bluuebunny/crossref_metadata_2025_split huggingface dataset:
SU‐F‐J‐80: Deformable Image Registration for Residual Organ Motion Estimation in Respiratory Gated Treatments with Scanned Carbon Ion Beams
Authors: Meschini G , Seregni M , Pella A , Baroni G , Riboldi M 
Published: July 2016

Purpose:At the Centro Nazionale di Adroterapia Oncologica (CNAO, Pavia, Italy) C‐ions respiratory gated treatments of patients with abdominal tumours started in 2014. In these cases, the therapeutic dose is delivered around end‐exhale. We propose the use of a respiratory motion model to evaluate residual tumour motion. Such a model requires motion fields obtained from deformable image registration (DIR) between 4DCT phases, estimating anatomical motion through interpolation. The aim of this work is to identify the optimal DIR technique to be integrated in the modeling pipeline.Methods:We used 4DCT datasets from 4 patients to test 4 DIR algorithms: Bspline, demons, log‐domain and symmetric log domain diffeomorphic demons. We evaluate DIR performance in terms of registration accuracy (RMSE between registered images) and anatomical consistency of the motion field (Jacobian) when registering end‐inhale to end‐exhale. We subsequently employed the model to estimate the tumour trajectory within the ideal gating window.Results:Within the liver contour, the RMSE is in the range 31–46 HU for the best performing algorithm (Bspline) and 43–145 HU for the worst one (demons). The Jacobians featured zero negative voxels (which indicate singularities in the motion field) for the Bspline fields in 3 of 4 patients, whereas diffeomorphic demons fields showed a non‐null number of negative voxels in every case. GTV motion in the gating window measured less than 7 mm for every patient, displaying a predominant superior‐inferior (SI) component.Conclusion:The Bspline algorithm allows for acceptable DIR results in the abdominal region, exhibiting the property of anatomical consistency of the computed field. Computed trajectories are in agreement with clinical expectations (small and prevalent SI displacements), since patients lie wearing semi‐rigid immobilizing masks. In future, the model could be used for retrospective estimation of organ motion during treatment, as guided by the breathing surrogate signal.
SU‐F‐J‐82: A Rapid Direct Method for Inverting Respiratory Deformation Fields
Authors: Dubey A , Iliopoulos AS , Sun X , Yin FF , Ren L 
Published: July 2016

Purpose:To enable efficient and consistent registrationbetween source and target images, related bynonlinear but periodic deformation, with particular focus on 4D CTimages.Methods:We present a non‐iterative method for inverting forward (or backward) deformation fields from a sequence of p CT images in arespiratory cycle. By exploiting the cyclic structure, the direct inversion methodeffectively factors the inverse transformation between any two frames inthe respiratory sequence into no more than p forward (or backward) transformations, which are available in the provided forward (or backward) sequence.Results:The direct method, inspired by a fixed‐point iteration method, iscompared to the iterative method with an analytical phantom and a XCATlung phantom. With the analytic phantom, the new method renders the reversed deformation field in no more than p steps with satisfactory accuracy (RMSE is below 1E‐10, for example), while the iterative method becomes slow, very slow or divergent under various conditions such as large deformation. The direct method is efficient and with the XCAT phantom as well. However, when interpolations are spatial resolution limited and by low‐degree interpolant, the direct method suffers from the introduced perturbation due to the lack of self‐correction capability. The direct method can be used as aprediction step, making large deformation small and followed bycorrection by an iterative method.Conclusion:A direct method is presented for inverting periodic motion fields with high efficiency. When interpolation is resolution limited, the method can be used in combination with an iterative method, especially, for the case where the deformation is large and the iterative method may not converge.NIH Grant No: R01‐184173
SU‐F‐J‐83: Estimation of Deformation Field with Two‐Scale Supervoxel Equations
Authors: Dubey A , Iliopoulos AS , Sun X , Yin FF , Ren L 
Published: July 2016

Purpose:To circumvent the ill‐posedness in the problem to estimate inhomogeneous motion or deformation field without resorting to global regularization conditions.Methods:We present a novel method for deformable registration. First, we estimate the deformation field at a coarse resolution level, with super‐voxels as the spatial elements, keeping the target/reference image remains at the fine resolution. The resultant system of nonlinear equations are no longer under‐determined. Next we establish local systems of 2‐scale equations to determine the difference in deformation between the coarser level and the fine level, namely, the relative deformation between each super‐voxel and its 8 sub‐pixels. The equations are set up as follows. Consider an arbitrarily fixed super‐voxel, we refer to it as the pivot voxel to be refined. Partition the other super‐voxels as its near neighbors or far neighbors. In the local equations, the deformation at far neighbors are fixed as that obtained at the coarse resolution. The relative deformation at the sub‐voxels within the pivot voxel is unknown and to be estimated. The deformation at the near neighbors is allowed to undergo changes, acting as elastic variables bridging the deformation associated with sub‐pixels within the pivot voxel and that over the far neighbors. Each local system is not under‐determined. The refinement is regularized by the principle of strong near‐neighbor influence and weak far‐neighbor influence, inspired primarily by the celebrated numerical Fast Multiple Method.Results:We demonstrate the viability and efficacy of the new method using 2D XCAT lung images. We provide comparisons to two other commonly used iterative methods.Conclusion:The proposed method is essentially a self‐regularization mechanism, which is adaptive, non‐parametric, non‐global, in the sense that the solution at the finer resolution is regulated by the deformation structure itself at multiple resolution scale.NIH Grant No: R01‐184173
SU‐F‐J‐86: Method to Include Tissue Dose Response Effect in Deformable Image Registration
Authors: Zhu J , Liang J , Chen S , Qin A , Yan D 
Published: July 2016

Purpose:Organ changes shape and size during radiation treatment due to both mechanical stress and radiation dose response. However, the dose response induced deformation has not been considered in conventional deformable image registration (DIR). A novel DIR approach is proposed to include both tissue elasticity and radiation dose induced organ deformation.Methods:Assuming that organ sub‐volume shrinkage was proportional to the radiation dose induced cell killing/absorption, the dose induced organ volume change was simulated applying virtual temperature on each sub‐volume. Hence, both stress and heterogeneity temperature induced organ deformation. Thermal stress finite element method with organ surface boundary condition was used to solve deformation. Initial boundary correspondence on organ surface was created from conventional DIR. Boundary condition was updated by an iterative optimization scheme to minimize elastic deformation energy. The registration was validated on a numerical phantom. Treatment dose was constructed applying both the conventional DIR and the proposed method using daily CBCT image obtained from HN treatment.Results:Phantom study showed 2.7% maximal discrepancy with respect to the actual displacement. Compared with conventional DIR, subvolume displacement difference in a right parotid had the mean±SD (Min, Max) to be 1.1±0.9(−0.4∼4.8), −0.1±0.9(−2.9∼2.4) and −0.1±0.9(−3.4∼1.9)mm in RL/PA/SI directions respectively. Mean parotid dose and V30 constructed including the dose response induced shrinkage were 6.3% and 12.0% higher than those from the conventional DIR.Conclusion:Heterogeneous dose distribution in normal organ causes non‐uniform sub‐volume shrinkage. Sub‐volume in high dose region has a larger shrinkage than the one in low dose region, therefore causing more sub‐volumes to move into the high dose area during the treatment course. This leads to an unfavorable dose‐volume relationship for the normal organ. Without including this effect in DIR, treatment dose in normal organ could be underestimated affecting treatment evaluation and planning modification.Acknowledgement: Partially Supported by Elekta Research Grant
SU‐F‐J‐89: Assessment of Delivered Dose in Understanding HCC Tumor Progression Following SBRT
Authors: McCulloch M , Cazoulat G , Polan D , Schipper M , Lawrence T , Feng M , Brock K 
Published: July 2016

Purpose:It is well documented that the delivered dose to patients undergoing radiotherapy (RT) is often different from the planned dose due to geometric variability and uncertainties in patient positioning. Recent work suggests that accumulated dose to the GTV is a better predictor of progression compared to the minimum planned dose to the PTV. The purpose of this study is to evaluate if deviations from the planned dose can contributed to tumor progression.Methods:From 2010 to 2014 an in‐house Phase II clinical trial of adaptive stereotactic body RT was completed. Of the 90 patients enrolled, 7 patients had a local recurrence defined on contrast enhanced CT or MR imaging 3–21 months after completion of RT. Retrospective dose accumulation was performed using a biomechanical model‐based deformable image registration algorithm (DIR) to accumulate the dose based on the kV CBCT acquired prior to each fraction for soft tissue alignment of the patient. The DIR algorithm was previously validated for geometric accuracy in the liver (target registration error = 2.0 mm) and dose accumulation in a homogeneous image, similar to a liver CBCT (gamma index = 91%). Following dose accumulation, the minimum dose to 0.5 cc of the GTV was compared between the planned and accumulated dose. Work is ongoing to evaluate the tumor control probability based on the planned and accumulated dose.Results:DIR and dose accumulation was performed on all fractions for 6 patients with local recurrence. The difference in minimum dose to 0.5 cc of the GTV ranged from −0.3–2.3 Gy over 3–5 fractions. One patient had a potentially significant difference in minimum dose of 2.3 Gy.Conclusion:Dose accumulation can reveal tumor underdosage, improving our ability to understand recurrence and tumor progression patterns, and could aid in adaptive re‐planning during therapy to correct for this.This work was supported in part by NIH P01CA059827.
SU‐F‐J‐91: Sparing Lung Function in Treatment Planning Using Dual Energy Tomography
Authors: Lapointe A , Bahig H , Zerouali K , Blais D , De Guise J , Carrier J , Filion E , Roberge D , Bedwani S 
Published: July 2016

Purpose:To propose an alternate treatment plan that minimizes the dose to the functional lung tissues. In clinical situation, the evaluation of the lung functionality is typically derived from perfusion scintigraphy. However, such technique has spatial and temporal resolutions generally inferior to those of a CT scan. Alternatively, it is possible to evaluate pulmonary function by analysing the iodine concentration determined via contrast‐enhanced dual energy CT (DECT) scan.Methods:Five lung cancer patients underwent a scintigraphy and a contrast‐enhanced DECT scan (SOMATOM Definition Flash, Siemens). The iodine concentration was evaluated using the two‐material decomposition method to produce a functional map of the lung. The validation of the approach is realized by comparison between the differential function computed by DECT and scintigraphy. The functional map is then used to redefine the V5 (volume of the organ that received more than 5 Gy during a radiotherapy treatment) to a novel functional parameter, the V5f. The V5f, that uses a volume weighted by its function level, can assist in evaluating optimal beam entry points for a specific treatment plan.Results:The results show that the differential functions obtained by scintigraphy and DECT are in good agreement with a mean difference of 6%. In specific cases, we are able to visually correlate low iodine concentration with abnormal pulmonary lung or cancerous tumors. The comparison between V5f and V5 has shown that some entry points can be better exploited and that new ones are now accessible, 2.34 times more in average, without increasing the V5f ‐‐ thus allowing easier optimization of other planning objectives.Conclusion:In addition to the high‐resolution DECT images, the iodine map provides local information used to detect potential functional heterogeneities in the 3D space. We propose that this information be used to calculate new functional dose parameters such as the V5f.The presenting author, Andreanne Lapointe, received a canadian scholarship from MITACS. Part of the funding is from the compagny Siemens.
SU‐F‐J‐92: Predictive Value of Diffusion Tensor Imaging Parameters for Gamma Knife Radiosurgery in Meningiomas
Authors: Speckter H , Bido J , Hernandez G , Suazo L , Rivera D , Valenzuela S , Stoeter P 
Published: July 2016

Purpose:Subtypes of WHO grade I meningiomas are difficult to distinguish with conventional magnetic resonance imaging. Control rates in meningiomas after Gamma Knife Stereotactic Radiosurgery (GKRS) are high; however, there are about 7.5 % of meningiomas which continue to grow [Santacroce et al, Neurosurgery 70:32–39, 2012]. A superior control rate may be achieved if there would be a possibility to predict the meningioma subtype without intervention and to adjust prescription dose accordingly. Diffusion Tensor Imaging (DTI) parameters are able to differentiate between meningioma subtypes, based on their fibrous tissue concentration [Tropine et al, J Magn Reson Imaging 25(4):703–8, 2007]. We tested the hypothesis that there is a correlation between different DTI parameters and the change of tumor volume after GKRS, expecting that fibrous‐rich tissue has lower radiosensitivity.Methods:DTI parameters were measured by Magnetic Resonance Imaging (3T Achieva Philips) before GKRS in 34 patients with meningiomas. After GKRS treatment with a prescription dose of 11 to 18 (mean: 13.9±1.7) Gy, the change rate of tumor size was followed over more than 12 month, up to 43 months (average: 27.9 months).Results:Only those meningiomas showing the highest Fractional Anisotropy (FA), the lowest Spherical Index (Cs) and the lowest Radial Diffusibility (RD) increased or remained stable in volume, whereas all others decreased. The correlation between DTI parameters (FA: −0.78, Cs: 0.71, RD: 0.66) and volume change rate was significant (p<0.001). Other factors, including original tumor size, prescription dose and patient's age, do not correlate significantly.Conclusion:Meningiomas showing high FA, as well as low Cs and low RD are less susceptible to GKRS. This finding might be due to their higher content of fibrous tissue. In order to improve the control rate of meningiomas showing high FA we propose to increase the prescription dose.
SU‐F‐J‐93: Automated Segmentation of High‐Resolution 3D WholeBrain Spectroscopic MRI for Glioblastoma Treatment Planning
Authors: Schreibmann E , Cordova J , Gurbani S , Holder C , Cooper L , Shu H , Shim H 
Published: July 2016

Purpose:We report on an automated segmentation algorithm for defining radiation therapy target volumes using spectroscopic MR images (sMRI) acquired at nominal voxel resolution of 100 microliters.Methods:Wholebrain sMRI combining 3D echo‐planar spectroscopic imaging, generalized auto‐calibrating partially‐parallel acquisitions, and elliptical k‐space encoding were conducted on 3T MRI scanner with 32‐channel head coil array creating images. Metabolite maps generated include choline (Cho), creatine (Cr), and N‐acetylaspartate (NAA), as well as Cho/NAA, Cho/Cr, and NAA/Cr ratio maps. Automated segmentation was achieved by concomitantly considering sMRI metabolite maps with standard contrast enhancing (CE) imaging in a pipeline that first uses the water signal for skull stripping. Subsequently, an initial blob of tumor region is identified by searching for regions of FLAIR abnormalities that also display reduced NAA activity using a mean ratio correlation and morphological filters. These regions are used as starting point for a geodesic level‐set refinement that adapts the initial blob to the fine details specific to each metabolite.Results:Accuracy of the segmentation model was tested on a cohort of 12 patients that had sMRI datasets acquired pre, mid and post‐treatment, providing a broad range of enhancement patterns. Compared to classical imaging, where heterogeneity in the tumor appearance and shape across posed a greater challenge to the algorithm, sMRI's regions of abnormal activity were easily detected in the sMRI metabolite maps when combining the detail available in the standard imaging with the local enhancement produced by the metabolites. Results can be imported in the treatment planning, leading in general increase in the target volumes (GTV60) when using sMRI+CE MRI compared to the standard CE MRI alone.Conclusion:Integration of automated segmentation of sMRI metabolite maps into planning is feasible and will likely streamline acceptance of this new acquisition modality in clinical practice.
SU‐F‐J‐97: A Joint Registration and Segmentation Approach for Large Bladder Deformations in Adaptive Radiotherapy
Authors: Derksen A , Koenig L , Meine H , Heldmann S 
Published: July 2016

Purpose:To improve results of deformable image registration (DIR) in adaptive radiotherapy for large bladder deformations in CT/CBCT pelvis imaging.Methods:A variational multi‐modal DIR algorithm is incorporated in a joint iterative scheme, alternating between segmentation based bladder matching and registration. Using an initial DIR to propagate the bladder contour to the CBCT, in a segmentation step the contour is improved by discrete image gradient sampling along all surface normals and adapting the delineation to match the location of each maximum (with a search range of +−5/2mm at the superior/inferior bladder side and step size of 0.5mm). An additional graph‐cut based constraint limits the maximum difference between neighboring points. This improved contour is utilized in a subsequent DIR with a surface matching constraint. By calculating an euclidean distance map of the improved contour surface, the new constraint enforces the DIR to map each point of the original contour onto the improved contour. The resulting deformation is then used as a starting guess to compute a deformation update, which can again be used for the next segmentation step. The result is a dense deformation, able to capture much larger bladder deformations. The new method is evaluated on ten CT/CBCT male pelvis datasets, calculating Dice similarity coefficients (DSC) between the final propagated bladder contour and a manually delineated gold standard on the CBCT image.Results:Over all ten cases, an average DSC of 0.93±0.03 is achieved on the bladder. Compared with the initial DIR (0.88±0.05), the DSC is equal (2 cases) or improved (8 cases). Additionally, DSC accuracy of femoral bones (0.94±0.02) was not affected.Conclusion:The new approach shows that using the presented alternating segmentation/registration approach, the results of bladder DIR in the pelvis region can be greatly improved, especially for cases with large variations in bladder volume.Fraunhofer MEVIS received funding from a research grant by Varian Medical Systems.
SU‐F‐J‐99: Dose Accumulation and Evaluation in Lung SBRT Among All Phases of Respiration
Authors: Azcona JD , Burguete J , Barbes B , Aristu J , Moreno M , Zubiria A , Arce P , Lagares JI 
Published: July 2016

Purpose:To calculate the total planning dose on lung tumors (GTV) by accumulating the dose received in all respiration phases.Methods:A patient 4D planning CT (phase‐binned, from a Siemens Somatom CT) was used to locate the GTV of a lung tumor in all respiratory phases with Pinnacle (v9.10). GTV contours defined in all phases were projected to the reference phase, where the ITV was defined. Centroids were calculated for all the GTV projections. No deformation or rotation was taken into account. The only GTV contour as defined in the reference phase was voxelized to track each voxel individually. We accumulated the absorbed dose in different phases on each voxel. A 3DCRT and a VMAT plan were designed on the reference phase fulfilling the ITV dosimetric requirements, using the 10MV FFF photon model from an Elekta Versa linac. ITV‐to‐PTV margins were set to 5mm. In‐house developed MATLAB code was used for tumor voxeling and dose accumulation, assuming that the dose distribution planned in the reference phase behaved as a “dose‐cloud” during patient breathing.Results:We tested the method on a patient 4DCT set of images exhibiting limited tumor motion (<5mm). For the 3DCRT plan, D95 was calculated for the GTV with motion and for the ITV, showing an agreement of 0.04%. For the VMAT plan, we calculated the D95 for every phase as if the GTV in that phase had received the whole treatment. Differences in D95 for all phases are within 1%, and estimate the potential interplay effect during delivery.Conclusion:A method for dose accumulation and assessment was developed that can compare GTV motion with ITV dosage, and estimate the potential interplay effect for VMAT plans. Work in progress includes the incorporation of deformable image registration and 4D CBCT dose calculation for dose reconstruction and assessment during treatment.
SU‐F‐J‐104: Weekly MRI for Dose Assessment of Organs at Risk During Treatment of HN Cancer of the Oropharynx
Authors: Ludwig K , Li J , Venigalla P , Zhang J , Tang X , Tyagi N , Fontenla S , Lee N , Saleh Z 
Published: July 2016

Purpose:Investigate the feasibility of using weekly MRI to assess dose to organs at risk utilizing deformable image registration.Methods:Sixteen H&N patients with oropharyngeal cancer were imaged on a 3T MR scanner using T2W and mDIXON sequence. Patients were imaged on a weekly basis in treatment position. Parotids (LP & RP), submandibular glands (LS, RS), and oral cavity (OC) were delineated on the weekly MR and reviewed by a board certified radiation oncologist. The original planning CT (pCT), RT‐Dose, and RT‐Structures were deformed and registered to each weekly MRIs. The deformed CTs and RT‐Structures were imported to the treatment planning system (TPS) and rigidly registered to the pCT. Forward dose calculation of the original RT‐Plan was used to estimate the delivered dose on the deformed CT. The dose volume histograms (DVH) statistics were performed to compare planned dose, deformed dose, and forward calculated dose. In addition, Dice similarity metric (DSM) was used to compare deformed and reference structures.Results:The average (min,max) DSM between deformed and reference structures was 0.71 (0.69,0.93); 0.70 (0.64,0.89); 0.65 (0.48,0.86); 0.63 (0.37,0.89); and 0.63 (0.58,0.87); for LP, RP, LS, RS, and OC respectively. The respective average relative structures volumes changed at a weekly rate of −4.99%; −4.40%; +3.45%; +1.46%; −1.39%, respectively. The percentage difference %(min,max) between estimated delivered dose and planned dose was +3.94 (−51.3,+30.5); +6.33 (−58.6,+82.7); +2.46 (−38.9,+37.6,); +2.38(−49.0,+28.9); +3.55(−17.0,+43.1).Conclusion:The recalculated dose based on weekly MRI deviated from planned dose for all OARs. Meanwhile, the deformed dose did not reflect the subtle changes in OARs as compared to the recalculated dose. This study demonstrates the feasibility of using weekly MRI to monitor volumetric changes which has important implications on actual delivered dose.