Deformable Image Registration Tool Research Articles

Evaluation and risk factors of volume and dose differences of selected structures in patients with head and neck cancer treated on Helical TomoTherapy by using Deformable Image Registration tool

Abstract Introduction: The aim of this study was the evaluation of volume and dose differences in selected structures in patients with head and neck cancer during treatment on Helical TomoTherapy (HT) using a commercially available deformable image registration (DIR) tool. We attempted to identify anatomical and clinical predictive factors for significant volume changes probability. Material and methods: According to our institutional protocol, we retrospectively evaluated the group of 20 H&N cancer patients treated with HT who received Adaptive Radiotherapy (ART) due to soft tissue alterations spotted on daily MVCT. We compared volumes on initial computed tomography (iCT) and replanning computed tomography (rCT) for clinical target volumes (CTV) – CTV1 (the primary tumor) and CTV2 (metastatic lymph nodes), parotid glands (PG) and body contour (B-body). To estimate the planned and delivered dose discrepancy, the dose from the original plan was registered and deformed to create a simulation of dose distribution on rCT (DIR-rCT). Results: The decision to replan was made at the 4th week of RT (N = 6; 30%). The average volume reduction in parotid right PG[R] and left PG[L] was 4.37 cc (18.9%) (p < 0.001) and 3.77 cc (16.8%) (p = 0.004), respectively. In N = 13/20 cases, the delivered dose was greater than the planned dose for PG[R] of mean 3 Gy (p < 0.001), and in N = 6/20 patients for PG[L] the mean of 3.6 Gy (p = 0.031). Multivariate regression analysis showed a very strong predictor explaining 88% (R2 = 0.88) and 83% (R2 = 0.83) of the variance based on the mean dose of iPG[R] and iPG[L] (p < 0.001), respectively. No statistically significant correlation between volume changes and risk factors was found. Conclusions: Dosimetric changes to the target demonstrated the validity of replanning. A DIR tool can be successfully used for dose deformation and ART qualification, significantly reducing the workload of radiotherapy centers. In addition, the mean dose for PG was a significant predictor that may indicate the need for a replan.

Validation of a commercial deformable image registration for surface-guided radiotherapy using an ad hoc-developed deformable phantom.

The use of optical surface systems (OSSs) for patient setup verification in external radiation therapy is increasing. To manage potential deformations in a patient's anatomy, a novel deformable image registration (DIR) tool has been applied in a commercial OSS. In this study we investigate the accuracy of the DIR as compared to rigid image registration (RR). The positioning accuracy of the DIR and RR implemented in the OSS was investigated using an ad hoc-developed anthropomorphic deformable phantom, named Mary. The phantom consists of 33 slices of expanded polystyrene slabs shaped thus to simulate part of a female body. Anatomical details, simulating the ribs and spinal cord, together with 10 inner targets at different depths are included in thorax and abdominal parts. Mary is capable of realistic body movements and deformations, such as head and arm rotations, body torsion and moderate breast/abdomen swelling. The accuracy of DIR and RR was investigated for four internal targets after deliberately deforming the phantom nine times. Breast and abdomen enlargements and torsions around x, y, and z axes were applied. For reference purposes, rigid displacements (where Mary's anatomy was kept intact) were included. The phantom was positioned on the linac couch under the OSS guidance and for each target and displacement a CBCT was acquired. The accuracy of DIR and RR was assessed evaluating the difference in means of absolute values between CBCT and the OSS registration parameters (lateral, longitudinal, vertical, rot, pitch, and roll), using both a reference surface extracted from CT (CTr) or acquired with the OSS (OSSr). A comparison of the four different combinations, DIR+OSSr, DIR+CTr, RR+OSSr, and RR+CTr, was carried out to evaluate the position accuracy for the various combinations. Finally, the positioning accuracy of the different target positions using only OSSr was investigated for the DIR. A paired sample Wilcoxon signed-rank test (P<0.05) and a two-tailed Mann-Whitney test (P<0.05) were carried out. The DIR in combination with OSSr showed significantly (P<0.05) improved positioning accuracy in the lateral and longitudinal directions and in pitch, compared to RR, when deformations were applied to Mary. The positioning accuracy improved from 1.9±1.5mm, 1.1±0.8mm to 1.1±1.2mm, 0.6±0.5mm in lateral and longitudinal directions, respectively, and from 0.8±0.6° to 0.4±0.4° in pitch, using DIR compared to RR. Both the DIR and RR showed a similar positioning accuracy when rigid displacements of Mary were applied. For DIR, the OSSr generally showed improved calculation accuracy compared to CTr. Independent of the reference image used, the target position influenced the registration accuracy, and hence, one target could not be evaluated using RR due to its inability to calculate the correct position. Improved positioning accuracy was observed for DIR with respect to RR when deformations of Mary's anatomy were applied. For both DIR and RR, improved positioning accuracy was observed using OSSr as compared to CTr. The position of the target inside the phantom influenced the positioning accuracy for DIR.

Deforming to Best Practice: Key considerations for deformable image registration in radiotherapy.

Image registration is a process that underlies many new techniques in radiation oncology – from multimodal imaging and contour propagation in treatment planning to dose accumulation throughout treatment. Deformable image registration (DIR) is a subset of image registration subject to high levels of complexity in process and validation. A need for local guidance to assist in high‐quality utilisation and best practice was identified within the Australian community, leading to collaborative activity and workshops. This report communicates the current limitations and best practice advice from early adopters to help guide those implementing DIR in the clinic at this early stage. They are based on the state of image registration applications in radiotherapy in Australia and New Zealand (ANZ), and consensus discussions made at the ‘Deforming to Best Practice’ workshops in 2018. The current status of clinical application use cases is presented, including multimodal imaging, automatic segmentation, adaptive radiotherapy, retreatment, dose accumulation and response assessment, along with uptake, accuracy and limitations. Key areas of concern and preliminary suggestions for commissioning, quality assurance, education and training, and the use of automation are also reported. Many questions remain, and the radiotherapy community will benefit from continued research in this area. However, DIR is available to clinics and this report is intended to aid departments using or about to use DIR tools now.

Evaluation of the effect of user-guided deformable image registration of thoracic images on registration accuracy among users

User-guided deformable image registration (DIR) has allowed users to actively participate in the DIR process and is expected to improve DIR accuracy. The purpose of this study was to evaluate the time required for and effect of user-guided DIR on registration accuracy for thoracic images among users. In this study, 4-dimensional computed tomographic images of 10 thoracic cancer patients were used. The dataset for these patients was provided by DIR-Lab (www.dir-lab.com) and included a coordinate list of anatomical landmarks (300 bronchial bifurcations). Four medical physicists from different institutions performed DIR between peak-inhale and peak-exhale images with/without the user-guided DIR tool, Reg Refine, implemented in MIM Maestro (MIM software, Cleveland, OH). DIR accuracy was quantified by using target registration errors (TREs) for 300 anatomical landmarks in each patient. The average TREs with user-guided DIR in the 10 images by the 4 medical physicists were 1.48, 1.80, 3.46, and 3.55 mm, respectively, whereas the TREs without user-guided DIR were 3.28, 3.45, 3.56, and 3.28 mm, respectively. The average times taken by the 4 physicists to use the user-guided DIR were 10.0, 6.7, 7.1, and 8.0 min, respectively. This study demonstrated that user-guided DIR can improve DIR accuracy and requires only a moderate amount of time (<10 min). However, 2 of the 4 users did not show much improvement in DIR accuracy, which indicated the necessity of training prior to use of user-guided DIR.

Deformable Image Registration and Dose Accumulation for Locally Advanced Non-Small Cell Lung Cancer, Comparing Delivered and Planned Radiotherapy Doses

Uncertainty in the radiotherapy doses actually received over the course of treatment for locally-advanced non-small cell lung cancer (LA-NSCLC) may explain, in part, low long term survival rates for these patients. This is because target and nodal dose coverage, up to this point, have been assumed constant; however disease volume and location are known to change during the course of radiation treatment. In this study, deformable registration (DIR) and dose accumulation (DA) were used to calculate the accumulated dose received over the course of treatment. These accumulated doses are then compared with the clinical treatment plan against acceptable tolerances. This single institution retrospective study randomly selected 26 patients diagnosed with LA-NSCLS receiving radical chemo-radiotherapy. 9 Patients received a dose of 60Gy/30fx and the other 17 patients received a dose of 66/33fx. The clinical delivered plan was exported into RayStation 4.5.2. Using this system's deformable image registration (DIR) tools, doses calculated on daily cone-beam CT images acquired for daily verification are deformed and mapped onto the planning CT images, thus accounting for daily treatment incorporating set-up shifts and changes in the patients anatomy. The accumulated dose delivered was then compared to the clinical treatment plan in terms of target coverage and avoidance of organs at risk. This study demonstrates successfully that, on average, the accumulated doses calculated were not statistically different from the clinical plan. Furthermore, the accumulated doses to the clinical target volumes (CTV's) for both targets and nodes are within acceptable range, illustrating that our current PTV margins are robust against anatomical changes observed during the course of radiation therapy treatment. Differences between CTV doses calculated for the clinical treatment plan compared to the accumulated plan was within 2%. The accumulated OAR doses are also maintained as compared to the clinical plan. We successfully demonstrated that DIR and DA is a useful and valued tool confirming doses received for patients receiving radiation for LA-NSCLC. We have confirmed that our PTV margins are adequate and robust from a dosimetric perspective. Given our relatively small sample size, our results may not be representative of the entire population. Further accrual would confirm our initial findings.

44. Deformable image registration for dose accumulation: Principle and evaluation

Most Treatment Planning Systems for adaptive radiotherapy today propose Deformable Image Registration (DIR) tools which enable contour propagation or dose accumulation between images acquired over the course of treatment. While the results of DIR for contour propagation can be easily assessed and eventually manually corrected, the evaluation of DIR for dose accumulation relies on a knowledge of anatomical point correspondences and is therefore much more challenging. This talk will review the methodological principle of DIR for dose accumulation and current evaluation methods. Accumulating dose in a tissue element contained in a voxel of the reference image requires to determine the location of that element in the considered longitudinal images. The role of DIR is to automatically establish those spatial correspondences usually in the form of displacement vector fields (DVF). The first natural way to evaluate DIR results is to deform the longitudinal image onto the reference image based on the DVF and to measure the resulting similarity between the images. However, as demonstrated in previous studies, popular DIR algorithms for contour propagation can lead to high similarity between the deformed and reference images and critically wrong anatomical point correspondences. For this reason, image similarity measures or visual assessment with image fusion tools should be considered in clinical practice only after the local accuracy (in millimeters) has been quantified for a significant number of cases. Among DIR validation methods for dose accumulation, the most reliable one consists of manually identifying pairs of landmarks in the images and to relate the misalignment of those landmark pairs after DIR to the spatial resolution of the dose distributions. This approach can be easily implemented for some anatomical localizations but identifying correspondences on the surface of smooth organs or in large homogeneous tissues is not always feasible. In that case, DIR validation will have to verify that the estimated DVF respect physical considerations such as a reasonable range of local volume variations measured with the Jacobian determinant of the DVF. DIR algorithms can also be tested with images derived from numerical or physical phantoms which provide a ground truth deformation. Phantoms have demonstrated that traditional DIR algorithms could fail to estimate complex deformations such as a sliding motion between organs and justified the need to develop anatomical site-specific models. Finally, a limited number of studies have addressed DIR of longitudinal images presenting inconsistent content (i.e. in case of tumor growth or erosion) and a special attention should be paid in those situations. In parallel of efforts to develop more accurate DIR methods, it is important today to define a commissioning strategy for available DIR solutions to be used in clinical trials involving dose accumulation. In that sense, a Task Group of the American Association of Medical Physicists recently reported its recommendations.

Validation of biomechanical deformable image registration in the abdomen, thorax, and pelvis in a commercial radiotherapy treatment planning system

The accuracy of deformable image registration tools can vary widely between imaging modalities and specific implementations of the same algorithms. A biomechanical model-based algorithm initially developed in-house at an academic institution was translated into a commercial radiotherapy treatment planning system and validated for multiple imaging modalities and anatomic sites. Biomechanical deformable registration (Morfeus) is a geometry-driven algorithm based on the finite element method. Boundary conditions are derived from the model-based segmentation of controlling structures in each image which establishes a point-to-point surface correspondence. For each controlling structure, material properties and fixed or sliding interfaces are assigned. The displacements of internal volumes for controlling structures and other structures implicitly deformed are solved with finite element analysis. Registration was performed for 74 patients with images (mean vector resolution) of thoracic and abdominal 4DCT (2.8mm) and MR (5.3mm), liver CT-MR (4.5mm), and prostate MR (2.6mm). Accuracy was quantified between deformed and actual target images using distance-to-agreement (DTA) for structure surfaces and the target registration error (TRE) for internal point landmarks. The results of the commercial implementation were as follows. The mean DTA was ≤1.0mm for controlling structures and 1.0-3.5mm for implicitly deformed structures on average. TRE ranged from 2.0mm on prostate MR to 5.1mm on lung MR on average, within 0.1mm or lower than the image voxel sizes. Accuracy was not overly sensitive to changes in the material properties or variability in structure segmentations, as changing these inputs affected DTA and TRE by ≤0.8mm. Maximum DTA >5mm occurred for 88% of the structures evaluated although these were within the inherent segmentation uncertainty for 82% of structures. Differences in accuracy between the commercial and in-house research implementations were ≤0.5mm for mean DTA and ≤0.7mm for mean TRE. Accuracy of biomechanical deformable registration evaluated on a large cohort of images in the thorax, abdomen and prostate was similar to the image voxel resolution on average across multiple modalities. Validation of this treatment planning system implementation supports biomechanical deformable registration as a versatile clinical tool to enable accurate target delineation at planning and treatment adaptation.

Dose warping performance in deformable image registration in lung

PurposeIt is unclear that spatial accuracy can reflect the impact of deformed dose distribution. In this study, we used dosimetric parameters to compare an in-house deformable image registration (DIR) system using NiftyReg, with two commercially available systems, MIM Maestro (MIM) and Velocity AI (Velocity). MethodsFor 19 non-small-cell lung cancer patients, the peak inspiration (0%)-4DCT images were deformed to the peak expiration (50%)-4DCT images using each of the three DIR systems, which included computation of the deformation vector fields (DVF). The 0%-gross tumor volume (GTV) and the 0%-dose distribution were also then deformed using the DVFs. The agreement in the dose distributions for the GTVs was evaluated using generalized equivalent uniform dose (gEUD), mean dose (Dmean), and three-dimensional (3D) gamma index (criteria: 3mm/3%). Additionally, a Dice similarity coefficient (DSC) was used to measure the similarity of the GTV volumes. ResultsDmean and gEUD demonstrated good agreement between the original and deformed dose distributions (differences were generally less than 3%) in 17 of the patients. In two other patients, the Velocity system resulted in differences in gEUD of 50.1% and 29.7% and in Dmean of 11.8% and 4.78%. The gamma index comparison showed statistically significant differences for the in-house DIR vs. MIM, and MIM vs. Velocity. ConclusionsThe finely tuned in-house DIR system could achieve similar spatial and dose accuracy to the commercial systems. Care must be taken, as we found errors of more than 5% for Dmean and 30% for gEUD, even with a commercially available DIR tool.

Performance variations among clinically available deformable image registration tools in adaptive radiotherapy - how should we evaluate and interpret the result?

The purpose of this study is to evaluate the performance variations in commercial deformable image registration (DIR) tools for adaptive radiation therapy and further to interpret the differences using clinically available terms. Three clinical examples (prostate, head and neck (HN), and cranial spinal irradiation (CSI) with L‐spine boost) were evaluated in this study. Firstly, computerized deformed CT images were generated using simulation QA software with virtual deformations of bladder filling (prostate), neck flexion/bite‐block repositioning/tumor shrinkage (HN), and vertebral body rotation (CSI). The corresponding transformation matrices served as a “reference” for the following comparisons. Three commercialized DIR algorithms: the free‐form deformation from MIMVista 5.5 and the RegRefine from MIMMaestro 6.0, the multipass B‐spline from VelocityAI v3.0.1, and the adaptive demons from OnQ rts 2.1.15, were applied between the initial images and the deformed CT sets. The generated adaptive contours and dose distributions were compared with the “reference” and among each other. The performance in transferring contours was comparable among all three tools with an average Dice similarity coefficient of 0.81 for all the organs. However, the dose warping accuracy appeared to rely on the evaluation end points and methodologies. Point‐dose differences could show a difference of up to 23.3 Gy inside the PTVs and to overestimate up to 13.2 Gy for OARs, which was substantial for a 72 Gy prescription dose. Dosevolume histogram‐based evaluation might not be sensitive enough to illustrate all the detailed variations, while isodose assessment on a slice‐by‐slice basis could be tedious. We further explored the possibility of using 3D gamma index analysis for warping dose variation assessment, and observed differences in dose warping using different DIR tools. Overall, our results demonstrated that evaluation based only on the performance of contour transformation could not guarantee the accuracy in dose warping, while dose‐transferring validation strongly relied on the evaluation endpoint. As dose‐transferring errors could cause misinterpretations when attempting to accumulate dose for adaptive radiation therapy and more DIR tools are available for clinical use, a standard and clinically meaningful quality assurance criterion should be established for DIR QA in the near future.PACS number(s): 87.57

Cardiac dose reduction during tangential breast irradiation using deep inspiration breath hold: a dose comparison study based on deformable image registration.

BackgroundRadiation therapy (RT) for a left-sided breast cancer often involves some incidental exposure of the heart and increase in the rate of major coronary events. One method to reduce the dose to the heart during a tangential breast irradiation is the deep inspiration breath hold (DIBH) technique. Our department adopted DIBH for selected left breast cancer patients with a maximum cardiac distance ≥ 10 mm. We evaluated the effect of the DIBH on cardiac dose compared to normal free breathing (FB). The secondary objective of our present study was to use modeled risk estimates to quantify the risk of coronary events after RT with DIBH.Methods and materialsThirty-two patients who underwent RT with DIBH at our hospital were retrospectively analyzed. For each patient, two computed tomography (CT) scans were acquired, FB-CT and DIBH-CT. Using a deformable image registration tool, the target volume was deformed from DIBH-CT to FB-CT, and conventional tangential treatment planning was performed, focusing on the equality of target coverage between the two plans. Doses to the heart, left anterior descending (LAD) artery, and ipsilateral lung were assessed.ResultsBy using DIBH, the average mean heart dose was reduced from 724.1 cGy to 279.3 (p < 0.001). The relative heart volume irradiated with 10 Gy–50 Gy was consistently reduced. The mean dose to the LAD coronary artery was reduced from 4079.1 cGy to 2368.9 cGy (p < 0.001). The ipsilateral lung volume receiving 20 Gy or more and 40 Gy or more was reduced by 2.2 % in both cases. Estimated risks of coronary events at 10 years were 4.03 and 2.55 % for RT with FB and DIBH, respectively (p < 0.001).ConclusionsThe use of DIBH during RT of the left-sided breast considerably reduces the doses delivered to the heart and LAD artery with similar target coverage. For the current study patients, the probability of major coronary events was reduced with DIBH.

SU-E-J-102: Performance Variations Among Clinically Available Deformable Image Registration Tools in Adaptive Radiotherapy: How Should We Evaluate and Interpret the Result?

Purpose: To evaluate the performance variations in commercial deformable image registration (DIR) tools for adaptive radiation therapy. Methods: Representative plans from three different anatomical sites, prostate, head-and-neck (HN) and cranial spinal irradiation (CSI) with L-spine boost, were included. Computerized deformed CT images were first generated using virtual DIR QA software (ImSimQA) for each case. The corresponding transformations served as the “reference”. Three commercial software packages MIMVista v5.5 and MIMMaestro v6.0, VelocityAI v2.6.2, and OnQ rts v2.1.15 were tested. The warped contours and doses were compared with the “reference” and among each other. Results: The performance in transferring contours was comparable among all three tools with an average DICE coefficient of 0.81 for all the organs. However, the performance of dose warping accuracy appeared to rely on the evaluation end points. Volume based DVH comparisons were not sensitive enough to illustrate all the detailed variations while isodose assessment on a slice-by-slice basis could be tedious. Point-based evaluation was over-sensitive by having up to 30% hot/cold-spot differences. If adapting the 3mm/3% gamma analysis into the evaluation of dose warping, all three algorithms presented a reasonable level of equivalency. One algorithm had over 10% of the voxels not meeting this criterion for the HN case while another showed disagreement for the CSI case. Conclusion: Overall, our results demonstrated that evaluation based only on the performance of contour transformation could not guarantee the accuracy in dose warping. However, the performance of dose warping accuracy relied on the evaluation methodologies. Nevertheless, as more DIR tools are available for clinical use, the performance could vary at certain degrees. A standard quality assurance criterion with clinical meaning should be established for DIR QA, similar to the gamma index concept, in the near future.

SP-0586: Role, clinical application and validation of deformable image registration and dose mapping tools

SP-0586: Role, clinical application and validation of deformable image registration and dose mapping tools

MO‐C‐17A‐13: Uncertainty Evaluation of CT Image Deformable Registration for H&amp;N Cancer Adaptive Radiotherapy

Purpose:To evaluate uncertainties of organ specific Deformable Image Registration (DIR) for H&amp;N cancer Adaptive Radiation Therapy (ART).Methods:A commercial DIR evaluation tool, which includes a digital phantom library of 8 patients, and the corresponding “Ground truth Deformable Vector Field” (GT‐DVF), was used in the study. Each patient in the phantom library includes the GT‐DVF created from a pair of CT images acquired prior to and at the end of the treatment course. Five DIR tools, including 2 commercial tools (CMT1, CMT2), 2 in‐house (IH_FFD1, IH_FFD2), and a classic DEMON algorithms, were applied on the patient images. The resulting DVF was compared to the GT‐DVF voxel by voxel. Organ specific DVF uncertainty was calculated for 10 ROIs: Whole Body, Brain, Brain Stem, Cord, Lips, Mandible, Parotid, Esophagus and Submandibular Gland. Registration error‐volume histogram was constructed for comparison.Results:The uncertainty is relatively small for brain stem, cord and lips, while large in parotid and submandibular gland. CMT1 achieved best overall accuracy (on whole body, mean vector error of 8 patients: 0.98±0.29 mm). For brain, mandible, parotid right, parotid left and submandibular glad, the classic Demon algorithm got the lowest uncertainty (0.49±0.09, 0.51±0.16, 0.46±0.11, 0.50±0.11 and 0.69±0.47 mm respectively). For brain stem, cord and lips, the DVF from CMT1 has the best accuracy (0.28±0.07, 0.22±0.08 and 0.27±0.12 mm respectively). All algorithms have largest right parotid uncertainty on patient#7, which has image artifact caused by tooth implantation.Conclusion:Uncertainty of deformable CT image registration highly depends on the registration algorithm, and organ specific. Large uncertainty most likely appears at the location of soft‐tissue organs far from the bony structures. Among all 5 DIR methods, the classic DEMON and CMT1 seem to be the best to limit the uncertainty within 2mm for all OARs.Partially supported by research grant from Elekta.

SU-E-J-241: Creation of Ventilation CT From Daily 4D CTs Or 4D Conebeam CTs Acquired During IGRT for Thoracic Cancers

Purpose: To develop a method to create ventilation CTs from daily 4D CTs or 4D KV conebeam CTs (4DCBCT) acquired during image-guided radiation therapy (IGRT) for thoracic tumors, and to explore the potential for using the ventilation CTs as a means for early detection of lung injury during radiation treatment. Methods: 4DCT acquired using an in-room CT (CTVision, Siemens) and 4DCBCT acquired using the X-ray Volume Imaging (XVI) system (Infinity, Elekta) for representative lung cancer patients were analyzed. These 4D data sets were sorted into 10 phase images. A newly-available deformable image registration tool (ADMIRE, Elekta) is used to deform the phase images at the end of exhale (EE) to the phase images at the end of inhale (EI). The lung volumes at EI and EE were carefully contoured using an intensity-based auto-contour tool and then manually edited. The ventilation images were calculated from the variations of CT numbers of those voxels masked by the lung contour at EI between the registered phase images. The deformable image registration is also performed between the daily 4D images and planning 4DCT, and the resulting deformable field vector (DFV) is used to deform the planning doses to the daily images by an in-house Matlab program. Results: The ventilation images were successfully created. The tide volumes calculated using the ventilation images agree with those measured through volume difference of contours at EE and EI, indicating the accuracy of ventilation images. The association between the delivered doses and the change of lung ventilation from the daily ventilation CTs is identified. Conclusions: A method to create the ventilation CT using daily 4DCTs or 4D KV conebeam CTs was developed and demonstrated.

Accuracy quantification of a deformable image registration tool applied in a clinical setting

The purpose of this study was to test the accuracy of a commercially available deformable image registration tool in a clinical situation. In addition, to demonstrate a method to evaluate the resulting transformation of such a tool to a reference defined by multiple experts. For 16 patients (seven head and neck, four thoracic, five abdominal), 30‐50 anatomical landmarks were defined on recognizable spots of a planning CT and a corresponding fraction CT. A commercially available deformable image registration tool, Velocity AI, was used to align all fraction CTs with the respective planning CTs. The registration accuracy was quantified by means of the target registration error in respect to expert‐defined landmarks, considering the interobserver variation of five observers. The interobserver uncertainty of the landmark definition in our data sets is found to be 1.2±1.1mm. In general the deformable image registration tool decreases the extent of observable misalignments from 4‐8 mm to 1‐4 mm for nearly 50% of the landmarks (to 77% in sum). Only small differences are observed in the alignment quality of scans with different tumor location. Smallest residual deviations were achieved in scans of the head and neck region (79%,≤4mm) and the thoracic cases (79%,≤4mm), followed by the abdominal cases (59%,≤4mm). No difference is observed in the alignment quality of different tissue types (bony vs. soft tissue). The investigated commercially available deformable image registration tool is capable of reducing a mean target registration error to a level that is clinically acceptable for the evaluation of retreatment plans and replanning in case of gross tumor change during treatment. Yet, since the alignment quality needs to be improved further, the individual result of the deformable image registration tool has still to be judged by the physician prior to application.PACS numbers: 87.57.nj, 87.57.N‐, 87.55.‐x

SU-E-J-112: Improving Target Delineation by Using Deformably Registered Multi-Modality Images for Radiation Therapy of Pancreatic Cancer

Purpose: Combined multi-modality images can provide unsurpassed target recognition, yet the large variation of contour volumes from different modalities prevents accurate contour transfer onto CT images for radiation therapy (RT) planning. This work demonstrates improved agreement between target contours from multi-modality images after deformable multi-modality image registration for pancreatic cancer RT. Methods: PET, and various MRI including T1, T2, DWI and DCE, were rigidly registered with CT for representative patients with pancreatic cancer. Gross tumor volume (GTV) and organs at risk (OARs) were delineated on multi-modality images and were exported into a presently-developed deformable multi-modality image registration tool. The derived deformation fields were applied to deform the corresponding modality contours, which were later overlapped onto the planning CT. Results: Substantial variations among contours from multi-modality images were observed for both GTV and OARs. When using T1 weighted contour volume as nominator, the delineated volumes vary from 0.5 to 1.8 for GTV, from 0.81 to 1.05 for OARs between the image modalities. The overlapping ratio between different modalities varies from 0.22 to 0.74 for GTV, and from 0.65 to 0.84 for OARs. After deformable image registration, the contour volumes are changed by deformation fields by 6% to 11%. These changes do not impact volume variation between different modalities, but improve significantly the overlapping ratio between contours from different modalities, for example, changing from 0.55 to 0.82 for GTV. Conclusion: The deformable image registration of multi-modality images increases the agreement between contours from different image modalities, improving accuracy for target and normal structure delineation for radiation treatment planning of pancreatic cancer.

SU-E-J-157: Evaluation of Surface-Tracking and Respiratory Gating Capacities of a Novel Surface-Mapping System Using Deformable Image Registration

Purpose: We have tested the capabilities of an innovative surface-mapping system that utilizes deformable image registration tools (C-RAD Catalyst). Its 3D positioning stability has been verified as well as its respiratory capabilities. Methods: The Catalyst daily QA phantom was used to test the stability of the system. A MatriXX ion-chamber array in a solid water phantom was mounted on a motion platform which can provide longitudinal 1D motion.The vertical-motion plate (respiratory plate) of the platform was used to mimic the chest movement in respiratory cycles. The respiratory plate was tracked by the Catalyst surface-mapping system. A static 10×10 field was first delivered to establish the baseline. Gated deliveries using different gating windows (from 10% to 90% duty cycle) were also performed and the results were recorded. A comparison between the Catalyst surface tracking signal and ABC data was performed for a breast cancer patient on-treatment. Results: Analysis of the experiment data indicates that the Catalyst is stable and reliable in detecting surface position and movement. With 50 numbers of phantom setups, the mean deviation of the shifts and rotations along all three directions was 0.6mm and 0.02 degrees, respectively. The gating capacity study suggested that respiratory gating using Catalyst system on an Elekta linac can be delivered safely and accurately. In fact, in gated beam delivery with the Catalyst system, dose distribution, dose profiles, gamma passing rates all show improvements as the gating window gets smaller. Gamma passing rates increase from 84.7% at non-gating to 95.6% at 10% gating window. The Catalyst system also correctly recognizes the respiratory pattern of a patient under our ABC gated treatment delivery. Conclusion: Based on a phantom study and clinical observations, we have found that Catalyst system is robust in surface tracking and positioning. It also can serve as a respiratory gating solution. Funded by Elekta

TU‐C‐141‐07: Limitations of Summing Dose Across Fractions: A Simple Test to Identify Failure

Purpose: With the increased availability of clinical deformable image registration tools, summing dose distributions calculated over different CT volumes is a tempting option. However, visual inspections of image registrations are insufficient to assess accuracy, and no patient‐specific QA methods exist to‐date. If the plan quality of the resulting summed dose is poor, it is difficult to discern whether the degradation results from organ motion or registration inaccuracies. We present a straightforward patient‐specific test that identifies invalid dose registrations. Methods: We applied the proposed test to assess dose registration accuracy for an illustrative 2‐fraction HDR brachytherapy prostate case. One plan per fraction was optimized using a unique CT acquired and contoured for each fraction and MIMVista was used to deformably register the clinical dose and contours. The resulting deformed and target CTs were compared. DVHs for the original dose distributions were calculated on their corresponding contours and for the deformed dose using both the target and warped contours. The four resulting DVH sets were compared and analyzed. Results: Though the deformed and target CTs match closely, V100 for the deformed dose plan is 42.0% as compared to 88.6% and 89.6% for the first and second day plans. Computing the deformed dose prostate DVH on the warped contours instead produces a target DVH with V100 of 82.6%, which differs greatly from the deformed V100 calculated on the target contours. Conclusion: When assessing a deformed dose, it is impossible to determine a priori whether degradation of the plan DVHs has resulted from organ motion or registration inaccuracies. If contoured and registered properly, the DVHs of the deformed dose should be similar regardless of whether they are computed over the deformed or target CT contours. Large differences between the two are a strong indication that the warped dose is unusable.

Lung sparing and dose escalation in a robust‐inspired IMRT planning method for lung radiotherapy that accounts for intrafraction motion

To test the efficacy of a simple, robust-inspired intensity modulated radiotherapy (IMRT) planning strategy for lung radiotherapy designed to reduce lung dose and escalate tumor dose using realistic dose accumulation tools. A deformable image registration tool was used to plan and accumulate dose over all phases of the breathing cycle for conventional and robust-inspired IMRT strategies of eight nonsmall cell lung cancer patients exhibiting peak-to-peak respiratory motion with amplitudes ranging from 1 to 2 cm in the craniocaudal direction. The authors' robust-inspired plans were designed to have smaller beam apertures based on target location during exhale, combined with edge-enhanced intensity maps to ensure target coverage during inspiration. For these, a new planning target volume defined as the rPTV was generated from a 5-mm isotropic expansion of the clinical target volume (CTV) on end-exhale combined with a boost volume, set to 110% of the prescription dose. Plans were evaluated in terms of (i) lung sparing and (ii) dose escalation for mean lung dose (MLD) isotoxicity. CTV and planning target volumes (PTV) coverage and lung dose were compared to the conventional IMRT approach. Robust-inspired plans showed potential lung dose reductions in seven out of eight patients. For non-GTV lung, percent reductions of 3%-14% in MLD and 6%-15% in V20 were observed. For seven of eight cases, the robust-like approach yielded increased accumulated doses to CTV. Isotoxicity studies for MLD showed increased dose to the CTV and the rPTV, in the range of 104%-118% and 95%-114% of prescription dose, respectively. A 4D dose calculation based on deformable image registration was used to evaluate a robust-inspired planning strategy for lung radiotherapy. This method offers notable reductions to lung dose while improving tumor coverage through the use of reduced geometric margins combined with edge enhancements.

Deformable Breast MRI and CT Registration for Radiation Treatment Planning Using B-spline With Rigidity and Feature Point Distance Regularization

To develop a software tool for accurate and automatic deformable registration between MRI and CT breast images, as particularly preferred in preoperative breast radiation therapy planning. A novel B-Spline registration approach of using feature point distance and local rigidity transformation measure as regularization is adopted to correct fine structure inaccuracy and bone area warping artifact due to B-Spline method's lack of physical property modeling and global intensity based similarity metric. The software tool uses Insight Toolkit (ITK) for image input/output, filtering, feature points identification and auto-segmentation. A B-Spline registration toolkit with invertibility regularization was adopted for mutual information similarity measure and feature point distance penalty. It includes the following steps and functionalities: (1) accepting input of images of different modalities and performing initial rigid registration. (2) Finding feature point pairs, and filtering them by bifurcation identification and distance histogram. (3) Segmenting bone, air, and soft tissue in three levels, in CT by Hounsfield value, or in MR by distinguishing piecewise zero-bound intensity areas' volume and location. Three levels of stiffness are assigned to the segmentation result for rigidity regularization. (4) Using multi-scale approach to update B-Spline coefficients and using conjugate gradient for the solver iteration. (5) Within every step, updating feature point's new position from the deformation field for distance penalty, updating mutual information and transformation Jacobian for regularization. MRI and CT data acquired for three representative breast cancer patients were used to test the software tool. The MRI T1 images were registered upon CT images. Feature point pair distances were evaluated among rigid registration, simple B-Spline registration and our proposed registration. The newly developed deformable multimodality image registration tool can accurately register MRI to CT for breast cancer patients without user interaction. The average feature point pair distance was reduced from 6.7 mm to 3.2 mm by simple B-Spline registration, and was reduced to 2.1 mm by the proposed registration method. The bone area warping artifact in deformed MRI also disappeared in the proposed method. The resulting feature point pair distance is satisfactory considering the resolution of MR images is 1.3 mm. Multimodal images (MRI and CT) for breast cancer patients, which often have large soft tissue deformation, were successfully registered to an acceptable accuracy by using the newly developed software tool, enabling RT planning with MRI-based targeting.