bluuebunny/crossref_metadata_2025 huggingface dataset:
SU‐D‐202‐03: Statistical Segmentation On Quantitative CT for Assessing Spatial Tumor Response During Radiation Therapy Delivery
Authors: Schott D , Schmidt T , Chen X , Klawikowski S , Noid G , Dalah E , Li X
Published: July 2016

Purpose:

Develop a method to segment regions of interest (ROIs) in tumor with statistically similar Hounsfield unit (HU) values and/or HU changes during chemoradiation therapy (CRT) delivery, to assess spatial tumor treatment response based on daily CTs during CRT delivery.

Methods:

Generate a three region map of ROIs with differential HUs, by sampling neighboring voxels around a selected voxel and comparing to the mean of the entire ROI using a t‐test. The cumulative distribution function, P, is calculated from the t‐test. The P value is assigned to be the value at the selected voxel, and this is repeated over all voxels in the initial ROI. Three regions are defined as: (1‐P) < 0.00001 (mid region), and 0.00001 < (1‐P) (mean greater than baseline and mean lower than baseline). The test is then expanded to compare daily CT sets acquired during routine CT‐guided RT delivery using a CT‐on‐rails. The first fraction CT is used as the baseline for comparison. We tested 15 pancreatic head tumor cases undergoing CRT, to identify the ROIs and changes corresponding to normal, fibrotic, and tumor tissue. The obtained ROIs were compared with MRI‐ADC maps acquired pre‐ and post‐CRT.

Results:

The ROIs in 13 out of 15 patients’ first fraction CTs and pre‐CRT MRIs matched the general region and slices covered, as well as in 6 out of the 9 patients with post‐CRT MRIs. The high HU region designated by the t‐test was seen to correlate with the tumor region in MR, and these ROIs are positioned within the same region over the course of treatment. In patients with poorly delineated tumors in MR, the t‐test was inconclusive.

Conclusion:

The proposed statistical segmentation technique shows the potential to identify regions in tumor with differential HUs and HU changes during CRT delivery for patients with pancreas head cancer.
SU‐D‐202‐04: Validation of Deformable Image Registration Algorithms for Head and Neck Adaptive Radiotherapy in Routine Clinical Setting
Authors: Zhang L , Wang Z , Shi C , Pi Y , Long T , Luo W , Wang F , Chen Z , Xu X
Published: July 2016

Purpose:

To evaluate the ROI contours and accumulated dose difference using different deformable image registration (DIR) algorithms for head and neck (H&N) adaptive radiotherapy.

Methods:

Eight H&N cancer patients were randomly selected from the affiliated hospital. During the treatment, patients were rescanned every week with ROIs well delineated by radiation oncologist on each weekly CT. New weekly treatment plans were also re‐designed with consistent dose prescription on the rescanned CT and executed for one week on Siemens CT‐on‐rails accelerator. At the end, we got six weekly CT scans from CT1 to CT6 including six weekly treatment plans for each patient. The primary CT1 was set as the reference CT for DIR proceeding with the left five weekly CTs using ANACONDA and MORFEUS algorithms separately in RayStation and the external skin ROI was set to be the controlling ROI both. The entire calculated weekly dose were deformed and accumulated on corresponding reference CT1 according to the deformation vector field (DVFs) generated by the two different DIR algorithms respectively. Thus we got both the ANACONDA‐based and MORFEUS‐based accumulated total dose on CT1 for each patient. At the same time, we mapped the ROIs on CT1 to generate the corresponding ROIs on CT6 using ANACONDA and MORFEUS DIR algorithms. DICE coefficients between the DIR deformed and radiation oncologist delineated ROIs on CT6 were calculated.

Results:

For DIR accumulated dose, PTV D95 and Left‐Eyeball Dmax show significant differences with 67.13 cGy and 109.29 cGy respectively (Table1). For DIR mapped ROIs, PTV, Spinal cord and Left‐Optic nerve show difference with −0.025, −0.127 and −0.124 (Table2).

Conclusion:

Even two excellent DIR algorithms can give divergent results for ROI deformation and dose accumulation. As more and more TPS get DIR module integrated, there is an urgent need to realize the potential risk using DIR in clinical.
SU‐D‐202‐05: Evaluation of Four‐Dimensional Dose Reconstruction Under Breathing Irregularity
Authors: Yoon J , Yeo I , Jung J , Yi B
Published: July 2016

Purpose:

A method of four dimensional dose reconstruction (4D‐DR) using a cine mode of an EPID to determine the delivered 4D dose distribution has been suggested. This method, however, has not been tested under irregular breathing. This study investigated their effects on 4D‐DR.

Methods:

The 4D‐DR attempts to find the patient's breathing phase associated with each EPID image by comparing it to pre‐generated‐EPID‐quality DRRs of every breathing phases. A lung phantom with a tumor object (3cm diameter cylinder) on a moving platform was used for this test under conditions of amplitude reduction by 1/2 during (1) the entire delivery and (2) the duration when MLC blocked the tumor (hindering the phase determination). The dose delivered to the phantom was inversely reconstructed in the associated phase image of the phantom from each EPID image based on our documented inverse method of the 4D‐DR; the phase‐specific dose was integrated, generating the 4D reconstructed dose. Forward 4D Monte Carlo calculations were used as the 4D dose of a ground truth.

Results:

The reconstructed dose showed 98.1% gamma pass rate for 3%/3mm under regular breathing (i.e. no amplitude reduction) when compared with the forward 4D dose. When the irregular condition (#1) was adopted for treatment, the pass rate became 94.2%. The irregularity under the MLC block (#2) showed the pass rate of 91.3%. The two conditions did not affect the reconstruction noticeably in DVH plots of the tumor and lung‐tumor.

Conclusion:

As long as the extent of on‐treatment motion is smaller than that of the planning CT, the 4D‐DR can be done accurately. Otherwise, ontreatment 4D CT images are necessary.
SU‐D‐202‐06: Prospective Free‐Breathing CT Scan Selection for 5DCT
Authors: O'Connell D , Thomas D , Dou T , Yang L , Lamb J , Lewis J , Ruan D , Lee P , Low D
Published: July 2016

Purpose:

5DCT employs 25 fast helical scans and breathing surrogate monitoring to sample the respiratory cycle. Deformable image registration is used to fit a correspondence model between tissue motion and breathing amplitude and rate. The number of scans was chosen to ensure a high probability that tissues were imaged at sufficiently distinct breathing phases for accurate modeling of the entire breathing cycle. This work describes a method to prospectively select scan start times and reduce the protocol's number of scans from 25 to 6.

Methods:

Breathing traces from 7 patients imaged with 5DCT were used to simulate acquisition of 6 scans. Breathing phase was estimated using only observations from previous time points. Cross‐correlation between the representative breath and the most recent half period was continuously computed. If phase and cross‐correlation criteria were met, scans were triggered with a 2 second delay before acquisition. Blind acquisition, 6 scans separated by a fixed delay, was modeled at staggered start times. The spread of prospectively and blindly sampled breathing waveforms was characterized using a previously published objective function.

Results:

Prospectively selected scans ranked on average in the 84th percentile of objective function values obtained by blind acquisition at staggered start times for 7 patient breathing traces.

Conclusion:

A method to prospectively determine scan start times for 5DCT was developed and tested by simulating acquisition on patient breathing traces. The method is computationally inexpensive enough for real‐time implementation and would result in an imaging dose of less than one quarter of the current 5DCT protocol.
SU‐D‐202‐07: Clinical Applicability of An Optical‐Surface‐Imaging‐Based Technique for Spirometric Measurement, Breathing Pattern Monitoring and Body Drift Correction
Authors: Zhang S , Huang H , Wei J , Li G
Published: July 2016

Purpose:

To explore the capabilities of optical surface imaging (OSI) as a comprehensive tumor motion surrogate to provide dynamic spirometric measurements, breathing pattern monitoring and body positioning correction.

Methods:

OSI captures the moving surface of the torso with all respiration‐induced external motions in real time. Tidal volume (TV) and its time derivative (TV’, airflow) were measured based on the volume conservation rule within the pseudo‐closed torso system: torso volume change equals TV in reference to full exhalation. In addition, breathing pattern (BP=ΔVchest/TV), indicating TV distribution within the torso, was quantified using this OSI‐based technique. Moreover, slow body position changes were detected by OSI via surface image registration in every breathing cycle at full‐exhalation phases, which are most reproducible phases unless voluntary body shift occurs. Volume changes due to body shift out of the volume of interest (VOI) were calculated to correct TV baseline drifts. Real‐time OSI images captured in both high‐resolution and low‐resolution was applied for TV, TV’ and BP measurements and baseline drift correction. Eleven volunteers participated in the IRB‐approved protocol study and performed free‐breathing, belly‐breathing and chest‐breathing exercises during OSI image acquisition.

Results:

Small TV baseline shifts are often observed in OSI‐based spirometry measurement with an average rate of ∼0.4cc/s. Using surface registration among fullexhalation phases and volume calculation from the body shifts relative to the fixed VOI, 80–90% baseline drift on average is corrected in three breathing exercises. The baseline drift is a useful indication of patient body shift and can be effectively corrected. When reducing OSI resolution from high to low, image capture rate increases from 5Hz to 10Hz, while the TV measurement accuracy is retained.

Conclusion:

The OSI‐based spirometric technique provides multiple parameters for monitoring patient respirations and body shift. The spirometric measurements, BP monitoring, and body‐shift detection are useful for tumor motion surrogating.

This study is in part supported by the NIH (U54CA137788/U54CA132378).
SU‐D‐207A‐03: Potential Role of BOLD MRI in Discrimination of Aggressive Tumor Habitat in Prostate Cancer
Authors: Ford J , Lopez C , Tschudi Y , Breto A , Padgett K , Pollack A , Stoyanova R
Published: July 2016

Purpose:

To determine whether blood oxygenation level dependent (BOLD) MRI signal measured in prostate cancer patients, in addition to quantitative diffusion and perfusion parameters from multiparametric (mp)MRI exams, can help discriminate aggressive and/or radioresistant lesions.

Methods:

Several ongoing clinical trials in our institution require mpMRI exam to determine eligibility (presence of identifiable tumor lesion on mpMRI) and prostate volumes for dose escalation. Upon consent, patients undergo fiducial markers placement and a T2*‐weighted imaging at the time of CT sim to facilitate the fusion. In a retrospective analysis eleven clinical trial patients were identified who had undergone mpMRI on GE 3T magnet, followed by T2*‐weighted imaging (time‐period mean±SD = 48±20 days) using a consistent protocol (gradient echo, TR/TE=30/11.8ms, flip angle=12, matrix=256×256×75, voxel size=1.25×1.25×2.5mm). ROIs for prostate tumor lesions were automatically determined using ADC threshold ≤1200 µm2/s. Although the MR protocol was not intended for BOLD analysis, we utilized the T2*‐weighted signal normalized to that in nearby muscle; likewise, T2‐weighted lesion signal was normalized to muscle, following rigid registration of the T2 to T2* images. The ratio of these normalized signals, T2*/T2, is a measure of BOLD effect in the prostate tumors. Perfusion parameters (Ktrans, ve, kep) were also calculated.

Results:

T2*/T2 (mean±SE) was found to be substantially lower for Gleason score (GS) 8&9 (0.82±0.04) compared to GS 7 (1.08±0.07). A k‐means cluster analysis of T2*/T2 versus kep = Ktrans/ve revealed two distinct clusters, one with higher T2*/T2 and lower kep, containing only GS 7 lesions, and another with lower T2*/T2 and higher kep, associated with tumor aggressiveness. This latter cluster contained all GS 8&9 lesions, as well as some GS 7.

Conclusion:

BOLD MRI, in addition to ADC and kep, may play a role (perhaps orthogonal to Gleason score) in identifying prostate lesions that would benefit from more aggressive radiotherapy.
SU‐D‐207A‐05: Investigating Sparse‐Sampled MRI for Motion Management in Thoracic Radiotherapy
Authors: Sabouri P , Arai T , Sawant A
Published: July 2016

Purpose:

Sparse sampling and reconstruction‐based MRI techniques represent an attractive strategy to achieve sufficiently high image acquisition speed while maintaining image quality for the task of radiotherapy guidance. In this study, we examine rapid dynamic MRI using a sparse sampling sequence k‐t BLAST in capturing motion‐induced, cycle‐to‐cycle variations in tumor position. We investigate the utility of long‐term MRI‐based motion monitoring as a means of better characterizing respiration‐induced tumor motion compared to a single‐cycle 4DCT.

Methods:

An MRI‐compatible, programmable, deformable lung motion phantom with eleven 1.5 ml water marker tubes was placed inside a 3.0 T whole‐body MR scanner (Philips Ingenia). The phantom was programmed with 10 lung tumor motion traces previously recorded using the Synchrony system. 2D+t image sequences of a coronal slice were acquired using a balanced‐SSFP sequence combined with k‐t BLAST (accn=3, resolution=0.66×0.66×5 mm3; acquisition time = 110 ms/slice). kV fluoroscopic (ground truth) and 4DCT imaging was performed with the same phantom setup and motion trajectories. Marker positions in all three modalities were segmented and tracked using an opensource deformable image registration package, NiftyReg.

Results:

Marker trajectories obtained from rapid MRI exhibited <1 mm error compared to kv Fluoro trajectories in the presence of complex motion including baseline shifts and changes in respiratory amplitude, indicating the ability of MRI to monitor motion with adequate geometric fidelity for the purpose of radiotherapy guidance. In contrast, the trajectory derived from 4DCT exhibited significant errors up to 6 mm due to cycle‐to‐cycle variations and baseline shifts. Consequently, 4DCT was found to underestimate the range of marker motion by as much as 50%.

Conclusion:

Dynamic MRI is a promising tool for radiotherapy motion management as it permits for longterm, dose‐free, soft‐tissue‐based monitoring of motion, yielding richer and more accurate information about tumor position and motion range compared to the current state‐of‐the‐art, 4DCT.

This work was partially supported through research funding from National Institutes of Health (R01CA169102).
SU‐D‐207A‐06: Pediatric Abdominal Organ Motion Quantified Via a Novel 4D MRI Method
Authors: Uh J , Krasin MJ , Lucas JT , Tinkle C , Merchant TE , Hua C
Published: July 2016

Purpose:

To develop a 4D MRI method for assessing respiration‐induced abdominal organ motion in children receiving radiation therapy.

Methods:

A 4D MRI using internal image‐based respiratory surrogate has been developed and implemented on a clinical scanner (1.5T Siemens Avanto). Ten patients (younger group: N=6, 2–5 years, anesthetized; older group: N=4, 11–15 years) with neuroblastoma, Wilm's tumor rhabdomyosarcoma, or desmoplastic small round cell tumor received free breathing 4D MRI scans for treatment planning. Coronal image slices of the entire abdomen were retrospectively constructed in 10 respiratory phases. A B‐spline deformable registration (Metz et al. 2011) was performed on 4D datasets to automatically derive motion trajectories of selected anatomical landmarks, including the dome and the center of the liver, and the superior edges of kidneys and spleen. The extents of the motion in three dimensions (anteroposterior, AP; mediolateral, ML; superoinferior, SI) and the correlations between organ motion trajectories were quantified.

Results:

The 4D MRI scans were successfully performed in <20 minutes for all patients without the use of any external device. Organ motion extents were larger in adolescents (kidneys: 3–13 mm SI, liver and spleen: 6–18 mm SI) than in younger children (kidneys:<3mm in all directions; liver and spleen: 1–8 mm SI, 1–5 mm ML and AP). The magnitude of respiratory motion in some adolescents may warrant special motion management. Motion trajectories were not synchronized across selected anatomical landmarks, particularly in the ML and AP directions, indicating inter‐ and intra‐organ variations of the respiratory‐induced motion.

Conclusion:

The developed 4D MRI acquisition and motion analysis methods provide a non‐ionizing, non‐invasive approach to automatically measure the organ motion trajectory in the pediatric abdomen. It is useful for defining ITV and PRV, monitoring changes in target motion patterns during the treatment course, and studying interplay effects in proton scanning.
SU‐D‐206‐01: Employing a Novel Consensus Optimization Strategy to Achieve Iterative Cone Beam CT Reconstruction On a Multi‐GPU Platform
Authors: Li B , Tian Z , Zhou L , Jiang S , Jia X
Published: July 2016

Purpose:

While compressed sensing‐based cone‐beam CT (CBCT) iterative reconstruction techniques have demonstrated tremendous capability of reconstructing high‐quality images from undersampled noisy data, its long computation time still hinders wide application in routine clinic. The purpose of this study is to develop a reconstruction framework that employs modern consensus optimization techniques to achieve CBCT reconstruction on a multi‐GPU platform for improved computational efficiency.

Methods:

Total projection data were evenly distributed to multiple GPUs. Each GPU performed reconstruction using its own projection data with a conventional total variation regularization approach to ensure image quality. In addition, the solutions from GPUs were subject to a consistency constraint that they should be identical. We solved the optimization problem with all the constraints considered rigorously using an alternating direction method of multipliers (ADMM) algorithm. The reconstruction framework was implemented using OpenCL on a platform with two Nvidia GTX590 GPU cards, each with two GPUs. We studied the performance of our method and demonstrated its advantages through a simulation case with a NCAT phantom and an experimental case with a Catphan phantom.

Result:

Compared with the CBCT images reconstructed using conventional FDK method with full projection datasets, our proposed method achieved comparable image quality with about one third projection numbers. The computation time on the multi‐GPU platform was ∼55 s and ∼ 35 s in the two cases respectively, achieving a speedup factor of ∼ 3.0 compared with single GPU reconstruction.

Conclusion:

We have developed a consensus ADMM‐based CBCT reconstruction method which enabled performing reconstruction on a multi‐GPU platform. The achieved efficiency made this method clinically attractive.
SU‐D‐206‐02: Evaluation of Partial Storage of the System Matrix for Cone Beam Computed Tomography Using a GPU Platform
Authors: Matenine D , Cote G , Mascolo‐Fortin J , Goussard Y , Despres P
Published: July 2016

Purpose:

Iterative reconstruction algorithms in computed tomography (CT) require a fast method for computing the intersections between the photons’ trajectories and the object, also called ray‐tracing or system matrix computation. This work evaluates different ways to store the system matrix, aiming to reconstruct dense image grids in reasonable time.

Methods:

We propose an optimized implementation of the Siddon's algorithm using graphics processing units (GPUs) with a novel data storage scheme. The algorithm computes a part of the system matrix on demand, typically, for one projection angle. The proposed method was enhanced with accelerating options: storage of larger subsets of the system matrix, systematic reuse of data via geometric symmetries, an arithmetic‐rich parallel code and code configuration via machine learning. It was tested on geometries mimicking a cone beam CT acquisition of a human head. To realistically assess the execution time, the ray‐tracing routines were integrated into a regularized Poisson‐based reconstruction algorithm. The proposed scheme was also compared to a different approach, where the system matrix is fully pre‐computed and loaded at reconstruction time.

Results:

Fast ray‐tracing of realistic acquisition geometries, which often lack spatial symmetry properties, was enabled via the proposed method. Ray‐tracing interleaved with projection and backprojection operations required significant additional time. In most cases, ray‐tracing was shown to use about 66 % of the total reconstruction time. In absolute terms, tracing times varied from 3.6 s to 7.5 min, depending on the problem size. The presence of geometrical symmetries allowed for non‐negligible ray‐tracing and reconstruction time reduction. Arithmetic‐rich parallel code and machine learning permitted a modest reconstruction time reduction, in the order of 1 %.

Conclusion:

Partial system matrix storage permitted the reconstruction of higher 3D image grid sizes and larger projection datasets at the cost of additional time, when compared to the fully pre‐computed approach.

This work was supported in part by the Fonds de recherche du Quebec ‐ Nature et technologies (FRQ‐NT). The authors acknowledge partial support by the CREATE Medical Physics Research Training Network grant of the Natural Sciences and Engineering Research Council of Canada (Grant No. 432290).
SU‐D‐206‐04: Iterative CBCT Scatter Shading Correction Without Prior Information
Authors: Bai Y , Wu P , Mao T , Gong S , Wang J , Sheng K , Xie Y , Niu T
Published: July 2016

Purpose:

To estimate and remove the scatter contamination in the acquired projection of cone‐beam CT (CBCT), to suppress the shading artifacts and improve the image quality without prior information.

Methods:

The uncorrected CBCT images containing shading artifacts are reconstructed by applying the standard FDK algorithm on CBCT raw projections. The uncorrected image is then segmented to generate an initial template image. To estimate scatter signal, the differences are calculated by subtracting the simulated projections of the template image from the raw projections. Since scatter signals are dominantly continuous and low‐frequency in the projection domain, they are estimated by low‐pass filtering the difference signals and subtracted from the raw CBCT projections to achieve the scatter correction. Finally, the corrected CBCT image is reconstructed from the corrected projection data. Since an accurate template image is not readily segmented from the uncorrected CBCT image, the proposed scheme is iterated until the produced template is not altered.

Results:

The proposed scheme is evaluated on the Catphan©600 phantom data and CBCT images acquired from a pelvis patient. The result shows that shading artifacts have been effectively suppressed by the proposed method. Using multi‐detector CT (MDCT) images as reference, quantitative analysis is operated to measure the quality of corrected images. Compared to images without correction, the method proposed reduces the overall CT number error from over 200 HU to be less than 50 HU and can increase the spatial uniformity.

Conclusion:

An iterative strategy without relying on the prior information is proposed in this work to remove the shading artifacts due to scatter contamination in the projection domain. The method is evaluated in phantom and patient studies and the result shows that the image quality is remarkably improved. The proposed method is efficient and practical to address the poor image quality issue of CBCT images.

This work is supported by the Zhejiang Provincial Natural Science Foundation of China (Grant No. LR16F010001), National High‐tech R&D Program for Young Scientists by the Ministry of Science and Technology of China (Grant No. 2015AA020917).
SU‐D‐206‐05: A Critical Look at CBCT‐Based Dose Calculation Accuracy as It Is Applied to Adaptive Radiotherapy
Authors: Bejarano Buele A , Sperling N , Parsai E
Published: July 2016

Purpose:

Cone‐beam CTs (CBCT) obtained from On‐Board Imaging Devices (OBI) are increasingly being used for dose calculation purposes in adaptive radiotherapy. Patient and target morphology are monitored and the treatment plan is updated using CBCT. Due to the difference in image acquisition parameters, dose calculated in a CBCT can differ from planned dose. We evaluate the difference between dose calculation in kV CBCT and simulation CT, and the effect of HU‐density tables in dose discrepancies

Methods:

HU values for various materials were obtained using a Catphan 504 phantom for a simulator CT (CTSIM) and two different OBI systems using three imaging protocols: Head, Thorax and Pelvis. HU‐density tables were created in the TPS for each OBI image protocol. Treatment plans were made on each Catphan 504 dataset and on the head, thorax and pelvis sections of an anthropomorphic phantom, with and without the respective HU‐density table. DVH information was compared among OBI systems and planning CT.

Results:

Dose calculations carried on the Catphan 504 CBCTs, with and without the respective CT‐density table, had a maximum difference of −0.65% from the values on the planning CT. The use of the respective HU‐density table decreased the percent differences from planned values by half in most of the protocols. For the anthropomorphic phantom datasets, the use of the correct HU‐density table reduced differences by 0.89% on OBI1 and 0.59% on OBI2 for the head, 0.49% on OBI1 for the thorax, and 0.25% on OBI2 for the pelvis. Differences from planned values without HU‐density correction ranged from 3.13% (OBI1, thorax) to 0.30% (OBI2, thorax).

Conclusion:

CT‐density tables in the TPS yield acceptable differences when used in partly homogeneous medium. Further corrections are needed when the medium contains pronounced density differences for accurate CBCT calculation. Current difference range (1–3%) can be clinically acceptable.
SU‐D‐206‐06: Task‐Specific Optimization of Scintillator Thickness for CMOS‐Detector Based Cone‐Beam Breast CT
Authors: Vedantham S , Shrestha S , Shi L , Vijayaraghavan G , Karellas A
Published: July 2016

Purpose:

To optimize the cesium iodide (CsI:Tl) scintillator thickness in a complimentary metal‐oxide semiconductor (CMOS)‐based detector for use in dedicated cone‐beam breast CT.

Methods:

The imaging task considered was the detection of a microcalcification cluster comprising six 220µm diameter calcium carbonate spheres, arranged in the form of a regular pentagon with 2 mm spacing on its sides and a central calcification, similar to that in ACR‐recommended mammography accreditation phantom, at a mean glandular dose of 4.5 mGy. Generalized parallel‐cascades based linear systems analysis was used to determine Fourier‐domain image quality metrics in reconstructed object space, from which the detectability index inclusive of anatomical noise was determined for a non‐prewhitening numerical observer. For 300 projections over 2π, magnification‐associated focal‐spot blur, Monte Carlo derived x‐ray scatter, K‐fluorescent emission and reabsorption within CsI:Tl, CsI:Tl quantum efficiency and optical blur, fiberoptic plate transmission efficiency and blur, CMOS quantum efficiency, pixel aperture function and additive noise, and filtered back‐projection to isotropic 105µm voxel pitch with bilinear interpolation were modeled. Imaging geometry of a clinical prototype breast CT system, a 60 kV Cu/Al filtered x‐ray spectrum from 0.3 mm focal spot incident on a 14 cm diameter semi‐ellipsoidal breast were used to determine the detectability index for 300–600 µm thick (75µm increments) CsI:Tl. The CsI:Tl thickness that maximized the detectability index was considered optimal.

Results:

The limiting resolution (10% modulation transfer function, MTF) progressively decreased with increasing CsI:Tl thickness. The zero‐frequency detective quantum efficiency, DQE(0), in projection space increased with increasing CsI:Tl thickness. The maximum detectability index was achieved with 525µm thick CsI:Tl scintillator. Reduced MTF at mid‐to‐high frequencies for 600µm thick CsI:Tl lowered the detectability index than 525µm CsI:Tl.

Conclusion:

For the x‐ray spectrum and imaging conditions considered, a 525µm thick CsI:Tl scintillator integrated with the CMOS detector is optimal for detecting microcalcification cluster.

Funding support: Supported in part by NIH R01 CA195512. The contents are solely the responsibility of the authors and do not reflect the official views of the NIH or the NCI. Disclosures: SV, GV and AK ‐ Research collaboration, Koning Corp., West Henrietta, NY.
SU‐D‐209‐02: Percent Depth Dose Curves for Fluoroscopic X‐Ray Beam Qualities Incorporating Copper Filtration
Authors: Wunderle K , Godley A , Shen Z , Rakowski J , Dong F
Published: July 2016

Purpose:

The purpose of this investigation was to quantify percent depth dose (PDD) curves for fluoroscopic x‐ray beam qualities incorporating added copper filtration.

Methods:

A PTW (Freiburg, Germany) MP3 water tank was used with a Standard Imaging (Middleton, WI) Exradin Model 11 Spokas Chamber to measure PDD curves for 60, 80, 100 and 120 kVp x‐ray beams with copper filtration ranging from 0.0–0.9 mm at 22cm and 42cm fields of view from 0 to 150 mm of water. A free‐in‐air monitor chamber was used to normalize the water tank data to fluctuations in output from the fluoroscope. The measurements were acquired on a Siemens (Erlangen, Germany) Artis ZeeGo fluoroscope. The fluoroscope was inverted from the typical orientation providing an x‐ray beam originating from above the water tank. The water tank was positioned so that the water level was located at 60cm from the focal spot; which also represents the focal spot to interventional reference plane distance for that fluoroscope.

Results:

PDDs for 60, 80, 100, and 120 kVp with 0 mm of copper filtration compared well to previously published data by Fetterly et al. [Med Phys, 28, 205 (2001)] for those beam qualities given differences in fluoroscopes, geometric orientation, type of ionization chamber, and the water tank used for data collection. PDDs for 60, 80, 100, and 120 kVp with copper filtration were obtained and are presented, which have not been previously investigated and published.

Conclusion:

The equipment and processes used to acquire the reported data were sound and compared well with previously published data for PDDs without copper filtration. PDD data for the fluoroscopic x‐ray beams incorporating copper filtration can be used as reference data for estimating organ or soft tissue dose at depth involving similar beam qualities or for comparison with mathematical models.
SU‐D‐209‐03: Radiation Dose Reduction Using Real‐Time Image Processing in Interventional Radiology
Authors: Kanal K , Moirano J , Zamora D , Stewart B
Published: July 2016

Purpose:

To characterize changes in radiation dose after introducing a new real‐time image processing technology in interventional radiology systems.

Methods:

Interventional radiology (IR) procedures are increasingly complex, at times requiring substantial time and radiation dose. The risk of inducing tissue reactions as well as long‐term stochastic effects such as radiation‐induced cancer is not trivial. To reduce this risk, IR systems are increasingly equipped with dose reduction technologies.Recently, ClarityIQ (Philips Healthcare) technology was installed in our existing neuroradiology IR (NIR) and vascular IR (VIR) suites respectively. ClarityIQ includes real‐time image processing that reduces noise/artifacts, enhances images, and sharpens edges while also reducing radiation dose rates. We reviewed 412 NIR (175 pre‐ and 237 post‐ClarityIQ) procedures and 329 VIR (156 preand 173 post‐ClarityIQ) procedures performed at our institution pre‐ and post‐ClarityIQ implementation. NIR procedures were primarily classified as interventional or diagnostic. VIR procedures included drain port, drain placement, tube change, mesenteric, and implanted venous procedures. Air Kerma (AK in units of mGy) was documented for all the cases using a commercial radiation exposure management system.

Results:

When considering all NIR procedures, median AK decreased from 1194 mGy to 561 mGy. When considering all VIR procedures, median AK decreased from 49 to 14 mGy. Both NIR and VIR exhibited a decrease in AK exceeding 50% after ClarityIQ implementation, a statistically significant (p<0.05) difference. Of the 5 most common VIR procedures, all median AK values decreased, but significance (p<0.05) was only reached in venous access (N=53), angio mesenteric (N=41), and drain placement procedures (N=31).

Conclusion:

ClarityIQ can reduce dose significantly for both NIR and VIR procedures. Image quality was not assessed in conjunction with the dose reduction.
SU‐D‐207B‐05: Robust Intra‐Tumor Partitioning to Identify High‐Risk Subregions for Prognosis in Lung Cancer
Authors: Wu J , Gensheimer M , Dong X , Rubin D , Napel S , Diehn M , Loo B , Li R
Published: July 2016

Purpose:

To develop an intra‐tumor partitioning framework for identifying high‐risk subregions from 18F‐fluorodeoxyglucose positron emission tomography (FDG‐PET) and CT imaging, and to test whether tumor burden associated with the high‐risk subregions is prognostic of outcomes in lung cancer.

Methods:

In this institutional review board‐approved retrospective study, we analyzed the pre‐treatment FDG‐PET and CT scans of 44 lung cancer patients treated with radiotherapy. A novel, intra‐tumor partitioning method was developed based on a two‐stage clustering process: first at patient‐level, each tumor was over‐segmented into many superpixels by k‐means clustering of integrated PET and CT images; next, tumor subregions were identified by merging previously defined superpixels via population‐level hierarchical clustering. The volume associated with each of the subregions was evaluated using Kaplan‐Meier analysis regarding its prognostic capability in predicting overall survival (OS) and out‐of‐field progression (OFP).

Results:

Three spatially distinct subregions were identified within each tumor, which were highly robust to uncertainty in PET/CT co‐registration. Among these, the volume of the most metabolically active and metabolically heterogeneous solid component of the tumor was predictive of OS and OFP on the entire cohort, with a concordance index or CI = 0.66–0.67. When restricting the analysis to patients with stage III disease (n = 32), the same subregion achieved an even higher CI = 0.75 (HR = 3.93, logrank p = 0.002) for predicting OS, and a CI = 0.76 (HR = 4.84, logrank p = 0.002) for predicting OFP. In comparison, conventional imaging markers including tumor volume, SUVmax and MTV50 were not predictive of OS or OFP, with CI mostly below 0.60 (p < 0.001).

Conclusion:

We propose a robust intra‐tumor partitioning method to identify clinically relevant, high‐risk subregions in lung cancer. We envision that this approach will be applicable to identifying useful imaging biomarkers in many cancer types.
SU‐F‐SPS‐02: Accuracy of the Small Field Dosimetry Using the Monte Carlo and Sequential Dose Calculation Algorithms of Multiplan Treatment Planning System Within and Beyond Heterogeneous Media for Cyberknife M6 Unit
Authors: Serin E. , Codel G. , Mabhouti H. , Cebe M. , Sanli E. , Pacaci P. , Kucuk N. , Kucukmorkoc E. , Doyuran M. , Canoglu D. , Altinok A. , Acar H. , Caglar Ozkok H.
Published: July 2016

Purpose:

In small field geometries, the electronic equilibrium can be lost, making it challenging for the dose‐calculation algorithm to accurately predict the dose, especially in the presence of tissue heterogeneities. In this study, dosimetric accuracy of Monte Carlo (MC) advanced dose calculation and sequential algorithms of Multiplan treatment planning system were investigated for small radiation fields incident on homogeneous and heterogeneous geometries.

Methods:

Small open fields of fixed cones of Cyberknife M6 unit 100 to 500 mm2 were used for this study. The fields were incident on in house phantom containing lung, air, and bone inhomogeneities and also homogeneous phantom. Using the same film batch, the net OD to dose calibration curve was obtained using CK with the 60 mm fixed cone by delivering 0‐ 800 cGy. Films were scanned 48 hours after irradiation using an Epson 1000XL flatbed scanner. The dosimetric accuracy of MC and sequential algorithms in the presence of the inhomogeneities was compared against EBT3 film dosimetry

Results:

Open field tests in a homogeneous phantom showed good agreement between two algorithms and film measurement For MC algorithm, the minimum gamma analysis passing rates between measured and calculated dose distributions were 99.7% and 98.3% for homogeneous and inhomogeneous fields in the case of lung and bone respectively. For sequential algorithm, the minimum gamma analysis passing rates were 98.9% and 92.5% for for homogeneous and inhomogeneous fields respectively for used all cone sizes. In the case of the air heterogeneity, the differences were larger for both calculation algorithms. Overall, when compared to measurement, the MC had better agreement than sequential algorithm.

Conclusion:

The Monte Carlo calculation algorithm in the Multiplan treatment planning system is an improvement over the existing sequential algorithm. Dose discrepancies were observed for in the presence of air inhomogeneities.
SU‐F‐SPS‐04: Dosimetric Evaluation of the Dose Calculation Accuracy of Different Algorithms for Two Different Treatment Techniques During Whole Breast Irradiation
Authors: Pacaci P , Cebe M , Mabhouti H , Codel G , Serin E , Sanli E , Kucukmorkoc E , Doyuran M , Kucuk N , Canoglu D , Altinok A , Acar H , Caglar Ozkok H
Published: July 2016

Purpose:

In this study, dosimetric comparison of field in field (FIF) and intensity modulated radiation therapy (IMRT) techniques used for treatment of whole breast radiotherapy (WBRT) were made. The dosimetric accuracy of treatment planning system (TPS) for Anisotropic Analytical Algorithm (AAA) and Acuros XB (AXB) algorithms in predicting PTV and OAR doses was also investigated.

Methods:

Two different treatment planning techniques of left‐sided breast cancer were generated for rando phantom. FIF and IMRT plans were compared for doses in PTV and OAR volumes including ipsilateral lung, heart, left ascending coronary artery, contralateral lung and the contralateral breast. PTV and OARs doses and homogeneity and conformality indexes were compared between two techniques. The accuracy of TPS dose calculation algorithms was tested by comparing PTV and OAR doses measured by thermoluminescent dosimetry with the dose calculated by the TPS using AAA and AXB for both techniques.

Results:

IMRT plans had better conformality and homogeneity indexes than FIF technique and it spared OARs better than FIF. While both algorithms overestimated PTV doses they underestimated all OAR doses. For IMRT plan, PTV doses, overestimation up to 2.5 % was seen with AAA algorithm but it decreased to 1.8 % when AXB algorithm was used. Based on the results of the anthropomorphic measurements for OAR doses, underestimation greater than 7 % is possible by the AAA. The results from the AXB are much better than the AAA algorithm. However, underestimations of 4.8 % were found in some of the points even for AXB. For FIF plan, similar trend was seen for PTV and OARs doses in both algorithm.

Conclusion:

When using the Eclipse TPS for breast cancer, AXB the should be used instead of the AAA algorithm, bearing in mind that the AXB may still underestimate all OAR doses.
SU‐F‐SPS‐06: Implementation of a Back‐Projection Algorithm for 2D in Vivo Dosimetry with An EPID System
Authors: Hernandez Reyes B , Rodriguez Perez E , Sosa Aquino M
Published: July 2016

Purpose:

To implement a back‐projection algorithm for 2D dose reconstructions for in vivo dosimetry in radiation therapy using an Electronic Portal Imaging Device (EPID) based on amorphous silicon.

Methods:

An EPID system was used to calculate dose‐response function, pixel sensitivity map, exponential scatter kernels and beam hardenig correction for the back‐projection algorithm. All measurements were done with a 6 MV beam. A 2D dose reconstruction for an irradiated water phantom (30×30×30 cm3) was done to verify the algorithm implementation. Gamma index evaluation between the 2D reconstructed dose and the calculated with a treatment planning system (TPS) was done.

Results:

A linear fit was found for the dose‐response function. The pixel sensitivity map has a radial symmetry and was calculated with a profile of the pixel sensitivity variation. The parameters for the scatter kernels were determined only for a 6 MV beam. The primary dose was estimated applying the scatter kernel within EPID and scatter kernel within the patient. The beam hardening coefficient is σBH= 3.788×10−4 cm2 and the effective linear attenuation coefficient is µAC= 0.06084 cm−1. The 95% of points evaluated had γ values not longer than the unity, with gamma criteria of ΔD = 3% and Δd = 3 mm, and within the 50% isodose surface.

Conclusion:

The use of EPID systems proved to be a fast tool for in vivo dosimetry, but the implementation is more complex that the elaborated for pre‐treatment dose verification, therefore, a simplest method must be investigated. The accuracy of this method should be improved modifying the algorithm in order to compare lower isodose curves.
SU‐F‐SPS‐07: Magnetic Resonance Spectroscopy Findings in Early‐Phase Psychosis
Authors: Wright A. , Ma R. , Hummer T. , Francis M. , Mehdiyoun N. , Dydak U. , Breier A.
Published: July 2016

Purpose:

Schizophrenia is a psychiatric disorder characterized by disordered thoughts, abnormal social behaviors, flat affect, and auditory or visual hallucinations. The current study aims to investigate alterations in brain metabolism in patients near the onset of psychosis (early‐phase psychosis, EPP), to characterize abnormalities during the early stages of schizophrenia. To this end, we used magnetic resonance imaging (MRI) and spectroscopy (MRS) to measure metabolite levels and subsequently monitor the effect of treatment with N‐acetylcysteine (NAC).

Methods:

Here we report on the cross‐sectional comparison at the baseline scan between 13 healthy controls (mean age = 21.5 yrs) and 28 EPP patients (mean age = 23.9 yrs), within three years of psychotic illness onset. Metabolite levels of glutamine + glutamate (Glx), N‐acetylaspartate (NAA), creatine (Cre), and myo‐inositol (mI) were measured on a Siemens 3T whole‐body scanner with MRS voxels placed in the frontal lobe (size = 2×2×2 cm3; TE = 30ms; TA = 4min). Metabolite levels were quantified using LCModel V6.2‐0R, scaled to the internal water signal, and reported in institutional units (i.u.). Comparison of NAA, Cre and Glx levels between the two groups was performed using two‐tailed unpaired t‐tests.

Results:

A significant decrease of Glx concentration in FEP patients was found (patients: 4.1±1.4 i.u.; controls: 5.2 ± 0.2 i.u.; p=0.04). No significant differences were found at baseline in Cre nor NAA concentrations.

Conclusion:

Significant decreases in Glx were observed in the frontal lobe of the FEP patients. This decrease supports prior research on schizophrenia in similar cortical regions. The alteration in frontal Glx levels may be involved in the behavioral and cognitive abnormalities. Future steps include investigating the effect of NAC vs. placebo treatment on reversing this decrease in Glx in EPP patients over a 12‐month period.

This project is supported by the Stanley Medical Research Institute.
SU‐F‐SPS‐08: Measuring the Interaction Of DDR Cell Receptors and Extracellular Matrix Collagen in Prostate Cells
Authors: Dong J , Sarkar A , Suhail A , Fridman R , Hoffmann P
Published: July 2016

Purpose:

Discoidin domain receptors (DDR) have recently been recognized as important players in cancer progression. DDRs are cell receptors that interact with collagen, an extracellular matrix (ECM) protein. However the detailed mechanism of their interaction is unclear. Here we attempted to examine their interaction in terms of structural (surface topography), mechanical (rupture force), and kinetic (binding probability) information on the single molecular scale with the use of atomic force microscopy (AFM).

Methods:

The Quantitative Nano‐mechanical property Mapping (QNM) mode of AFM allowed to assess the cells in liquid growth media at their optimal physiological while being viable. Human benign prostate hyperplasia (BPH‐1) cell line was genetically regulated to suppress DDR expression (DDR‐ cells) and was compared with naturally DDR expressing cells (DDR+).

Results:

Binding force measurements (n = 1000) were obtained before and after the two groups were treated with fibronectin (FN), an integrin‐inhibiting antibody to block the binding of integrin. The quantification indicates that cells containing DDR bind with collagen at a most probable force of 80.3–83.0 ±7.6 pN. The probability of them binding is 0.167 when other interactions (mainly due to integrin‐collagen binding) are minimized.

Conclusion:

Together with further force measurements at different pulling speeds will determine dissociation rate, binding distance and activation barrier. These parameters in benign cells provides some groundwork in understanding DDR's behavior in various cell microenvironments such as in malignant tumor cells.

Funding supported by Richard Barber Interdisciplinary Research Program of Wayne State University
SU‐F‐SPS‐09: Parallel MC Kernel Calculations for VMAT Plan Improvement
Authors: Chamberlain S , French S , Nazareth D
Published: July 2016

Purpose:

Adding kernels (small perturbations in leaf positions) to the existing apertures of VMAT control points may improve plan quality. We investigate the calculation of kernel doses using a parallelized Monte Carlo (MC) method.

Methods:

A clinical prostate VMAT DICOM plan was exported from Eclipse. An arbitrary control point and leaf were chosen, and a modified MLC file was created, corresponding to the leaf position offset by 0.5cm. The additional dose produced by this 0.5 cm × 0.5 cm kernel was calculated using the DOSXYZnrc component module of BEAMnrc. A range of particle history counts were run (varying from 3 × 106 to 3 × 107); each job was split among 1, 10, or 100 parallel processes. A particle count of 3 × 106 was established as the lower range because it provided the minimal accuracy level.

Results:

As expected, an increase in particle counts linearly increases run time. For the lowest particle count, the time varied from 30 hours for the single‐processor run, to 0.30 hours for the 100‐processor run.

Conclusion:

Parallel processing of MC calculations in the EGS framework significantly decreases time necessary for each kernel dose calculation. Particle counts lower than 1 × 106 have too large of an error to output accurate dose for a Monte Carlo kernel calculation. Future work will investigate increasing the number of parallel processes and optimizing run times for multiple kernel calculations.