Michael Velec

Accumulated Dose in Liver Stereotactic Body Radiotherapy: Positioning, Breathing, and Deformation Effects

PURPOSE To investigate the accumulated dose deviations to tumors and normal tissues in liver stereotactic body radiotherapy (SBRT) and investigate their geometric causes. METHODS AND MATERIALS Thirty previously treated liver cancer patients were retrospectively evaluated. Stereotactic body radiotherapy was planned on the static exhale CT for 27-60 Gy in 6 fractions, and patients were treated in free-breathing with daily cone-beam CT guidance. Biomechanical model-based deformable image registration accumulated dose over both the planning four-dimensional (4D) CT (predicted breathing dose) and also over each fractions respiratory-correlated cone-beam CT (accumulated treatment dose). The contribution of different geometric errors to changes between the accumulated and predicted breathing dose were quantified. RESULTS Twenty-one patients (70%) had accumulated dose deviations relative to the planned static prescription dose >5%, ranging from -15% to 5% in tumors and -42% to 8% in normal tissues. Sixteen patients (53%) still had deviations relative to the 4D CT-predicted dose, which were similar in magnitude. Thirty-two tissues in these 16 patients had deviations >5% relative to the 4D CT-predicted dose, and residual setup errors (n = 17) were most often the largest cause of the deviations, followed by deformations (n = 8) and breathing variations (n = 7). CONCLUSION The majority of patients had accumulated dose deviations >5% relative to the static plan. Significant deviations relative to the predicted breathing dose still occurred in more than half the patients, commonly owing to residual setup errors. Accumulated SBRT dose may be warranted to pursue further dose escalation, adaptive SBRT, and aid in correlation with clinical outcomes.

A hybrid biomechanical intensity based deformable image registration of lung 4DCT.

Deformable image registration (DIR) has been extensively studied over the past two decades due to its essential role in many image-guided interventions (IGI). IGI demands a highly accurate registration that maintains its accuracy across the entire region of interest. This work evaluates the improvement in accuracy and consistency by refining the results of Morfeus, a biomechanical model-based DIR algorithm. A hybrid DIR algorithm is proposed based on, a biomechanical model-based DIR algorithm and a refinement step based on a B-spline intensity-based algorithm. Inhale and exhale reconstructions of four-dimensional computed tomography (4DCT) lung images from 31 patients were initially registered using the biomechanical DIR by modeling contact surface between the lungs and the chest cavity. The resulting deformations were then refined using the intensity-based algorithm to reduce any residual uncertainties. Important parameters in the intensity-based algorithm, including grid spacing, number of pyramids, and regularization coefficient, were optimized on 10 randomly-chosen patients (out of 31). Target registration error (TRE) was calculated by measuring the Euclidean distance of common anatomical points on both images after registration. For each patient a minimum of 30 points/lung were used. Grid spacing of 8 mm, 5 levels of grid pyramids, and regularization coefficient of 3.0 were found to provide optimal results on 10 randomly chosen patients. Overall the entire patient population (n = 31), the hybrid method resulted in mean ± SD (90th%) TRE of 1.5 ± 1.4 (2.9) mm compared to 3.1 ± 1.9 (5.6) using biomechanical DIR and 2.6 ± 2.5 (6.1) using intensity-based DIR alone. The proposed hybrid biomechanical modeling intensity based algorithm is a promising DIR technique which could be used in various IGI procedures. The current investigation shows the efficacy of this approach for the registration of 4DCT images of the lungs with average accuracy of 1.5 mm.

Dose escalated liver stereotactic body radiation therapy at the mean respiratory position

PURPOSE The dosimetric impact of dose probability based planning target volume (PTV) margins for liver cancer patients receiving stereotactic body radiation therapy (SBRT) was compared with standard PTV based on the internal target volume (ITV). Plan robustness was evaluated by accumulating the treatment dose to ensure delivery of the intended plan. METHODS AND MATERIALS Twenty patients planned on exhale CT for 27 to 50 Gy in 6 fractions using an ITV-based PTV and treated free-breathing were retrospectively evaluated. Isotoxic, dose escalated plans were created on midposition computed tomography (CT), representing the mean breathing position, using a dose probability PTV. The delivered doses were accumulated using biomechanical deformable registration of the daily cone beam CT based on liver targeting at the exhale or mean breathing position, for the exhale and midposition CT plans, respectively. RESULTS The dose probability PTVs were on average 38% smaller than the ITV-based PTV, enabling an average ± standard deviation increase in the planned dose to 95% of the PTV of 4.0 ± 2.8 Gy (9 ± 5%) on the midposition CT (P<.01). For both plans, the delivered minimum gross tumor volume (GTV) doses were greater than the planned nominal prescribed dose in all 20 patients and greater than the planned dose to 95% of the PTV in 18 (90%) patients. Nine patients (45%) had 1 or more GTVs with a delivered minimum dose more than 5 Gy higher with the midposition CT plan using dose probability PTV, compared with the delivered dose with the exhale CT plan using ITV-based PTV. CONCLUSIONS For isotoxic liver SBRT planned and delivered at the mean respiratory, reduced dose probability PTV enables a mean escalation of 4 Gy (9%) in 6 fractions over ITV-based PTV. This may potentially improve local control without increasing the risk of tumor underdosing.

Accumulated Delivered Dose Response of Stereotactic Body Radiation Therapy for Liver Metastases.

PURPOSE To determine whether the accumulated dose using image guided radiation therapy is a stronger predictor of clinical outcomes than the planned dose in stereotactic body radiation therapy (SBRT) for liver metastases. METHODS AND MATERIALS From 2003 to 2009, 81 patients with 142 metastases were treated in institutional review board-approved SBRT studies (5-10 fractions). Patients were treated during free breathing (with or without abdominal compression) or with controlled exhale breath-holding. SBRT was planned on a static exhale computed tomography (CT) scan, and the minimum planning target volume dose to 0.5 cm(3) (minPTV) was recorded. The accumulated minimum dose to the 0.5 cm(3) gross tumor volume (accGTV) was calculated after performing dose accumulation from exported image guided radiation therapy data sets registered to the planning CT using rigid (2-dimensional MV/kV orthogonal) or deformable (3-dimensional/4-dimensional cone beam CT) image registration. Univariate and multivariate Cox regression models assessed the factors influencing the time to local progression (TTLP). Hazard ratios for accGTV and minPTV were compared using model goodness-of-fit and bootstrapping. RESULTS Overall, the accGTV dose exceeded the minPTV dose in 98% of the lesions. For 5 to 6 fractions, accGTV doses of >45 Gy were associated with 1-year local control of 86%. On univariate analysis, the cancer subtype (breast), smaller tumor volume, and increased dose were significant predictors for improved TTLP. The dose and volume were uncorrelated; the accGTV dose and minPTV dose were correlated and were tested separately on multivariate models. Breast cancer subtype, accGTV dose (P<.001), and minPTV dose (P=.02) retained significance in the multivariate models. The univariate hazard ratio for TTLP for 5-Gy increases in accGTV versus minPTV was 0.67 versus 0.74 (all patients; 95% confidence interval of difference 0.03-0.14). Goodness-of-fit testing confirmed the accGTV dose as a stronger dose-response predictor than the minPTV dose. CONCLUSIONS The accGTV dose is a better predictor of TTLP than the minPTV dose for liver metastasis SBRT. The use of modern image guided radiation therapy in future analyses of dose-response outcomes should increase the concordance between the planned and delivered doses.

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

Purpose 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. Methods 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 (2.8 mm) and MR (5.3 mm), liver CT‐MR (4.5 mm), and prostate MR (2.6 mm). 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. Results The results of the commercial implementation were as follows. The mean DTA was ≤ 1.0 mm for controlling structures and 1.0–3.5 mm for implicitly deformed structures on average. TRE ranged from 2.0 mm on prostate MR to 5.1 mm on lung MR on average, within 0.1 mm 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 ≤ 0.8 mm. Maximum DTA > 5 mm 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 ≤ 0.5 mm for mean DTA and ≤ 0.7 mm for mean TRE. Conclusions 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.

Utility and validation of biomechanical deformable image registration in low-contrast images.

PURPOSE The application of a biomechanical deformable image registration algorithm has been demonstrated to overcome the potential limitations in the use of intensity-based algorithms on low-contrast images that lack prominent features. Because validation of deformable registration is particularly challenging on such images, the dose distribution predicted via a biomechanical algorithm was evaluated using the measured dose from a deformable dosimeter. METHODS AND MATERIALS A biomechanical model-based image registration algorithm registered computed tomographic (CT) images of an elastic radiochromic dosimeter between its undeformed and deformed positions. The algorithm aligns the external boundaries of the dosimeter, created from CT contours, and the internal displacements are solved by modeling the physical material properties of the dosimeter. The dosimeter was planned and irradiated in its deformed position, and subsequently, the delivered dose was measured with optical CT in the undeformed position. The predicted dose distribution, created by applying the deformable registration displacement map to the planned distribution, was then compared with the measured optical CT distribution. RESULTS Compared with the optical CT distribution, biomechanical image registration predicted the position and size of the deformed dose fields with mean errors of ≤1 mm (maximum, 3 mm). The accuracy did not differ between cross sections with a greater or lesser deformation magnitude despite the homogenous CT intensities throughout the dosimeter. The overall 3-dimensional voxel passing rate of the predicted distribution was γ3%/3mm = 91% compared with optical CT. CONCLUSIONS Biomechanical registration accurately predicted the deformed dose distribution measured in a deformable dosimeter, whereas previously, evaluations of a commercial intensity-based algorithm demonstrated substantial errors. The addition of biomechanical algorithms to the collection of adaptive radiation therapy tools would be valuable for dose accumulation, particularly in feature-poor images such as cone beam CT and organs such as the liver.

Simplified strategies to determine the mean respiratory position for liver radiation therapy planning

PURPOSE Establishing the time-weighted mean respiratory position in the liver is challenging due to poor tumor contrast on 4-dimensional (4D) imaging. The purpose of this study is to validate simplified strategies in determining the mean position of liver tumors for radiation therapy planning, and quantify the potential for planning target volume (PTV) reduction. METHODS AND MATERIALS Full, 10-phase 4D computed tomography (CT) data sets from 10 liver radiation therapy patients were analyzed to compare 2 techniques. First, a mid-ventilation CT was chosen from the initial reconstruction of the 4DCT. This was based on the minimum displacement of the diaphragm at each phase relative to its mean respiratory position, calculated using rigid registration over all 4DCT phases. Second, the exhale 4DCT was deformed to the inhale 4DCT using biomechanical-based deformable registration. The diaphragms mean cranio-caudal position in the respiratory cycle (normalized as a percentage relative to exhale) was applied to the exhale-to-inhale deformation map assuming a linear trajectory to reconstruct a mid-position CT. These strategies were compared with the time-weighted mean respiratory position, calculated with deformable registration over all 10 4DCT phases. PTVs incorporating respiratory motion were then compared for 2 planning strategies: exhale 4DCT using the internal target volume (ITV), or mid-position CT using dose-probability margins. RESULTS Compared with the mean respiratory tumor position, the mid-ventilation CT and mid-position CT had mean (maximum) tumor vector errors of 1.0 ± 0.5 (2.1) mm and 0.6 ± 0.3 (1.4) mm, respectively, within the image resolution. Compared with ITV-based PTV, dose-probability PTV reduced the irradiated volume by 34% ± 7% on average, up to 43%. CONCLUSIONS Simplified strategies to select a mid-ventilation CT or reconstruct a mid-position CT for the liver were validated with respect to the mean respiratory position. These data sets require significantly smaller PTVs, potentially allowing for dose-escalated liver stereotactic body radiation therapy to improve local control.

A hybrid biomechanical intensity based deformable image registration of lung 4DCT

Deformable Image Registration (DIR) has been extensively studied over the past two decades due to its essential role in many image-guided interventions. Morfeus is a DIR algorithm that works based on finite element biomechanical modeling. However, Morfeus does not utilize the entire image contrast and features which could potentially lead to a more accurate registration result. A hybrid biomechanical intensity-based method is proposed to investigate this potential benefit. Inhale and exhale 4DCT lung images of 26 patients were initially registered using Morfeus by modeling contact surface between the lungs and the chest cavity. The resulting deformations using Morfeus were refined using a B-spline intensity-based algorithm (Drop, Munich, Germany). Important parameters in Drop including grid spacing, number of pyramids, and regularization coefficient were optimized on 10 randomly-chosen patients (out of 26). The remaining parameters were selected empirically. Target Registration Error (TRE) was calculated by measuring the Euclidean distance of common anatomical points on both images before and after registration. For each patient a minimum of 30 points/lung were used. The Hybrid method resulted in mean±SD (90th%) TRE of 1.5±1.4 (2.8) mm compared to 3.1±2.0 (5.6) using Morfeus and 2.6±2.6 (6.2) using Drop alone.

A simulation study to assess the potential impact of developing normal tissue complication probability models with accumulated dose

Purpose This study aimed to analyze the potential clinical impact of the differences between planned and accumulated doses on the development and use of normal tissue complication probability (NTCP) models. Methods and Materials Thirty patients who were previously treated with stereotactic body radiation therapy for liver cancer and for whom the accumulated dose was computed were assessed retrospectively. The linear quadratic equivalent dose at 2 Gy per fraction and generalized equivalent uniform dose were calculated for planned and accumulated doses. Stomach and duodenal Lyman-Kutcher-Burman NTCP models (α/β = 2.5; n = .09) were developed on the basis of planned and accumulated generalized equivalent uniform doses and the differences between the models assessed. In addition, the error in determining the probability of toxicity on the basis of the planned dose was evaluated by comparing planned doses in the NTCP model that were created from accumulated doses. Results The standard, planned-dose NTCP model overestimates toxicity risk for both the duodenal and stomach models at doses that are below approximately 20 Gy (6 fractions) and underestimates toxicity risk for doses above approximately 20 Gy (6 fractions). Building NTCP models with accumulated rather than planned doses changes the predicted risk by up to 16% (mean: 6%; standard deviation: 7%) for duodenal toxicity and 6% (mean: 2%; standard deviation: 2%) for stomach toxicity. For a protocol that plans a 10% iso-toxicity risk to the duodenum, a 15.7 Gy (6 fractions) maximum dose constraint would be necessary when using standard NTCP models on the basis of a planned dose and a 17.6 Gy (6 fractions) maximum dose would be allowed when using NTCP models on the basis of accumulated doses. Conclusions Assuming that accumulated dose is a more accurate representation of the true delivered dose than the planned dose, this simulation study indicates the need for prospective clinical trials to evaluate the impact of building NTCP models on the basis of accumulated doses.