bluuebunny/crossref_metadata_2025 huggingface dataset:
SU‐E‐J‐167: Improvement of Time‐Ordered Four Dimensional Cone‐Beam CT; Image Mosaicing with Real and Virtual Projections
Authors: Nakano M , Kida S , Masutani Y , Shiraki T , Yamamoto K , Shiraishi K , Nakagawa K , Haga A
Published: July 2014

Purpose:

In the previous study, we developed time‐ordered fourdimensional (4D) cone‐beam CT (CBCT) technique to visualize nonperiodic organ motion, such as peristaltic motion of gastrointestinal organs and adjacent area, using half‐scan reconstruction method. One important obstacle was that truncation of projection was caused by asymmetric location of flat‐panel detector (FPD) in order to cover whole abdomen or pelvis in one rotation. In this study, we propose image mosaicing to extend projection data to make possible to reconstruct full field‐of‐view (FOV) image using half‐scan reconstruction.

Methods:

The projections of prostate cancer patients were acquired using the X‐ray Volume Imaging system (XVI, version 4.5) on Synergy linear accelerator system (Elekta, UK). The XVI system has three options of FOV, S, M and L, and M FOV was chosen for pelvic CBCT acquisition, with a FPD panel 11.5 cm offset. The method to produce extended projections consists of three main steps: First, normal three‐dimensional (3D) reconstruction which contains whole pelvis was implemented using real projections. Second, virtual projections were produced by reprojection process of the reconstructed 3D image. Third, real and virtual projections in each angle were combined into one extended mosaic projection. Then, 4D CBCT images were reconstructed using our inhouse reconstruction software based on Feldkamp, Davis and Kress algorithm. The angular range of each reconstruction phase in the 4D reconstruction was 180 degrees, and the range moved as time progressed.

Results:

Projection data were successfully extended without discontinuous boundary between real and virtual projections. Using mosaic projections, 4D CBCT image sets were reconstructed without artifacts caused by the truncation, and thus, whole pelvis was clearly visible.

Conclusion:

The present method provides extended projections which contain whole pelvis. The presented reconstruction method also enables time‐ordered 4D CBCT reconstruction of organs with non‐periodic motion with full FOV without projection‐truncation artifacts.

This work was partly supported by the JSPS Core‐to‐Core Program(No. 23003). This work was partly supported by JSPS KAKENHI 24234567.
SU‐E‐J‐169: Process for QA of Normal Tissue Delineation and Reported Doses in Clinical Trials
Authors: Williamson R , Yang J , Timmerman R , Court L
Published: July 2014

Purpose:

To create and evaluate a process of using auto‐segmentation for quality assurance of doses reported to normal structures in clinical trials.

Methods:

Multiple atlases for normal tissue segmentation were created for the esophagus, trachea/large bronchus, and brachial plexus. These atlases were used to independently delineate 21 patients who were enrolled in a phase III study of accelerated hypofractionated IGRT for patients with stage II‐III NSCLC. The results of the multi‐atlas segmentation were visually evaluated for acceptability. The dose volume limits and the maximum point doses specified by the protocol were compared for the originally delineated and auto‐segmented contours. It was noted whether these differences affected whether plans met or failed the protocol constraints.

Results:

On visual inspection, the auto‐segmented contour was acceptable with the exception of 8 cases (38%) of the esophagus. In these cases, the anatomy of the esophagus was notably different from that of atlases so that the autosegmentation failed. On the other hand, the process using auto‐segmentation identified two cases where not all contours of the structure had been delineated in the original plan (one trachea/large bronchus case and one brachial plexus case). The average difference in maximum dose to the esophagus, trachea, and brachial plexus were 0.2±4.4Gy (range: – 13.6:4.7Gy), 0.2±1.1Gy (−3.9:0.8Gy), and 3.6±10.7Gy (−1.2:34.1Gy), respectively. In one esophagus case and one trachea case, the plan became unacceptable when calculated using the auto‐segmented contour, but in both cases the dosimetric difference was very small.

Conclusion:

Two cases (10%) of contouring with insufficient coverage (trachea/large bronchus and brachial plexus) in the original plan were identified using the proposed process. However, patient‐to‐patient variations in the position of the esophagus meant that our current auto‐segmentation is inadequate to evaluate this organ, and more work is needed to optimize the process.

Work funded by Cancer Prevention Research Institute of Texas (CPRIT)
SU‐E‐J‐170: Beyond Single‐Cycle 4DCT: Maximum a Posteriori (MAP) Reconstruction‐Based Binning‐Free Multicycle 4DCT for Lung Radiotherapy
Authors: Cheung Y , Hinkle J , Joshi S , Sawant A
Published: July 2014

Purpose:

Thoracic motion changes from cycle‐to‐cycle and day‐to‐day. Conventional 4DCT does not capture these cycle to cycle variations. We present initial results of a novel 4DCT reconstruction technique based on maximum a posteriori (MAP) reconstruction. The technique uses the same acquisition process (and therefore dose) as a conventional 4DCT in order to create a high spatiotemporal resolution cine CT that captures several breathing cycles.

Methods:

Raw 4DCT data were acquired from a lung cancer patient. The continuous 4DCT was reconstructed using MAP algorithm which uses the raw, time‐stamped CT data to reconstruct images while simultaneously estimating deformation in the subject's anatomy. This framework incorporates physical effects such as hysteresis and is robust to detector noise and irregular breathing patterns. The 4D image is described in terms of a 3D reference image defined at one end of the hysteresis loop, and two deformation vector fields (DVFs) corresponding to inhale motion and exhale motion respectively. The MAP method uses all of the CT projection data and maximizes the log posterior in order to iteratively estimate a timevariant deformation vector field that describes the entire moving and deforming volume.

Results:

The MAP 4DCT yielded CT‐quality images for multiple cycles corresponding to the entire duration of CT acquisition, unlike the conventional 4DCT, which only yielded a single cycle. Variations such as amplitude and frequency changes and baseline shifts were clearly captured by the MAP 4DC

Conclusion:

We have developed a novel, binning‐free, parameterized 4DCT reconstruction technique that can capture cycle‐to‐cycle variations of respiratory motion. This technique provides an invaluable tool for respiratory motion management research. This work was supported by funding from the National Institutes of Health and VisionRT Ltd.

Amit Sawant receives research funding from Varian Medical Systems, Vision RT and Elekta
SU‐E‐J‐172: A Quantitative Assessment of Lung Tumor Motion Using 4DCT Imaging Under Conditions of Controlled Breathing in the Management of Non‐Small Cell Lung Cancer (NSCLC) Using Stereotactic Body Radiation Therapy (SBRT)
Authors: Mohatt D , Gomez J , Singh A , Malhotra H
Published: July 2014

Purpose:

To study breathing related tumor motion amplitudes by lung lobe location under controlled breathing conditions used in Stereotactic Body Radiation Therapy (SBRT) for NSCLC.

Methods:

Sixty‐five NSCLC SBRT patients since 2009 were investigated. Patients were categorized based on tumor anatomic location (RUL‐17, RML‐7, RLL‐18, LUL‐14, LLL‐9). A 16‐slice CT scanner [GE RT16 Pro] along with Varian Realtime Position Management (RPM) software was used to acquire the 4DCT data set using 1.25 mm slice width. Images were binned in 10 phases, T00 being at maximum inspiration ' T50 at maximum expiration phase. Tumor volume was segmented in T50 using the CT‐lung window and its displacement were measured from phase to phase in all three axes; superiorinferior, anterior‐posterior ' medial‐lateral at the centroid level of the tumor.

Results:

The median tumor movement in each lobe was as follows: RUL= 3.8±2.0 mm (mean ITV: 9.5 cm3), RML= 4.7±2.8 mm (mean ITV: 9.2 cm3), RLL=6.6±2.6 mm (mean ITV: 12.3 cm3), LUL=3.8±2.4 mm (mean ITV: 18.5 cm3), ' LLL=4.7±2.5 mm (mean ITV: 11.9 cm3). The median respiratory cycle for all patients was found to be 3.81 ± 1.08 seconds [minimum 2.50 seconds, maximum 7.07 seconds]. The tumor mobility incorporating breathing cycle was RUL = 0.95±0.49 mm/s, RML = 1.35±0.62 mm/s, RLL = 1.83±0.71 mm/s, LUL = 0.98 ±0.50 mm/s, and LLL = 1.15 ±0.53 mm/s.

Conclusion:

Our results show that tumor displacement is location dependent. The range of motion and mobility increases as the location of the tumor nears the diaphragm. Under abdominal compression, the magnitude of tumor motion is reduced by as much as a factor of 2 in comparison to reported tumor magnitudes under conventional free breathing conditions. This study demonstrates the utility of abdominal compression in reducing the tumor motion leading to reduced ITV and planning tumor volumes (PTV).
SU‐E‐J‐173: Evaluation of Deformable Registration for Correcting Respiratory Motion in 4DCT Lung Images
Authors: Larrue A , van Elmpt W , Kaster F , Kadir T , Gooding M
Published: July 2014

Purpose:

Deformable Image Registration (DIR) is gaining wider clinical acceptance in radiation oncology. The aim of this work is to characterise a DIR algorithm on publically available 4DCT lung images, such that comparison can be performed against other algorithms. We propose an evaluation method of registration accuracy that takes into account the initial misregistration of the datasets.

Methods:

The “DIR Validation dataset” (http://www.creatis.insa‐lyon.fr/rio/dir_validation_data) provides benchmark data for evaluating 3D CT registration algorithms. It consists of six 4DCT lung datasets (1×1×2mm resolution) with 100 landmarks identified on the end‐exhalation and end‐inhalation phases. Images were registered to end‐inhalation using proprietary form of optical flow in commercial software (Mirada RTx, Mirada Medical, UK). Target registration error was measured before and after DIR, referred to as Initial Registration Error (IRE) and Final Registration Error (FRE).

Results:

The mean FRE over all landmarks was 1.37±1.81mm. FRE increased with IRE. Mean FRE of 0.86, 0.86, 1.53, 3.38, 4.45, 7.58mm was observed for IRE in the ranges 0–5, 5–10, 10–15, 15–20, 20–25, >25 mm. Higher FRE was observed at the inferior lung, where IRE was greater. Out‐of‐plane motion contributed more to IRE, and therefore to FRE. Maximum FRE of 20.6mm was observed for IRE of 32.1mm, located at the posterior of the middle lobe for dataset 2. Sub‐voxel registration accuracy was achieved for up to 10mm IRE, and increased linearly at 0.3mm FRE/mm IRE thereafter.

Conclusion:

Publicly available clinical datasets enable algorithms to be compared objectively between publications. However, only reporting average TRE after registration can be misleading as the ability of an algorithm to correct for displacements varies with the IRE or position within the patient. Consequently, algorithms should be characterized using the entire range of initial displacements. For the algorithm assessed, clinically acceptable error within one voxel was achieved for IRE of up to 15mm.

TK, AL, and MG are employees of Mirada Medical
SU‐E‐J‐184: Stereo Time‐Of‐Flight System for Patient Positioning in Radiotherapy
Authors: Wentz T , Gilles M , Le Fur E , Pradier O , Visvikis D
Published: July 2014

Purpose:

The objective of this work is to test the advantage of using the surface acquired by two stereo Time‐of‐Flight (ToF) cameras in comparison of the use of one camera only for patient positioning in radiotherapy.

Methods:

A first step consisted on validating the use of a stereo ToFcamera system for positioning management of a phantom mounted on a linear actuator producing very accurate and repeatable displacements. The displacements between two positions were computed from the surface point cloud acquired by either one or two cameras thanks to an iterative closest point algorithm. A second step consisted on determining the displacements on patient datasets, with two cameras fixed on the ceiling of the radiotherapy room. Measurements were done first on voluntary subject with fixed translations, then on patients during the normal clinical radiotherapy routine.

Results:

The phantom tests showed a major improvement in lateral and depth axis for motions above 10 mm when using the stereo‐system instead of a unique camera (Fig1). Patient measurements validate these results with a mean real and measured displacement differences in the depth direction of 1.5 mm when using one camera and 0.9 mm when using two cameras (Fig2). In the lateral direction, a mean difference of 1 mm was obtained by the stereo‐system instead of 3.2 mm. Along the longitudinal axis mean differences of 5.4 and 3.4 mm with one and two cameras respectively were noticed but these measurements were still inaccurate and globally underestimated in this direction as in the literature. Similar results were also found for patient subjects with a mean difference reduction of 35%, 7%, and 25% for the lateral, depth, and longitudinal displacement with the stereo‐system.

Conclusion:

The addition of a second ToF‐camera to determine patient displacement strongly improved patient repositioning results and therefore insures better radiation delivery.
SU‐E‐J‐185: Gated CBCT Imaging for Positioning Moving Lung Tumor in Lung SBRT Treatment
Authors: Li X , Li T , Zhang Y , Burton S , Karlovits B , Clump D , Heron D , Huq M
Published: July 2014

Purpose:

Lung stereo‐tactic body radiotherapy(SBRT) treatment requires high accuracy of lung tumor positioning during treatment, which is usually accomplished by free breathing Cone‐Beam computerized tomography (CBCT) scan. However, respiratory motion induced image artifacts in free breathing CBCT may degrade such positioning accuracy. The purpose of this study is to investigate the feasibility of gated CBCT imaging for lung SBRT treatment.

Methods:

Six Lung SBRT patients were selected for this study. The respiratory motion of the tumors ranged from 1.2cm to 3.5cm, and the gating windows for all patients were set between 35% and 65% of the respiratory phases. Each Lung SBRT patient underwent free‐breathing CBCT scan using half‐fan scan technique. The acquired projection images were transferred out for off‐line analyses. An In‐house semi‐automatic algorithm was developed to trace the diaphragm movement from those projection images to acquire a patient's specific respiratory motion curve, which was used to correlate respiratory phases with each projection image. Afterwards, a filtered back‐projection algorithm was utilized to reconstruct the gated CBCT images based on the projection images only within the gating window.

Results:

Target volumes determined by free breathing CBCT images were 71.9%±72% bigger than the volume shown in gated CBCT image. On the contrary, the target volume differences between gated CBCT and planning CT images at exhale stage were 5.8%±2.4%. The center to center distance of the targets shown in free breathing CBCT and gated CBCT images were 9.2±8.1mm. For one particular case, the superior boundary of the target was shifted 15mm between free breathing CBCT and gated CBCT.

Conclusion:

Gated CBCT imaging provides better representation of the moving lung tumor with less motion artifacts, and has the potential to improve the positioning accuracy in lung SBRT treatment.
SU‐E‐J‐187: Individually Optimized Contrast‐Enhancement 4D‐CT for Pancreatic Adenocarcinoma in Radiotherapy Simulation
Authors: Xue M , Patel K , Regine W , Lane B , D' Souza W , Klahr P , Lu W
Published: July 2014

Purpose:

To study the feasibility of individually optimized contrastenhancement (CE) 4D‐CT for pancreatic adenocarcinoma (PDA) in radiotherapy simulation. To evaluate the image quality and contrast enhancement of tumor in the CE 4D‐CT, compared to the clinical standard of CE 3D‐CT and 4D‐CT.

Methods:

In this IRB‐approved study, each of the 7 PDA patients enrolled underwent 3 CT scans: a free‐breathing 3D‐CT with contrast (CE 3D‐CT) followed by a 4D‐CT without contrast (4D‐CT) in the first study session, and a 4D‐CT with individually synchronized contrast injection (CE 4D‐CT) in the second study session. In CE 4D‐CT, the time of full contrast injection was determined based on the time of peak enhancement for the test injection, injection rate, table speed, and longitudinal location and span of the pancreatic region. Physicians contoured both the tumor (T) and the normal pancreatic parenchyma (P) on the three CTs (end‐of‐exhalation for 4D‐CT). The contrast between the tumor and normal pancreatic tissue was computed as the difference of the mean enhancement level of three 1 cm3 regions of interests in T and P, respectively. Wilcoxon rank sum test was used to statistically compare the scores and contrasts.

Results:

In qualitative evaluations, both CE 3D‐CT and CE 4D‐CT scored significantly better than 4D‐CT (4.0 and 3.6 vs. 2.6). There was no significant difference between CE 3D‐CT and CE 4D‐CT. In quantitative evaluations, the contrasts between the tumor and the normal pancreatic parenchyma were 0.6±23.4, −2.1±8.0, and −19.6±28.8 HU, in CE 3D‐CT, 4D‐CT, and CE 4D‐CT, respectively. Although not statistically significant, CE 4D‐CT achieved better contrast enhancement between the tumor and the normal pancreatic parenchyma than both CE 3D‐CT and 4DCT.

Conclusion:

CE 4D‐CT achieved equivalent image quality and better contrast enhancement between tumor and normal pancreatic parenchyma than the clinical standard of CE 3D‐CT and 4D‐CT.

This study was supported in part by Philips Healthcare.
SU‐E‐J‐189: Credentialing of IGRT Equipment and Processes for Clinical Trials
Authors: Court L , Aristophanous M , Bellezza D , Followill D , Kirsner S , Kisling K , Massingill B , Papanikolaou N , Parker B , Pidikiti R , Wong P , Zhen H , Balter P
Published: July 2014

Purpose:

Current dosimetry phantoms used for clinical trial credentialing do not directly assess IGRT processes. This work evaluates a custom‐built IGRT phantom for credentialing of multiple IGRT modalities and processes.

Methods:

An IGRT phantom was built out of a low‐density body with two inserts. Insert A is used for the CT simulation. Insert B is used for the actual treatment. The inserts contain identical targets in different locations. Relative positions are unknown to the user. The user simulates the phantom (with insert A) as they would a patient, including marking the phantom. A treatment plan is created and sent to the treatment unit. The phantom (with insert B) is then positioned using local IGRT practice. Shifts (planned isocenter, if applicable, and final isocenter) are marked on the phantom using room lasers. The mechanical reproducibility of re‐inserting the inserts within the phantom body was tested using repeat high‐resolution CT scans. The phantom was tested at 7 centers, selected to include a wide variety of imaging equipment.

Results:

Mechanical reproducibility was measured as 0.5‐0.9mm, depending on the direction. Approaches tested to mark (and transfer) simulation isocenter included lasers, fiducials and reflective markers. IGRT approaches included kV imaging (Varian Trilogy, Brainlab ExacTrac), kV CT (CT‐on‐rails), kV CBCT (Varian Trilogy, Varian Truebeam, Elekta Agility) and MV CT (Tomotherapy). Users were able to successfully use this phantom for all combinations of equipment and processes. IGRT‐based shifts agreed with the truth within 0.8mm, 0.8mm and 1.9mm in the LR, AP, and SI directions, respectively.

Conclusion:

Based on these preliminary results, the IGRT phantom can be used for credentialing of clinical trials with an action level of 1mm in AP and LR directions, and 2mm in the SI direction, consistent with TG142. We are currently testing with additional institutions with different equipment and processes, including Cyberknife.

This project was funded by the Cancer Prevention Research Institute of Texas
SU‐E‐J‐190: Characterization of Radiation Induced CT Number Changes in Tumor and Normal Lung During Radiation Therapy for Lung Cancer
Authors: Yang C , Liu F , Tai A , Gore E , Johnstone C , Li X
Published: July 2014

Purpose:

To measure CT number (CTN) changes in tumor and normal lung as a function of radiation therapy (RT) dose during the course of RT delivery for lung cancer using daily IGRT CT images and single respiration phase CT images.

Methods:

4D CT acquired during planning simulation and daily 3D CT acquired during daily IGRT for 10 lung cancer cases randomly selected in terms of age, caner type and stage, were analyzed using an in‐house developed software tool. All patients were treated in 2 Gy fractions to primary tumors and involved nodal regions. Regions enclosed by a series of isodose surfaces in normal lung were delineated. The obtained contours along with target contours (GTVs) were populated to each singlephase planning CT and daily CT. CTN in term of Hounsfield Unit (HU) of each voxel in these delineated regions were collectively analyzed using histogram, mean, mode and linear correlation.

Results:

Respiration induced normal lung CTN change, as analyzed from single‐phase planning CTs, ranged from 9 to 23 (±2) HU for the patients studied. Normal lung CTN change was as large as 50 (±12) HU over the entire treatment course, was dose and patient dependent and was measurable with dose changes as low as 1.5 Gy. For patients with obvious tumor volume regression, CTN within the GTV drops monotonically as much as 10 (±1) HU during the early fractions with a total dose of 20 Gy delivered. The GTV and CTN reductions are significantly correlated with correlation coefficient >0.95.

Conclusion:

Significant RT dose induced CTN changes in lung tissue and tumor region can be observed during even the early phase of RT delivery, and may potentially be used for early prediction of radiation response. Single respiration phase CT images have dramatically reduced statistical noise in ROIs, making daily dose response evaluation possible.
SU‐E‐J‐191: Automated Detection of Anatomic Changes in H' N Patients
Authors: Usynin A , Ramsey C
Published: July 2014

Purpose:

To develop a novel statistics‐based method for automated detection of anatomical changes using cone‐beam CT data. A method was developed that can provide a reliable and automated early warning system that enables a “just‐in‐time” adaptation of the treatment plan.

Methods:

Anatomical changes were evaluated by comparing the original treatment planning CT with daily CBCT images taken prior treatment delivery. The external body contour was computed on a given CT slice and compared against the corresponding contour on the daily CBCT. In contrast to threshold‐based techniques, a statistical approach was employed to evaluate the difference between the contours using a given confidence level. The detection tool used the two‐sample Kolmogorov‐Smirnov test, which is a non‐parametric technique that compares two samples drawn from arbitrary probability distributions. 11 H' N patients were retrospectively selected from a clinical imaging database with a total of 186 CBCT images. Six patients in the database were confirmed to have anatomic changes during the course of radiotherapy. Five of the H' N patients did not have significant changes. The KS test was applied to the contour data using a sliding window analysis. The confidence level of 0.99 was used to moderate false detection.

Results:

The algorithm was able to correctly detect anatomical changes in 6 out of 6 patients with an excellent spatial accuracy as early as at the 14th elapsed day. The algorithm provided a consistent and accurate delineation of the detected changes. The output of the anatomical change tool is easy interpretable, and can be shown overlaid on a 3D rendering of the patient's anatomy.

Conclusion:

The detection method provides the basis for one of the key components of Adaptive Radiation Therapy. The method uses tools that are readily available in the clinic, including daily CBCT imaging, and image co‐registration facilities.
SU‐E‐J‐195: Quantification of Rotations and Deformations in Head and Heck Radiotherapy
Authors: Kim J , Liu C , Kumarasiri A , Chetvertkov M , Gordon J , Siddiqui F , Chetty I J
Published: July 2014

Purpose:

To quantify the magnitude of patient rotations and deformations over the course of head and neck radiotherapy.

Methods:

45 CBCT images acquired weekly were selected retrospectively from 5 head and neck cancer patients. CBCT images were registered to the corresponding planning CT images using translation, rigid‐body, and cubic B‐spline deformable transformations. Elastix (elastix.isi.uu.nl), an open‐source public domain registration algorithm, was used for all registrations with mutual information as similarity metric and gradient descent as optimization. Four‐level multiresolution approach was employed with 2 cm B‐spline grid spacing at the finest resolution. Registration qualities were visually verified. Rotational occurrences were quantified from the rigid‐body registrations. The magnitude of deformations in planning target volumes (PTV) and organs were quantified from the deformation vector fields with rigid registrations as baseline.

Results:

The measured rotations (mean±std) were 1.0±1.0 deg, – 0.3±1.0 deg, and 0.1±0.8 deg in the sagittal, coronal, and axial plains respectively. The estimated magnitudes of deformations (mean±std) were 3.4±2.1 mm for PTVs, 2.9±1.2 mm for parotid glands, 2.8±1.2 mm for mandible, and 2.2±1.1 mm for spinal cord. The overall deformation in the body contour was 4.3±4.3 mm. The organ spatial deviation due to rotation was small and approximately 8.4% of that from deformations. Results varied among patients.

Conclusion:

Rotations occurred about 1.0 deg (1SD) in the H' N area. Daily geometric deviation of target volumes was considerable and mainly from tissue deformation than rotations. Proper safety margin is necessary for adequate target coverage. Online plan adaptation may mitigate the daily differences between the plan and actual patient poses.

Partially supported by a grant from Varian Medical Systems, Palo Alto, CA.
SU‐E‐J‐196: New Visualization Methods for Longitudinal MRI Registrations and Segmentations
Authors: Veeraraghavan H , Deasy J
Published: July 2014

Purpose:

To develop visualization techniques to facilitate easy assessment of (a) registration and (b) tracking volumetric changes in structures during radiation therapy from MRI.

Method:

The frequently used method for visualizing registrations between scans is a multi‐color overlay technique or deformation vector fields. However, the overlay technique is unintuitive and does not help to appreciate the quality of registration particularly when the registration mismatches are not very large. Similarly, the deformation fields give an indication of extent of deformation but do not help to assess the differences in registration. We present a mirroring and edge‐augmented mirroring technique that places the fixed and moving image next to each other and allows the user to quickly assess the small differences in registration. Next, we present a volumetric intersection based 3D model to visualize the changes in diseased lymph node volumes in head and neck cancer. 3D model‐based visualization provides more information about the location‐specific changes in volume rather than the simplistic one dimensional information obtained from 2D plot of nodal volume changes.

Result:

We show results comparing our approach with the standard colorbased overlay method for comparing registrations of intra‐patient registrations using T2‐MRI. Upon comparing the mirroring technique with the color‐overlay, one can more easily appreciate the differences in registration. Adding edge‐based mirroring seems to further assist in evaluating the registration. Our approach for viewing registrations seems to be more intuitive and easy to use in order to help assess the quality of registration compared to color‐based overlays. Similarly, the change volumetric model together with a 2D plot reveals more information including the locations undergoing changes and responding to treatment.

Conclusions:

Better approaches are necessary for assessing the quality of registrations and changes in diseased structures over time. Our approach presents some novel visualization solutions for registration and segmentation.
SU‐E‐J‐201: Position Verification in Breast Cancer Radiotherapy Using Tantalum Clips in the Lumpectomy Cavity
Authors: van Santvoort J , Van der Drift M , Kuipers J , Mast M , Van Egmond J , Struikmans H
Published: July 2014

Purpose:

To find out whether tantalum surgical clips can be used for online position verification in treatment of the lumpectomy cavity (LC) in breast cancer patients. Tantalum is a high density metal that could be visible on Electronic Portal Images (EPIs) and be an affordable alternative to gold markers. Clips are considered more representative for the LC position than nearby bony structures.

Methods:

In twelve patients the surgeon had placed 2 to 5 tantalum clips in the LC. The AP and lateral fields used for portal imaging, were adapted. In doing so, both bony structures and tantalum clips were visible on EPIs. The following analyses were performed:1. Image degradation, with respect to delineating the CTV, of the axial CT slices by artefacts because of the tantalum clips was evaluated by a radiation oncologist;2. The visibility of the tantalum clips on the EPIs was evaluated by four radiation therapists (RTTs);3. Bony anatomy and tantalum clip matches were performed on the same images independently by two observers.

Results:

1. Delineation of the CTV by the radiation oncologist was not hampered by CT image artefacts because of the clips.2. The mean score for visibility of the clips on the EPIs, analysed by the four RTTs, was 5.6 on a scale of 10 (range 3.9 – 8.0).3. In total 12 patients with 16 fractions each were analysed. The differences between clip match and bone match are significant with a mean vector length of 5.2 mm (SD 1.9 mm) for the difference.

Conclusion:

Results of matches on tantalum clips as compared to matches on bony structures differ substantially. Therefore clip matches can result in smaller CTV to PTV margins than bone matches. Visibility of the clips on EPIs is sufficient, so they can be an alternative to gold markers.
SU‐E‐J‐202: Is Pretreatment Imaging at Each Treatment Fraction Needed in Spine SBRT to Enable Margin Reduction?
Authors: Mynampati D , Yaparpalvi R , Garg M , Hong L , Kuo H , Tome' W
Published: July 2014

Purpose:

To study translational setup errors of Spine SBRT treatments using BodyFIX immobilization system and the potential for margin reduction using pretreatment imaging.

Methods:

148 online match results of 39 Spine SBRT patients treated at our institution were reviewed. All treatments performed using Varian, TrueBeam and MI™, BodyFIX immobilization device. Prescriptions (dose‐fractionation schedules) for the patients in the study are 8 Gy X 3 (n=24), 6 Gy X 4 (n=10) and 16Gy X 1 (n=5). For all patients, OBI was performed on verification day and before each treatment. Recorded shifts are from adopted couch positions after physician online review of KV image‐pair and CBCT. Data analyzed by computing Mean error (M), Systematic error (Σ) and Random error (σ) for three translation directional shifts and 3D Vector length. To estimate correlation between imaging sessions, Anova‐test and T‐Test with alpha of 0.05 performed over the data.

Results:

Mean error (M), Systematic error (Σ) and Random error (σ) of Vertical direction are ‐1.81mm, 4.05mm and 2.01mm respectively. Similarly, Errors in Longitudinal direction are 0.76mm (M), 4.21mm (Σ) and 1.34mm (σ). Errors in Lateral direction are – 0.16mm (M), 3.22mm (Σ) and 1.83 mm (σ). Mean, SD and CI95% of 3D Vector lengths are 7.93mm, 4.41mm and 0.7mm respectively. Anova‐test results show, P‐Values for longitudinal and lateral shifts are > 0.3 and P‐value of vertical shift is 0.054. This signifies mean of the each imaging session are not significantly different. T‐Test on treatment sessions data of vertical shifts with respect to verification day shows, mean of Vertical shifts on verification day are different from Vertical shifts on treatment sessions.

Conclusion:

Results shows immobilization with BodyFIX is reproducible in the mm range. To eliminate systematic error component and to enable margin reduction, pretreatment imaging prior to each treatment fraction is indispensable.
SU‐E‐J‐204: Radiation Dose to Patients Resulting From Image Guidance Procedures and AAPM TG‐180 Update
Authors: Ding G , Alaei P
Published: July 2014

Purpose:

Image‐guided radiation therapy (IGRT) is the new paradigm for patient positioning and target localization in radiotherapy. Daily imaging procedures add additional dose to the patient's treatment volume and normal tissues and may expose the organs at risk to unaccounted doses. This presentation is to update the progress of AAPM TG‐180 which aims to provide strategies to quantify and account the dose from both MV and kV imaging in patient treatment planning.

Methods:

Our current knowledge on image guidance dose is presented. A summary of doses from image guidance procedures delivered to patients in relationship with therapeutic doses is given. Different techniques in reducing the image guidance dose are summarized. Typical organ doses resulting from different image acquisition procedures used in IGRT are tabulated.

Results:

Many techniques to reduce the imaging doses are available in clinical applications. There are large variations between dose to bone and dose to soft tissues for x‐rays at kilovoltage energy range. Methods for clinical implementation of accounting for the imaging dose from an imaging procedure are available. Beam data from imaging systems can be generated by combining Monte Carlo simulations and experimental measurements for commissioning imaging beams in the treatment planning.

Conclusion:

The current treatment planning systems are not yet equipped to perform patient specific dose calculations resulting from kV imaging procedures. The imaging dose from current kV image devices has been significantly reduced and is generally much less than that resulting from MV. Because the magnitude of kV imaging dose is significantly low and the variation between patients is modest, it is feasible to estimate dose based on imaging producers or protocols using tabulated values which provides an alternative to accomplish the task of accounting and reporting imaging doses.
SU‐E‐J‐206: A Comparison of Different Hardware Design Approaches for Feature‐Supported Optical Head‐Tracking with Respect to Angular Dependencies
Authors: Stueber P , Wissel T , Wagner B , Bruder R , Schweikard A , Ernst F
Published: July 2014

Purpose:

Recent research has shown that optical features significantly improve marker‐less optical head‐tracking for cranial radiotherapy. Simulations, however, showed that these optical features, which are used to derive tissue thickness, depend on the incident angle of the IR scanning laser beam and the perspective of the camera analyzing the reflective patterns. We present an experimental analysis determining which is the most robust optical setup concerning angular influences.

Methods:

In three consecutive experiments, the incident angle of the laser (1), the perspective of the camera (2) or both simultaneously (3, ‘inBeam’‐perspective) were changed with respect to the target. We analyzed how this affects feature intensity. These intensities were determined from seven concentric regions of interest (ROIs) around the laser spot. Two targets were used: a tissue‐like silicone phantom and a human's forehead.

Results:

For each experiment, the feature intensity generally decreases with increasing angle. We found that the optical properties of the silicone phantom do not fit the properties of human skin. Furthermore, the angular influence of the laser on the features is significantly higher than the perspective of the camera. With the ‘inBeam’‐ perspective, the smoothest decays of feature intensity were found. We suppose that this is because of a fixed relationship between both devices. This smoothness, suggesting a predictable functional relationship, may simplify angle compensation for machine learning algorithms. This is particularly prominent for the medial ROIs. The inner ROIs highly depend on the angle and power of the laser. The outer ROIs show less angular dependency but the signal strength is critically low and prone to artifacts. Therefore and because of the smooth decays, medial ROIs are a suitable tradeoff between susceptibility, signal‐noise‐ratio and distance to the center of the laser spot.

Conclusion:

For tissue thickness correlated feature acquisition, the medial ROIs with the ‘inBeam’‐setup provide most valuable features

This work was supported by Varian Medical Systems Inc. (Palo Alto, CA, USA). In addition, this work was supported by the Graduate School for Computing in Medicine and Life Sciences funded by Germany's Excellence Initiative [DFG GSC 235/1].
SU‐E‐J‐209: Verification of 3D Surface Registration Between Stereograms and CT Images
Authors: Han T , Smith B , Salehpour M , Gifford K
Published: July 2014

Purpose:

Stereography can provide a visualization of the skin surface for radiation therapy patients. The aim of this study was to verify the registration algorithm in a commercial image analysis software, 3dMDVultus, for the fusion of stereograms and CT images.

Methods:

CT and stereographic scans were acquired of a head phantom and a deformable phantom. CT images were imported in 3dMDVultus and the surface contours were generated by threshold segmentation. Stereograms were reconstructed in 3dMDVultus. The resulting surfaces were registered with Vultus algorithm and then exported to in‐house registration software and compared with four algorithms: rigid, affine, non‐rigid iterative closest point (ICP) and b‐spline algorithm. RMS (root‐mean‐square residuals of the surface point distances) error between the registered CT and stereogram surfaces was calculated and analyzed.

Results:

For the head phantom, the maximum RMS error between registered CT surfaces to stereogram was 6.6 mm for Vultus algorithm, whereas the mean RMS error was 0.7 mm. For the deformable phantom, the maximum RMS error was 16.2 mm for Vultus algorithm, whereas the mean RMS error was 4.4 mm. Non‐rigid ICP demonstrated the best registration accuracy, as the mean of RMS errors were both within 1 mm.

Conclusion:

The accuracy of registration algorithm in 3dMDVultus was verified and exceeded RMS of 2 mm for deformable cases. Non‐rigid ICP and b‐spline algorithms improve the registration accuracy for both phantoms, especially in deformable one. For those patients whose body habitus deforms during radiation therapy, more advanced nonrigid algorithms need to be used.
SU‐E‐J‐210: Thoracic Atlas Segmentation Model Based On Consensus Contours
Authors: Turian J , Wu Z , Miller L , Darwish N , Templeton A , Chu J
Published: July 2014

Purpose:

Generation of a thoracic segmentation atlas based on consensus contours obtained through input from individual experts

Method and Materials:

A cohort of 30 patients treated for lung disease was selected for this study. All patients had 4D‐CT studies with image segmentation based on respiration‐averaged images. For each subject, three experts delineated the eighteen agreed‐upon structures using tools available in Eclipse ver.10.0. Consensus structures were generated using CERR(4.0β2). The EM‐STAPLE method was chosen to generate the consensus contours based on published reports which state that iterative methods yield better results over analytical methods in medical imaging. Once the consensus contours were generated they were re‐imported in Eclipse for further processing and evaluation. For each structure, each expert's contour was scored against the consensus using two scoring indices: Dice similarity coefficient, DSC, and Dice‐Jaccard coefficient, DJC. Visual inspection was always performed to detect large segmentation errors

Results:

The respiration‐averaged CT set proved to be adequate for all structures included in the thoracic atlas. As expected, anatomic variability between patients was larger than the variability due to the level of expertise. Across the entire cohort the smallest structure segmented was the brachial plexus with a 9.4cc (+/− 3.5) volume, while the chest wall was the largest (2933cc +/‐560). The DSC and DJC coefficients were smallest for Left Brachial Plexus 0.894 (+/−0.138) and 0.842 (+/− 0.138), respectively, while the largest were 0.992(+/−0.004) and 0.990(+/− 0.004), observed for the right lung.

Conclusions:

Consensus contours generated using expert input were analyzed using comparison indices and visual evaluation. With appropriate atlas selection (e.g. patient gender, arm position) a robust thoracic atlas segmentation tool can be set up and may be used in conjunction with an automatic segmentation algorithm.

Project supported by Varian Medical System
SU‐E‐J‐274: Image Distortion Quantification and Image Registration QA in GammaKnife Radiosurgery Using A Modus GRID3D Phantom
Authors: Lu L , Noa K , Woods K , Weldon M , Gupta N
Published: July 2014

Purpose:

To quantify image distortion in MRI and CT images used in GammaKnife radiosurgery planning with a Modus GRID3D phantom.

Methods:

Image distortion in GammaKnife radiosurgery can affect treatment efficacy by inaccurately depicting tumors and organs at risk in the brain. It is therefore important that a quantified QA check on image distortion be performed periodically. A commercial 3‐dimensional grid phantom and its associated software, GRID3D (Modus Medical Devices Inc.), was used in determining image distortion on the MRI machines and the CT‐simulator that are used clinically for GammaKnife treatment planning. The GammaKnife head frame and frame box were placed on the phantom and imaged on each MRI and CT machine according to GammaKnife imaging protocols used clinically at our institution. The obtained images were imported into the GRID3D Image Distortion Analysis System where the distortion of each image set was calculated. The calculation works by quantifying the 3D spatial deviation between the reconstructed image sets and the program's reference phantom. For registration QA, the CT and MR image sets were registered with each other. The regular analysis of grids alignment allows us to evaluate the quality of image registration from MRI to CT (commonly used in the Gamma Knife preplan scheme) and vice versa.

Results:

Distortion analysis using the GRID3D phantom numerically represented image distortion in the x, y, and z direction for each MRI machine and CT simulator used clinically for GammaKnife treatments. The spatial deviation between images in each direction is generally less than or equal to 1 mm when the imager is functioning properly. Image registration QA using the GRID3D phantom proves to be very efficient.

Conclusion:

The quantified image distortion check is important and should be incorporated into routine QA practice. It is especially important to perform this check immediately after a major machine upgrade.
SU‐E‐J‐275: Impact of the Intra and Inter Observer Variability in the Delineation of Parotid Glands On the Dose Calculation During Head and Neck Helical Tomotherapy
Authors: Jodda A , Piotrowski T
Published: July 2014

Purpose:

The intra‐ and inter‐observer variability in delineation of the parotids on the kilo‐voltage computed tomography (kVCT) and mega‐voltage computed tomography (MVCT) were examined to establish their impact on the dose calculation during adaptive head and neck helical tomotherapy (HT).

Methods:

Three observers delineated left and right parotids for ten randomly selected patients with oropharynx cancer treated on HT. The pre‐treatment kVCT and the MVCT from the first fraction of irradiation were selected to delineation. The delineation procedure was repeated three times by each observer. The parotids were delineated according to the institutional protocol. The analyses included intra‐observer reproducibility and inter‐structure, ‐observer and ‐modality variability of the volume and dose.

Results:

The differences between the left and right parotid outlines were not statistically significant (p>0.3). The reproducibility of the delineation was confirmed for each observer on the kVCT (p>0.2) and on the MVCT (p>0.1). The inter‐observer variability of the outlines was significant (p<0.001) as well as the inter‐modality variability (p<0.006). The parotids delineated on the MVCT were 10% smaller than on the kVCT. The inter‐observer variability of the parotids delineation did not affect the average dose (p=0.096 on the kVCT and p=0.176 on the MVCT). The dose calculated on the MVCT was higher by 3.3% than dose from the kVCT (p=0.009).

Conclusion:

Usage of the institutional protocols for the parotids delineation reduces intra‐observer variability and increases reproducibility of the outlines. These protocols do not eliminate delineation differences between the observers, but these differences are not clinically significant and do not affect average doses in the parotids. The volumes of the parotids delineated on the MVCT are smaller than on the kVCT, which affects the differences in the calculated doses.
SU‐E‐T‐05: A 2D EPID Transit Dosimetry Model Based On An Empirical Quadratic Formalism
Authors: Tan Y , Metwaly M , Glegg M , Baggarley S , Elliott A
Published: July 2014

Purpose:

To describe a 2D electronic portal imaging device (EPID) transit dosimetry model, based on an empirical quadratic formalism, that can predict either EPID or in‐phantom dose distribution for comparisons with EPID captured image or treatment planning system (TPS) dose respectively.

Methods:

A quadratic equation can be used to relate the reduction in intensity of an exit beam to the equivalent path length of the attenuator. The calibration involved deriving coefficients from a set of dose planes measured for homogeneous phantoms with known thicknesses under reference conditions. In this study, calibration dose planes were measured with EPID and ionisation chamber (IC) in water for the same reference beam (6MV, 100mu, 20×20cm2) and set of thicknesses (0–30cm). Since the same calibration conditions were used, the EPID and IC measurements can be related through the quadratic equation. Consequently, EPID transit dose can be predicted from TPS exported dose planes and in‐phantom dose can be predicted using EPID distribution captured during treatment as an input. The model was tested with 4 open fields, 6 wedge fields, and 7 IMRT fields on homogeneous and heterogeneous phantoms. Comparisons were done using 2D absolute gamma (3%/3mm) and results were validated against measurements with a commercial 2D array device.

Results:

The gamma pass rates for comparisons between EPID measured and predicted ranged from 93.6% to 100.0% for all fields and phantoms tested. Results from this study agreed with 2D array measurements to within 3.1%. Meanwhile, comparisons in‐phantom between TPS computed and predicted ranged from 91.6% to 100.0%. Validation with 2D array device was not possible for inphantom comparisons.

Conclusion:

A 2D EPID transit dosimetry model for treatment verification was described and proven to be accurate. The model has the advantage of being generic and allows comparisons at the EPID plane as well as multiple planes in‐phantom.