Automated testing platform for radiotherapy treatment planning scripts.

Realizing the potential of user-developed automation software interacting with a treatment planning system (TPS) requires rigorous testing to ensure patient safety and data integrity. We developed an automated test platform to allow comparison of the treatment planning database before and after the execution of a write-enabled script interacting with a commercial TPS (Eclipse, Varian Medical Systems, Palo Alto, CA) using the vendor-provided Eclipse Scripting Application Programming Interface (ESAPI). The C#-application known as Write-Enable Script Testing Engine (WESTE) serializes the treatment planning objects (Patient, Structure Set, PlanSetup) accessible through ESAPI, and then compares the serialization acquired before and after the execution of the script being tested, documenting identified differences to highlight the changes made to the treatment planning data. The first two uses of WESTE demonstrated that the testing platform could acquire and analyze the data quickly (<4 s per test case) and facilitate the clinical implementation of write-enabled scripts.

Implementation of free breathing respiratory amplitude-gated treatments.

PURPOSE: The purpose of this study was to provide guidance in developing and implementing a process for the accurate delivery of free breathing respiratory amplitude-gated treatments. METHODS: A phase-based 4DCT scan is acquired at time of simulation and motion is evaluated to determine the exhale phases that minimize respiratory motion to an acceptable level. A phase subset average CT is then generated for treatment planning and a tracking structure is contoured to indicate the location of the target or a suitable surrogate over the planning phases. Prior to treatment delivery, a 4DCBCT is acquired and a phase subset average is created to coincide with the planning phases for an initial match to the planning CT. Fluoroscopic imaging is then used to set amplitude gate thresholds corresponding to when the target or surrogate is in the tracking structure. The final imaging prior to treatment is an amplitude-gated CBCT to verify both the amplitude gate thresholds and patient positioning. An amplitude-gated treatment is then delivered. This technique was commissioned using an in-house lung motion phantom and film measurements of a simple two-field 3D plan. RESULTS: The accuracy of 4DCBCT motion and target position measurements were validated relative to 4DCT imaging. End to end testing showed strong agreement between planned and film measured dose distributions. Robustness to interuser variability and changes in respiratory motion were demonstrated through film measurements. CONCLUSIONS: The developed workflow utilizes 4DCBCT, respiratory-correlated fluoroscopy, and gated CBCT imaging in an efficient and sequential process to ensure the accurate delivery of free breathing respiratory-gated treatments.

Deep learning based linear energy transfer calculation for proton therapy.

Objective.This study aims to address the limitations of traditional methods for calculating linear energy transfer (LET), a critical component in assessing relative biological effectiveness (RBE). Currently, Monte Carlo (MC) simulation, the gold-standard for accuracy, is resource-intensive and slow for dose optimization, while the speedier analytical approximation has compromised accuracy. Our objective was to prototype a deep-learning-based model for calculating dose-averaged LET (LETd) using patient anatomy and dose-to-water (DW) data, facilitating real-time biological dose evaluation and LET optimization within proton treatment planning systems.Approach. 275 4-field prostate proton Stereotactic Body Radiotherapy plans were analyzed, rendering a total of 1100 fields. Those were randomly split into 880, 110, and 110 fields for training, validation, and testing. A 3D Cascaded UNet model, along with data processing and inference pipelines, was developed to generate patient-specific LETddistributions from CT images and DW. The accuracy of the LETdof the test dataset was evaluated against MC-generated ground truth through voxel-based mean absolute error (MAE) and gamma analysis.Main results.The proposed model accurately inferred LETddistributions for each proton field in the test dataset. A single-field LETdcalculation took around 100 ms with trained models running on a NVidia A100 GPU. The selected model yielded an average MAE of 0.94 ± 0.14 MeV cm-1and a gamma passing rate of 97.4% ± 1.3% when applied to the test dataset, with the largest discrepancy at the edge of fields where the dose gradient was the largest and counting statistics was the lowest.Significance.This study demonstrates that deep-learning-based models can efficiently calculate LETdwith high accuracy as a fast-forward approach. The model shows great potential to be utilized for optimizing the RBE of proton treatment plans. Future efforts will focus on enhancing the model's performance and evaluating its adaptability to different clinical scenarios.

Knowledge-based quality assurance of a comprehensive set of organ at risk contours for head and neck radiotherapy.

Introduction: Manual review of organ at risk (OAR) contours is crucial for creating safe radiotherapy plans but can be time-consuming and error prone. Statistical and deep learning models show the potential to automatically detect improper contours by identifying outliers using large sets of acceptable data (knowledge-based outlier detection) and may be able to assist human reviewers during review of OAR contours. Methods: This study developed an automated knowledge-based outlier detection method and assessed its ability to detect erroneous contours for all common head and neck (HN) OAR types used clinically at our institution. We utilized 490 accurate CT-based HN structure sets from unique patients, each with forty-two HN OAR contours when anatomically present. The structure sets were distributed as 80% for training, 10% for validation, and 10% for testing. In addition, 190 and 37 simulated contours containing errors were added to the validation and test sets, respectively. Single-contour features, including location, shape, orientation, volume, and CT number, were used to train three single-contour feature models (z-score, Mahalanobis distance [MD], and autoencoder [AE]). Additionally, a novel contour-to-contour relationship (CCR) model was trained using the minimum distance and volumetric overlap between pairs of OAR contours to quantify overlap and separation. Inferences from single-contour feature models were combined with the CCR model inferences and inferences evaluating the number of disconnected parts in a single contour and then compared. Results: In the test dataset, before combination with the CCR model, the area under the curve values were 0.922/0.939/0.939 for the z-score, MD, and AE models respectively for all contours. After combination with CCR model inferences, the z-score, MD, and AE had sensitivities of 0.838/0.892/0.865, specificities of 0.922/0.907/0.887, and balanced accuracies (BA) of 0.880/0.900/0.876 respectively. In the validation dataset, with similar overall performance and no signs of overfitting, model performance for individual OAR types was assessed. The combined AE model demonstrated minimum, median, and maximum BAs of 0.729, 0.908, and 0.980 across OAR types. Discussion: Our novel knowledge-based method combines models utilizing single-contour and CCR features to effectively detect erroneous OAR contours across a comprehensive set of 42 clinically used OAR types for HN radiotherapy.

Automated target placement for VMAT lattice radiation therapy: enhancing efficiency and consistency.

Objective. An algorithm was developed for automated positioning of lattice points within volumetric modulated arc lattice radiation therapy (VMAT LRT) planning. These points are strategically placed within the gross tumor volume (GTV) to receive high doses, adhering to specific separation rules from adjacent organs at risk (OARs). The study goals included enhancing planning safety, consistency, and efficiency while emulating human performance.Approach. A Monte Carlo-based algorithm was designed to optimize the number and arrangement of lattice points within the GTV while considering placement constraints and objectives. These constraints encompassed minimum spacing between points, distance from OARs, and longitudinal separation along thez-axis. Additionally, the algorithm included an objective to permit, at the user's discretion, solutions with more centrally placed lattice points within the GTV. To validate its effectiveness, the automated approach was compared with manually planned treatments for 24 previous patients. Prior to clinical implementation, a failure mode and effects analysis (FMEA) was conducted to identify potential shortcomings.Main results.The automated program successfully met all placement constraints with an average execution time (over 24 plans) of 0.29 ±0.07 min per lattice point. The average lattice point density (# points per 100 c.c. of GTV) was similar for automated (0.725) compared to manual placement (0.704). The dosimetric differences between the automated and manual plans were minimal, with statistically significant differences in certain metrics like minimum dose (1.9% versus 1.4%), D5% (52.8% versus 49.4%), D95% (7.1% versus 6.2%), and Body-GTV V30% (20.7 c.c. versus 19.7 c.c.).Significance.This study underscores the feasibility of employing a straightforward Monte Carlo-based algorithm to automate the creation of spherical target structures for VMAT LRT planning. The automated method yields similar dose metrics, enhances inter-planner consistency for larger targets, and requires fewer resources and less time compared to manual placement. This approach holds promise for standardizing treatment planning in prospective patient trials and facilitating its adoption across centers seeking to implement VMAT LRT techniques.

Volumetric-modulated arc therapy for the treatment of a large planning target volume in thoracic esophageal cancer.

Recently, volumetric-modulated arc therapy (VMAT) has demonstrated the ability to deliver radiation dose precisely and accurately with a shorter delivery time compared to conventional intensity-modulated fixed-field treatment (IMRT). We applied the hypothesis of VMAT technique for the treatment of thoracic esophageal carcinoma to determine superior or equivalent conformal dose coverage for a large thoracic esophageal planning target volume (PTV) with superior or equivalent sparing of organs-at-risk (OARs) doses, and reduce delivery time and monitor units (MUs), in comparison with conventional fixed-field IMRT plans. We also analyzed and compared some other important metrics of treatment planning and treatment delivery for both IMRT and VMAT techniques. These metrics include: 1) the integral dose and the volume receiving intermediate dose levels between IMRT and VMATI plans; 2) the use of 4D CT to determine the internal motion margin; and 3) evaluating the dosimetry of every plan through patient-specific QA. These factors may impact the overall treatment plan quality and outcomes from the individual planning technique used. In this study, we also examined the significance of using two arcs vs. a single-arc VMAT technique for PTV coverage, OARs doses, monitor units and delivery time. Thirteen patients, stage T2-T3 N0-N1 (TNM AJCC 7th edn.), PTV volume median 395 cc (range 281-601 cc), median age 69 years (range 53 to 85), were treated from July 2010 to June 2011 with a four-field (n = 4) or five-field (n = 9) step-and-shoot IMRT technique using a 6 MV beam to a prescribed dose of 50 Gy in 20 to 25 F. These patients were retrospectively replanned using single arc (VMATI, 91 control points) and two arcs (VMATII, 182 control points). All treatment plans of the 13 study cases were evaluated using various dose-volume metrics. These included PTV D99, PTV D95, PTV V9547.5Gy(95%), PTV mean dose, Dmax, PTV dose conformity (Van't Riet conformation number (CN)), mean lung dose, lung V20 and V5, liver V30, and Dmax to the spinal canal prv3mm. Also examined were the total plan monitor units (MUs) and the beam delivery time. Equivalent target coverage was observed with both VMAT single and two-arc plans. The comparison of VMATI with fixed-field IMRT demonstrated equivalent target coverage; statistically no significant difference were found in PTV D99 (p = 0.47), PTV mean (p = 0.12), PTV D95 and PTV V9547.5Gy (95%) (p = 0.38). However, Dmax in VMATI plans was significantly lower compared to IMRT (p = 0.02). The Van't Riet dose conformation number (CN) was also statistically in favor of VMATI plans (p = 0.04). VMATI achieved lower lung V20 (p = 0.05), whereas lung V5 (p = 0.35) and mean lung dose (p = 0.62) were not significantly different. The other OARs, including spinal canal, liver, heart, and kidneys showed no statistically significant differences between the two techniques. Treatment time delivery for VMATI plans was reduced by up to 55% (p = 5.8E-10) and MUs reduced by up to 16% (p = 0.001). Integral dose was not statistically different between the two planning techniques (p = 0.99). There were no statistically significant differences found in dose distribution of the two VMAT techniques (VMATI vs. VMATII) Dose statistics for both VMAT techniques were: PTV D99 (p = 0.76), PTV D95 (p = 0.95), mean PTV dose (p = 0.78), conformation number (CN) (p = 0.26), and MUs (p = 0.1). However, the treatment delivery time for VMATII increased significantly by two-fold (p = 3.0E-11) compared to VMATI. VMAT-based treatment planning is safe and deliverable for patients with thoracic esophageal cancer with similar planning goals, when compared to standard IMRT. The key benefit for VMATI was the reduction in treatment delivery time and MUs, and improvement in dose conformality. In our study, we found no significant difference in VMATII over single-arc VMATI for PTV coverage or OARs doses. However, we observed significant increase in delivery time for VMATII compared to VMATI.

Validation of clinical acceptability of deep-learning-based automated segmentation of organs-at-risk for head-and-neck radiotherapy treatment planning.

Introduction: Organ-at-risk segmentation for head and neck cancer radiation therapy is a complex and time-consuming process (requiring up to 42 individual structure, and may delay start of treatment or even limit access to function-preserving care. Feasibility of using a deep learning (DL) based autosegmentation model to reduce contouring time without compromising contour accuracy is assessed through a blinded randomized trial of radiation oncologists (ROs) using retrospective, de-identified patient data. Methods: Two head and neck expert ROs used dedicated time to create gold standard (GS) contours on computed tomography (CT) images. 445 CTs were used to train a custom 3D U-Net DL model covering 42 organs-at-risk, with an additional 20 CTs were held out for the randomized trial. For each held-out patient dataset, one of the eight participant ROs was randomly allocated to review and revise the contours produced by the DL model, while another reviewed contours produced by a medical dosimetry assistant (MDA), both blinded to their origin. Time required for MDAs and ROs to contour was recorded, and the unrevised DL contours, as well as the RO-revised contours by the MDAs and DL model were compared to the GS for that patient. Results: Mean time for initial MDA contouring was 2.3 hours (range 1.6-3.8 hours) and RO-revision took 1.1 hours (range, 0.4-4.4 hours), compared to 0.7 hours (range 0.1-2.0 hours) for the RO-revisions to DL contours. Total time reduced by 76% (95%-Confidence Interval: 65%-88%) and RO-revision time reduced by 35% (95%-CI,-39%-91%). All geometric and dosimetric metrics computed, agreement with GS was equivalent or significantly greater (p<0.05) for RO-revised DL contours compared to the RO-revised MDA contours, including volumetric Dice similarity coefficient (VDSC), surface DSC, added path length, and the 95%-Hausdorff distance. 32 OARs (76%) had mean VDSC greater than 0.8 for the RO-revised DL contours, compared to 20 (48%) for RO-revised MDA contours, and 34 (81%) for the unrevised DL OARs. Conclusion: DL autosegmentation demonstrated significant time-savings for organ-at-risk contouring while improving agreement with the institutional GS, indicating comparable accuracy of DL model. Integration into the clinical practice with a prospective evaluation is currently underway.

Quality assurance for image-guided radiation therapy utilizing CT-based technologies: a report of the AAPM TG-179.

PURPOSE: Commercial CT-based image-guided radiotherapy (IGRT) systems allow widespread management of geometric variations in patient setup and internal organ motion. This document provides consensus recommendations for quality assurance protocols that ensure patient safety and patient treatment fidelity for such systems. METHODS: The AAPM TG-179 reviews clinical implementation and quality assurance aspects for commercially available CT-based IGRT, each with their unique capabilities and underlying physics. The systems described are kilovolt and megavolt cone-beam CT, fan-beam MVCT, and CT-on-rails. A summary of the literature describing current clinical usage is also provided. RESULTS: This report proposes a generic quality assurance program for CT-based IGRT systems in an effort to provide a vendor-independent program for clinical users. Published data from long-term, repeated quality control tests form the basis of the proposed test frequencies and tolerances. CONCLUSION: A program for quality control of CT-based image-guidance systems has been produced, with focus on geometry, image quality, image dose, system operation, and safety. Agreement and clarification with respect to reports from the AAPM TG-101, TG-104, TG-142, and TG-148 has been addressed.

A local shift-variant Fourier model and experimental validation of circular cone-beam computed tomography artifacts.

Large field of view cone-beam computed tomography (CBCT) is being achieved using circular source and detector trajectories. These circular trajectories are known to collect insufficient data for accurate image reconstruction. Although various descriptions of the missing information exist, the manifestation of this lack of data in reconstructed images is generally nonintuitive. One model predicts that the missing information corresponds to a shift-variant cone of missing frequency components. This description implies that artifacts depend on the imaging geometry, as well as the frequency content of the imaged object. In particular, objects with a large proportion of energy distributed over frequency bands that coincide with the missing cone will be most compromised. These predictions were experimentally verified by imaging small, localized objects (acrylic spheres, stacked disks) at varying positions in the object space and observing the frequency spectrums of the reconstructions. Measurements of the internal angle of the missing cone agreed well with theory, indicating a right circular cone for points on the rotation axis, and an oblique, circular cone elsewhere. In the former case, the largest internal angle with respect to the vertical axis corresponds to the (half) cone angle of the CBCT system (typically approximately 5 degrees - 7.5 degrees in IGRT). Object recovery was also found to be strongly dependent on the distribution of the object's frequency spectrum relative to the missing cone, as expected. The observed artifacts were also reproducible via removal of local frequency components, further supporting the theoretical model. Larger objects with differing internal structures (cellular polyurethane, solid acrylic) were also imaged and interpreted with respect to the previous results. Finally, small animal data obtained using a clinical CBCT scanner were observed for evidence of the missing cone. This study provides insight into the influence of incomplete data collection on the appearance of objects imaged in large field of view CBCT.

Novel dosimetric phantom for quality assurance of volumetric modulated arc therapy.

The objective of this work is to assess the suitability and performance of a new dosimeter system with a novel geometry for the quality assurance (QA) of volumetric modulated arc therapy (VMAT). The new dosimeter system consists of a hollow cylinder (15 and 25 cm inner and outer diameters) with 124 diodes embedded in the phantom's cylindrical wall forming four rings of detectors. For coplanar beams, the cylindrical geometry and the ring diode pattern offer the advantage of invariant perpendicular incidence on the beam central axis for any gantry angle and also have the benefit of increasing the detector density as both walls of the cylinder sample the beam. Other advantages include real-time readout and reduced weight with the hollow phantom shape. A calibration method taking into account the variation in radiation sensitivity of the diodes as a function of gantry angle was developed and implemented. In this work, the new dosimeter system was used in integrating mode to perform composite dose measurements along the cylindrical surface supporting the diodes. The reproducibility of the dosimeter response and the angular dependence of the diodes were assessed using simple 6 MV photon static beams. The performance of the new dosimeter system for VMAT QA was then evaluated using VMAT plans designed for a head and neck, an abdominal sarcoma, and a prostate patient. These plans were optimized with 90 control points (CPs) and additional versions of each plan were generated by increasing the number of CPs to 180 and 360 using linear interpolation. The relative dose measured with the dosimeter system for the VMAT plans was compared to the corresponding TPS dose map in terms of relative dose difference (% deltaD) and distance to agreement (DTA). The dosimeter system's sensitivity to gantry rotation offset and scaling errors as well as setup errors was also evaluated. For static beams, the dosimeter system offered good reproducibility and demonstrated small residual diode angular dependence after calibration. For VMAT deliveries, the agreement between measured and calculated doses was good with > or = 86.4% of the diodes satisfying 3% of % deltaD or 2 mm DTA for the 180 CP plans. The phantom offered sufficient sensitivity for the detection of small gantry rotation offset (3 degrees) and scaling errors (1 degree) as well as phantom setup errors of 1 mm, although the results were plan dependent. With its novel geometry, the dosimeter system was also able to experimentally demonstrate the discretization effect of the number of CPs used in the TPS to simulate a continuous arc. These results demonstrate the suitability of the new dosimeter system for the patient-specific QA of VMAT plans and suggest that the dosimeter system can be an effective tool in the routine QA and commissioning of treatment machines capable of VMAT delivery and cone-beam CT image guidance.

2D-3D registration for prostate radiation therapy based on a statistical model of transmission images.

PURPOSE: In external beam radiation therapy of pelvic sites, patient setup errors can be quantified by registering 2D projection radiographs acquired during treatment to a 3D planning computed tomograph (CT). We present a 2D-3D registration framework based on a statistical model of the intensity values in the two imaging modalities. METHODS: The model assumes that intensity values in projection radiographs are independently but not identically distributed due to the nonstationary nature of photon counting noise. Two probability distributions are considered for the intensity values: Poisson and Gaussian. Using maximum likelihood estimation, two similarity measures, maximum likelihood with a Poisson (MLP) and maximum likelihood with Gaussian (MLG), distribution are derived. Further, we investigate the merit of the model-based registration approach for data obtained with current imaging equipment and doses by comparing the performance of the similarity measures derived to that of the Pearson correlation coefficient (ICC) on accurately collected data of an anthropomorphic phantom of the pelvis and on patient data. RESULTS: Registration accuracy was similar for all three similarity measures and surpassed current clinical requirements of 3 mm for pelvic sites. For pose determination experiments with a kilovoltage (kV) cone-beam CT (CBCT) and kV projection radiographs of the phantom in the anterior-posterior (AP) view, registration accuracies were 0.42 mm (MLP), 0.29 mm (MLG), and 0.29 mm (ICC). For kV CBCT and megavoltage (MV) AP portal images of the same phantom, registration accuracies were 1.15 mm (MLP), 0.90 mm (MLG), and 0.69 mm (ICC). Registration of a kV CT and MV AP portal images of a patient was successful in all instances. CONCLUSIONS: The results indicate that high registration accuracy is achievable with multiple methods including methods that are based on a statistical model of a 3D CT and 2D projection images.

Accuracy of automatic couch corrections with on-line volumetric imaging.

The purpose of this study was to characterize automatic remote couch adjustment and to assess the accuracy of automatic couch corrections following localization with cone-beam CT (CBCT). Automatic couch movement was evaluated through passive reflector markers placed on a phantom, tracked with an optical tracking system (OTS). Repeated couch movements in the lateral, cranial/caudal, and vertical directions were monitored through the OTS to assess velocity and response time. In conjunction with CBCT, remote table movement for patient displacements following initial setup was available on four linear accelerators (Elekta Synergy). After the initial CBCT scan assessment, patients with isocenter displacements that exceeded clinical protocol tolerances were corrected using remote automatic couch movement. A verification CBCT scan was acquired after any remote movements. These verification CBCT datasets were assessed for the following time periods: one month post clinical installation, and six months later to monitor remote couch correction stability. Residual error analysis was evaluated using the verification scans. The mean +/- standard deviations (mu +/- sigma) of couch movement based on phantom measurements with the OTS were 0.16 +/- 0.48 mm, 0.32 +/- 0.30 mm, 0.11 +/- 0.12 mm in the L/R, A/P, and S/I couch directions, respectively. The fastest maximum velocity was observed in the inferior direction at 10.5 mm/s, and the slowest maximum velocity in the left direction at 3.6 mm/s. From 1134 verification CBCT registrations for 207 patients, the residual error for each translational direction from each month evaluated are reported. The mu was less than 0.3 mm in all directions, and sigma was in the order of 1 mm. At a 3 mm threshold, 21 of the 1134 fractions (2%) exceeded tolerance, attributed to patient intrafraction movement. Remote automatic couch movement is reliable and effective for adjusting patient position with a precision of approximately 1mm. Patient residual error observed in this study demonstrates that displacement is minimal after remote couch adjustment.

Palliation of Vertebral Metastases with Radiotherapy: Exploration of Volumetric-Modulated Arc Therapy From Development to Implementation in Routine Clinical Practice.

The development of volumetric-modulated arc therapy (VMAT) in radiation therapy has allowed for improved dose escalation and a decrease in radiation-induced toxicities for patients. This article will describe a single centre's experience in development and implementation of VMAT for palliation of vertebral metastases. A retrospective planning analysis of 10 cases identified that utilization of VMAT decreases overall planning time with a statistically significant improvement in target coverage when compared with the current conventional technique. PTV Dmax (P = .02), PTV V9519Gy (95%) (P = .01), dose conformation (P = 1.8e-004), and the homogeneity index (P = .019) were all superior for VMAT plans with an average PTV length of 22.46 cm. Another benefit of VMAT utilization is a significant decrease in treatment delivery time, which reduced treatment times from 9.95 minutes to 2.98 minutes. Immobilization was also carefully considered, and rotational errors were measured and fell within institutional tolerances when VMAT was delivered using simple immobilization devices. Clinical implementation of this technique, utilizing a highly conformal target volume to decrease radiation-induced toxicities and minimizing the length of time patients are required to maintain their treatment positions, aims to improve the palliative radiotherapy experience for patients with painful spinal metastases.

Development of a Collaboration Model between Two Cancer Centres to Maintain Patient Access to Radiation Therapy during the Replacement of a Sole CT Simulator at a Regional Cancer Centre.

INTRODUCTION: Replacement of a sole computed tomography (CT) simulator at a Regional Cancer Centre risks interruption of patient access to radiation therapy clinical services. This study reports a collaboration model between two cancer centres to maintain patient access to radiation therapy during the replacement period. METHODS: Representatives from each cancer centre collaborated to plan and facilitate offsite CT simulation. Activities required were identified and included process coordination, patient consent, patient registration, requisitions, appointment bookings, immobilization equipment, staffing strategy, clinical practice protocols, data transfer, and cost recovery. The logistics of each activity were planned and mapped, with roles identified to perform each activity. During the 2-week replacement duration, from April 30 to May 11, 2018, patients consulted for radiotherapy were offered offsite CT simulation. RESULTS: A detailed process was developed to outline the flow of activities for successful coordination of offsite CT simulations. A total of 14 patients consented to radiation treatment during the CT simulator replacement downtime, of which 8 patients agreed to offsite CT simulation. A total of 11 body regions were simulated for the 8 patients. CT images acquired offsite were electronically transferred to the primary cancer centre to proceed with treatment planning and delivery. DISCUSSION: A collaboration model between two cancer centres was successfully developed and implemented to maintain patient access to radiation therapy during the replacement of a sole CT simulator at a regional cancer centre. CONCLUSION: This strategy and process developed could be valuable for future major equipment upgrades/replacements at other centres.

A quality assurance program for image quality of cone-beam CT guidance in radiation therapy.

The clinical introduction of volumetric x-ray image-guided radiotherapy systems necessitates formal commissioning of the hardware and image-guided processes to be used and drafts quality assurance (QA) for both hardware and processes. Satisfying both requirements provides confidence on the system's ability to manage geometric variations in patient setup and internal organ motion. As these systems become a routine clinical modality, the authors present data from their QA program tracking the image quality performance of ten volumetric systems over a period of 3 years. These data are subsequently used to establish evidence-based tolerances for a QA program. The volumetric imaging systems used in this work combines a linear accelerator with conventional x-ray tube and an amorphous silicon flat-panel detector mounted orthogonally from the accelerator central beam axis, in a cone-beam computed tomography (CBCT) configuration. In the spirit of the AAPM Report No. 74, the present work presents the image quality portion of their QA program; the aspects of the QA protocol addressing imaging geometry have been presented elsewhere. Specifically, the authors are presenting data demonstrating the high linearity of CT numbers, the uniformity of axial reconstructions, and the high contrast spatial resolution of ten CBCT systems (1-2 mm) from two commercial vendors. They are also presenting data accumulated over the period of several months demonstrating the long-term stability of the flat-panel detector and of the distances measured on reconstructed volumetric images. Their tests demonstrate that each specific CBCT system has unique performance. In addition, scattered x rays are shown to influence the imaging performance in terms of spatial resolution, axial reconstruction uniformity, and the linearity of CT numbers.

Statistical process control for IMRT dosimetric verification.

Patient-specific measurements are typically used to validate the dosimetry of intensity-modulated radiotherapy (IMRT). To evaluate the dosimetric performance over time of our IMRT process, we have used statistical process control (SPC) concepts to analyze the measurements from 330 head and neck (H&N) treatment plans. The objectives of the present work are to: (i) Review the dosimetric measurements of a large series of consecutive head and neck treatment plans to better understand appropriate dosimetric tolerances; (ii) analyze the results with SPC to develop action levels for measured discrepancies; (iii) develop estimates for the number of measurements that are required to describe IMRT dosimetry in the clinical setting; and (iv) evaluate with SPC a new beam model in our planning system. H&N IMRT cases were planned with the PINNACLE treatment planning system versions 6.2b or 7.6c (Philips Medical Systems, Madison, WI) and treated on Varian (Palo Alto, CA) or Elekta (Crawley, UK) linacs. As part of regular quality assurance, plans were recalculated on a 20-cm-diam cylindrical phantom, and ion chamber measurements were made in high-dose volumes (the PTV with highest dose) and in low-dose volumes (spinal cord organ-at-risk, OR). Differences between the planned and measured doses were recorded as a percentage of the planned dose. Differences were stable over time. Measurements with PINNACLE3 6.2b and Varian linacs showed a mean difference of 0.6% for PTVs (n=149, range, -4.3% to 6.6%), while OR measurements showed a larger systematic discrepancy (mean 4.5%, range -4.5% to 16.3%) that was due to well-known limitations of the MLC model in the earlier version of the planning system. Measurements with PINNACLE3 7.6c and Varian linacs demonstrated a mean difference of 0.2% for PTVs (n=160, range, -3.0%, to 5.0%) and -1.0% for ORs (range -5.8% to 4.4%). The capability index (ratio of specification range to range of the data) was 1.3 for the PTV data, indicating that almost all measurements were within +/-5%. We have used SPC tools to evaluate a new beam model in our planning system to produce a systematic difference of -0.6% for PTVs and 0.4% for ORs, although the number of measurements is smaller (n=25). Analysis of this large series of H&N IMRT measurements demonstrated that our IMRT dosimetry was stable over time and within accepted tolerances. These data provide useful information for assessing alterations to beam models in the planning system. IMRT is enhanced by the addition of statistical process control to traditional quality control procedures.

Automated 2D-3D registration of portal images and CT data using line-segment enhancement.

In prostate radiotherapy, setup errors with respect to the patient's bony anatomy can be reduced by aligning 2D megavoltage (MV) portal images acquired during treatment to a reference 3D kilovoltage (kV) CT acquired for treatment planning purposes. The purpose of this study was to evaluate a fully automated 2D-3D registration algorithm to quantify setup errors in 3D through the alignment of line-enhanced portal images and digitally reconstructed radiographs computed from the CT. The line-enhanced images were obtained by correlating the images with a filter bank of short line segments, or "sticks" at different orientations. The proposed methods were validated on (1) accurately collected gold-standard data consisting of a 3D kV cone-beam CT scan of an anthropomorphic phantom of the pelvis and 2D MV portal images in the anterior-posterior (AP) view acquired at 15 different poses and (2) a conventional 3D kV CT scan and weekly 2D MV AP portal images of a patient over 8 weeks. The mean (and standard deviation) of the absolute registration error for rotations around the right-lateral (RL), inferior-superior (IS), and posterior-anterior (PA) axes were 0.212 degree (0.214 degree), 0.055 degree (0.033 degree) and 0.041 degree (0.039 degree), respectively. The corresponding registration errors for translations along the RL, IS, and PA axes were 0.161 (0.131) mm, 0.096 (0.033) mm, and 0.612 (0.485) mm. The mean (and standard deviation) of the total registration error was 0.778 (0.543) mm. Registration on the patient images was successful in all eight cases as determined visually. The results indicate that it is feasible to automatically enhance features in MV portal images of the pelvis for use within a completely automated 2D-3D registration framework for the accurate determination of patient setup errors. They also indicate that it is feasible to estimate all six transformation parameters from a 3D CT of the pelvis and a single portal image in the AP view.

A dual modality phantom for cone beam CT and ultrasound image fusion in prostate implant.

In transrectal ultrasound (TRUS) guided prostate seed brachytherapy, TRUS provides good delineation of the prostate while x-ray imaging, e.g., C-arm, gives excellent contrast for seed localization. With the recent availability of cone beam CT (CBCT) technology, the combination of the two imaging modalities may provide an ideal system for intraoperative dosimetric feedback during implantation. A dual modality phantom made of acrylic and copper wire was designed to measure the accuracy and precision of image coregistration between a C-arm based CBCT and 3D TRUS. The phantom was scanned with TRUS and CBCT under the same setup condition. Successive parallel transverse ultrasound (US) images were acquired through manual stepping of the US probe across the phantom at an increment of 1 mm over 7.5 cm. The CBCT imaging was done with three reconstructed slice thicknesses (0.4, 0.8, and 1.6 mm) as well as at three different tilt angles (0 degrees, 15 degrees, 30 degrees), and the coregistration between CBCT and US images was done using the Variseed system based on four fiducial markers. Fiducial localization error (FLE), fiducial registration error (FRE), and target registration error (TRE) were calculated for all registered image sets. Results showed that FLE were typically less than 0.4 mm, FRE were less than 0.5 mm, and TRE were typically less than 1 mm within the range of operation for prostate implant (i.e., < 6 cm to surface of US probe). An analysis of variance test showed no significant difference in TRE for the CBCT-US fusion among the three slice thicknesses (p = 0.37). As a comparison, the experiment was repeated with a US-conventional CT scanner combination. No significant difference in TRE was noted between the US-conventional CT fusion and that for all three CBCT image slice thicknesses (p = 0.21). CBCT imaging was also performed at three different C-arm tilt angles of 0 degrees, 15 degrees and 30 degrees and reconstructed at a slice thickness of 0.8 mm. There is no significant difference in TRE between 0 degrees and 15 degrees (p = 0.191) as well as between 0 degrees and 30 degrees (p = 0.275), which suggests that the C-arm may be tilted intraoperatively to acquire CBCT images without compromising the quality of image fusion. The results conclude a high degree of accuracy and precision for the CBCT-TRUS fusion, which could be useful toward achieving real time intraoperative dosimetry in prostate brachytherapy.

Clinical implementation of prostate image guided radiation therapy: a prospective study to define the optimal field of interest and image registration technique using automated x-ray volumetric imaging software.

Alignment of the CBCT with the reference CT is called image registration (IR). The parameters for utilizing the automated Elekta XVI IR software for IGRT of the prostate still remain to be defined. In this study, we compare several automated XVI IR parameters to manual registration to identify the optimal automated IR technique for the prostate gland. 280 prostate IRs were conducted as follows: 210 automated, and 70 manual IR were performed using 70 CBCT scans of seven patients. The three arms of the automated registrations were: (i) extended FOI/Bone + grey scale (double IR); (ii) limited FOI/GS (single IR); and (iii) extended FOI/GS (single IR). Automated IRs were compared to manual IRs; x, y, z shifts, failures, and errors recorded for off-line analysis. Based on the most successful parameters, a departmental protocol was developed and 432 automated IR were performed (on 20 patients) for analysis. Automated IR were classified as: Successful, failed, error, or unregistered. In arm 1, the rate of successful, failed, error, and unregistered IR were 52.8%, 1.5%, 8.6%, 37.1%, respectively, arm 2: 90% successful, 10% failed, arm 3: 100% successful. Using the arm 3 parameters for the 432 automated IRs, the incidence of unregistered scans was 0%, rescanning was required in 1% of treatments, and the time for performing the auto IR was < 5.5 minutes. We found that extended FOI + single (GS) IR results in shifts comparable to manual IR using automated XVI software. We experienced multiple unsuccessful registrations with the other methods. We conclude that when utilizing the Elekta XVI automated IR software, the extended FOI/single IR results in successful registrations most often. In addition, it is currently effectively used in our clinical practice.

Improving image-guided target localization through deformable registration.

PURPOSE: To quantify the improvements in online target localization using kV cone beam CT (CBCT) with deformable registration. METHODS AND MATERIAL: Twelve patients treated under a 6 fraction liver cancer radiation therapy protocol were imaged in breath hold using kV CBCT at each treatment fraction. The images were imported into the treatment planning software and rigidly registered by fitting the liver, identified on the daily kV CBCT image, into the liver contours, previously drawn on the planning CT. The liver was then manually contoured on each CBCT image. Deformable registration was automatically performed, aligning the CT liver to the liver on each CBCT image using MORFEUS, a biomechanical model based deformable registration algorithm. The tumor, defined on planning CT, was mapped onto the CBCT, through MORFEUS. The center of mass (COM) displacement of the tumor was computed. RESULTS: The mean (SD) displacement magnitude (absolute value) of the COM following deformable registration was 0.08 (0.07), 0.10 (0.11), and 0.10 (0.17) cm in the left-right (LR), anterior-posterior (AP), and superior-inferior (SI) directions, respectively. The maximum displacement of the COM was 0.34, 0.65, and 0.97 cm in the LR, AP, and SI directions, respectively. Fifteen percent of the treatment fractions had a COM displacement of greater than 0.3 cm and 33% of patients had at least 1 fraction with a displacement of greater than 0.3 cm. The deformable registration, excluding the manual contouring of the liver, was performed in less than 1 minute, on average. DISCUSSION: Rigid registration of the liver volume between planning CT and verification kV CBCT localizes the tumor to within 0.3 cm for the majority (66%) of patients; however, larger offsets in tumor position can be observed due to liver deformation.