guided radiation therapy could benefit from implementing adaptive radiation therapy (ART) techniques. A cycle-generative adversarial network (cycle-GAN)-based cone-beam computed tomography (CBCT)-to-synthetic CT (sCT) conversion algorithm was evaluated regarding image quality, image segmentation and dosimetric accuracy for head and neck (H&N), thoracic and pelvic body regions.

METHODS

Using a cycle-GAN, three body site-specific models were priorly trained with independent paired CT and CBCT datasets of a kV imaging system (XVI, Elekta). sCT were generated based on first-fraction CBCT for 15 patients of each body region. Mean errors (ME) and mean absolute errors (MAE) were analyzed for the sCT. On the sCT, manually delineated structures were compared to deformed structures from the planning CT (pCT) and evaluated with standard segmentation metrics. Treatment plans were recalculated on sCT. A comparison of clinically relevant dose-volume parameters (D₉₈, D₅₀ and D₂ of the target volume) and 3D-gamma (3%/3mm) analysis were performed.

RESULTS

The mean ME and MAE were 1.4, 29.6, 5.4 Hounsfield units (HU) and 77.2, 94.2, 41.8 HU for H&N, thoracic and pelvic region, respectively. Dice similarity coefficients varied between 66.7 ± 8.3% (seminal vesicles) and 94.9 ± 2.0% (lungs). Maximum mean surface distances were 6.3 mm (heart), followed by 3.5 mm (brainstem). The mean dosimetric differences of the target volumes did not exceed 1.7%. Mean 3D gamma pass rates greater than 97.8% were achieved in all cases.

CONCLUSIONS

The presented method generates sCT images with a quality close to pCT and yielded clinically acceptable dosimetric deviations. Thus, an important prerequisite towards clinical implementation of CBCT-based ART is fulfilled.

Anthropomorphic lung phantom based validation of in-room proton therapy 4D-CBCT image correction for dose calculation

PURPOSE

Ventilation-induced tumour motion remains a challenge for the accuracy of proton therapy treatments in lung patients. We investigated the feasibility of using a 4D virtual CT (4D-vCT) approach based on deformable image registration (DIR) and motion-aware 4D CBCT reconstruction (MA-ROOSTER) to enable accurate daily proton dose calculation using a gantry-mounted CBCT scanner tailored to proton therapy.

METHODS

Ventilation correlated data of 10 breathing phases were acquired from a porcine ex-vivo functional lung phantom using CT and CBCT. 4D-vCTs were generated by (1) DIR of the mid-position 4D-CT to the mid-position 4D-CBCT (reconstructed with the MA-ROOSTER) using a diffeomorphic Morphons algorithm and (2) subsequent propagation of the obtained mid-position vCT to the individual 4D-CBCT phases. Proton therapy treatment planning was performed to evaluate dose calculation accuracy of the 4D-vCTs. A robust treatment plan delivering a nominal dose of 60Gy was generated on the average intensity image of the 4D-CT for an approximated internal target volume (ITV). Dose distributions were then recalculated on individual phases of the 4D-CT and the 4D-vCT based on the optimized plan. Dose accumulation was performed for 4D-vCT and 4D-CT using DIR of each phase to the mid position, which was chosen as reference. Dose based on the 4D-vCT was then evaluated against the dose calculated on 4D-CT both, phase-by-phase as well as accumulated, by comparing dose volume histogram (DVH) values (D_mean, D_2%, D_98%, D_95%) for the ITV, and by a 3D-gamma index analysis (global, 3%/3mm, 5Gy, 20Gy and 30Gy dose thresholds).

RESULTS

Good agreement was found between the 4D-CT and 4D-vCT-based ITV-DVH curves. The relative differences ((CT-vCT)/CT) between accumulated values of ITV D_mean, D_2%, D_95% and D_98% for the 4D-CT and 4D-vCT-based dose distributions were -0.2%, 0.0%, -0.1% and -0.1%, respectively. Phase specific values varied between -0.5% and 0.2%, -0.2% and 0.5%, -3.5% and 1.5%, and -5.7% and 2.3%. The relative difference of accumulated D_mean over the lungs was 2.3% and D_mean for the phases varied between -5.4% and 5.8%. The gamma pass-rates with 5Gy, 20Gy and 30Gy thresholds for the accumulated doses were 96.7%, 99.6% and 99.9%, respectively. Phase-by-phase comparison yielded pass-rates between 86% and 97%, 88% and 98%, and 94% and 100%.

CONCLUSIONS

Feasibility of the suggested 4D-vCT workflow using proton therapy specific imaging equipment was shown. Results indicate the potential of the method to be applied for daily 4D proton dose estimation.

Comparison of CBCT conversion methods for dose calculation in the head and neck region

The purpose of this study was to compare different methods of CBCT conversion respect to dose calculation accuracy. Twelve head and neck cancer patients treated with VMAT using simultaneous integrated boost technique were selected for the study. For each patient a planning CT (pCT), a control. CT acquired in the fourth week of treatment and a CBCT scan acquired on the closest day with the control CT were used. In order to re-calculate dose directly on CBCT image sets, a population based approach (CBCTPop) and a Histogram Matching (HM) approach based on rigid (CBCTHM-R) and deformable registration (CBCTHM-D) were used. Additionally, virtual CTs (vCTs) were generated using two deformable image registration algorithms (CTELX and CTANC) of the planning CT to the CBCT by using two different deformable image registration (DIR) algorithms. The corresponding control CTs were selected as ground truth and dose distributions on CBCT were analyzed using 3D global gamma index analysis applying a threshold of 10% with respect to the prescribed dose. Using the 2%/2mm gamma criterion, the results were 89.9%(±8.3%), 94.1%(±5.0%), 94.3%(±5.7%), 96.1%(±3.9%), 93.4%(±6.3%) for the CBCTPop, CBCTHM-R, CBCTHM-D, CTELX and CTANC, respectively. On average, the HM and DIR techniques showed a higher accuracy compared to the population based approach, but Kruskal-Wallis test did not show significant difference among the investigated dose calculation techniques assuming p<0.05. More sophisticated CBCT dose calculation methods seem to improve the dose calculation accuracy, but statistical significance remains to be demonstrated.

Investigating the use of virtual 4DCT from 4DMRI in gated carbon ion radiation therapy of abdominal tumors

PURPOSE

To generate virtual 4DCT from 4DMRI with field of view (FOV) extended to the entire involved patient anatomy, in order to evaluate its use in carbon ion radiation therapy (CIRT) of the abdominal site in a clinical scenario.

MATERIALS AND METHODS

The virtual 4DCT was generated by deforming a reference CT in order to (1) match the anatomy depicted in the 4DMRI within its FOV, by calculating deformation fields with deformable image registration to describe inter-fractional and breathing motion, and (2) obtain physically plausible deformation outside of the 4DMRI FOV, by propagating and modulating the previously obtained deformation fields. The implemented method was validated on a digital anthropomorphic phantom, for which a ground truth (GT) 4DCT was available. A CIRT treatment plan was optimized at the end-exhale reference CT and the RBE-weighted dose distribution was recalculated on both the virtual and GT 4DCTs. The method estimation error was quantified by comparing the virtual and GT 4DCTs and the corresponding recomputed doses. The method was then evaluated on 8 patients with pancreas or liver tumors treated with CIRT using respiratory gating at end-exhale. The clinical treatment plans adopted at the National Center for Oncological Hadrontherapy (CNAO, Pavia, Italy) were considered and the dose distribution was recomputed on all respiratory phases of the planning and virtual 4DCTs. By comparing the two datasets and the corresponding dose distributions, the geometrical and dosimetric impact of organ motion was assessed.

RESULTS

For the phantom, the error outside of the 4DMRI FOV was up to 4.5mm, but it remained sub-millimetric in correspondence to the target within the 4DMRI FOV. Although the impact of motion on the target D_95% resulted in variations ranging from 22% to 90% between the planned dose and the doses recomputed on the GT 4DCT phases, the corresponding estimation error was ≤2.2%. In the patient cases, the variation of the baseline tumor position between the planning and the virtual end-exhale CTs presented a median (interquartile range) value of 6.0 (4.9) mm. For baseline variations larger than 5mm, the tumor D_95% variation between the plan and the dose recomputed on the end-exhale virtual CT resulted larger than 10%. Median variations higher than 10% in the target D_95% and gastro-intestinal OARs D_2% were quantified at the end-inhale, whereas close to the end-exhale phase, limited variations of relevant dose metrics were found for both tumor and OARs.

CONCLUSIONS

The negligible impact of the geometrical inaccuracy in the estimated anatomy outside of the 4DMRI FOV on the overall dosimetric accuracy suggests the feasibility of virtual 4DCT with extended FOV in CIRT of the abdominal site. In the analyzed patient group, inter-fractional variations such as baseline variation and breathing variability were quantified, demonstrating the method capability to support treatment planning in gated CIRT of the abdominal site.

Comparison of CBCT-based dose calculation methods in head and neck cancer radiotherapy: from Hounsfield unit to density calibration curve to deep learning

PURPOSE

Anatomical variations occur during head and neck (H&N) radiotherapy treatment. kV cone-beam computed tomography (CBCT) images can be used for daily dose monitoring to assess dose variations owing to anatomic changes. Deep learning methods (DLMs) have recently been proposed to generate pseudo-CT (pCT) from CBCT to perform dose calculation. This study aims to evaluate the accuracy of a DLM and to compare this method with three existing methods of dose calculation from CBCT in H&N cancer radiotherapy.

METHODS

Forty-four patients received VMAT for H&N cancer (70-63-56 Gy). For each patient, reference CT (Bigbore, Philips) and CBCT images (XVI, Elekta) were acquired. The DLM was based on a generative adversarial network. The three compared methods were: (a) a method using a density to Hounsfield Unit (HU) relation from phantom CBCT image (HU-D curve method), (b) a water-air-bone density assignment method (DAM), and iii) a method using deformable image registration (DIR). The imaging endpoints were the mean absolute error (MAE) and mean error (ME) of HU from pCT and reference CT (CT_ref ). The dosimetric endpoints were dose discrepancies and 3D gamma analyses (local, 2%/2 mm, 30% dose threshold). Dose discrepancies were defined as the mean absolute differences between DVHs calculated from the CT_ref and pCT of each method.

RESULTS

In the entire body, the MAEs and MEs of the DLM, HU-D curve method, DAM, and DIR method were 82.4 and 17.1 HU, 266.6 and 208.9 HU, 113.2 and 14.2 HU, and 95.5 and -36.6 HU, respectively. The MAE obtained using the DLM differed significantly from those of other methods (Wilcoxon, P ≤ 0.05). The DLM dose discrepancies were 7 ± 8 cGy (maximum = 44 cGy) for the ipsilateral parotid gland D_mean and 5 ± 6 cGy (max = 26 cGy) for the contralateral parotid gland mean dose (D_mean ). For the parotid gland D_mean , no significant dose difference was observed between the DLM and other methods. The mean 3D gamma pass rate ± standard deviation was 98.1 ± 1.2%, 91.0 ± 5.3%, 97.9 ± 1.6%, and 98.8 ± 0.7% for the DLM, HU-D method, DAM, and DIR method, respectively. The gamma pass rates and mean gamma results of the HU-D curve method, DAM, and DIR method differed significantly from those of the DLM.

CONCLUSIONS

For H&N radiotherapy, DIR method and DLM appears as the most appealing CBCT-based dose calculation methods among the four methods in terms of dose accuracy as well as calculation time. Using the DIR method or DLM with CBCT images enables dose monitoring in the parotid glands during the treatment course and may be used to trigger replanning.

Feasibility of using calibrated cone-beam computed tomography scans to validate the heart dose in left breast post-mastectomy radiotherapy

Objective

In post-mastectomy radiotherapy, high-conformal techniques are a valid method for determining the dose distribution around a target. However, the proximity of critical structures is a reason for concern. This study aims to evaluate the feasibility of using calibrated cone-beam computed tomography (CBCT) scans as a valid tool for a timely heart dose evaluation.

Methods

A retrospective analysis was conducted on 170 retrospective CBCT scans of 17 patients who underwent high-conformal post-mastectomy irradiation. The delivered doses that were calculated using personalized calibrated CBCT were compared with the doses planned, using the dose–volume histogram dosimetric parameters.

Results

The heart volume that was evaluated using CBCT presented a mean increase of 6%; this discrepancy impacted the heart dose in 4 of 17 patients, with an absolute increase of V25 Gy (range, 2.5%–7.6%) and an increase in the mean dose (range, 1.1–3.4 Gy). The dose for the target, ipsilateral lung, and contralateral breast remained unchanged.

Conclusion

Using CBCT to monitor the dose that is delivered to the heart is feasible, allowing for a timely shift to an adaptive plan if clinically necessary.

Optimized CyberKnife Lung Treatment: Effect of Fractionated Tracking Volume Change on Tracking Results

Objectives

To explore the impact of volume change in the fractionated tracking of stereotactic radiotherapy on the results of synchronous, respiratory tracking algorithm using CyberKnife.

Methods

A total of 38 lung tumor patients receiving stereotactic radiotherapy at our center from March 2018 to October 2019 were counted. Photoshop CS4 image processing software was used to obtain the pixels and the average value of brightness of the tracking volume in the image and calculate the grayscale within the contour of the tracking volume on the real-time X-ray image. At the same time, parameters of the synchronous respiratory tracking algorithm of the fractional CyberKnife were extracted for comparison between the volume of image-guided image tracking and the number of fractions during stereotactic radiotherapy. We also analyzed the relationship between fraction tumor location and characteristics and the calculated results of synchronous respiratory tracking by CyberKnife.

Results

There were no significant differences between the first four fractions (p > 0.05) for left lung lesions and no significant differences between the first five fractions for right lung lesions (p ≥ 0.05). For peripheral lung cancer, longer fractional treatment led to greater variation in grayscale (G-A: >4 fractions p < 0.05), while for central lung cancer, longer fractional treatment led to greater variation in parameters of the synchronous respiratory tracking algorithm (Uncertainty A and Uncertainty B: >4 fractions p < 0.05). There was a significant correlation between radiotherapy-graded tumor density and relevant parameters, and the correlation was strong (>0.7, p < 0.05).

Conclusion

With the increase of treatment fractions, the gray value in the patient tracking volume decreased. Patients of >4 fractions were advised to reevaluate with simulated CT and replan. For tumors with small diameter and low density, the imaging changes of volume should be closely followed during treatment. For left lung and central lung cancer, carefully select the synchronous tracking treatment with 2-view.

Pelvic multi-organ segmentation on cone-beam CT for prostate adaptive radiotherapy

BACKGROUND AND PURPOSE

The purpose of this study is to develop a deep learning-based approach to simultaneously segment five pelvic organs including prostate, bladder, rectum, left and right femoral heads on cone-beam CT (CBCT), as required elements for prostate adaptive radiotherapy planning.

MATERIALS AND METHODS

We propose to utilize both CBCT and CBCT-based synthetic MRI (sMRI) for the segmentation of soft tissue and bony structures, as they provide complementary information for pelvic organ segmentation. CBCT images have superior bony structure contrast and sMRIs have superior soft tissue contrast. Prior to segmentation, sMRI was generated using a cycle-consistent adversarial networks (CycleGAN), which was trained using paired CBCT-MR images. To combine the advantages of both CBCT and sMRI, we developed a cross-modality attention pyramid network with late feature fusion. Our method processes CBCT and sMRI inputs separately to extract CBCT-specific and sMRI-specific features prior to combining them in a late-fusion network for final segmentation. The network was trained and tested using 100 patients' datasets, with each dataset including the CBCT and manual physician contours. For comparison, we trained another two networks with different network inputs and architectures. The segmentation results were compared to manual contours for evaluations.

RESULTS

For the proposed method, dice similarity coefficients and mean surface distances between the segmentation results and the ground truth were 0.96 ± 0.03, 0.65 ± 0.67 mm; 0.91 ± 0.08, 0.93 ± 0.96 mm; 0.93 ± 0.04, 0.72 ± 0.61 mm; 0.95 ± 0.05, 1.05 ± 1.40 mm; and 0.95 ± 0.05, 1.08 ± 1.48 mm for bladder, prostate, rectum, left and right femoral heads, respectively. As compared to the other two competing methods, our method has shown superior performance in terms of the segmentation accuracy.

CONCLUSION

We developed a deep learning-based segmentation method to rapidly and accurately segment five pelvic organs simultaneously from daily CBCTs. The proposed method could be used in the clinic to support rapid target and organs-at-risk contouring for prostate adaptive radiation therapy.

Technical note: development and validation of a Monte Carlo tool for analysis of patient-generated photon scatter

Scattered radiation unavoidably generated in the patient will negatively impact both kilovoltage (KV) and megavoltage (MV) imaging applications. Recently, 'hybrid' methods (i.e. combining analytical and Monte Carlo (MC) techniques) are being investigated as a solution to accurately yet quickly calculate the scattered contribution for both KV and MV images. We have developed a customized MC simulation user code for investigating the individual components of patient-scattered photon fluence, which serves as a valuable tool in this area of research. The MC tool is based on the EGSnrc/DOSXYZnrc user code. The IAUSFL flag options associated with subroutine AUSGAB, combined with LATCH tracking, are used to classify the various interactions of particles with the media. Photons are grouped into six different categories: primary, 1st Compton scatter, 1st Rayleigh scatter, multiple scatter, bremsstrahlung, and positron annihilation. We take advantage of the geometric boundary check in DOSXYZnrc, to write exiting photon particle information to a phase-space file. The tool is validated using homogeneous and heterogeneous phantom configurations with monoenergetic and polyenergetic beams under parallel and divergent beam geometry, comparing MC-simulated exit primary fluence and singly-scattered fluence to corresponding analytical calculations. This MC tool has been validated to separately score the primary and scatter fluence components of the KV and MV imaging applications in the field of radiation therapy. The results are acceptable for the various configurations and beam energies tested here. Overall, the mean percentage differences are less than 0.2% and standard deviations less than 1.6%. This will be a critical test instrument for research in photon scatter applications and particularly for the development of hybrid methods, and is freely available from the authors for research purposes.⁵.

Accuracy of automatic deformable structure propagation for high-field MRI guided prostate radiotherapy

BACKGROUND

In this study we have evaluated the accuracy of automatic, deformable structure propagation from planning CT and MR scans for daily online plan adaptation for MR linac (MRL) treatment, which is an important element to minimize re-planning time and reduce the risk of misrepresenting the target due to this time pressure.

METHODS

For 12 high-risk prostate cancer patients treated to the prostate and pelvic lymph nodes, target structures and organs at risk were delineated on both planning MR and CT scans and propagated using deformable registration to three T2 weighted MR scans acquired during the treatment course. Generated structures were evaluated against manual delineations on the repeated scans using intra-observer variation obtained on the planning MR as ground truth.

RESULTS

MR-to-MR propagated structures had significant less median surface distance and larger Dice similarity index compared to CT-MR propagation. The MR-MR propagation uncertainty was similar in magnitude to the intra-observer variation. Visual inspection of the deformed structures revealed that small anatomical differences between organs in source and destination image sets were generally well accounted for while large differences were not.

CONCLUSION

Both CT and MR based propagations require manual editing, but the current results show that MR-to-MR propagated structures require fewer corrections for high risk prostate cancer patients treated at a high-field MRL.

"Dose of the day" based on cone beam computed tomography and deformable image registration for lung cancer radiotherapy

Purpose

Adaptive radiotherapy (ART) has potential to reduce toxicity and facilitate safe dose escalation. Dose calculations with the planning CT deformed to cone beam CT (CBCT) have shown promise for estimating the “dose of the day”. The purpose of this study is to investigate the “dose of the day” calculation accuracy based on CBCT and deformable image registration (DIR) for lung cancer radiotherapy.

Methods

A total of 12 lung cancer patients were identified, for which daily CBCT imaging was performed for treatment positioning. A re‐planning CT (rCT) was acquired after 20 Gy for all patients. A virtual CT (vCT) was created by deforming initial planning CT (pCT) to the simulated CBCT that was generated from deforming CBCT to rCT acquired on the same day. Treatment beams from the initial plan were copied to the vCT and rCT for dose calculation. Dosimetric agreement between vCT‐based and rCT‐based accumulated doses was evaluated using the Bland‐Altman analysis.

Results

Mean differences in dose‐volume metrics between vCT and rCT were smaller than 1.5%, and most discrepancies fell within the range of ± 5% for the target volume, lung, esophagus, and heart. For spinal cord D_max, a large mean difference of −5.55% was observed, which was largely attributed to very limited CBCT image quality (e.g., truncation artifacts).

Conclusion

This study demonstrated a reasonable agreement in dose‐volume metrics between dose accumulation based on vCT and rCT, with the exception for cases with poor CBCT image quality. These findings suggest potential utility of vCT for providing a reasonable estimate of the “dose of the day”, and thus facilitating the process of ART for lung cancer.