Gabriela Stroian

A deformable phantom for 4D radiotherapy verification: Design and image registration evaluation

Motion of thoracic tumors with respiration presents a challenge for three-dimensional (3D) conformal radiation therapy treatment. Validation of techniques aimed at measuring and minimizing the effects of respiratory motion requires a realistic deformable phantom for use as a gold standard. The purpose of this study was to develop and study the characteristics of a reproducible, tissue equivalent, deformable lung phantom. The phantom consists of a Lucite cylinder filled with water containing a latex balloon stuffed with dampened natural sponges. The balloon is attached to a piston that mimics the human diaphragm. Nylon wires and Lucite beads, emulating vascular and bronchial bifurcations, were uniformly glued at various locations throughout the sponges. The phantom is capable of simulating programmed irregular breathing patterns with varying periods and amplitudes. A tissue equivalent tumor, suitable for holding radiochromic film for dose measurements was embedded in the sponge. To assess phantom motion, eight 3D computed tomography data sets of the static phantom were acquired for eight equally spaced positions of the piston. The 3D trajectories of 12 manually chosen point landmarks and the tumor center-of-mass were studied. Motion reproducibility tests of the deformed phantom were established on seven repeat scans of three different states of compression. Deformable image registration (DIR) of the extreme breathing phases was performed. The accuracy of the DIR was evaluated by visual inspection of image overlays and quantified by the distance-to-agreement (DTA) of manually chosen point landmarks and triangulated surfaces obtained from 3D contoured structures. In initial tests of the phantom, a 20-mm excursion of the piston resulted in deformations of the balloon of 20 mm superior-inferior, 4 mm anterior-posterior, and 5 mm left-right. The change in the phantom mean lung density ranged from 0.24 (0.12 SD) g/cm3 at peak exhale to 0.19 (0.12 SD) g/cm3 at peak inhale. The SI displacement of the landmarks varied between 94% and 3% of the piston excursion for positions closer and farther away from the piston, respectively. The reproducibility of the phantom deformation was within the image resolution (0.7 x 0.7 x 1.25 mm3). Vector average registration accuracy based on point landmarks was found to be 0.5 (0.4 SD) mm. The tumor and lung mean 3D DTA obtained from triangulated surfaces were 0.4 (0.1 SD) mm and 1.0 (0.8 SD) mm, respectively. This phantom is capable of reproducibly emulating the physically realistic lung features and deformations and has a wide range of potential applications, including four-dimensional (4D) imaging, evaluation of deformable registration accuracy, 4D planning and dose delivery.

Magnitude of speed of sound aberration corrections for ultrasound image guided radiotherapy for prostate and other anatomical sites

PURPOSE The purpose of this work is to assess the magnitude of speed of sound (SOS) aberrations in three-dimensional ultrasound (US) imaging systems in image guided radiotherapy. The discrepancy between the fixed SOS value of 1540 m∕s assumed by US systems in human soft tissues and its actual nonhomogeneous distribution in patients produces small but systematic errors of up to a few millimeters in the positions of scanned structures. METHODS A correction, provided by a previously published density-based algorithm, was applied to a set of five prostate, five liver, and five breast cancer patients. The shifts of the centroids of target structures and the change in shape were evaluated. RESULTS After the correction the prostate cases showed shifts up to 3.6 mm toward the US probe, which may explain largely the reported positioning discrepancies in the literature on US systems versus other imaging modalities. Liver cases showed the largest changes in volume of the organ, up to almost 9%, and shifts of the centroids up to more than 6 mm either away or toward the US probe. Breast images showed systematic small shifts of the centroids toward the US probe with a maximum magnitude of 1.3 mm. CONCLUSIONS The applied correction in prostate and liver cancer patients shows positioning errors of several mm due to SOS aberration; the errors are smaller in breast cancer cases, but possibly becoming more important when breast tissue thickness increases.

Local Correlation Between Monte-Carlo Dose and Radiation-Induced Fibrosis in Lung Cancer Patients

PURPOSE To present a new method of evaluating the correlation between radiotherapy (RT)-induced fibrosis and the local dose delivered to non-small-cell lung cancer patients. METHODS AND MATERIALS Treatment plans were generated using the CadPlan treatment planning system (pencil beam, no heterogeneity corrections), and RT delivery was based on these plans. Retrospective Monte-Carlo dose calculations were performed, and the Monte-Carlo distributions of dose to real tissue were calculated using the planning computed tomography (CT) images and the number of monitor units actually delivered. After registration of the follow-up CT images with the planning CT images, different grades of radiologic fibrosis were automatically segmented on the follow-up CT images. Subsequently, patient-specific fibrosis probabilities were studied as a function of the local dose and a function of time after RT completion. RESULTS A strong patient-specific variation in the fibrosis volumes was found during the follow-up period. For both lungs, the threshold dose for which the probability of fibrosis became significant coincided with the threshold dose at which significant volumes of the lung were exposed. At later stages, only fibrosis localized in the high-dose regions persisted for both lungs. Overall, the Monte-Carlo dose distributions correlated much better with the probability of RT-induced fibrosis than did the CadPlan dose distributions. CONCLUSION The presented method allows for an accurate, systematic, patient-specific and post-RT time-dependent numeric study of the relationship between RT-induced fibrosis and the local dose.

Analytical modelling of regional radiotherapy dose response of lung

Knowledge of the dose-response of radiation-induced lung disease (RILD) is necessary for optimization of radiotherapy (RT) treatment plans involving thoracic cavity irradiation. This study models the time-dependent relationship between local radiation dose and post-treatment lung tissue damage measured by computed tomography (CT) imaging. Fifty-eight follow-up diagnostic CT scans from 21 non-small-cell lung cancer patients were examined. The extent of RILD was segmented on the follow-up CT images based on the increase of physical density relative to the pre-treatment CT image. The segmented RILD was locally correlated with dose distribution calculated by analytical anisotropic algorithm and the Monte Carlo method to generate the corresponding dose-response curves. The Lyman-Kutcher-Burman (LKB) model was fit to the dose-response curves at six post-RT time periods, and temporal change in the LKB parameters was recorded. In this study, we observed significant correlation between the probability of lung tissue damage and the local dose for 96% of the follow-up studies. Dose-injury correlation at the first three months after RT was significantly different from later follow-up periods in terms of steepness and threshold dose as estimated from the LKB model. Dependence of dose response on superior-inferior tumour position was also observed. The time-dependent analytical modelling of RILD might provide better understanding of the long-term behaviour of the disease and could potentially be applied to improve inverse treatment planning optimization.

SU‐E‐T‐274: Evaluation of Atlas‐Based Segmentation Algorithms: VelocityAI vs. MIMvista

Purpose: IMRT is driven by volumetric segmentation, thus greater care and accuracy are necessary when contouring structures. The contouring process requires staff experience and ample time. We have evaluated the performance of two commercial atlas‐based segmentation algorithms. Methods: VelocityAI and MIMvista were compared. Twenty‐one IMRT head and neck cases were randomly and retrospectively chosen. These cases included their respective CT scans and physician‐drawn structures. The twenty‐one cases were divided into two sets: one to create the atlas (eleven) and the other to test the atlas on (ten). In MIMvista the atlas was created using the in‐software tool and setting the most representative patient as the template. In VelocityAI the atlas was created using all ten cases to create an average patient atlas. The averaging used on the ten cases for the VelocityAI atlas was created using the STAPLE algorithm (provided by Velocity Medical Solutions).Results: Twelve OARs were compared to physician‐drawn structures using the Dice similarity coefficient (DSC). VelocityAI and MIMvista performed quite well on the brain, brainstem, spinal cord and eyes with mean DSCs ranging between 0.770– 0.947 for VelocityAI and 0.647– 0.978 for MIMvista. Neither program performed too well on the esophagus, larynx, oral cavity, parotids and sphincter muscle with mean DSCs ranging between 0.348– 0.690 for VelocityAI and 0.389–0.709 for MIMvista Conclusions: This work revealed that neither of the software truly outperformed the other. MIMvista did yield slightly better structures, yet the problem is that much modification is required to render the structures valid. VelocityAI and MIMvista both have great potential and can be used to provide a quick draft of structures, which may reduce physician‐contouring time.

MO-D-105-05: A Novel Web-Based Tool for Quantification of VMAT/IMRT Treatment Plan Quality

PURPOSE To develop a novel web-based tool for VMAT/IMRT treatment plan evaluation and to design a unique plan Quality Index (QI) quantifier to aid in decision-making for SRS, SBRT, and ENT treatment planning and evaluationMethods: A high level Python web-framework, Django, is used to develop the web application. Django uses an SQL-like database for data storage and retrieval. The front-end of the web application is styled with CSS and written in HTML. Tumor site dependent evaluation templates for SRS, SBRT and ENT plans are created in collaboration with physicians at our institution. Previously approved treatment plans are imported into the web application to populate the database for analysis. With physician feedback, retrospective treatment plans are subjected to scoring algorithms to develop a plan QI. RESULTS The web tool is currently deployed internally at our institution for VMAT treatment planners. The web site also serves as a portal for site-specific treatment planning instructions. Specific plan details are imported to an SQL-like database when treatment plans are pushed to the tool. The electronic nature of the database allows new retrospective studies to be easily conducted. A site specific QI is developed to quantify SRS, SBRT, and ENT plan quality. When the tool is used, QIs are generated automatically and a histogram of site specific QIs is produced. This information can then be used to evaluate the best candidate plan for treatment approval. The database can be used to query legacy plan specific details in order to extract the optimization objectives that best fit the anatomy and prescription doses from a new planning case. CONCLUSION The full implementation of the tool aims to standardize and unify the planning and evaluation of IMRT/VMAT techniques. Validation of the QI robustness will include correlation with clinical outcome and inter-institutional case studies.

WE‐G‐BRA‐02: Model for Time‐Dependent Radiation‐Induced Lung Disease Risk Based on Systematic Image‐Based Scoring and Monte‐Carlo Dose Calculations

Purpose: To construct an analytical model for radiation‐induced lung injury (RILD) risk using computed tomography(CT)image analysis correlated to Monte Carlo (MC) dose calculations along with investigation of the models post‐RT dependency. Methods: The extent of RILD was segmented on the difference CTimage between a planning CTimage and registered post‐RT diagnostic CTimage. Radiation dose was calculated using the anisotropic analytical algorithm (AAA) and MC methods. The segmented RILD was spatially correlated with the dose distribution to generate a dose‐response curve for each of 39 follow‐up studies from 12 subjects. The response curves were grouped into 6 follow‐up periods with 3 months intervals according to the time elapsed since the completion of RT. For each period, a probit function derived from the Lyman‐Kutcher‐Burman (LKB) model was fit to the patient data with the two adjustable parameters: TD50 (dose at 50% chances of complication) and m (steepness of the curve). Results: TD50 demonstrated a monotonic increase from its initial level (73 Gy/77 Gy for AAA/MC dose) to its peak (130 Gy/116 Gy) at 9∼12 months post‐RT after which it fell to 85 Gy/80 Gy beyond 15 months post‐ RT. The change in TD50 occurred coincidently with the decrease in the proportion of injured lung volume, demonstrating the association between TD50 and the severity of RILD. The value of m significantly decreased in time from its initial values (0.51/0.55) to 0.24/0.25 beyond 15 months post‐RT. This suggests a transition in the dose‐response from a linear‐no‐threshold to nonlinear‐threshold type behavior. Replacement of AAA calculation by MC did not yield a significant difference in the fitting parameters. Conclusions: Time‐dependent results from the analytical modeling of RILD dose response indicates the transition from early to late radiation effects and the necessity to incorporate a temporal factor into the current time‐static RILD risk models.

Poster — Thur Eve — 46: Image-Based Scoring of Radiation Injury in Lung: Analysis of Sources of Uncertainties

We are studying the robustness and uncertainties of an automated method for quantifying radiotherapy‐induced lung injury from CTimages and delineate its relationship with radiationdose at different post‐radiation (post‐RT) time points. Methods: Using multi‐resolution affine optimization technique, post‐RT diagnostic CTimages were registered to planning CTimages. Following the registration and patient tissue‐based CTcalibration, a change in physical density at each voxel position of the planning CT was evaluated and voxels which density change is considered pathological were segmented as injury. Retrospective dose calculations using anisotropic analytical algorithm (AAA) and Monte‐Carlo (MC) were performed. The segmented injury was spatially correlated to the dose distributions to deduce a patient‐specific dose‐response relationship for radiation‐induced injury. Results: We found the probability of injury as a function of dose and post‐treatment time was patient‐specific. Due to the inaccuracy of the affine registration, the injury segmentation was manually corrected for the misalignment of normal tissue features, which gave rise to a case‐dependent uncertainty of up to 10%. Inter‐patient variability in CTcalibration contributed 4% or less to the uncertainty on the probability. Finally, dose calculation from MC simulation occasionally yielded a significantly modified complication probability compared to AAA model suggesting that dose calculation accuracy is important for the investigation on dose‐response of lung injury. Conclusion: The presented method provided a quantitative approach for dose‐responseanalysis in normal lungtissues if the accuracy in image registration and dose calculation can be assured and will provide better options to complication‐driven treatment planning.

WE‐C‐204B‐04: Image‐Based Scoring of Radiation Injury in Lung for Dose‐Effect Correlations: Analysis of Sources of Uncertainties

Purpose: To investigate the robustness and uncertainties of an automated method of quantifying radiation‐induced lung injuries (pneumonitis and fibrosis) from CTimage density changes and to correlate the probabilities for the injuries with radiation dose at different post‐radiation time points.Methods and Materials: Using multi‐resolution affine optimization technique, post‐radiotherapy (RT) diagnostic CTimages were registered to planning CTimages. Following the registration and patient tissue‐based CT number calibration, a change in physical density at each voxel position of the post‐RT CT was evaluated and the voxels which density change is considered pathological was segmented as injury. The PTV was excluded from the analysis due to the lack of functional information to differentiate between recurrence and injury. Retrospective patient dose calculations using the anisotropic analytical method (AAA) and the Monte‐Carlo (MC) were performed. The segmented injury was spatially correlated to the dose distributions to deduce a patient‐specific dose‐response relationship for the radiation‐induced injury. Results: Probability of lung injury as a function of dose and post‐treatment time is patient‐dependent and can be up to 70% at the highest dose. Due to the inaccuracy of the affine registration, the injury segmentation was manually corrected for the misalignment of normal tissue features, which gave rise to a case‐dependent uncertainty of up to 10%. Inter‐patient variability in CTcalibration contributed by 4% or less to the uncertainty on the complication probability and was dependent on dose. Finally, dose calculation from direct MC simulation occasionally yielded a significantly modified complication probability than using the AAA model suggesting that dose calculation accuracy is important in the accuracy of dose‐response model of lung.Conclusion: The presented method facilitates dose‐responseanalysis in normal lungtissues if the accuracy in image registration and dose calculation can be assured and will provide options to complication‐driven treatment planning.

TH‐E‐M100J‐01: A Novel Deformable Lung Phantom for 4D Radiotherapy Verification

Purpose: To develop a reproducible, tissue equivalent, deformable lung phantom for verification of 4D‐CT scanning procedures, deformable image registration (DIR) and 4D dose calculation in moving/deformable anatomies.Methods and Materials: The phantom consists of a Lucite cylinder filled with water containing a latex balloon filled with dampened natural sponges. The balloon is attached to a piston that mimics the human diaphragm. Nylon wires and Lucite beads, emulating vascular and bronchial bifurcations, were glued at various locations, uniformly, throughout the sponges. The phantom is capable of simulating programmed irregular breathing patterns with varying periods and amplitudes. A deformable, tissue equivalent tumour holding radiochromic film was embedded in the sponge. Eight 3D‐CT datasets (0.7×0.7×1.25 mm) of the phantom in eight static positions of the piston were acquired. 3D trajectories of 12 anatomical point landmarks as well as the tumour center‐of‐mass were studied. Results: Reproducible lung deformation is achieved by piston‐provoked pressure changes in water surrounding the deforming balloon. The resulting mean density for the artificial lung was 0.243 g/cm3 comparable to 0.252 g/cm3 for a real lung. A truly 3D, non‐isotropic deformation of the balloon similar to a real lung has been obtained. The SI displacement of the landmarks varies between 94% and 3% of the diaphragm excursion for positions closer and farther away from the diaphragm, respectively. Reproducibility in the deformed phantom, established by seven repeat scans at the same phantom compression state, was within image resolution. The accuracy of DIR of the extreme phases was 0.7(±0.7) mm. Conclusions: Our novel phantom is tissue‐equivalent, deformable, and can reproducibly emulate 3D non‐isotropic lung deformations. The presence of vascular and bronchial bifurcations allows verification of DIR of 4D‐CT images of the phantom. Registered phases of the phantom can be used in 4D dose calculations that can be validated by comparison with dose measurements.