bluuebunny/crossref_metadata_2025 huggingface dataset:
SU‐F‐J‐29: Dosimetric Effect of Image Registration ROI Size and Focus in Automated CBCT Registration for Spine SBRT
Authors: Magnelli A , Smith A , Chao S , Suh J , Xia P
Published: July 2016

Purpose:

Spinal stereotactic body radiotherapy (SBRT) involves highly conformal dose distributions and steep dose gradients due to the proximity of the spinal cord to the treatment volume. To achieve the planning goals while limiting the spinal cord dose, patients are setup using kV cone‐beam CT (kV‐CBCT) with 6 degree corrections. The kV‐CBCT registration with the reference CT is dependent on a user selected region of interest (ROI). The objective of this work is to determine the dosimetric impact of ROI selection.

Methods:

Twenty patients were selected for this study. For each patient, the kV‐CBCT was registered to the reference CT using three ROIs including: 1) the external body, 2) a large anatomic region, and 3) a small region focused in the target volume. Following each registration, the aligned CBCTs and contours were input to the treatment planning system for dose evaluation. The minimum dose, dose to 99% and 90% of the tumor volume (D99%, D90%), dose to 0.03cc and the dose to 10% of the spinal cord subvolume (V10Gy) were compared to the planned values.

Results:

The average deviations in the tumor minimum dose were 2.68%±1.7%, 4.6%±4.0%, 14.82%±9.9% for small, large and the external ROIs, respectively. The average deviations in tumor D99% were 1.15%±0.7%, 3.18%±1.7%, 10.0%±6.6%, respectively. The average deviations in tumor D90% were 1.00%±0.96%, 1.14%±1.05%, 3.19%±4.77% respectively. The average deviations in the maximum dose to the spinal cord were 2.80%±2.56%, 7.58%±8.28%, 13.35%±13.14%, respectively. The average deviation in V10Gy to the spinal cord were 1.69%±0.88%, 1.98%±2.79%, 2.71%±5.63%.

Conclusion:

When using automated registration algorithms for CBCT‐Reference alignment, a small target‐focused ROI results in the least dosimetric deviation from the plan. It is recommended to focus narrowly on the target volume to keep the spinal cord dose below tolerance.
SU‐F‐J‐32: Do We Need KV Imaging During CBCT Based Patient Set‐Up for Lung Radiation Therapy?
Authors: Gopal A , Zhou J , Prado K , D'souza W , Yi B
Published: July 2016

Purpose:

To evaluate the role of 2D kilovoltage (kV) imaging to complement cone beam CT (CBCT) imaging in a shift threshold based image guided radiation therapy (IGRT) strategy for conventional lung radiotherapy.

Methods:

A retrospective study was conducted by analyzing IGRT couch shift trends for 15 patients that received lung radiation therapy to evaluate the benefit of performing orthogonal kV imaging prior to CBCT imaging. Herein, a shift threshold based IGRT protocol was applied, which would mandate additional CBCT verification if the applied patient shifts exceeded 3 mm to avoid intraobserver variability in CBCT registration and to confirm table shifts. For each patient, two IGRT strategies: kV + CBCT and CBCT alone, were compared and the recorded patient shifts were categorized into whether additional CBCT acquisition would have been mandated or not. The effectiveness of either strategy was gauged by the likelihood of needing additional CBCT imaging for accurate patient set‐up.

Results:

The use of CBCT alone was 6 times more likely to require an additional CBCT than KV+CBCT, for a 3 mm shift threshold (88% vs 14%). The likelihood of additional CBCT verification generally increased with lower shift thresholds, and was significantly lower when kV+CBCT was used (7% with 5 mm shift threshold, 36% with 2 mm threshold), than with CBCT alone (61% with 5 mm shift threshold, 97% with 2 mm threshold). With CBCT alone, treatment time increased by 2.2 min and dose increased by 1.9 cGy per fraction on average due to additional CBCT with a 3mm shift threshold.

Conclusion:

The benefit of kV imaging to screen for gross misalignments led to more accurate CBCT based patient localization compared with using CBCT alone. The subsequently reduced need for additional CBCT verification will minimize treatment time and result in less overall patient imaging dose.
SU‐F‐J‐33: On‐Line Daily KV Image Protocol of Lung Patient Setup with Minimal CBCT
Authors: Zhou J , Prado K , Gopal A , D'souza W , Lasio G , Yi B
Published: July 2016

Purpose:

This study's intent is to test if the first 3 fractions of an IGRT protocol consisting of a kV orthogonal pair and subsequent CBCT are representative of all remaining treatment fractions.

Methods:

At our institution the standard IGRT protocol includes CBCT after kV imaging for the first 3 fractions followed by daily kV and weekly CBCT. We randomly selected 20 lung patients who have at least 8 CBCTs in the entire treatment course (total 187 sets of orthogonal kV images plus CBCT). Our evaluation criterion is the fraction of kV‐vs‐CBCT position mismatches in the first 3 fractions. An additional CBCT is acquired if only 1 fraction mismatches among the first three. We define as 'protocol eligible’ (eGroup) the group of patients for whom the setups with kV images match within the pre‐selected thresholds of 3, 4 and 5 mm those of the consecutive CBCTs for at least 60% of the fractions. A protocol ineligible (iGroup) is defined as the group of patients other than eGroup.

Results:

The fractions of patients in the eGroup were 70%, 85% and 95%, when the setup thresholds selected were 3, 4 and 5mm respectively. The sensitivities of determining iGroup from the first 3 fractions of kV and CBCT were 0.83, 1.0, and 1.0, and the specificities were 0.93, 0.94 and 0.89 with thresholds 3, 4 and 5 mm respectively.

Conclusion:

The method suggested here well categorized cases for our kV‐based on‐line IGRT protocol. More patients are eGroup eligible if larger setup threshold is used. CBCT frequency in the on‐line daily kV plus weekly CBCT protocol may need to increase for protocol ineligible patients. Also, our IGRT CBCT frequency could be decreased when position differences between kVs and CBCTs are less than 1.5mm, the average positional standard deviation of out kV‐CBCT sets.
SU‐F‐J‐37: Commissioning a Six Degree of Freedom Couch
Authors: Roberts D , Lam K , Bredfeldt J , Covington E
Published: July 2016

Purpose:

The proper operation of a six degree of freedom couch (6DOFC) to position a patient for treatment requires that a number systems on the treatment unit work together correctly. Commissioning a 6DOFC requires not only the commissioning of each separate system but also commissioning the interactions between the systems.

Methods:

To commission a 6DOFC, we tested the resolvers that readout the linear and angular positions; the orthogonality of the axes of the laser positioning system, the imaging system, the gantry and the couch as well as their relationship to each other. An automated Winston‐Lutz test was used verify the coincidence of the origins of the laser system, imaging system and treatment unit. The IsoCal phantom was used to verify the consistency of axes orientations between systems. The operation of the couch and imaging system was verified under simulated load conditions and an end to end test was performed to verify correct operation of the system.

Results:

The tests on the couch resolvers, orthogonality and coincidence of the axes of each system were successfully completed and showed excellent agreement. The automated Winston‐Lutz test showed that the maximum displacement of the center of the radiation field with respect to the isocenter was <0.6 mm (radius) at isocenter. The analysis of the IsoCal phantom showed that the maximum variation of the radiation field with respect to known locations in the phantom was ∼0.9 mm for all the BBs in the phantom. Load tests showed maximum errors of 1 mm.

Conclusion:

We tested all system associated with the 6DOFC and found the uncertainty due to imaging was <.9mm and the uncertainty due to loading ∼1 mm, resulting in a total error of ∼1.4 mm.
SU‐F‐J‐39: Dose Reduction Strategy Using Attenuation‐Based Tube Current Modulation Method in CBCT for IGRT
Authors: Son K , Lee H , Kim C , Kim J , Cho S
Published: July 2016

Purpose:

To reduce radiation dose to the patients, tube current modulation (TCM) method has been actively used in diagnostic CT systems. However, TCM method has not yet been applied to a kV‐CBCT system on a LINAC machine. The purpose of this study is to investigate whether the use of TCM method is desirable in kV‐CBCT system for IGRT. We have developed an attenuation‐based tube current modulation (a‐TCM) method using the prior knowledge of treatment CT image of a patient.

Methods:

Patients go through a diagnostic CT scan for RT planning; therefore, using this prior information of CT images, one can estimate the total attenuation of an x‐ray through the patient body in a CBCT setting for radiation therapy. We performed a numerical study incorporating major factors into account such as polychromatic x‐ray, scatter, noise, and bow‐tie filter to demonstrate that a‐TCM method can produce equivalent quality of images at reduced imaging radiation doses. Using the CT projector program, 680 projection images of the pediatric XCAT phantom were obtained both in conventional scanning condition, i.e., without modulating the tube current, and in the proposed a‐TCM scanning condition. FDK reconstruction algorithm was used for image reconstruction, and the organ dose due to imaging radiation has been calculated in both cases and compared using GATE/Geant4 simulation toolkit.

Results:

Reconstructed CT images in the a‐TCM method showed similar SSIM values and noise properties to the reference images acquired by the conventional CBCT. In addition, reduction of organ doses ranged from 12% to 27%.

Conclusion:

We have successfully demonstrated the feasibility and dosimetric merit of the a‐TCM method for kV‐CBCT, and envision that it can be a useful option of CBCT scanning that provides patient dose reduction without degrading image quality.
SU‐F‐J‐40: Evaluation of Sensitivity of the Automatic Matching Between Cone‐Beam CT Image and Simulation CT Image in TrueBeam 2.0 Imaging System 6DoF Considering Different Uncertainty Sources
Authors: Bonaque J , Bautista‐Ballesteros J , Ibanez‐Rosello B , Lliso F , Carmona V , Gimeno J , Perez‐Calatayud J
Published: July 2016

Purpose:

To estimate the sensitivity of TrueBeam 2.0 Imaging System 6DoF automatic matching tool through the acquisition of cone‐beam CT images in different phantoms applying submillimeter translations and rotations of tenths of a degree and registered with image simulation CT.

Methods:

To evaluate overall system‐wide image, we consider two uncertainties source; First, the uncertainty of the manual phantom displacement (ε_m). This uncertainty is calculated by a digital caliper (0.01 mm) for vertical (Vrt), lateral (Lat) and longitudinal (Lng). A digital inclinometer (0.01°) for the pitch and roll and the own phantom scale to evaluate the coordinate rotation (Rtn). The second uncertainty is the displacement detected by the algorithm system of matching (σ_d) that we obtain from the standard deviations of the different measurements. We use three different phantoms. The BrainLab Radiosurgery system for supporting masks with an anthropomorphic dummy adapted to allow displacements of 0.1 mm in Vrt, Lat and Lng dimensions and rotations of 0.1° in Pitch dimension. For the analysis of the Rtn and Roll dimensions we use two homemade phantoms (RinoRot and RinoRoll, La Fe Hospital, Valencia, Spain) that allow rotations of 0.3°.

Results:

In the case of manual displacement of 0.10 ± 0.03 mm in the translations, the system detect 0.10 ± 0.07 mm, 0.12 ± 0.07 mm and 0.13 ± 0.07 mm (mean ± SD) in Lat, Vrt and Lng respectively. In the case of rotational dimension, manual displacement of 0.3 ± 0.1° was detected with 0.19 ± 0.06°, 0.29 ± 0.03° and 0.27 ± 0.06° in Pitch, Roll and Rtn.

Conclusion:

We conclude that the sensitivity of the automatic matching system is within 0.10 mm in translations and 0.3° in rotations. These values are under the own sensitivity of the software.
SU‐F‐J‐43: Positional Variation of Implanted Fiducial Markers Over the Course of Image Guided Radiotherapy for Pancreatic Cancer
Authors: Shen S , Jacob R , Popple R , Wu X , Cardan R , Brezovich I
Published: July 2016

Purpose:

Pancreas is a soft‐tissue organ, implanted fiducials can change positions due to migration or tissue deformation. This study quantified positional variation of fiducials in IGRT for pancreatic cancer.

Methods:

20 patients had at least 3 gold fiducials implanted in pancreas under EUS guidance. Patients had 4D‐CT simulation for gated treatment. Daily gated OBI kV images (Turebeam) were used for positional alignment with fiducials for total of 25 or 28 fractions. Relative distances among 3 fiducials (d1 – 2, d1 – 3, d2 – 3) were measured from 4D‐CT end‐of‐expiration phase bin; and from gated kV images in first, mid, and last fraction (n=180).

Results:

The median duration between implant and simulation was 11 (range 0–41) days. The median duration between simulation and first fraction was 17 (range 8–24) days. The median relative distance was 12 (range 4–78) mm for d1 – 2, 24 (range 6–80) mm for d1 – 3, and 19 (range 5–63) mm for d2 – 3. The median deviation was 1 mm for d1 – 2, d1 – 3, d2 – 3 between simulation and first fraction, first and mid fraction, mid and last fraction (n=180). Two patients (10%) had deviation >= 5 mm (5, 11 mm) between simulation and first fraction. One patient (5%) had deviation >= 5 mm (11 mm) between first and mid fraction. No patient (0%) had deviation >= 5 mm between mid and last fraction. In all 3 cases with deviation >=5 mm, only one fiducial was significantly deviated. No clear evidence that deviation size was associated with time interval between implant and first fraction.

Conclusion:

Implanted gold fiducials were quite stable over time in their relative positions in pancreas. Our data suggested at least 3 fiducials are needed. In cases that one fiducial was significantly deviated in daily kV images, this fiducial should be excluded in image guidance.
SU‐F‐J‐60: Impact of DIR Method On Treatment Dose Wrapping
Authors: Qin A , Liang J , Zhu J , Ding X , Castillo E , Guerrero T , Yan D
Published: July 2016

Purpose:

To investigate clinical relevant discrepancy between doses wrapped by pure image and biomechanical model based deformable registration (DIR).

Methods:

12 patients, each with a CT pair, were included (5 H&N, 5 Prostate and 2 Lung). A research DIR tool (ADMRIE) was utilized for image based DIR (IMG‐DIR). To assure organ matching, contour constrain was applied for prostate patients. Tetrahedron meshes were generated for organs (parotid, bladder, rectum and lung). Deformable vector fields (DVF) from IMG‐DIR were interpolated to the surface node of meshes as boundary condition. Biomechanical models using finite element modeling (FEM) were generated by assigning organ specific material properties. The models were then input into a FEM tool (ABAQUS) to calculate internal deformation (FEM‐DIR). The output volume node displacements were then interpolated to image grids to get refined DVF. The IMRT treatment doses were wrapped by both DVFs to pre‐treatment CTs. DVF vector distance (DVF‐VD) was calculated on each organ. Dose parameters were calculated for wrapped doses and normalized to pretreatment plan. Gamma passing rate (GPR) was calculated with IMG‐DIR dose as reference. Correlation was evaluated between parotid shrinkage and DVF‐VD /dose‐discrepancy.

Results:

H&N:parotid volume with DVF‐VD (>1.5mm) was 6.5±4.7%. The normalized mean dose difference (NMDD) of IMG‐DIR and FEM‐DIR was −0.8±1.5%, with range (−4.7% to 1.5%). 2mm/2% GPR was 99.0±1.4%. Moderate correlation was found between parotid shrinkage and DVF‐VD (R=0.61)/NMDD (R=0.68). Prostate:bladder had a NMDD of −9.9±9.7%, with FEM‐DIR wrapped dose systematically higher. Only minor deviation was observed for rectum NMDD (0.5±1.1%). 3mm/3% GPR of bladder and rectum were 81.9±12.0% and 93.1±4.3%, respectively. One of lung patients had 3.9%NMDD and 3mm/3%GPR of 95.2% inside lung.

Conclusion:

Impact of DIR methods on treatment dose wrapping is patient and organ specific. Generally, bigger organ with larger volume variation leads to greater dose wrapping uncertainty.Acknowledgement:Elekta research grant support.

This work was supported by research funding from Elekta
SU‐F‐J‐67: Dosimetric Changes During Radiotherapy in Lung Cancer Patients with Atelectasis
Authors: Guy C , Weiss E , Jan N , Reshko L , Christensen G , Hugo G
Published: July 2016

Purpose:

Large geometric changes which occur during thoracic radiotherapy alter normal anatomy and target position and may induce clinically important dose changes. This study investigates variation of organ‐at‐risk (OAR) dose caused by atelectasis resolution during radiotherapy.

Methods:

3D IMRT treatment plans were obtained for 14 non‐small‐cell lung cancer patients. Dose of the clinical plan was recalculated on a baseline scan in which lung was collapsed and on a midtreatment scan in which lung re‐aeration had occurred. The changes in OAR doses were compared between the two time points. RTOG‐0617 and inhouse dose‐volume constraints were chosen for investigation and included spinal cord, esophagus, heart, and healthy lung.

Results:

17 dose metrics were evaluated. The mean (SD) of change in mean lung dose, from baseline to mid‐treatment (average taken across all patients), was 0.2 Gy (2.2 Gy) and ranged from −3.2 Gy to 6.0 Gy. 50% of patients experienced relative changes in mean lung dose of greater than 5% of baseline value. The mean (SD) of changes in heart V40, V45, and V60 were 3.2% (3.4%), 3.0% (2.9%), and 1.4% (2.1%), respectively, and were significant for the study cohort (Wilcoxon signed‐rank test, p=0.0107 for V40, p=0.0052 for V45, and p= 0.0353 for V60. Ranges in changes of Heart V40, V45, and V60 were −1.9% to 8.6%, −1.7% to 7.5%, and −2.1% to 4.5%, respectively. The mean (SD) of changes in Esophagus PRV Dmean and V60 were 0.3 Gy (3.3 Gy) and 0.8% (7.7%), respectively, and ranged from −4.8 Gy to 6.8 Gy for Dmean and −15.2% to 14.6% for V60.

Conclusion:

Patients with atelectasis present at the start of radiotherapy experience significant increases in heart dose. Substantial increases in mean lung dose also occur in a subset of patients.

This work supported by the National Cancer Institute of National Institutes of Health under Award Number R01CA166119. Disclosures: Phillips Medical systems (Hugo, Weiss), National Institutes of Health (Hugo, Weiss, Christensen), and Roger Koch (Christensen) support, UpToDate (Weiss) royalties, and Varian Medical Systems (Hugo, Weiss) license. No potential conflicts of interest.
SU‐F‐J‐72: A Clinical Usable Integrated Contouring Quality Evaluation Software for Radiotherapy
Authors: Jiang S , Dolly S , Cai B , Mutic S , Li H
Published: July 2016

Purpose:

To introduce the Auto Contour Evaluation (ACE) software, which is the clinical usable, user friendly, efficient and all‐in‐one toolbox for automatically identify common contouring errors in radiotherapy treatment planning using supervised machine learning techniques.

Methods:

ACE is developed with C# using Microsoft .Net framework and Windows Presentation Foundation (WPF) for elegant GUI design and smooth GUI transition animations through the integration of graphics engines and high dots per inch (DPI) settings on modern high resolution monitors. The industrial standard software design pattern, Model‐View‐ViewModel (MVVM) pattern, is chosen to be the major architecture of ACE for neat coding structure, deep modularization, easy maintainability and seamless communication with other clinical software. ACE consists of 1) a patient data importing module integrated with clinical patient database server, 2) a 2D DICOM image and RT structure simultaneously displaying module, 3) a 3D RT structure visualization module using Visualization Toolkit or VTK library and 4) a contour evaluation module using supervised pattern recognition algorithms to detect contouring errors and display detection results. ACE relies on supervised learning algorithms to handle all image processing and data processing jobs. Implementations of related algorithms are powered by Accord.Net scientific computing library for better efficiency and effectiveness.

Results:

ACE can take patient's CT images and RT structures from commercial treatment planning software via direct user input or from patients’ database. All functionalities including 2D and 3D image visualization and RT contours error detection have been demonstrated with real clinical patient cases.

Conclusion:

ACE implements supervised learning algorithms and combines image processing and graphical visualization modules for RT contours verification. ACE has great potential for automated radiotherapy contouring quality verification. Structured with MVVM pattern, it is highly maintainable and extensible, and support smooth connections with other clinical software tools.
SU‐F‐J‐74: High Z Geometric Integrity and Beam Hardening Artifact Assessment Using a Retrospective Metal Artifact Reduction (MAR) Reconstruction Algorithm
Authors: Woods K , DiCostanzo D , Gupta N
Published: July 2016

Purpose:

To test the efficacy of a retrospective metal artifact reduction (MAR) reconstruction algorithm for a commercial computed tomography (CT) scanner for radiation therapy purposes.

Methods:

High Z geometric integrity and artifact reduction analysis was performed with three phantoms using General Electric's (GE) Discovery CT. The three phantoms included: a Computerized Imaging Reference Systems (CIRS) electron density phantom (Model 062) with a 6.5 mm diameter titanium rod insert, a custom spine phantom using Synthes Spine hardware submerged in water, and a dental phantom with various high Z fillings submerged in water. Each phantom was reconstructed using MAR and compared against the original scan. Furthermore, each scenario was tested using standard and extended Hounsfield Unit (HU) ranges. High Z geometric integrity was performed using the CIRS phantom, while the artifact reduction was performed using all three phantoms.

Results:

Geometric integrity of the 6.5 mm diameter rod was slightly overestimated for non‐MAR scans for both standard and extended HU. With MAR reconstruction, the rod was underestimated for both standard and extended HU. For artifact reduction, the mean and standard deviation was compared in a volume of interest (VOI) in the surrounding material (water and water equivalent material, ∼0HU). Overall, the mean value of the VOI was closer to 0 HU for the MAR reconstruction compared to the non‐MAR scan for most phantoms. Additionally, the standard deviations for all phantoms were greatly reduced using MAR reconstruction.

Conclusion:

GE's MAR reconstruction algorithm improves image quality with the presence of high Z material with minimal degradation of its geometric integrity. High Z delineation can be carried out with proper contouring techniques. The effects of beam hardening artifacts are greatly reduced with MAR reconstruction. Tissue corrections due to these artifacts can be eliminated for simple high Z geometries and greatly reduced for more complex geometries.
SU‐F‐J‐77: Variations in the Displacement Vector Fields Calculated by Different Deformable Image Registration Algorithms Used in Helical, Axial and Cone‐Beam CT Images of a Mobile
Authors: Ali I , Jaskowiak J , Alsbou N , Ahmad S
Published: July 2016

Purpose:

To investigate quantitatively the displacement‐vector‐fields (DVF) obtained from different deformable image registration algorithms (DIR) in helical (HCT), axial (ACT) and cone‐beam CT (CBCT) to register CT images of a mobile phantom and its correlation with motion amplitudes and frequencies.

Methods:

HCT, ACT and CBCT are used to image a mobile phantom which includes three targets with different sizes that are manufactured from water‐equivalent material and embedded in low density foam. The phantom is moved with controlled motion patterns where a range of motion amplitudes (0–40mm) and frequencies (0.125–0.5Hz) are used. The CT images obtained from scanning of the mobile phantom are registered with the stationary CT‐images using four deformable image registration algorithms including demons, fast‐demons, Horn‐Schunk and Locas‐Kanade from DIRART software.

Results:

The DVF calculated by the different algorithms correlate well with the motion amplitudes that are applied on the mobile phantom where maximal DVF increase linearly with the motion amplitudes of the mobile phantom in CBCT. Similarly in HCT, DVF increase linearly with motion amplitude, however, its correlation is weaker than CBCT. In ACT, the DVF's do not correlate well with the motion amplitudes where motion induces strong image artifacts and DIR algorithms are not able to deform the ACT image of the mobile targets to the stationary targets. Three DIR‐algorithms produce comparable values and patterns of the DVF for certain CT imaging modality. However, DVF from fast‐demons deviated strongly from other algorithms at large motion amplitudes.

Conclusion:

In CBCT and HCT, the DVF correlate well with the motion amplitude of the mobile phantom. However, in ACT, DVF do not correlate with motion amplitudes. Correlations of DVF with motion amplitude as in CBCT and HCT imaging techniques can provide information about unknown motion parameters of the mobile organs in real patients as demonstrated in this phantom visibility study.
SU‐F‐J‐79: Extension of Fixed‐Point Iteration Algorithm for Inverse Deformation
Authors: R Anders M , Chen M , Jiang S , Lu W
Published: July 2016

Purpose:

(I) To present a modification of the fixed point iteration algorithm to assure the convergence for a wide range of cases such as rotation and scaling deformations and (II) to provide implementation details with results from simulations and clinical images and emphasize more on practical considerations, such as how to choose good initial values to improve the speed of convergence. Inverse deformations are often applied to images, contours, and dose.

Methods:

The 2D or 3D inverse deformation field is iteratively found by taking a partial step size parameter (< 1) in a given direction which depends on the forward deformation field as opposed to a full step size parameter (= 1) as in the original fixed‐point inverse deformation paper. The step size parameter controls the size of the change in the inverse deformation field during each iteration. The step size parameter is also dynamically changed to achieve convergence faster.

Results:

The new method was implemented in Matlab and tested for both 2D simulated cases and 3D clinical cases. We started the main iteration loop with step size parameter = 1 and then dynamically changed it to achieve convergence of maximum voxel error of 0.01. The same method was implemented for deformation fields from deformable registration of three patients to another set of patient data. Convergence of the inverse deformation fields was also achieved for the patient cases.

Conclusion:

If the step size parameter is small enough, then the improved iterative algorithm achieves convergence for a wider array of cases such as rotations and scaling of the image. The method is demonstrated to be successful for 2D simulated data and 3D patient data sets and allows for the finding of inverse deformation fields for a wider range of cases.

Supported by Cancer Prevention & Research Institute of Texas (CPRIT) ‐ ID RP150485
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.