Conjoint Professor Peter Greer

© 2017 The Authors. Machine Performance Check (MPC) is an automated and integrated image-based tool for verification of beam and geometric performance of the TrueBeam linac. The aims of the study were to evaluate the MPC beam performance tests against current daily quality assurance (QA) methods, to compare MPC performance against more accurate monthly QA tests and to test the sensitivity of MPC to changes in beam performance. The MPC beam constancy checks test the beam output, uniformity, and beam center against the user defined baseline. MPC was run daily over a period of 5 months (n = 115) in parallel with the Daily QA3 device. Additionally, IC Profiler, in-house EPID tests, and ion chamber measurements were performed biweekly and results presented in a form directly comparable to MPC. The sensitivity of MPC was investigated using controlled adjustments of output, beam angle, and beam position steering. Over the period, MPC output agreed with ion chamber to within 0.6%. For an output adjustment of 1.2%, MPC was found to agree with ion chamber to within 0.17%. MPC beam center was found to agree with the in-house EPID method within 0.1 mm. A focal spot position adjustment of 0.4 mm (at isocenter) was measured with MPC beam center to within 0.01 mm. An average systematic offset of 0.5% was measured in the MPC uniformity and agreement of MPC uniformity with symmetry measurements was found to be within 0.9% for all beams. MPC uniformity detected a change in beam symmetry of 1.5% to within 0.3% and 0.9% of IC Profiler for flattened and FFF beams, respectively.

© Creative Commons Attribution 3.0 Unported License.Multileaf collimator (MLC) positions should be precisely and independently measured as a function of gantry angle as part of a comprehensive quality assurance (QA) program for volumetric-modulated arc therapy (VMAT). It is also ideal that such a QA program has the ability to relate MLC positional accuracy to patient-specific dosimetry in order to determine the clinical significance of any detected MLC errors. In this work we propose a method to verify individual MLC trajectories during VMAT deliveries for use as a routine linear accelerator QA tool. We also extend this method to reconstruct the 3D patient dose in the treatment planning system based on the measured MLC trajectories and the original DICOM plan file. The method relies on extracting MLC positions from EPID images acquired at 8.41fps during clinical VMAT deliveries. A gantry angle is automatically tagged to each image in order to obtain the MLC trajectories as a function of gantry angle. This analysis was performed for six clinical VMAT plans acquired at monthly intervals for three months. The measured trajectories for each delivery were compared to the MLC positions from the DICOM plan file. The maximum mean error detected was 0.07 mm and a maximum root-mean-square error was 0.8 mm for any leaf of any delivery. The sensitivity of this system was characterized by introducing random and systematic MLC errors into the test plans. It was demonstrated that the system is capable of detecting random and systematic errors on the range of 1-2mm and single leaf calibration errors of 0.5 mm. The methodology developed in the work has potential to be used for efficient routine linear accelerator MLC QA and pretreatment patient-specific QA and has the ability to relate measured MLC positional errors to 3D dosimetric errors within a patient volume.

We proposed to perform a basic dosimetry commissioning on a new imager system, the Varian aS1200 electronic portal imaging device (EPID) and TrueBeam 2.0 linear accelerator for flattened (FF) and flattening filter-free (FFF) beams, then to develop an image-based quality assurance (QA) model for verification of the system delivery accuracy for intensity-modulated radiation therapy (IMRT) treatments. For dosimetry testing, linearity of dose response with MU, imager lag, and effectiveness of backscatter shielding were investigated. Then, an image-based model was developed to convert images to planar dose onto a virtual water phantom. The model parameters were identified using energy fluence of the Acuros treatment planning system (TPS) and, reference dose profiles and output factors measured at depths of 5, 10, 15, and 20 cm in water phantom for square fields. To validate the model, its calculated dose was compared to measured dose from MapCHECK 2 diode arrays for 36 IMRT fields at 10 cm depth delivered with 6X, 6XFFF, 10X, and 10XFFF energies. An in-house gamma function was used to compare planar doses pixel-by-pixel. Finally, the method was applied to the same IMRT fields to verify their pretreatment delivery dose compared with Eclipse TPS dose. For the EPID commissioning, dose linearity was within 0.4% above 5 MU and ~ 1% above 2 MU, measured lag was smaller than the previous EPIDs, and profile symmetry was improved. The model was validated with mean gamma pass rates (standard deviation) of 99.0% (0.4%), 99.5% (0.6%), 99.3% (0.4%), and 98.0% (0.8%) at 3%/3 mm for respectively 6X, 6XFFF, 10X, and 10XFFF beams. Using the same comparison criteria, the beam deliveries were verified with mean pass rates of 100% (0.0%), 99.6% (0.3%), 99.9% (0.1%), and 98.7% (1.4%). Improvements were observed in dosimetric response of the aS1200 imager compared to previous EPID models, and the model was successfully developed for the new system and delivery energies of 6 and 10 MV, FF, and FFF modes.

© 2016 American Association of Physicists in Medicine.Purpose: The dynamic keyhole is a newMRimage reconstruction method for thoracic and abdominal MR imaging. To date, this method has not been investigated with cancer patient magnetic resonance imaging (MRI) data. The goal of this study was to assess the dynamic keyhole method for the task of lung tumor localization using cine-MR images reconstructed in the presence of respiratory motion. Methods: The dynamic keyhole method utilizes a previously acquired a library of peripheral k-space datasets at similar displacement and phase (where phase is simply used to determine whether the breathing is inhale to exhale or exhale to inhale) respiratory bins in conjunction with central k-space datasets (keyhole) acquired. External respiratory signals drive the process of sorting, matching, and combining the two k-space streams for each respiratory bin, thereby achieving faster image acquisition without substantial motion artifacts. This study was the first that investigates the impact of k-space undersampling on lung tumor motion and area assessment across clinically available techniques (zero-filling and conventional keyhole). In this study, the dynamic keyhole, conventional keyhole and zero-filling methods were compared to full k-space dataset acquisition by quantifying (1) the keyhole size required for central k-space datasets for constant image quality across sixty four cine-MRI datasets from nine lung cancer patients, (2) the intensity difference between the original and reconstructed images in a constant keyhole size, and (3) the accuracy of tumor motion and area directly measured by tumor autocontouring. Results: For constant image quality, the dynamic keyhole method, conventional keyhole, and zerofilling methods required 22%, 34%, and 49% of the keyhole size (P < 0.0001), respectively, compared to the full k-space image acquisition method. Compared to the conventional keyhole and zero-filling reconstructed images with the keyhole size utilized in the dynamic keyhole method, an average intensity difference of the dynamic keyhole reconstructed images (P < 0.0001) was minimal, and resulted in the accuracy of tumor motion within 99.6% (P < 0.0001) and the accuracy of tumor area within 98.0% (P < 0.0001) for lung tumor monitoring applications. Conclusions: This study demonstrates that the dynamic keyhole method is a promising technique for clinical applications such as image-guided radiation therapy requiring the MR monitoring of thoracic tumors. Based on the results from this study, the dynamic keyhole method could increase the imaging frequency by up to a factor of five compared with full k-space methods for real-time lung tumor MRI.

© 2017 The Authors on behalf of the American Society for Radiation Oncology. Purpose: Respiratory variation can increase the variability of tumor position and volume, accounting for larger treatment margins and longer treatment times. Audiovisual biofeedback as a breath-hold technique could be used to improve the reproducibility of lung tumor positions at inhalation and exhalation for the radiation therapy of mobile lung tumors. This study aimed to assess the impact of audiovisual biofeedback breath-hold (AVBH) on interfraction lung tumor position reproducibility and volume consistency for respiratory-gated lung cancer radiation therapy. Methods: Lung tumor position and volume were investigated in 9 patients with lung cancer who underwent a breath-hold training session with AVBH before 2 magnetic resonance imaging (MRI) sessions. During the first MRI session (before treatment), inhalation and exhalation breath-hold 3-dimensional MRI scans with conventional breath-hold (CBH) using audio instructions alone and AVBH were acquired. The second MRI session (midtreatment) was repeated within 6 weeks after the first session. Gross tumor volumes (GTVs) were contoured on each dataset. CBH and AVBH were compared in terms of tumor position reproducibility as assessed by GTV centroid position and position range (defined as the distance of GTV centroid position between inhalation and exhalation) and tumor volume consistency as assessed by GTV between inhalation and exhalation. Results: Compared with CBH, AVBH improved the reproducibility of interfraction GTV centroid position by 46% (P = .009) from 8.8 mm to 4.8 mm and GTV position range by 69% (P = .052) from 7.4 mm to 2.3 mm. Compared with CBH, AVBH also improved the consistency of intrafraction GTVs by 70% (P = .023) from 7.8 cm 3 to 2.5 cm 3 . Conclusions: This study demonstrated that audiovisual biofeedback can be used to improve the reproducibility and consistency of breath-hold lung tumor position and volume, respectively. These results may provide a pathway to achieve more accurate lung cancer radiation treatment in addition to improving various medical imaging and treatments by using breath-hold procedures.

© 2016 Institute of Physics and Engineering in Medicine.In-room cine-MRI guidance can provide non-invasive target localization during radiotherapy treatment. However, in order to cope with finite imaging frequency and system latencies between target localization and dose delivery, tumour motion prediction is required. This work proposes a framework for motion prediction dedicated to cine-MRI guidance, aiming at quantifying the geometric uncertainties introduced by this process for both tumour tracking and beam gating. The tumour position, identified through scale invariant features detected in cine-MRI slices, is estimated at high-frequency (25 Hz) using three independent predictors, one for each anatomical coordinate. Linear extrapolation, auto-regressive and support vector machine algorithms are compared against systems that use no prediction or surrogate-based motion estimation. Geometric uncertainties are reported as a function of image acquisition period and system latency. Average results show that the tracking error RMS can be decreased down to a [0.2; 1.2] mm range, for acquisition periods between 250 and 750 ms and system latencies between 50 and 300 ms. Except for the linear extrapolator, tracking and gating prediction errors were, on average, lower than those measured for surrogate-based motion estimation. This finding suggests that cine-MRI guidance, combined with appropriate prediction algorithms, could relevantly decrease geometric uncertainties in motion compensated treatments.

© 2016 Institute of Physics and Engineering in Medicine. Active shape models (ASMs) have proved successful in automatic segmentation by using shape and appearance priors in a number of areas such as prostate segmentation, where accurate contouring is important in treatment planning for prostate cancer. The ASM approach however, is heavily reliant on a good initialisation for achieving high segmentation quality. This initialisation often requires algorithms with high computational complexity, such as three dimensional (3D) image registration. In this work, we present a fast, self-initialised ASM approach that simultaneously fits multiple objects hierarchically controlled by spatially weighted shape learning. Prominent objects are targeted initially and spatial weights are progressively adjusted so that the next (more difficult, less visible) object is simultaneously initialised using a series of weighted shape models. The scheme was validated and compared to a multi-atlas approach on 3D magnetic resonance (MR) im ages of 38 cancer patients and had the same (mean, median, inter-rater) Dice's similarity coefficients of (0.79, 0.81, 0.85), while having no registration error and a computational time of 12-15 min, nearly an order of magnitude faster than the multi-atlas approach.

© Creative Commons Attribution 4.0 International License.In VMAT treatment delivery the ability of the linear accelerator (linac) to accurately control dose versus gantry angle is critical to delivering the plan correctly. A new VMAT test delivery was developed to specifically test the dose versus gantry angle with the full range of allowed gantry speeds and dose rates. The gantry-mounted IBA MatriXX with attached inclinometer was used in movie mode to measure the instantaneous relative dose versus gantry angle during the plan every 0.54 s. The results were compared to the expected relative dose at each gantry angle calculated from the plan. The same dataset was also used to compare the instantaneous gantry speeds throughout the delivery compared to the expected gantry speeds from the plan. Measurements performed across four linacs generally show agreement between measurement and plan to within 1.5% in the constant dose rate regions and dose rate modulation within 0.1 s of the plan. Instantaneous gantry speed was measured to be within 0.11°/s of the plan (1 SD). An error in one linac was detected in that the nominal gantry speed was incorrectly calibrated. This test provides a practical method to quality-assure critical aspects of VMAT delivery including dose versus gantry angle and gantry speed control. The method can be performed with any detector that can acquire time-resolved dosimetric information that can be synchronized with a measurement of gantry angle. The test fulfils several of the aims of the recent Netherlands Commission on Radiation Dosimetry (NCS) Report 24, which provides recommendations for comprehensive VMAT quality assurance.

In volumetric-modulated arc therapy (VMAT) treatment delivery perfect beam symmetry is assumed by the planning system. This study aims to test this assumption and present a method of measuring time-resolved beam symmetry measurement during a VMAT delivery that includes extreme variations of dose rate and gantry speed. The Sun Nuclear IC Profiler in gantry mount was used to measure time-resolved in-plane and cross-plane profiles during plan delivery from which symmetry could be determined. Time-resolved symmetry measurements were performed throughout static field exposures at cardinal gantry angles, conformal arcs with constant dose rate and gantry speed, and during a VMAT test plan with gantry speed and dose rate modulation. Measurements were performed for both clockwise and counterclockwise gantry rotation and across four Varian 21iX lin-acs. The symmetry was found to be generally constant throughout the static field exposures to within 0.3% with an exception on one linac of up to 0.7%. Agreement in symmetry between cardinal angles was always within 1.0% and typically within 0.6%. During conformal arcs the results for clockwise and counterclockwise rotation were in agreement to within 0.3%. Both clockwise and counterclockwise tended to vary in similar manner by up to 0.5% during arc consistent with the cardinal gantry angle static field results. During the VMAT test plan the symmetry generally was in agreement with the conformal arc results. Greater variation in symmetry was observed in the low-dose-rate regions by up to 1.75%. All results were within clinically acceptable levels using the tolerances of NCS Report 24 (2015).

© 2016 American Association of Physicists in Medicine. Purpose: The feasibility of radiation therapy treatment planning using substitute computed tomography (sCT) generated from magnetic resonance images (MRIs) has been demonstrated by a number of research groups. One challenge with an MRI-alone workflow is the accurate identification of intraprostatic gold fiducial markers, which are frequently used for prostate localization prior to each dose delivery fraction. This paper investigates a template-matching approach for the detection of these seeds in MRI. Methods: Two different gradient echo T1 and T2* weighted MRI sequences were acquired from fifteen prostate cancer patients and evaluated for seed detection. For training, seed templates from manual contours were selected in a spectral clustering manifold learning framework. This aids in clustering "similar" gold fiducial markers together. The marker with the minimum distance to a cluster centroid was selected as the representative template of that cluster during training. During testing, Gaussian mixture modeling followed by a Markovian model was used in automatic detection of the probable candidates. The probable candidates were rigidly registered to the templates identified from spectral clustering, and a similarity metric is computed for ranking and detection. Results: A fiducial detection accuracy of 95% was obtained compared to manual observations. Expert radiation therapist observers were able to correctly identify all three implanted seeds on 11 of the 15 scans (the proposed method correctly identified all seeds on 10 of the 15). Conclusions: An novel automatic framework for gold fiducial marker detection in MRI is proposed and evaluated with detection accuracies comparable to manual detection. When radiation therapists are unable to determine the seed location in MRI, they refer back to the planning CT (only available in the existing clinical framework); similarly, an automatic quality control is built into the automatic software to ensure that all gold seeds are either correctly detected or a warning is raised for further manual intervention.

© 2015 American Association of Physicists in Medicine.Purpose: Radiation treatments are trending toward delivering higher doses per fraction under stereotactic radiosurgery and hypofractionated treatment regimens. There is a need for accurate 3D in vivo patient dose verification using electronic portal imaging device (EPID) measurements. This work presents a model-based technique to compute full three-dimensional patient dose reconstructed from on-treatment EPID portal images (i.e., transmission images). Methods: EPID dose is converted to incident fluence entering the patient using a series of steps which include converting measured EPID dose to fluence at the detector plane and then back-projecting the primary source component of the EPID fluence upstream of the patient. Incident fluence is then recombined with predicted extra-focal fluence and used to calculate 3D patient dose via a collapsed-cone convolution method. This method is implemented in an iterative manner, although in practice it provides accurate results in a single iteration. The robustness of the dose reconstruction technique is demonstrated with several simple slab phantom and nine anthropomorphic phantom cases. Prostate, head and neck, and lung treatments are all included as well as a range of delivery techniques including VMAT and dynamic intensity modulated radiation therapy (IMRT). Results: Results indicate that the patient dose reconstruction algorithm compares well with treatment planning system computed doses for controlled test situations. For simple phantom and square field tests, agreement was excellent with a 2%/2 mm 3D chi pass rate .98.9%. On anthropomorphic phantoms, the 2%/2 mm 3D chi pass rates ranged from 79.9% to 99.9% in the planning target volume (PTV) region and 96.5% to 100% in the low dose region (>20% of prescription, excluding PTV and skin build-up region). Conclusions: An algorithm to reconstruct delivered patient 3D doses from EPID exit dosimetry measurements was presented. The method was applied to phantom and patient data sets, as well as for dynamic IMRT and VMAT delivery techniques. Results indicate that the EPID dose reconstruction algorithm presented in this work is suitable for clinical implementation.

Crown Copyright © 2015 Published by Elsevier Inc. All rights reserved.Purpose To validate automatic substitute computed tomography CT (sCT) scans generated from standard T2-weighted (T2w) magnetic resonance (MR) pelvic scans for MR-Sim prostate treatment planning. Patients and Methods A Siemens Skyra 3T MR imaging (MRI) scanner with laser bridge, flat couch, and pelvic coil mounts was used to scan 39 patients scheduled for external beam radiation therapy for localized prostate cancer. For sCT generation a whole-pelvis MRI scan (1.6 mm 3-dimensional isotropic T2w SPACE [Sampling Perfection with Application optimized Contrasts using different flip angle Evolution] sequence) was acquired. Three additional small field of view scans were acquired: T2w, T2*w, and T1w flip angle 80° for gold fiducials. Patients received a routine planning CT scan. Manual contouring of the prostate, rectum, bladder, and bones was performed independently on the CT and MR scans. Three experienced observers contoured each organ on MRI, allowing interobserver quantification. To generate a training database, each patient CT scan was coregistered to their whole-pelvis T2w using symmetric rigid registration and structure-guided deformable registration. A new multi-atlas local weighted voting method was used to generate automatic contours and sCT results. Results The mean error in Hounsfield units between the sCT and corresponding patient CT (within the body contour) was 0.6 ± 14.7 (mean ± 1 SD), with a mean absolute error of 40.5 ± 8.2 Hounsfield units. Automatic contouring results were very close to the expert interobserver level (Dice similarity coefficient): prostate 0.80 ± 0.08, bladder 0.86 ± 0.12, rectum 0.84 ± 0.06, bones 0.91 ± 0.03, and body 1.00 ± 0.003. The change in monitor units between the sCT-based plans relative to the gold standard CT plan for the same dose prescription was found to be 0.3% ± 0.8%. The 3-dimensional ¿ pass rate was 1.00 ± 0.00 (2 mm/2%). Conclusions The MR-Sim setup and automatic sCT generation methods using standard MR sequences generates realistic contours and electron densities for prostate cancer radiation therapy dose planning and digitally reconstructed radiograph generation.

© 2015 Institute of Physics and Engineering in Medicine.The quantification of tumor motion in sites affected by respiratory motion is of primary importance to improve treatment accuracy. To account for motion, different studies analyzed the translational component only, without focusing on the rotational component, which was quantified in a few studies on the prostate with implanted markers. The aim of our study was to propose a tool able to quantify lung tumor rotation without the use of internal markers, thus providing accurate motion detection close to critical structures such as the heart or liver. Specifically, we propose the use of an automatic feature extraction method in combination with the acquisition of fast orthogonal cine MRI images of nine lung patients. As a preliminary test, we evaluated the performance of the feature extraction method by applying it on regions of interest around (i) the diaphragm and (ii) the tumor and comparing the estimated motion with that obtained by (i) the extraction of the diaphragm profile and (ii) the segmentation of the tumor, respectively. The results confirmed the capability of the proposed method in quantifying tumor motion. Then, a point-based rigid registration was applied to the extracted tumor features between all frames to account for rotation. The median lung rotation values were -0.6 ± 2.3° and -1.5 ± 2.7° in the sagittal and coronal planes respectively, confirming the need to account for tumor rotation along with translation to improve radiotherapy treatment.

© 2015.Background: CT-MR registration is a critical component of many radiation oncology protocols. In prostate external beam radiation therapy, it allows the propagation of MR-derived contours to reference CT images at the planning stage, and it enables dose mapping during dosimetry studies. The use of carefully registered CT-MR atlases allows the estimation of patient specific electron density maps from MRI scans, enabling MRI-alone radiation therapy planning and treatment adaptation. In all cases, the precision and accuracy achieved by registration influences the quality of the entire process.Problem: Most current registration algorithms do not robustly generalize and lack inverse-consistency, increasing the risk of human error and acting as a source of bias in studies where information is propagated in a particular direction, e.g. CT to MR or vice versa. In MRI-based treatment planning where both CT and MR scans serve as spatial references, inverse-consistency is critical, if under-acknowledged.Purpose: A robust, inverse-consistent, rigid/affine registration algorithm that is well suited to CT-MR alignment in prostate radiation therapy is presented.Method: The presented method is based on a robust block-matching optimization process that utilises a half-way space definition to maintain inverse-consistency. Inverse-consistency substantially reduces the influence of the order of input images, simplifying analysis, and increasing robustness. An open source implementation is available online at http://aehrc.github.io/Mirorr/.Results: Experimental results on a challenging 35 CT-MR pelvis dataset demonstrate that the proposed method is more accurate than other popular registration packages and is at least as accurate as the state of the art, while being more robust and having an order of magnitude higher inverse-consistency than competing approaches.Conclusion: The presented results demonstrate that the proposed registration algorithm is readily applicable to prostate radiation therapy planning.

The purpose of this study was to investigate performance of the couch and coil mounts designed for MR-simulation prostate scanning using data from ten volunteers. Volunteers were scanned using the standard MR scanning protocol with the MR coil directly strapped on the external body and the volunteer lying on the original scanner table. They also were scanned using a MR-simulation table top and pelvic coil mounts. MR images from both setups were compared in terms of body contour variation and image quality effects within particular organs of interest. Six-field conformal plans were generated on the two images with assigned bulk density for dose calculation. With the MR-simulation devices, the anterior skin deformation was reduced by up to 1.7 cm. The hard tabletop minimizes the posterior body deformation which can be up to 2.3 cm on the standard table, depending on the weight of volunteer. The image signal-to-noise ratio reduced by 14% and 25% on large field of view (FOV) and small FOV images, respectively, after using the coil mount; the prostate volume contoured on two images showed difference of 1.05 ± 0.66 cm³. The external body deformation caused a mean dose reduction of 0.6 ± 0.3 Gy, while the coverage reduced by 22% ± 13% and 27% ± 6% in V98 and V100, respectively. A dedicated MR simulation setup for prostate radiotherapy is essential to ensure the agreement between planning anatomy and treatment anatomy. The image signal was reduced after applying the coil mount, but no significant effect was found on prostate contouring.

© 2015 Institute of Physics and Engineering in Medicine.To clinically implement MRI simulation or MRI-alone treatment planning requires comprehensive end-to-end testing to ensure an accurate process. The purpose of this study was to design and build a geometric phantom simulating a human male pelvis that is suitable for both CT and MRI scanning and use it to test geometric and dosimetric aspects of MRI simulation including treatment planning and digitally reconstructed radiograph (DRR) generation. A liquid filled pelvic shaped phantom with simulated pelvic organs was scanned in a 3T MRI simulator with dedicated radiotherapy couch-top, laser bridge and pelvic coil mounts. A second phantom with the same external shape but with an internal distortion grid was used to quantify the distortion of the MR image. Both phantoms were also CT scanned as the gold-standard for both geometry and dosimetry. Deformable image registration was used to quantify the MR distortion. Dose comparison was made using a seven-field IMRT plan developed on the CT scan with the fluences copied to the MR image and recalculated using bulk electron densities. Without correction the maximum distortion of the MR compared with the CT scan was 7.5 mm across the pelvis, while this was reduced to 2.6 and 1.7 mm by the vendor's 2D and 3D correction algorithms, respectively. Within the locations of the internal organs of interest, the distortion was <1.5 and <1 mm with 2D and 3D correction algorithms, respectively. The dose at the prostate isocentre calculated on CT and MRI images differed by 0.01% (1.1 cGy). Positioning shifts were within 1 mm when setup was performed using MRI generated DRRs compared to setup using CT DRRs. The MRI pelvic phantom allows end-to-end testing of the MRI simulation workflow with comparison to the gold-standard CT based process. MRI simulation was found to be geometrically accurate with organ dimensions, dose distributions and DRR based setup within acceptable limits compared to CT.

© 2015 Australasian College of Physical Scientists and Engineers in Medicine To quantify the dose calculation error and resulting optimization uncertainty caused by performing inverse treatment planning on inaccurate electron density data (pseudo-CT) as needed for adaptive radiotherapy and Magnetic Resonance Imaging (MRI) based treatment planning. Planning Computer Tomography (CT) data from 10 cervix cancer patients was used to generate 4 pseudo-CT data sets. Each pseudo-CT was created based on an available method of assigning electron density to an anatomic image. An inversely modulated radiotherapy (IMRT) plan was developed on each planning CT. The dose calculation error caused by each pseudo-CT data set was quantified by comparing the dose calculated each pseudo-CT data set with that calculated on the original planning CT for the same IMRT plan. The optimization uncertainty introduced by the dose calculation error was quantified by re-optimizing the same optimization parameters on each pseudo-CT data set and comparing against the original planning CT. Dose differences were quantified by assessing the Equivalent Uniform Dose (EUD) for targets and relevant organs at risk. Across all pseudo-CT data sets and all organs, the absolute mean dose calculation error was 0.2 Gy, and was within 2 % of the prescription dose in 98.5 % of cases. Then absolute mean optimisation error was 0.3 Gy EUD, indicating that that inverse optimisation is impacted by the dose calculation error. However, the additional uncertainty introduced to plan optimisation is small compared the sources of variation which already exist. Use of inaccurate electron density data for inverse treatment planning results in a dose calculation error, which in turn introduces additional uncertainty into the plan optimization process. In this study, we showed that both of these effects are clinically acceptable for cervix cancer patients using four different pseudo-CT data sets. Dose calculation and inverse optimization on pseudo-CT is feasible for this patient cohort.

© 2014 Associazione Italiana di Fisica Medica.A new tool with the potential to verify and track jaw position during delivery has been developed. The method should be suitable for independent quality assurance for jaw position during jaw tracking dynamic IMRT and VMAT treatments. The jaw detection and tracking algorithm developed consists of five main steps. Firstly, the image is enhanced by removing a normalised predicted EPID image (that does not include the collimator transmission) from each cine EPID image. Then, using a histogram clustering technique a global intensity threshold level was determined. This threshold level was used to classify each pixel of the image as either under the jaws or under the MLC. Additionally, the collimator angle was automatically detected and used to rotate the image to vertical direction. Finally, this rotation allows the jaw positions to be determined using vertical and horizontal projection profiles. Nine IMRT fields (with static jaws) and a single VMAT clinical field (with dynamic jaws) were tested by determining the root mean square difference between planned and detected jaw positions. The test results give a detection accuracy of ±1mm RMS error for static jaw IMRT treatments and ±1.5mm RMS error for the dynamic jaw VMAT treatment. This method is designed for quality assurance and verification in modern radiation therapy; to detect the position of static jaws or verify the position of tracking jaws in more complex treatments. This method uses only information extracted from EPID images and it is therefore independent from the linear accelerator.

© 2015 Elsevier Inc. All rights reserved.Purpose Gantry-mounted megavoltage electronic portal imaging devices (EPIDs) have become ubiquitous on linear accelerators. WatchDog is a novel application of EPIDs, in which the image frames acquired during treatment are used to monitor treatment delivery in real time. We report on the preliminary use of WatchDog in a prospective study of cancer patients undergoing intensity modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT) and identify the challenges of clinical adoption. Methods and Materials At the time of submission, 28 cancer patients (head and neck, pelvis, and prostate) undergoing fractionated external beam radiation therapy (24 IMRT, 4 VMAT) had =1 treatment fraction verified in real time (131 fractions or 881 fields). EPID images acquired continuously during treatment were synchronized and compared with model-generated transit EPID images within a frame time (~0.1 s). A ¿ comparison was performed to cumulative frames to gauge the overall delivery quality, and the resulting pass rates were reported graphically during treatment delivery. Every frame acquired (500-1500 per fraction) was saved for postprocessing and analysis. Results The system reported the mean ± standard deviation in real time ¿ 91.1% ± 11.5% (83.6% ± 13.2%) for cumulative frame ¿ analysis with 4%, 4 mm (3%, 3 mm) criteria, global over the integrated image. Conclusions A real-time EPID-based radiation delivery verification system for IMRT and VMAT has been demonstrated that aims to prevent major mistreatments in radiation therapy.

© 2014 The Authors.Methods: A custom-designed pelvic-shaped phantom was scanned by systematically increasing the anterior body-tocoil (BTC) distance from 30 to 90mm. The image quality near the organs of interest was determined in order to characterize the relationship between image quality and BTC distance at the critical organ structures. The half intensity reduction (HIR) was calculated to determine the sensitivity of each organ structure to the BTC distance change.Advances in knowledge: A method to characterize the effect on image quality due to the use of coil mounts was demonstrated. Coil mounts whose height can be adjusted individually to keep BTC distance constant are necessary to maintain a uniform image across the entire field of view.Results: As the BTC distance increased, the uniformity reduced at 3% per millimetre. The HIR value indicated that the bladder signal is most sensitive to the change in BTC distance. By maintaining a constant BTC distance set-up, the intensity uniformitywas improved by 28% along the B0 directions.Conclusion: Positioning the MRI coil on mounts can reduce body deformation but adversely degrades the image quality. The magnitude of this effect has been quantified for prostate MR simulation scanning. The coil needs to be positioned not only with a minimal but also uniform BTC distance in order to maximize image quality.Objective: To eliminate the effects of body deformation for MR-based prostate treatment planning, coil mounts are essential. In this study, we evaluated the effect of the coil set-up on image quality.

MRI-alone treatment planning and adaptive MRI-based prostate radiation therapy are two promising techniques that could significantly increase the accuracy of the curative dose delivery processes while reducing the total radiation dose. State-of-the-art methods rely on the registration of a patient MRI with a MR-CT atlas for the estimation of pseudo-CT [5]. This atlas itself is generally created by registering many CT and MRI pairs. Most registration methods are not symmetric, but the order of the images influences the result [8]. The computed transformation is therefore biased, introducing unwanted variability. This work examines how much a symmetric algorithm improves the registration. Methods: A robust symmetric registration algorithm is proposed that simultaneously optimises a half space transform and its inverse. During the registration process, the two input volumetric images are transformed to a common position in space, therefore minimising any computational bias. An asymmetrical implementation of the same algorithm was used for comparison purposes. Results: Whole pelvis MRI and CT scans from 15 prostate patients were registered, as in the creation of MR-CT atlases. In each case, two registrations were performed, with different input image orders, and the transformation error quantified. Mean residuals of 0.63±0.26 mm (translation) and (8.7±7.3) × 10-3 rad (rotation) were found for the asymmetrical implementation with corresponding values of 0.038±0.039 mm and (1.6 ± 1.3) × 10-3 rad for the proposed symmetric algorithm, a substantial improvement. Conclusions: The increased registration precision will enhance the generation of pseudo-CT from MRI for atlas based MR planning methods. © Published under licence by IOP Publishing Ltd.

Objective: Manual contouring and registration for radiotherapy treatment planning and online adaptation for cervical cancer radiation therapy in computed tomography (CT) and magnetic resonance images (MRI) are often necessary. However manual intervention is time consuming and may suffer from inter or intra-rater variability. In recent years a number of computer-guided automatic or semi-automatic segmentation and registration methods have been proposed. Segmentation and registration in CT and MRI for this purpose is a challenging task due to soft tissue deformation, inter-patient shape and appearance variation and anatomical changes over the course of treatment. The objective of this work is to provide a state-of-the-art review of computer-aided methods developed for adaptive treatment planning and radiation therapy planning for cervical cancer radiation therapy. Methods: Segmentation and registration methods published with the goal of cervical cancer treatment planning and adaptation have been identified from the literature (PubMed and Google Scholar). A comprehensive description of each method is provided. Similarities and differences of these methods are highlighted and the strengths and weaknesses of these methods are discussed. A discussion about choice of an appropriate method for a given modality is provided. Results: In the reviewed papers a Dice similarity coefficient of around 0.85 along with mean absolute surface distance of 2-4. mm for the clinically treated volume were reported for transfer of contours from planning day to the treatment day. Conclusions: Most segmentation and non-rigid registration methods have been primarily designed for adaptive re-planning for the transfer of contours from planning day to the treatment day. The use of shape priors significantly improved segmentation and registration accuracy compared to other models.

Our group have been developing methods for MRI-alone prostate cancer radiation therapy treatment planning. To assist with clinical validation of the workflow we are investigating a cloud platform solution for research purposes. Benefits of cloud computing can include increased scalability, performance and extensibility while reducing total cost of ownership. In this paper we demonstrate the generation of DICOM-RT directories containing an automatic average atlas based electron density image and fast pelvic organ contouring from whole pelvis MR scans. © Published under licence by IOP Publishing Ltd.

EPID images acquired in cine mode during arc therapy have inaccurate gantry angles recorded in their image headers. In this work, methods were developed to assess the accuracy of the gantry potentiometer for linear accelerators. As well, assessments of the accuracy of other, more accessible, sources of gantry angle information (i.e., treatment log files, analysis of EPID image headers) were investigated. The methods used in this study are generally applicable to any linear accelerator unit, and have been demonstrated here with Clinac/Trilogy systems. Gantry angle data were simultaneously acquired using three methods: i) a direct gantry potentiometer measurement, ii) an incremental rotary encoder, and iii) a custom-made radiographic gantry-angle phantom which produced unique wire intersections as a function of gantry angle. All methods were compared to gantry angle data from the EPID image header and the linac MLC DynaLog file. The encoder and gantry-angle phantom were used to validate the accuracy of the linac's potentiometer. The EPID image header gantry angles and the DynaLog file gantry angles were compared to the potentiometer. The encoder and gantry-angle phantom mean angle differences with the potentiometer were 0.13° ± 0.14° and 0.10°± 0.30°, respectively. The EPID image header angles analyzed in this study were within ± 1° of the potentiometer angles only 35% of the time. In some cases, EPID image header gantry angles disagreed by as much as 3° with the potentiometer. A time delay in frame acquisition was determined using the continuous acquisition mode of the EPID. After correcting for this time delay, 75% of the header angles, on average, were within ± 1° of the true gantry angle, compared to an average of only 35% without the correction. Applying a boxcar smoothing filter to the corrected gantry angles further improved the accuracy of the header-derived gantry angles to within ± 1° for almost all images (99.4%). An angle accuracy of 0.11° ± 0.04° was determined using a point-by-point comparison of the gantry angle data in the MLC DynaLog file and the potentiometer data. These simple correction methods can be easily applied to individual treatment EPID images in order to more accurately define the gantry angle.

Radiotherapy is an effective therapy in the treatment of cervix cancer. However tumor and normal tissue motion and shape deformation of the cervix, the bladder and the rectum over the course of the treatment can limit the efficacy of radiotherapy and safe delivery of the dose. A number of studies have presented the potential benefits of adaptive radiotherapy for cervix cancer with high soft tissue contrast magnetic resonance images. To enable practical implementation of adaptive radiotherapy for the cervix, computer aided segmentation is necessary. Accurate computer aided automatic or semi-automatic segmentation of the cervix is a challenging task due to inter patient shape variation, soft tissue deformation, organ motion, and anatomical changes during the course of the treatment. This article reviews the methods developed for cervix segmentation in magnetic resonance images. The objective of this work is to present different methods for cervix segmentation in the literature highlighting their similarities, differences, strengths and weaknesses. © 2013 Springer-Verlag.

The set-up variation of 11 patients treated supine with radical radiotherapy for carcinoma of the prostate was measured with an electronic portal imaging device to determine the adequacy of set-up techniques and current margins, as well as the need for immobilization. During the treatments 172 images of the anterior fields and 159 images of the left- lateral fields were taken and the errors in treatment placement were measured by template matching. The variation in the superior-inferior direction was small, 1.4-1.6 mm (1 SD), while the medio-lateral variation was 2.8 mm (1 SD). The anterior-posterior variation was largest, 4.6 mm (1 SD) with an offset of 3.3 mm anterior. This anterior offset and large anterior-posterior variation suggests that set-up techniques were not optimal for this direction. The 1 cm margin used was adequate for set-up variation except in a small number of cases, which was mainly due to the anterior trend. Random (treatment-to-treatment) variations were small (1.1-2.3 mm; 1 SD), indicating that immobilization would result in only modest improvement in reproducibility for these supine patients.

Multimodal registration of CT and MR scans is a required step in leading edge adaptive MR-based image guided radiation therapy protocols. Yet, anatomical changes limit the precision of the registration process and therefore that of the whole intervention. In prostate radiation therapy, the difference in bladder and rectum filling can significantly displace both the targeted area and the organs at risk. Here, we describe a method that integrates an image-based similarity criterion with the anatomical information from manual contours to guide the registration process toward an accurate solution. Whole pelvis CT and MR scans of 33 patients have been nonrigidly registered, and the proposed method leads to an average improvement of 0.17 DSC when compared to a baseline nonrigid registrations. The increased accuracy will thus enhance an MR-based prostate radiation therapy protocol. © 2014 Springer International Publishing.