Evaluation and Clinical Application of a Commercially Available Iterative Reconstruction Algorithm for CBCT-Based IGRT

Performance of cone-beam computed tomography imaging during megavoltage beam irradiation under phase-gated conditions

PURPOSE

Target positions should be acquired during beam delivery for accurate lung stereotactic body radiotherapy. We aimed to perform kilovoltage (kV) imaging during beam irradiation (intra-irradiation imaging) under phase-gated conditions and evaluate its performance.

METHODS

Catphan 504 and QUASAR respiratory motion phantoms were used to evaluate image quality and target detectability, respectively. TrueBeam STx linac and the Developer Mode was used. The imaging parameters were 125 kVp and 1.2 mAs/projection. Flattened megavoltage (MV) X-ray beam energies 6, 10 and 15 MV and un-flattened beam energies 6 and 10 MV were used with field sizes of 5 × 5 and 15 × 15 cm2 and various frame rates for intra-irradiation imaging. In addition, using a QUASAR phantom, intra-irradiation imaging was performed during intensity-modulated plan delivery. The root-mean-square error (RMSE) of the CT-number for the inserted rods, image noise, visual assessment, and contrast-to-noise ratio (CNR) were evaluated.

RESULTS

The RMSEs of intra-irradiation cone-beam computed tomography (CBCT) images under gated conditions were 50-230 Hounsfield Unit (HU) (static < 30 HU). The noise of the intra-irradiation CBCT images under gated conditions was 15-35 HU, whereas that of the standard CBCT images was 8.8-27.2 HU. Lower frame rates exhibited large RMSEs and noise; however, the iterative reconstruction algorithm (IR) was effective at improving these values. Approximately 7 fps with the IR showed an equivalent CNR of 15 fps without the IR. The target was visible on all the gated intra-irradiation CBCT images.

CONCLUSION

Several image quality improvements are required; however, intra-irradiated CBCT images showed good visual target detection.

The effects of distance between the imaging isocenter and brain center on the image quality of cone-beam computed tomography for brain stereotactic irradiation

In linear accelerator-based stereotactic irradiation (STI) for brain metastasis, cone-beam computed tomography (CBCT) image quality is essential for ensuring precise patient setup and tumor localization. However, CBCT images may be degraded by the deviation of the CBCT isocenter from the brain center. This study aims to investigate the effects of the distance from the brain center to the CBCT isocenter (DBI) on the image quality in STI. An anthropomorphic phantom was scanned with varying DBI in right, anterior, superior, and inferior directions. Thirty patients undergoing STI were prospectively recruited. Objective metrics, utilizing regions of interest included contrast-to-noise ratio (CNR) at the centrum semiovale, lateral ventricle, and basal ganglia levels, gray and white matter noise at the basal ganglia level, artifact index (AI), and nonuniformity (NU). Two radiation oncologists assessed subjective metrics. In this phantom study, objective measures indicated a degradation in image quality for non-zero DBI. In this patient study, there were significant correlations between the CNR at the centrum semiovale and lateral ventricle levels (rs = - 0.79 and - 0.77, respectively), gray matter noise (rs = 0.52), AI (rs = 0.72), and NU (rs = 0.91) and DBI. However, no significant correlations were observed between the CNR at the basal ganglia level, white matter noise, and subjective metrics and DBI (rs < ± 0.3). Our results demonstrate the effects of DBI on contrast, noise, artifacts in the posterior fossa, and uniformity of CBCT images in STI. Aligning the CBCT isocenter with the brain center can aid in improving image quality.

Custom-Trained Deep Learning-Based Auto-Segmentation for Male Pelvic Iterative CBCT on C-Arm Linear Accelerators

PURPOSE

The purpose of this investigation was to evaluate the clinical applicability of a commercial artificial intelligence-driven deep learning auto-segmentation (DLAS) tool on enhanced iterative cone beam computed tomography (iCBCT) acquisitions for intact prostate and prostate bed treatments.

METHODS AND MATERIALS

DLAS models were trained using 116 iCBCT data sets with manually delineated organs at risk (bladder, femoral heads, and rectum) and target volumes (intact prostate and prostate bed) adhering to institution-specific contouring guidelines. An additional 25 intact prostate and prostate bed iCBCT data sets were used for model testing. Segmentation accuracy relative to a reference structure set was quantified using various geometric comparison metrics and qualitatively evaluated by trained physicists and physicians. These results were compared with those obtained for an additional DLAS-based model trained on planning computed tomography (pCT) data sets and for a deformable image registration (DIR)-based automatic contour propagation method.

RESULTS

In most instances, statistically significant differences in the Dice similarity coefficient (DSC), 95% directed Hausdorff distance, and mean surface distance metrics were observed between the models, as the iCBCT-trained DLAS model outperformed the pCT-trained DLAS model and DIR-based method for all organs at risk and the intact prostate target volume. Mean DSC values for the proposed method were ≥0.90 for these volumes of interest. The iCBCT-trained DLAS model demonstrated a relatively suboptimal performance for the prostate bed segmentation, as the mean DSC value was <0.75 for this target contour. Overall, 90% of bladder, 93% of femoral head, 67% of rectum, and 92% of intact prostate contours generated by the proposed method were deemed clinically acceptable based on qualitative scoring, and approximately 63% of prostate bed contours required moderate or major manual editing to adhere to institutional contouring guidelines.

CONCLUSIONS

The proposed method presents the potential for improved segmentation accuracy and efficiency compared with the DIR-based automatic contour propagation method as commonly applied in CBCT-based dose evaluation and calculation studies.

Impact of technological advances in treatment planning, image guidance, and treatment delivery on target margin design for prostate cancer radiotherapy: an updated review

Recent innovations in image guidance, treatment delivery, and adaptive radiotherapy (RT) have created a new paradigm for planning target volume (PTV) margin design for patients with prostate cancer. We performed a review of the recent literature on PTV margin selection and design for intact prostate RT, excluding post-operative RT, brachytherapy, and proton therapy. Our review describes the increased focus on prostate and seminal vesicles as heterogenous deforming structures with further emergence of intra-prostatic GTV boost and concurrent pelvic lymph node treatment. To capture recent innovations, we highlight the evolution in cone beam CT guidance, and increasing use of MRI for improved target delineation and image registration and supporting online adaptive RT. Moreover, we summarize new and evolving image-guidance treatment platforms as well as recent reports of novel immobilization strategies and motion tracking. Our report also captures recent implementations of artificial intelligence to support image guidance and adaptive RT. To characterize the clinical impact of PTV margin changes via model-based risk estimates and clinical trials, we highlight recent high impact reports. Our report focusses on topics in the context of PTV margins but also showcase studies attempting to move beyond the PTV margin recipes with robust optimization and probabilistic planning approaches. Although guidelines exist for target margins conventional using CT-based image guidance, further validation is required to understand the optimal margins for online adaptation either alone or combined with real-time motion compensation to minimize systematic and random uncertainties in the treatment of patients with prostate cancer.

Mitigation of motion-induced artifacts in cone beam computed tomography using deep convolutional neural networks

BACKGROUND

Cone beam computed tomography (CBCT) is often employed on radiation therapy treatment devices (linear accelerators) used in image-guided radiation therapy (IGRT). For each treatment session, it is necessary to obtain the image of the day in order to accurately position the patient and to enable adaptive treatment capabilities including auto-segmentation and dose calculation. Reconstructed CBCT images often suffer from artifacts, in particular those induced by patient motion. Deep-learning based approaches promise ways to mitigate such artifacts.

PURPOSE

We propose a novel deep-learning based approach with the goal to reduce motion induced artifacts in CBCT images and improve image quality. It is based on supervised learning and includes neural network architectures employed as pre- and/or post-processing steps during CBCT reconstruction.

METHODS

Our approach is based on deep convolutional neural networks which complement the standard CBCT reconstruction, which is performed either with the analytical Feldkamp-Davis-Kress (FDK) method, or with an iterative algebraic reconstruction technique (SART-TV). The neural networks, which are based on refined U-net architectures, are trained end-to-end in a supervised learning setup. Labeled training data are obtained by means of a motion simulation, which uses the two extreme phases of 4D CT scans, their deformation vector fields, as well as time-dependent amplitude signals as input. The trained networks are validated against ground truth using quantitative metrics, as well as by using real patient CBCT scans for a qualitative evaluation by clinical experts.

RESULTS

The presented novel approach is able to generalize to unseen data and yields significant reductions in motion induced artifacts as well as improvements in image quality compared with existing state-of-the-art CBCT reconstruction algorithms (up to +6.3 dB and +0.19 improvements in peak signal-to-noise ratio, PSNR, and structural similarity index measure, SSIM, respectively), as evidenced by validation with an unseen test dataset, and confirmed by a clinical evaluation on real patient scans (up to 74% preference for motion artifact reduction over standard reconstruction).

CONCLUSIONS

For the first time, it is demonstrated, also by means of clinical evaluation, that inserting deep neural networks as pre- and post-processing plugins in the existing 3D CBCT reconstruction and trained end-to-end yield significant improvements in image quality and reduction of motion artifacts.

Review of cone beam computed tomography based online adaptive radiotherapy: current trend and future direction

Adaptive radiotherapy (ART) was introduced in the late 1990s to improve the accuracy and efficiency of therapy and minimize radiation-induced toxicities. ART combines multiple tools for imaging, assessing the need for adaptation, treatment planning, quality assurance, and has been utilized to monitor inter- or intra-fraction anatomical variations of the target and organs-at-risk (OARs). Ethos™ (Varian Medical Systems, Palo Alto, CA), a cone beam computed tomography (CBCT) based radiotherapy treatment system that uses artificial intelligence (AI) and machine learning to perform ART, was introduced in 2020. Since then, numerous studies have been done to examine the potential benefits of Ethos™ CBCT-guided ART compared to non-adaptive radiotherapy. This review will explore the current trends of Ethos™, including improved CBCT image quality, a feasible clinical workflow, daily automated contouring and treatment planning, and motion management. Nevertheless, evidence of clinical improvements with the use of Ethos™ are limited and is currently under investigation via clinical trials.

Quantification of six-degree-of-freedom motion during beam delivery in spine stereotactic body radiotherapy using intra-irradiation cone-beam computed tomography imaging technique

PURPOSE

Quantifying intra-fractional six-degree-of-freedom (6DoF) residual errors or motion from approved patient setups is necessary for accurate beam delivery in spine stereotactic body radiotherapy. However, previously reported errors were not acquired during beam delivery. Therefore, we aimed to quantify the 6DoF residual errors and motions during arc beam delivery using a concurrent cone-beam computed tomography (CBCT) imaging technique, intra-irradiation CBCT.

METHODS

Consecutive 15 patients, 19 plans for various treatment sites, and 199 CBCT images were analyzed. Pre-irradiation CBCT was performed to verify shifts from the initial patient setup using the ExacTrac system. During beam delivery by two or three co-planar full-arc rotations, CBCT imaging was performed concurrently. Subsequently, an intra-irradiation CBCT image was reconstructed. Pre- and intra-irradiation CBCT images were rigidly registered to a planning CT image based on the bone to quantify 6DoF residual errors.

RESULTS

6DoF residual errors quantified using pre- and intra-irradiation CBCTs were within 2.0 mm/2.0°, except for one measurement. The mean elapsed time (mean ± standard deviation [min:sec]) after pre-irradiation CBCT to the end of the last arc beam delivery was 6:08 ± 1:25 and 7:54 ± 2:14 for the 2- and 3-arc plans, respectively. Root mean squares of residual errors for several directions showed significant differences; however, they were within 1.0 mm/1.0°. Time-dependent analysis revealed that the residual errors tended to increase with elapsed time.

CONCLUSION

The errors represent the optimal intra-fractional error compared with those acquired using the pre-, inter-beam, and post-6DoF image guidance and can be acquired within a standard treatment timeslot.

Prospective imaging comparison of anatomic delineation with rapid kV cone beam CT on a novel ring gantry radiotherapy device

INTRODUCTION

A kV imager coupled to a novel, ring-gantry radiotherapy system offers improved on-board kV-cone-beam computed tomography (CBCT) acquisition time (17-40 seconds) and image quality, which may improve CT radiotherapy image-guidance and enable online adaptive radiotherapy. We evaluated whether inter-observer contour variability over various anatomic structures was non-inferior using a novel ring gantry kV-CBCT (RG-CBCT) imager as compared to diagnostic-quality simulation CT (simCT).

MATERIALS/METHODS

Seven patients undergoing radiotherapy were imaged with the RG-CBCT system at breath hold (BH) and/or free breathing (FB) for various disease sites on a prospective imaging study. Anatomy was independently contoured by seven radiation oncologists on: 1. SimCT 2. Standard C-arm kV-CBCT (CA-CBCT), and 3. Novel RG-CBCT at FB and BH. Inter-observer contour variability was evaluated by computing simultaneous truth and performance level estimation (STAPLE) consensus contours, then computing average symmetric surface distance (ASSD) and Dice similarity coefficient (DSC) between individual raters and consensus contours for comparison across image types.

RESULTS

Across 7 patients, 18 organs-at-risk (OARs) were evaluated on 27 image sets. Both BH and FB RG-CBCT were non-inferior to simCT for inter-observer delineation variability across all OARs and patients by ASSD analysis (p < 0.001), whereas CA-CBCT was not (p = 0.923). RG-CBCT (FB and BH) also remained non-inferior for abdomen and breast subsites compared to simCT on ASSD analysis (p < 0.025). On DSC comparison, neither RG-CBCT nor CA-CBCT were non-inferior to simCT for all sites (p > 0.025).

CONCLUSIONS

Inter-observer ability to delineate OARs using novel RG-CBCT images was non-inferior to simCT by the ASSD criterion but not DSC criterion.

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.

Dose Reduction and Low-Contrast Detectability Using Iterative CBCT Reconstruction Algorithm for Radiotherapy

Introduction: Several studies have reported the relation between the imaging dose and secondary cancer risk and have emphasized the need to minimize the additional imaging dose as low as reasonably achievable. The iterative cone-beam computed tomography (iCBCT) algorithm can improve the image quality by utilizing scatter correction and statistical reconstruction. We investigate the use of a novel iCBCT reconstruction algorithm to reduce the patient dose while maintaining low-contrast detectability and registration accuracy. Methods: Catphan and anthropomorphic phantoms were analyzed. All CBCT images were acquired with varying dose levels and reconstructed with a Feldkamp-Davis-Kress algorithm-based CBCT (FDK-CBCT) and iCBCT. The low-contrast detectability was subjectively assessed using a 9-point scale by 4 reviewers and objectively assessed using structure similarity index (SSIM). The soft tissue-based registration error was analyzed for each dose level and reconstruction technique. Results: The results of subjective low-contrast detectability found that the iCBCT acquired at two-thirds of a dose was superior to the FDK-CBCT acquired at a full dose (6.4 vs 5.4). Relative to FDK-CBCT acquired at full dose, SSIM was higher for iCBCT acquired at one-sixth dose in head and head and neck region while equivalent with iCBCT acquired at two-thirds dose in pelvis region. The soft tissue-based registration was 2.2 and 0.6 mm for FDK-CBCT and iCBCT, respectively. Conclusion: Use of iCBCT reconstruction algorithm can generally reduce the patient dose by approximately two-thirds compared to conventional reconstruction methods while maintaining low-contrast detectability and accuracy of registration.

Machine log file-based dose verification using novel iterative CBCT reconstruction algorithm in commercial software during volumetric modulated arc therapy for prostate cancer patients

PURPOSE

To evaluate the utility of the use of iterative cone-beam computed tomography (CBCT) for machine log file-based dose verification during volumetric modulated arc therapy (VMAT) for prostate cancer patients.

METHODS

All CBCT acquisition data were used to reconstruct images with the Feldkamp-Davis-Kress algorithm (FDK-CBCT) and the novel iterative algorithm (iCBCT). The Hounsfield unit (HU)-electron density curves for CBCT images were created using the Advanced Electron Density Phantom. The I'mRT and anthropomorphic phantoms were irradiated with VMAT after CBCT registration. Subsequently, fourteen prostate cancer patients received VMAT after CBCT registration. Machine log files and both CBCT images were exported to the PerFRACTION software, and a 3D patient dose was reconstructed. Mean dose for planning target volume (PTV), the bladder, and rectum and the 3D gamma analysis were evaluated.

RESULTS

For the phantom studies, the variation of HU values was observed at the central position surrounding the bones in FDK-CBCT. There were almost no changes in the difference of doses at the isocenter between measurement and reconstructed dose for planning CT (pCT), FDK-CBCT, and iCBCT. Mean dose differences of PTV, rectum, and bladder between iCBCT and pCT were approximately 2% lower than those between FDK-CBCT and pCT. For the clinical study, average gamma analysis for 2%/2 mm was 98.22% ± 1.07 and 98.81% ± 1.25% in FDK-CBCT and iCBCT, respectively.

CONCLUSIONS

A similar machine log file-based dose verification accuracy is obtained for FDK-CBCT and iCBCT during VMAT for prostate cancer patients.

Planning CT-guided robust and fast cone-beam CT scatter correction using a local filtration technique

PURPOSE

Cone-beam CT (CBCT) has been widely utilized in image-guided radiotherapy. Planning CT (pCT)-aided CBCT scatter correction could further enhance image quality and extend CBCT application to dose calculation and adaptive planning. Nevertheless, existing pCT-based approaches demand accurate registration between pCT and CBCT, leading to limited imaging performance and increased computational cost when large anatomical discrepancies exist. In this work, we proposed a robust and fast CBCT scatter correction method using local filtration technique and rigid registration between pCT and CBCT (LF-RR).

METHODS

First of all, the pCT was rigidly registered with CBCT, then forward projection was performed on registered pCT to create scatter-free projections. The raw scatter signals were obtained via subtracting the scatter-free projections from the measured CBCT projections. Based on frequency and intensity threshold criteria, reliable scatter signals were selected from the raw scatter signals, and further filtered for global scatter estimation via local filtration technique. Finally, corrected CBCT was reconstructed with the projections generated by subtracting the scatter estimation from the raw CBCT projections using FDK algorithm. The LF-RR method was evaluated via comparison with another pCT-based scatter correction method based on Median and Gaussian filters (MG method).

RESULTS

Proposed method was first validated on an anthropomorphic pelvis phantom, and showed satisfied performance on scatter removal even when anatomical mismatches were intentionally created on pCT. The quantitative analysis was further performed on four clinical CBCT images. Compared with the uncorrected CBCT, CBCT corrected by MG with rigid registration (MG-RR), MG with deformable registration (MG-DR), and LF-RR reduced the CT number error from 79 ± 35 to 25 ± 18 , 17 ± 13 and 7 ± 3 HU for adipose and from 115 ± 61 to 36 ± 22 , 30 ± 24 , 7 ± 3 HU for muscle, respectively. After correction, the spatial non-uniformity (SNU) of CBCT corrected with MG-RR, MG-DR and LF-RR was 51 ± 13 , 60 ± 21 , and 21 ± 9 HU for adipose, and 50 ± 22 , 57 ± 41 , and 25 ± 6 HU for muscle, respectively. Meanwhile, the contrast-to-noise ratio (CNR) between muscle and adipose was increased by a factor of 2.70, 2.89 and 2.56, respectively. Using the LF-RR method, the scatter correction of 656 projections can be finished within 10 s and the corrected volumetric images (200 slices) can be obtained within 2 min.

CONCLUSION

We developed a fast and robust pCT-based CBCT scatter correction method which exploits the local-filtration technique to promote the accuracy of scatter estimation and is resistant to pCT-to-CBCT registration uncertainties. Both phantom and patient studies showed the superiority of the proposed correction in imaging accuracy and computational efficiency, indicating promisingfuture clinical application.

Reducing residual-motion artifacts in iterative 3D CBCT reconstruction in image-guided radiation therapy

PURPOSE

Recent evaluations of a 3D iterative cone-beam computed tomography (iCBCT) reconstruction method available on Varian radiation treatment devices demonstrated that iCBCT provides superior image quality when compared to analytical Feldkamp-Davis-Kress (FDK) method. However, iCBCT employs statistical penalized likelihood (PL) that is known to be highly sensitive to inconsistencies due to physiological motion occurring during the acquisition. We propose a computationally inexpensive extension of iCBCT addressing this deficiency.

METHODS

During the iterative process, the gradients of PL are modified to avoid the generation of motion-related artifacts. To assess the impact of this modification, we propose a motion simulation generating CBCT projections of a moving anatomy together with artifact-free images used as ground truth. Contrast-to-noise ratio and power spectra of difference images are computed to quantify the impact of the motion on reconstructed CBCT volumes as well as the effect of the proposed modification.

RESULTS

Using both simulated and clinical data, it is shown that the motion of patient's abdominal wall during the acquisition results in artifacts that can be quantified as low-frequency components in volumes reconstructed with iCBCT. Further, a quantitative evaluation demonstrates that the proposed modification of PL reduces these low-frequency components. While preserving the advantages of PL, it effectively suppresses the propagation of motion-related artifacts into clinically important regions, thus increasing the motion resiliency of iCBCT.

CONCLUSIONS

The proposed modified iterative reconstruction method significantly improves the quality of CBCT images of anatomies suffering from residual motion.

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.

Actual delivered dose calculation on intra-irradiation cone-beam computed tomography images: a phantom study

Cone-beam computed tomography (CBCT) images acquired during volumetric modulated arc therapy (VMAT; ii-CBCT) can be used to calculate actual delivered doses (ADDs). However, such ii-CBCT images are degraded by scattered megavoltage x-rays (MV-scatters). We aimed to evaluate the dose calculation accuracy of the MV-scatter uncorrected or corrected ii-CBCT images acquired during VMAT deliveries. For MV-scatter correction on concurrent kilovoltage projections (P _MVkV), projections consisting only of MV-scatters (P _MVS) were acquired under the same MV beam parameters and gantry angles and subtracted from P _MVkV (P _MVScorr). In addition, the projections by kilovoltage beams were acquired for reference (P _kV). The corresponding CBCT images were reconstructed using the Feldkamp-Davis-Kress algorithm (CBCT_MVkV, CBCT_MVScorr, and CBCT_kV as reference). A multi-energy phantom with rods of various relative electron densities (REDs) was used to generate a CBCT-number-to-RED conversion table. First, CBCT_kV was reconstructed. Then, the mean CBCT-numbers within each rod were extracted, and a reference table was generated. Concurrent kilovoltage imaging with various field sizes was also demonstrated, and CBCT_MVkV and CBCT_MVScorr were reconstructed. The extracted CBCT-numbers of each ii-CBCT image were converted into REDs using the reference table. Next, the absolute differences of RED between the ii-CBCT image and CBCT_kV were calculated. Ten VMAT plans using a 10 MV flattening-filter-free beam were used for concurrent imaging of an anthropomorphic torso phantom. Moreover, an iterative reconstruction algorithm (IRA) was used for CBCT_MVScorr. The plans were recalculated for the corresponding CBCT_MVkV, CBCT_MVScorr, CBCT_MVScorr+IRA, and CBCT_kV with the reference table. Finally, the doses were evaluated using 3D gamma analysis (1%/1 mm). The median difference ranges between CBCT_MVkV/CBCT_MVScorr and the reference values were -0.58 to -0.10/-0.03 to 0.00. The median gamma pass rates of the doses on CBCT_MVkV, CBCT_MVScorr, and CBCT_MVScorr+IRA to the rate on CBCT_kV were 70.4, 99.5, and 98.2%, respectively. CBCT_MVScorr were comparable with CBCT_kV for calculating the ADD from VMAT.

Synthetic CT in assessment of anatomical and dosimetric variations in radiotherapy - procedure validation

Introduction: One of many procedures to control the quality of radiotherapy is daily imaging of the patient’s anatomy. The CBCT (Cone Beam Computed Tomography) plays an important role in patient positioning, and dose delivery monitoring. Nowadays, CBCT is a baseline for the calculation of fraction and total dose. Thus, it provides the potential for more comprehensive monitoring of the delivered dose and adaptive radiotherapy. However, due to the poor quality and the presence of numerous artifacts, the replacement of the CBCT image with the corrected one is desired for dose calculation. The aim of the study was to validate a method for generating a synthetic CT image based on deformable image registration.

Material and methods: A Head & Torso Freepoint phantom, model 002H9K (Computerized Imaging Reference Systems, Norfolk, USA) with inserts was imaged with CT (Computed Tomography). Then, contouring and treatment plan were created in Eclipse (Varian Medical Systems, Palo Alto, CA, USA) treatment planning system. The phantom was scanned again with the CBCT. The planning CT was registered and deformed to the CBCT, resulting in a synthetic CT in Velocity software (Varian Medical Systems, Palo Alto, CA, USA). The dose distribution was recalculated based on the created CT image.

Results: Differences in structure volumes and dose statistics calculated both on CT and synthetic CT were evaluated. Discrepancies between the original and delivered plan from 0.0 to 2.5% were obtained. Dose comparison was performed on the DVH (Dose-Volume Histogram) for all delineated inserts.

Conclusions: Our findings suggest the potential utility of deformable registration and synthetic CT for providing dose reconstruction. This study reports on the limitation of the procedure related to the limited length of the CBCT volume and deformable fusion inaccuracies.

Adaptive Radiation Therapy (ART) Strategies and Technical Considerations: A State of the ART Review From NRG Oncology

The integration of adaptive radiation therapy (ART), or modifying the treatment plan during the treatment course, is becoming more widely available in clinical practice. ART offers strong potential for minimizing treatment-related toxicity while escalating or de-escalating target doses based on the dose to organs at risk. Yet, ART workflows add complexity into the radiation therapy planning and delivery process that may introduce additional uncertainties. This work sought to review presently available ART workflows and technological considerations such as image quality, deformable image registration, and dose accumulation. Quality assurance considerations for ART components and minimum recommendations are described. Personnel and workflow efficiency recommendations are provided, as is a summary of currently available clinical evidence supporting the implementation of ART. Finally, to guide future clinical trial protocols, an example ART physician directive and a physics template following standard NRG Oncology protocol is provided.

Triggered Imaging With Auto Beam Hold and Pre-/Posttreatment CBCT During Prostate SABR: Analysis of Time Efficiency, Target Coverage, and Normal Volume Changes

PURPOSE

Our purpose was to investigate time efficiency and target coverage for prostate stereotactic ablative radiation therapy (SABR) using triggered imaging (TI) and auto beam hold.

METHODS AND MATERIALS

A total of 20 patients were treated with volumetric modulated arc-based SABR. Treatment verification consisted of pre- and post-radiation therapy cone beam computed tomography (CBCT) with gold marker-based TI every 3 seconds. In case of ≥3 mm (deviation limit) displacement, the treatment was interrupted and imaging-based correction was performed. Beam interruptions, intrafractional shifts, and treatment times were recorded. Prostate, rectum, and bladder were delineated on each CBCT. Target coverage was evaluated by comparing the individual prostate delineations with 98% isodose contour volumes (% of the evaluated volumes exceeding the reference). Both inter- and intrafractional changes of bladder and rectal volumes were assessed.

RESULTS

The average overall treatment time (±standard deviation) was 18 ± 11 min, with a radiation delivery time of 6 ± 3 min if no intrafractional CBCT acquisitions were necessary (91% of fractions). On average, 1.2 beam interruptions per fraction were required with 0/1 correction in 71% of the fractions. The mean residual 3-dimensional shift was 1.6 mm, exceeding the deviation limit in 8%. In the case of intrafractional CBCT and/or ≥2 corrections the treatment time dramatically increased. The 98% isodose lines did not encompass the prostate in only 8/180 (4%) evaluations in 6 different patients, leading to a loss of D98 between 0.1%-6% as a worst case scenario. The bladder volumes showed significant increases during treatment (P < .01) while rectal volumes were stable.

CONCLUSIONS

Time efficiency of TI + auto beam hold with 3 mm/3 sec threshold during prostate SABR is comparable with competitive techniques, resulting in minimal 3-dimensional residual errors with maintained target coverage. Technical developments are necessary to further reduce radiation delivery time. Use of CBCT allowed full control of rectal volumes, while bladder volumes showed significant increases over time.

Fast-switching dual energy cone beam computed tomography using the on-board imager of a commercial linear accelerator

To evaluate fast-kV switching (FS) dual energy (DE) cone beam computed tomography (CBCT) using the on-board imager (OBI) of a commercial linear accelerator to produce virtual monoenergetic (VM) and relative electron density (RED) images. Using an polynomial attenuation mapping model, CBCT phantom projections obtained at 80 and 140 kVp with FS imaging, were decomposed into equivalent thicknesses of aluminum (Al) and polymethyl methacrylate (PMMA). All projections were obtained with the titanium foil and bowtie filter in place. Basis material projections were then recombined to create VM images by using the linear attenuation coefficients at the specified energy for each material. Similarly, RED images were produced by replacing the linear attenuation values of Al and PMMA by their respective RED values in the projection space. VM and RED images were reconstructed using Feldkamp-Davis-Kress (FDK) and an iterative algorithm (iCBCT, Varian Medical Systems). Hounsfield units (HU), contrast-to-noise ratio (CNR) and RED values were compared against known values. The results after VM-CBCT production showed good material decomposition and consistent HU_VM values, with measured root mean square errors (RMSE) from theoretical values, after FDK reconstruction, of 20.5, 5.7, 12.8 and 21.7 HU for 50, 80, 100 and 150 keV, respectively. The largest CNR improvements, when compared to polychromatic images, were observed for the 50 keV VM images. Image noise was reduced up to 28% in the VM-CBCT images after iterative image reconstruction. RED values measured for our method resulted in a mean percentage error of 0.0%  ±  1.8%. This study describes a method to generate VM-CBCT and RED images using FS-DE scans obtained using the OBI of a linac, including the effects of the bowtie filter. The creation of VM and RED images increases the dynamic range of CBCT images, and provides additional data that may be used for adaptive radiotherapy, and on table verification for radiotherapy treatments.