Image Registration Uncertainty Research Articles

Evaluation and mitigation of deformable image registration uncertainties for MRI-guided adaptive radiotherapy.

We evaluate the performance of a deformable image registration (DIR) software package in registering abdominal magnetic resonance images (MRIs) and then develop a mechanical modeling method to mitigate detected DIR uncertainties. Three evaluation metrics, namely mean displacement to agreement (MDA), DICE similarity coefficient (DSC), and standard deviation of Jacobian determinants (STD-JD), are used to assess the multi-modality (MM), contour-consistency (CC), and image-intensity (II)-based DIR algorithms in the MIM software package, as well as an in-house developed, contour matching-based finite element method (CM-FEM). Furthermore, we develop a hybrid FEM registration technique to modify the displacement vector field of each MIM registration. The MIM and FEM registrations were evaluated on MRIs obtained from 10 abdominal cancer patients. One-tailed Wilcoxon-Mann-Whitney (WMW) tests were conducted to compare the MIM registrations with their FEM modifications. For the registrations performed with the MIM-CC, MIM-MM, MIM-II, and CM-FEM algorithms, their average MDAs are 0.62±0.27, 2.39±1.30, 3.07±2.42, 1.04±0.72mm, and average DSCs are 0.94±0.03, 0.80±0.12, 0.77±0.15, 0.90±0.11, respectively. The p-values of the WMW tests between the MIM registrations and their FEM modifications are less than 0.0084 for STD-JDs and greater than 0.87 for MDA and DSC. Among the three MIM DIR algorithms, MIM-CC shows the smallest errors in terms of MDA and DSC but exhibits significant Jacobian uncertainties in the interior regions of abdominal organs. The hybrid FEM technique effectively mitigates the Jacobian uncertainties in these regions.

Experimental validation of multi-fraction online adaptations in magnetic resonance guided radiotherapy

Background and purposeRadiotherapy plan verification is generally performed on the reference plan based on the pre-treatment anatomy. However, the introduction of online adaptive treatments demands a new approach, as plans are created daily on different anatomies. The aim of this study was to experimentally validate the accuracy of total doses of multi-fraction plan adaptations in magnetic resonance imaging guided radiotherapy in a phantom study, isolated from the uncertainty of deformable image registration. Materials and methodsWe experimentally verified the total dose, measured on external beam therapy 3 (EBT3) film, using a treatment with five online adapted fractions. Three series of experiments were performed, each focusing on a category of inter-fractional variation; translations, rotations and body modifications. Variations were introduced during each fraction and adapted plans were generated and irradiated. Single fraction doses and total doses over five online adapted fractions were investigated. ResultsThe online adapted measurements and calculations showed a good agreement for single fractions and multi-fraction treatments for the dose profiles, gamma passing rates, dose deviations and distances to agreement. The gamma passing rate using a 2%/2 mm criterion ranged from 99.2% to 99.5% for a threshold dose of 10% of the maximum dose (Dmax) and from 96.2% to 100% for a threshold dose of 90% of Dmax, for the total translations, rotations and body modifications. ConclusionsThe total doses of multi-fraction treatments showed similar accuracies compared to single fraction treatments, indicating an accurate dosimetric outcome of a multi-fraction treatment in adaptive magnetic resonance imaging guided radiotherapy.

Estimation of Cumulative Organ Maximum Dose and Confidence Intervals for MRI-Guided Adaptive Radiotherapy of Abdominal Cancer

<h3>Purpose/Objective(s)</h3> The maximum dose (Dmax), e.g., D0.03cc (dose to 0.03cc volume), of adjacent organs at risk (OARs) is a primary dose-limiting constraint in MRI-guided adaptive radiotherapy (MRgART) of abdominal cancer. We utilized inverse consistency error (ICE) maps to estimate voxel-wise uncertainties in deformable image registration (DIR) based dose accumulation (DDA) and confidence intervals in cumulative OARs Dmax during MRgART for pancreatic cancer. <h3>Materials/Methods</h3> Motion-average reference (first fraction) and subsequent daily MRIs, collected in MRgART for five pancreatic cancer patients treated with 33 Gy in 5 fractions on a 1.5T MR-Linac, were registered using a free-form DIR algorithm based on feature similarity scoring metrics and were used to accumulate daily doses. Forward and reverse DIRs were performed, and ICE maps were calculated in the reference image. The correlation between ICE and actual registration error (RE) was assessed by identifying anatomical landmarks (63) in a reference-daily image pair and measuring the landmark REs (after forward-DIR) and ICEs (after forward and reverse DIRs). To account for the deformation vector field spatial uncertainty affecting the DDA, for each voxel in the reference image we associated a cloud of dose grid points centered at the voxel landing coordinates in the daily image with a radius proportional to the ICE length. We considered that the cloud would encompass the "true" registration point with a high likelihood. The uncertainty in the dose mapped to each voxel from each fraction was determined as the standard deviation of the grid point doses within the cloud. The maxima and minima of the dose distributions were computed from the cumulative uncertainties, and confidence intervals for Dmax were determined. <h3>Results</h3> The measured REs and ICEs for landmarks indicated a positive correlation between these errors (Pearson's correlation coefficient r=0.795, p-value=7.04 × 10⁻¹⁵), RE being about twice ICE. The ICEs averaged 1.5 mm and 2.5 mm in the duodenum and stomach. For the duodenum, cumulative D0.03cc and D1cc at the end of treatment ranged from 85.7% to 100.4% of the plan constraint value (confidence intervals included). The uncertainty intervals were between 1.1% and 2.2% in four cases and approximately 7% for the fifth case. Cumulative D0.03cc in the stomach varied from 89.4% to 102.8%, with uncertainty intervals that extended from 2.5% to 6.4%. All Dmax lower limits were below 100%. <h3>Conclusion</h3> Voxel-wise uncertainties in DIR-based dose accumulation during MRgART of abdominal cancer can be estimated using an ICE-based technique. The derived confidence intervals for cumulative Dmax (D1cc or D0.03cc) of OARs (the duodenum and stomach) can be utilized to guide daily dose adaptation throughout MRgART.

Patient-Specific Quality Assurance of Deformable Image Registrations Using Atlas for Adaptive Radiotherapy of Lung Cancer

<h3>Purpose/Objective(s)</h3> Evaluating the uncertainty of deformable image registration (DIR) is challenging because the ground truth is often unavailable. We developed an automated method to create realistic deformations via an atlas and assess DIR algorithms on a patient-specific level for adaptive radiotherapy. <h3>Materials/Methods</h3> A library of deformations was created by extracting the longitudinal anatomical changes observed from an atlas of 60 locally advanced non-small cell lung cancer patients treated with IMRT (60Gy, 30 fx). The deformation vector field (DVF) between the planning CT (pCT) and last weekly CBCT of an atlas patient was derived via a free-form DIR algorithm and served as a ground truth pattern. An inquiry patient was first matched to an atlas patient on gross tumor volume (GTV) location and volume. The pCT of an inquiry patient was then deformably registered to that of an atlas patient to establish a voxel-based correspondence. Then, the deformation pattern of the atlas patient was transferred to the inquiry patient pCT by applying the known DVF to the corresponding voxels, resulting in a digital CT phantom. Subsequently, this CT phantom was appended with CBCT artifacts using a physics-based augmentation (Alam, PMB 2021) to imitate a weekly CBCT. To evaluate DIRs, a large deformation diffeomorphic metric mapping (LDDMM) algorithm, and two commercial systems (C1 C2) were used between the phantom (both simulated CT and CBCT) and actual pCT of the inquiry patient. Derived DVFs were compared to the ground truth. The voxel-level geometric and dosimetric uncertainties of DIRs were calculated using the DVF95% errors, fraction of volume with ≤1.5mm errors (V1.5mm) and mean dose errors (D_mean) for GTV and esophagus. <h3>Results</h3> In a retrospective evaluation of 10 paired inquiry and atlas patients, the actual deformations observed between the pCT and weekly CBCTs of inquiry patients were well-contained by the combined patterns from the matched atlas, validating the feasibility of an atlas. LDDMM performed consistently well, especially for the CT-CBCT registration (p<0.01, two-tailed t-test). GTV mean dose is less sensitive to DIR errors than esophagus mean dose. <h3>Conclusion</h3> It is feasible to augment anatomical changes for a particular inquiry patient using deformation patterns from matched patients in an atlas and evaluate the uncertainty of DIR algorithms in realistic simulations. Integration of such an automated program facilitates the clinical implementation of adaptive radiotherapy that involves longitudinal imaging studies.

An Estimate of Uncertainty in Deformable Image Registration-Based Accumulated Biological Equivalent Dose for Re-Irradiation

<h3>Purpose/Objective(s)</h3> We describe a dose volume histogram (DVH) overlay technique to estimate uncertainty in deformable image registration (DIR) based accumulated biologically equivalent dose (BED) for re-irradiation planning. We compare applicability of two DIR methods, contour-based (C-DIR) and image intensity and contour hybrid (H-DIR) DIR for BED accumulation. <h3>Materials/Methods</h3> Patient CT-based re-irradiation plans to the same anatomic regions as in their initial irradiations over a four-year period were analyzed. Among the organs-at-risk (OARs) for which BED was accumulated were stomach, heart, and esophagus. Physical dose distributions were converted to BED using OAR-specific parameters based on a linear-quadratic-linear model. For C-DIR, the registration was based only upon the contours drawn on both images. H-DIR is an image intensity-based DIR technique which includes contour-based registration to augment the DIR results. All prior BEDs were warped to the most recent CT image for accumulation. Data input to the DVH overlay workflow were the two CT images to be registered, the deformation vector field, the BED on the earlier CT, and the contours on the later CT. The later-CT contours were warped to the earlier CT, and the earlier-CT BED was warped to the later CT; BED DVHs from both images were then calculated and overlaid. For a fully invertible DIR, the two DVHs for the OAR should be identical; differences between the DVHs were interpreted as BED uncertainties due to inverse consistency error. For a given DVH point, the uncertainty was obtained from the differences between the overlaid DVHs. <h3>Results</h3> For an abdomen case, the stomach accumulated BED_max is 3% higher using C-DIR versus H-DIR; ΔBED_max is approximately 2% for both DIR methods. The higher isodoses were distal to the stomach for all plans; H-DIR, which accounts for regions distal to the OAR, is appropriate for re-irradiation BED calculations. For a thoracic case, both DIR methods yield similar results for the heart. The difference between H-DIR and C-DIR for accumulated heart BED_max is 2.4%; ΔBED_max is 0.9% and 0.6% for H-DIR and C-DIR, respectively. For the esophagus, accumulated BED_max is 54% higher using H-DIR instead of C-DIR, and ΔBED_max is much lower for C-DIR (0.2%) than for H-DIR (1.7%). Visual inspection showed that the BED distribution on the esophagus using H-DIR is unreasonable, attributed to H-DIR relying too heavily upon image intensity features. For accurate BED accumulation in the esophagus, C-DIR is essential during the re-irradiation planning for this case. <h3>Conclusion</h3> The DVH overlay technique can estimate the uncertainty in accumulated BED for re-irradiation scenarios. Caution should be exercised in using various DIR methods before applying DIR dose accumulation for re-irradiation planning. Contour-based DIR may be the preferred registration method for re-irradiation dose accumulation.

PD-0400 Quantitative deformable image registration uncertainty framework for proton head and neck treatment

PD-0400 Quantitative deformable image registration uncertainty framework for proton head and neck treatment

Uncertainty quantification in non-rigid image registration via stochastic gradient Markov chain Monte Carlo

We develop a new Bayesian model for non-rigid registration of three-dimensional medical images, with a focus on uncertainty quantification. Probabilistic registration of large images with calibrated uncertainty estimates is difficult for both computational and modelling reasons. To address the computational issues, we explore connections between the Markov chain Monte Carlo by backpropagation and the variational inference by backpropagation frameworks, in order to efficiently draw samples from the posterior distribution of transformation parameters. To address the modelling issues, we formulate a Bayesian model for image registration that overcomes the existing barriers when using a dense, high-dimensional, and diffeomorphic transformation parametrisation. This results in improved calibration of uncertainty estimates. We compare the model in terms of both image registration accuracy and uncertainty quantification to VoxelMorph, a state-of-the-art image registration model based on deep learning.

Consistency Check of Deformable Image Registration-Based Dose Summation for Off-Line Adaptive Re-Planning

<h3>Purpose/Objective(s)</h3> Uncertainty of deformable image registration (DIR) based dose accumulation is a concern due to the uncertainty with the DIR, in particular for a large deformation. In this work, we introduce a practical workflow of using a DVH overlay technique to check consistency in DIR-based dose accumulation during off-line adaptive replanning for large deformations observed during radiation therapy for abdominal tumors. <h3>Materials/Methods</h3> Required inputs to the DVH overlay workflow are deformably registered primary (original plan) and secondary (re-plan) images, primary regions-of-interest (ROIs), and a secondary dose distribution. Primary ROIs are forward warped to the secondary image, secondary dose is inversely warped to the primary image, and the ROI DVHs for each image are overlaid. Differences between the DVHs at a given dose point (e.g., V_45Gy) quantify the dose uncertainty due to inverse consistency error (ICE) inherent in the DIR. We applied the workflow to a pancreas case treated using modulated arc therapy (mARC) on a Linac equipped with integrated kVCT-on-rails IGRT. For the original plan, 65.25-Gy and 50.75-Gy PTVs were concurrently treated over 29 fractions. After fraction 21, the patient was observed to have lost sufficient weight to justify an adaptive mARC plan based on an updated kVCT image. A composite dose distribution was compiled on the original plan CT by summing 21 fractions of the original planned dose and 8 fractions of a dose distribution warped from the re-plan CT to the original plan CT. Warping was performed using a hybrid DIR algorithm combining contour-based and image-based registration. For each organ-at-risk (OAR) DVH dose point, the workflow-derived ICE (scaled to 8 fractions) was additively applied as an uncertainty to the summation DVH. <h3>Results</h3> For the re-planned pancreas case, ICE based on the DVH overlay workflow was greatest for the small bowel V_45Gy (approximately 5%) and for the stomach V_45Gy and V_56Gy (approximately 2% for both). ICE was also approximately 4% at V_15Gy for the duodenum and colon. For all other ROIs, ICE was 1% or less from the DVH overlay, indicating a favorable DIR for those regions. When applying the DVH overlay-based ICE the resulting accumulated dose remained compliant with the original plan objectives for all OARs except for the stomach V_56Gy, which equaled 7.9 cm³ with ICE included (plan objective < 5 cm³). <h3>Conclusion</h3> A DVH overlay technique was used to estimate ICE attributable to the uncertainty in DIR-based dose accumulation. The method was applied to a pancreas case for which dose accumulation was performed due to off-line adaptive re-planning for a large anatomic change during the treatment course. In instances where the ICE is over a pre-defined threshold or the summation dose exceeds plan objectives if ICE is included, it is prudent to review the DIR dose transfer and accumulation before using it to make clinical decisions.

Colorimetrical uncertainty estimation for the performance assessment of whole slide imaging scanners.

Purpose: Whole slide imaging (WSI) scanners produce tissue slide images with a large field of view and a high resolution for pathologists to use in diagnoses. Color performance tests of these color imaging devices are necessary and can use stained tissue slides if the color truth is established using a hyperspectral imaging microscopy system (HIMS). The purpose of this study was to estimate the reproducibility uncertainty of CIELAB coordinates for a reference tissue slide measured by both the HIMS and a WSI scanner. Approach: We compared the color performances of the WSI scanner to those of the reference established by the HIMS using the International Commission on Illumination (Commission Internationale de l'Éclairage, or CIE) 1976 color difference with the just noticeable color difference (JNCD, ), and the results from the overlap of the CIELAB coordinates' uncertainty within the error bar, with a coverage factor . The reported uncertainty results from measurements and image registration uncertainties. Results: For the blank area common to the HIMS and the WSI average images, the color agreement was higher using the JNCD condition versus the CIELAB uncertainty overlap criterion (82% and 20% of the pixels in the images, respectively). This difference is explained by the fact that numerous pixels have CIELAB coordinates near one another but corresponding to CIELAB uncertainty values small enough not to overlap. In the colored area of the images, the JNCD condition was met for 0.19% of the pixels in the images, compared with 4.3% for the CIELAB uncertainty overlap criterion. Conclusions: The distribution of uncertainties on the CIELAB coordinates was broader for the HIMS compared with the WSI scanner. The WSI scanner had a systemic error in the color reproduction, which pointed to a potential inadequate color calibration of this device.

Dosimetric influence of deformable image registration uncertainties on propagated structures for online daily adaptive proton therapy of lung cancer patients

PurposeA major burden of introducing an online daily adaptive proton therapy (DAPT) workflow is the time and resources needed to correct the daily propagated contours. In this study, we evaluated the dosimetric impact of neglecting the online correction of the propagated contours in a DAPT workflow. Material and methodsFor five NSCLC patients with nine repeated deep-inspiration breath-hold CTs, proton therapy plans were optimised on the planning CT to deliver 60 Gy-RBE in 30 fractions. All repeated CTs were registered with six different clinically used deformable image registration (DIR) algorithms to the corresponding planning CT. Structures were propagated rigidly and with each DIR algorithm and reference structures were contoured on each repeated CT. DAPT plans were optimised with the uncorrected, propagated structures (propagated DAPT doses) and on the reference structures (ideal DAPT doses), non-adapted doses were recalculated on all repeated CTs. ResultsDue to anatomical changes occurring during the therapy, the clinical target volume (CTV) coverage of the non-adapted doses reduces on average by 9.7% (V95) compared to an ideal DAPT doses. For the propagated DAPT doses, the CTV coverage was always restored (average differences in the CTV V95 < 1% compared to the ideal DAPT doses). Hotspots were always reduced with any DAPT approach. ConclusionFor the patients presented here, a benefit of online DAPT was shown, even if the daily optimisation is based on propagated structures with some residual uncertainties. However, a careful (offline) structure review is necessary and corrections can be included in an offline adaption.

Deformable image registration uncertainty for inter-fractional dose accumulation of lung cancer proton therapy

Background and purposeNon-small cell lung cancer (NSCLC) patients show typically large anatomical changes during treatment, making recalculation or adaption necessary. For report and review, the applied treatment dose can be accumulated on the reference planning CT using deformable image registration (DIR). We investigated the dosimetric impact of using six different clinically available DIR algorithms for dose accumulation in presence of inter-fractional anatomy variations. Materials and methodsFor seven NSCLC patients, proton treatment plans with 66 Gy-RBE to the planning target volume (PTV) were optimised. Nine repeated CTs were registered to the planning CT using six DIR algorithms each. All CTs were acquired in visually guided deep-inspiration breath-hold. The plans were recalculated on the repeated CTs and warped back to the planning CT using the corresponding DIRs. Fraction doses warped with the same DIR were summed up to six different accumulated dose distributions per patient, and compared to the initial dose. ResultsThe PTV-V95 of accumulated doses decreased by 16% on average over all patients, with variations due to DIR selection of 8.7%. A separation of the dose effects caused by anatomical changes and DIR uncertainty showed a good agreement between the dose degradation caused by anatomical changes and the dose predicted from the average of all DIRs (differences of only 1.6%). ConclusionThe dose degradation caused by anatomical changes was more pronounced than the uncertainty of employing different DIRs for dose accumulation, with averaged results from several DIRs providing a good representation of dose degradation caused by anatomy. However, accumulated dose variations between DIRs can be substantial, leading to an additional dose uncertainty.

The rationale for MR-only delineation and planning: retrospective CT–MR registration and target volume analysis for prostate radiotherapy

AbstractAim:Magnetic resonance imaging (MRI) is indispensable for treatment planning in prostate radiotherapy (PR). Registration of MRI when compared to planning CT (pCT) is prone to uncertainty and this is rarely reported. In this study, we have compared three different types of registration methods to justify the direct use of MRI in PR.Methods and materials:Thirty patients treated for PR were retrospectively selected for this study and all underwent both CT and MRI. The MR scans were registered to the pCT using markers, focused and unfocussed methods and their registration are REGM, REGF, and REGNF, respectively. Registration comparison is done using the translational differences of three axes from the centre-of-mass values of gross tumour volume (GTV) generated using MRI.Results:The average difference in all three axes (x, y, z) is (1, 2·5, 2·3 mm) and (1, 3, 2·3 mm) for REGF-REFNF and REGF-REGM, respectively. MR-based GTV Volume is less in comparison to CT-based GTV and it is significantly different (p &lt; 0·001).Findings:Image registration uncertainty is unavoidable for a regular CT–MR workflow. Additional planning target volume margin ranging from 2 to 3mm could be avoided if MR-only workflow is employed. This reduction in the margin is beneficial for small tumours treated with hypofractionation.

Registration uncertainty quantification via low-dimensional characterization of geometric deformations

This paper presents an efficient approach to quantifying image registration uncertainty based on a low-dimensional representation of geometric deformations. In contrast to previous methods, we develop a Bayesian diffeomorphic registration framework in a bandlimited space, rather than a high-dimensional image space. We show that a dense posterior distribution on deformation fields can be fully characterized by much fewer parameters, which dramatically reduces the computational complexity of model inferences. To further avoid heavy computation loads introduced by random sampling algorithms, we approximate a marginal posterior by using Laplace's method at the optimal solution of log-posterior distribution. Experimental results on both 2D synthetic data and real 3D brain magnetic resonance imaging (MRI) scans demonstrate that our method is significantly faster than the state-of-the-art diffeomorphic registration uncertainty quantification algorithms, while producing comparable results.

Efficient Laplace Approximation for Bayesian Registration Uncertainty Quantification.

This paper presents a novel approach to modeling the pos terior distribution in image registration that is computationally efficient for large deformation diffeomorphic metric mapping (LDDMM). We develop a Laplace approximation of Bayesian registration models entirely in a bandlimited space that fully describes the properties of diffeomorphic transformations. In contrast to current methods, we compute the inverse Hessian at the mode of the posterior distribution of diffeomorphisms directly in the low dimensional frequency domain. This dramatically reduces the computational complexity of approximating posterior marginals in the high dimensional imaging space. Experimental results show that our method is significantly faster than the state-of-the-art diffeomorphic image registration uncertainty quantification algorithms, while producing comparable results. The efficiency of our method strengthens the feasibility in prospective clinical applications, e.g., real- time image-guided navigation for brain surgery.

Deep inspiration breath-hold radiotherapy for lung cancer: impact on image quality and registration uncertainty in cone beam CT image guidance

We investigated the impact of deep inspiration breath-hold (DIBH) and tumour baseline shifts on image quality and registration uncertainty in image-guided DIBH radiotherapy (RT) for locally advanced lung cancer. Patients treated with daily cone beam CT (CBCT)-guided free-breathing (FB) RT had an additional CBCT in DIBH at three fractions. These CBCT scans were offline rigidly registered (on tumour) to FB and DIBH CT scans acquired at planning. All registrations were repeated to evaluate the intraobserver uncertainty. CBCT scans were scored on degree of streak artefacts and visualization of tumour and anatomical structures. We examined the impact of tumour baseline shift between consecutive DIBHs on CBCT image quality. CBCT scans from 15 patients were analysed. Intraobserver image registration uncertainty was approximately 2 mm in both FB and DIBH, except for the craniocaudal direction in FB, where it was >3 mm. On the 31st fraction, the intraobserver uncertainty increased compared with the second fraction. This increase was more pronounced in FB. Image quality scores improved in DIBH compared with FB for all parameters in all patients. Simulated tumour baseline shifts ≤2 mm did not affect the CBCT image quality considerably. DIBH CBCT improved image quality and reduced registration uncertainty in the craniocaudal direction in image-guided RT of locally advanced lung cancer. Baseline shifts ≤2 mm in DIBH during CBCT acquisition did not affect image quality. Advances in knowledge: DIBH RT has dosimetric advantages over FB; this work demonstrates an additional benefit of DIBH in terms of registration accuracy because of improved image quality.

A Systematic Analysis of Errors in Target Localization and Treatment Delivery for Stereotactic Radiosurgery Using 2D/3D Image Registration.

To determine the localization uncertainties associated with 2-dimensional/3-dimensional image registration in comparison to 3-dimensional/3-dimensional image registration in 6 dimensions on a Varian Edge Linac under various imaging conditions. The systematic errors in 6 dimensions were assessed by comparing automatic 2-dimensional/3-dimensional (kV/MV vs computed tomography) with 3-dimensional/3-dimensional (cone beam computed tomography vs computed tomography) image registrations under various conditions encountered in clinical applications. The 2-dimensional/3-dimensional image registration uncertainties for 88 patients with different treatment sites including intracranial and extracranial were evaluated by statistically analyzing 2-dimensional/3-dimensional pretreatment verification shifts of 192 fractions in stereotactic radiosurgery and stereotactic body radiotherapy. The systematic errors of 2-dimensional/3-dimensional image registration using kV-kV, MV-kV, and MV-MV image pairs were within 0.3 mm and 0.3° for the translational and rotational directions within a 95% confidence interval. No significant difference ( P > .05) in target localization was observed with various computed tomography slice thicknesses (0.8, 1, 2, and 3 mm). Two-dimensional/3-dimensional registration had the best accuracy when pattern intensity and content filter were used. For intracranial sites, means ± standard deviations of translational errors were -0.20 ± 0.70 mm, 0.04 ± 0.50 mm, and 0.10 ± 0.40 mm for the longitudinal, lateral, and vertical directions, respectively. For extracranial sites, means ± standard deviations of translational errors were -0.04 ± 1.00 mm, 0.2 ± 1.0 mm, and 0.1 ± 1.0 mm for the longitudinal, lateral, and vertical directions, respectively. Two-dimensional/3-dimensional image registration for intracranial and extracranial sites had comparable systematic errors that were approximately 0.2 mm in the translational direction and 0.08° in the rotational direction. The standard 2-dimensional/3-dimensional image registration tool available on the Varian Edge radiosurgery device, a state-of-the-art system, is helpful for robust and accurate target positioning for image-guided stereotactic radiosurgery.

Evaluation of positioning uncertainty for frameless radiosurgery for three IGRT methods with a head phantom

Introduction A BRAINLAB system for frameless radiosurgery is commissioned obtaining patient positioning accuracy with the STEEV head phantom (CIRS). Purpose Firstly the position accuracy for frameless radiosurgery has been compared with three different IGRT methods: EXACTRAC (BRANLAB), OBI-2D (VARIAN) and CBCT (VARIAN) with EXACTRAC registration. Secondly the uncertainty of image registration between MRI (PHILIPS INGENIA SYSTEMS 3.0T) and CT (PHILIPS BIG BORE) has been evaluated with IPLANRT image 4.1.1 software. Materials and methods Phantom positioning was done with automatic registration and with equivalent X-ray parameters for the three IGRT methods. Measurement was done 5 times, every of these the phantom with mask was replaced. Position accuracy was evaluated with the tool “detect Winston-Lutz pointer” from EXACTRAC. CT and MRI images of a multimodality fillable sphere insert in the phantom were registered. The registration was evaluated with IPLANRT image software finding the center of the sphere in each modality. Results For the three IGRT techniques the accuracy obtained was (0.466 ± 0.071)mm for EXACTRAC, (0.744 ± 0.209)mm for OBI-2D and (0.750 ± 0.386)mm for CBCT registered with EXACTRAC. For MRI was obtained (0.300 ± 0.1)mm. The total uncertainty for EXACTRACT IGRT system is (0.554 ± 0.374)mm (k = 2). Conclusions • The positioning system EXACTRAC have less uncertainty than both OBI-2D and CBCT registered with EXACTRAC for cranial SRS. • The total uncertainty for the EXACTRAC including IGRT and also image registration between CT and MRI is (0.554 ± 0.374)mm.

SU‐D‐BRA‐03: Analysis of Systematic Errors with 2D/3D Image Registration for Target Localization and Treatment Delivery in Stereotactic Radiosurgery

Purpose:Determine systematic deviations between 2D/3D and 3D/3D image registrations with six degrees of freedom (6DOF) for various imaging modalities and registration algorithms on the Varian Edge Linac.Methods:The 6DOF systematic errors were assessed by comparing automated 2D/3D (kV/MV vs. CT) with 3D/3D (CBCT vs. CT) image registrations from different imaging pairs, CT slice thicknesses, couch angles, similarity measures, etc., using a Rando head and a pelvic phantom. The 2D/3D image registration accuracy was evaluated at different treatment sites (intra‐cranial and extra‐cranial) by statistically analyzing 2D/3D pre‐treatment verification against 3D/3D localization of 192 Stereotactic Radiosurgery/Stereotactic Body Radiation Therapy treatment fractions for 88 patients.Results:The systematic errors of 2D/3D image registration using kV‐kV, MV‐kV and MV‐MV image pairs using 0.8 mm slice thickness CT images were within 0.3 mm and 0.3° for translations and rotations with a 95% confidence interval (CI). No significant difference between 2D/3D and 3D/3D image registrations (P&gt;0.05) was observed for target localization at various CT slice thicknesses ranging from 0.8 to 3 mm. Couch angles (30, 45, 60 degree) did not impact the accuracy of 2D/3D image registration. Using pattern intensity with content image filtering was recommended for 2D/3D image registration to achieve the best accuracy. For the patient study, translational error was within 2 mm and rotational error was within 0.6 degrees in terms of 95% CI for 2D/3D image registration. For intra‐cranial sites, means and std. deviations of translational errors were −0.2±0.7, 0.04±0.5, 0.1±0.4 mm for LNG, LAT, VRT directions, respectively. For extra‐cranial sites, means and std. deviations of translational errors were ‐ 0.04±1, 0.2±1, 0.1±1 mm for LNG, LAT, VRT directions, respectively. 2D/3D image registration uncertainties for intra‐cranial and extra‐cranial sites were comparable.Conclusion:The Varian Edge radiosurgery 6DOF‐based system, can perform 2D/3D image registration with high accuracy for target localization in image‐guided stereotactic radiosurgery.The work was supported by a Research Scholar Grant, RSG‐15‐137‐01‐CCE from the American Cancer Society.

Real patient data based cross verification of kilovoltage and megavoltage CT calibration for proton therapy

PurposeWe propose a methodology to evaluate the stoichiometric calibration method on MVCT against the corresponding kVCT calibration using patient data. MethodsStoichiometric calibrations were conducted for a MVCT and a kVCT scanner, respectively. We retrospectively analyzed kVCT and MVCT images of 21 patients by picking small tissue volumes in kVCT images and performing image registration to locate the tissue volumes in corresponding MVCT images. We computed the difference between the mean proton stopping power derived through kVCT and MVCT calibration, taking into account the uncertainties in calibration, imaging, and image registration. ResultskVCT and MVCT calibration curves were in good agreement for soft tissues such as muscle and brain, but showed statistically significant difference (p < 0.05) in stopping power of adipose (2.4 ± 1.7%) and bony structures such as spongiosa, and cranium (−3.2 ± 1.4 and −3.1 ± 2.1%, respectively). ConclusionThe MVCT calibration might not agree with the corresponding kVCT calibration for some tissues.

Focal partial salvage low-dose-rate brachytherapy for local recurrent prostate cancer after permanent prostate brachytherapy with a review of the literature.

PurposeTo investigate the treatment results for focal partial salvage re-implantation against local recurrence after permanent prostate brachytherapy.Material and methodsBetween January 2010 and September 2015, 12 patients were treated with focal partial salvage re-implantation for local recurrence after low-dose-rate brachytherapy using 125I seeds. The focal clinical target volume (F-CTV) was delineated on positive biopsy areas in a mapping biopsy, combining the cold spots on the post-implant dosimetry for initial brachytherapy. The F-CTV was expanded by 3 mm to create the planning target volume (PTV) as a margin to compensate for uncertainties in image registration and treatment delivery. The prescribed dose to the PTV was 145 Gy. The characteristics and biochemical disease-free survival (BdFS) rates were analyzed. Genitourinary (GU) and gastrointestinal (GI) toxicities were evaluated using the Common Terminology Criteria for Adverse Events version 4.ResultsThe median prostate-specific antigen (PSA) level at re-implantation was 4.09 ng/ml (range: 2.91-8.24 ng/ml). The median follow-up time was 56 months (range: 6-74 months). The median RD2cc and UD10 were 63 Gy and 159 Gy, respectively. The 4-year BdFS rate was 78%, which included non-responders. Biochemical recurrence occurred in two patients after 7 and 31 months, respectively. The former was treated with hormonal therapy after biochemical failure, and the latter underwent watchful waiting (PSA at the last follow-up of 53 months: 7.3 ng/ml) at the patient's request. No patients had grade 3 GU/GI toxicities or died after salvage re-implantation.ConclusionsThe partial salvage low-dose-rate brachytherapy used to treat local recurrence after permanent prostate brachytherapy is well-tolerated, with high biochemical response rates. This treatment can be not only a method to delay chemical castration but also a curative treatment option in cases of local recurrence of prostate carcinoma after seed implantation.