bluuebunny/crossref_metadata_2025_split huggingface dataset:
SU‐E‐QI‐13: Predictable Models for Radio‐Sensitizing Agent Kinetics: Application to Stereotactic Synchrotron Radiation Therapy
Authors: Obeid L , Schmitt M , Esteve F , Adam J 
Published: July 2014

Purpose:Iodine‐enhanced radiotherapy is an innovative treatment combining the selective accumulation of an iodinated contrast agent in brain tumors with irradiations using monochromatic medium energy x‐rays. The radiation dose enhancement depends on the time course of iodine in the tumors. A prolonged CT scanning (∼30 min) is required to follow‐up iodine kinetics for recruited patients. This protocol could lead to substantial radiation dose to the patient. A novel method is proposed to reduce the acquisition time.Methods:12 patients received an intravenous bolus of iodinated contrast agent, followed by a steady‐state infusion to ensure stable intra‐tumoral amounts of iodine during the treatment. Absolute iodine concentrations (IC) were derived from 40 multi‐slice dynamic conventional CT images of the brain. The impulse response function (IRF) to the bolus was estimated using the adiabatic approximation of the Johnson and Wilson's model. The arterial input function (AIF) of the steady‐state infusion was fitted with several models: Gamma, Gamma with recirculation and hybrid. Estimated IC were calculated by convolving the IRF with the modeled AIF and were compared to the measured data.Results:The gamma variate function was not relevant to model the AIF due to high differences with the measured AIF. The hybrid and the gamma with recirculation models provided differences below 8% during the whole acquisition time. The absolute difference between the measured and the estimated IC was lower than 0.5 mg/ml, which corresponds to 5% of dose enhancement error.Conclusion:The proposed method allows a good estimation of the iodine time course with reduced scanning delays (3 instead of 30 min) and dose to the patient. The results suggest that the dose errors may stay within the radiotherapy standards.
SU‐E‐QI‐14: Quantitative Variogram Detection of Mild, Unilateral Disease in Elastase‐Treated Rats
Authors: Jacob R , Carson J 
Published: July 2014

Purpose:Determining the presence of mild or early disease in the lungs can be challenging and subjective. We present a rapid and objective method for evaluating lung damage in a rat model of unilateral mild emphysema based on a new approach to heterogeneity assessment. We combined octree decomposition (used in three‐dimensional (3D) computer graphics) with variograms (used in geostatistics to assess spatial relationships) to evaluate 3D computed tomography (CT) lung images for disease.Methods:Male, Sprague‐Dawley rats (232 ± 7 g) were intratracheally dosed with 50 U/kg of elastase dissolved in 200 μL of saline to a single lobe (n=6) or with saline only (n=5). After four weeks, 3D micro‐CT images were acquired at end expiration on mechanically ventilated rats using prospective gating. Images were masked, and lungs were decomposed to homogeneous blocks of 2×2×2, 4×4×4, and 8×8×8 voxels using octree decomposition. The spatial variance – the square of the difference of signal intensity – between all pairs of the 8×8×8 blocks was calculated. Variograms – graphs of distance vs. variance – were made, and data were fit to a power law and the exponent determined. The mean HU values, coefficient of variation (CoV), and the emphysema index (EI) were calculated and compared to the variograms.Results:The variogram analysis showed that significant differences between groups existed (p<0.01), whereas the mean HU (p=0.07), CoV (p=0.24), and EI (p=0.08) did not. Calculation time for the variogram for a typical 1000 block decomposition was ∼6 seconds, and octree decomposition took ∼2 minutes. Decomposing the images prior to variogram calculation resulted in a ∼700x decrease in time as compared to other published approaches.Conclusions:Our results suggest that the approach combining octree decomposition and variogram analysis may be a rapid, non‐subjective, and sensitive imaging‐based biomarker for quantitative characterization of lung disease.
SU‐E‐QI‐15: Single Point Dosimetry by Means of Cerenkov Radiation Energy Transfer (CRET)
Authors: Volotskova O , Jenkins C , Xing L 
Published: July 2014

Purpose:Cerenkov light is generated when a charged particles with energy greater then 250 keV, moves faster than the speed of light in a given medium. Both x‐ray photons and electrons produce optical Cerenkov photons during the static megavoltage linear accelerator (LINAC) operational mode. Recently, Cerenkov radiation gained considerable interest as possible candidate as a new imaging modality. Optical signals generated by Cerenkov radiation may act as a surrogate for the absorbed superficial radiation dose. We demonstrated a novel single point dosimetry method for megavoltage photon and electron therapy utilizing down conversion of Cerenkov photons.Methods:The custom build signal characterization system was used: a sample holder (probe) with adjacent light tight compartments was connected via fiber‐optic cables to a photon counting photomultiplier tube (PMT). One compartment contains a medium only while the other contains medium and red‐shifting nano‐particles (Q‐dots, nanoclusters). By taking the difference between the two signals (Cerenkov photons and CRET photons) we obtain a measure of the down‐converted light, which we expect to be proportional to dose as measured with an adjacent ion chamber. Experimental results are compared to Monte Carlo simulations performed using the GEANT4 code.Results:The signal correlation between CR signal, CRET readings and dose produced by LINAC at a single point were investigated. The experimental results were compared with simulations. The dose linearity, signal to noise ratio and dose rate dependence were tested with custom build CRET based probe.Conclusion:Performance characteristics of the proposed single point CRET based probe were evaluated. The direct use of the induced Cerenkov emission and CRET in an irradiated single point volume as an indirect surrogate for the imparted dose was investigated. We conclude that CRET is a promising optical based dosimetry method that offers advantages over those already proposed.
SU‐E‐QI‐16: Reproducibility of Computed Tomography Quantitative Structural Features Using the FDA Thoracic Phantom Image Database
Authors: Budzevich M , Grove O , Balagurunathan Y , Gu Y , Wang H , Oliver J , Latifi K , Zhang G , Dilling T , Gillies R , Moros E , Lee H. 
Published: July 2014

Purpose:To assess the reproducibility of quantitative structural features using images from the computed tomography thoracic FDA phantom database under different scanning conditions.Methods:Development of quantitative image features to describe lesion shape and size, beyond conventional RECIST measures, is an evolving area of research in need of benchmarking standards. Gavrielides et al. (2010) scanned a FDA‐developed thoracic phantom with nodules of various Hounsfield units (HU) values, shapes and sizes close to vascular structures using several scanners and varying scanning conditions/parameters; these images are in the public domain. We tested six structural features, namely, Convexity, Perimeter, Major Axis, Minor Axis, Extent Mean and Eccentricity, to characterize lung nodules. Convexity measures lesion irregularity referenced to a convex surface. Previously, we showed it to have prognostic value in lung adenocarcinoma. The above metrics and RECIST measures were evaluated on three spiculated (8mm/‐300HU, 12mm/+30HU and 15mm/+30HU) and two non‐spiculated (8mm/+100HU and 10mm/+100HU) nodules (from layout 2) imaged at three different mAs values: 25, 100 and 200 mAs; on a Phillips scanner (16‐slice Mx8000‐IDT; 3mm slice thickness). The nodules were segmented semi‐automatically using a commercial software tool; the same HU range was used for all nodules.Results:Analysis showed convexity having the lowest maximum coefficient of variation (MCV): 1.1% and 0.6% for spiculated and non‐spiculated nodules, respectively, much lower compared to RECIST Major and Minor axes whose MCV were 10.1% and 13.4% for spiculated, and 1.9% and 2.3% for non‐spiculated nodules, respectively, across the various mAs. MCVs were consistently larger for speculated nodules. In general, the dependence of structural features on mAs (noise) was low.Conclusion:The FDA phantom CT database may be used for benchmarking of structural features for various scanners and scanning conditions; we used only a small fraction of available data. Our feature convexity outperformed other structural features including RECIST measures.
SU‐E‐QI‐17: Dependence of 3D/4D PET Quantitative Image Features On Noise
Authors: Oliver J , Budzevich M , Zhang G , Latifi K , Dilling T , Balagurunathan Y , Gu Y , Grove O , Feygelman V , Gillies R , Moros E , Lee H. 
Published: July 2014

Purpose:Quantitative imaging is a fast evolving discipline where a large number of features are extracted from images; i.e., radiomics. Some features have been shown to have diagnostic, prognostic and predictive value. However, they are sensitive to acquisition and processing factors; e.g., noise. In this study noise was added to positron emission tomography (PET) images to determine how features were affected by noise.Methods:Three levels of Gaussian noise were added to 8 lung cancer patients PET images acquired in 3D mode (static) and using respiratory tracking (4D); for the latter images from one of 10 phases were used. A total of 62 features: 14 shape, 19 intensity (1stO), 18 GLCM textures (2ndO; from grey level co‐occurrence matrices) and 11 RLM textures (2ndO; from run‐length matrices) features were extracted from segmented tumors. Dimensions of GLCM were 256×256, calculated using 3D images with a step size of 1 voxel in 13 directions. Grey levels were binned into 256 levels for RLM and features were calculated in all 13 directions.Results:Feature variation generally increased with noise. Shape features were the most stable while RLM were the most unstable. Intensity and GLCM features performed well; the latter being more robust. The most stable 1stO features were compactness, maximum and minimum length, standard deviation, root‐mean‐squared, I30, V10‐V90, and entropy. The most stable 2ndO features were entropy, sum‐average, sum‐entropy, difference‐average, difference‐variance, difference‐entropy, information‐correlation‐2, short‐run‐emphasis, long‐run‐emphasis, and run‐percentage. In general, features computed from images from one of the phases of 4D scans were more stable than from 3D scans.Conclusion:This study shows the need to characterize image features carefully before they are used in research and medical applications. It also shows that the performance of features, and thereby feature selection, may be assessed in part by noise analysis.
SU‐E‐QI‐18: QUATTRO: An Open‐Source Software Package for Quantitative Imaging Applications in Assessing Treatment Response
Authors: Bosca R , Johnson V , Jackson E 
Published: July 2014

Purpose:Quantitative imaging biomarkers are becoming increasingly utilized in early phase clinical trials as a means non‐invasively monitoring treatment response. However, such techniques require extensive data pipelines (e.g., image quantitation, image registration, ROI definition, statistical analyses) to capture and model longitudinal parameter changes. The aim of this study was to develop a comprehensive open‐source research software environment supporting such analyses with an emphasis on longitudinally assessing treatment response.Methods:Using the MATLAB programming environment, an intuitive graphical user interface (GUI) and associated advanced programming interface (API) were developed, providing an imaging study environment collectively titled Quantitative Utility for Assessing TreaTment RespOnse or QUATTRO. Standard tools were incorporated for importing/exporting common data formats such as DICOM 3.0 and associated RT contours, Pinnacle contours, and for performing ROI and voxel‐based modeling for a number of common quantitative MR imaging strategies (dynamic contrast‐enhanced, diffusion weighted, and dynamic susceptibility contrast, in addition to T1/T2 relaxometry). Advanced features for preforming longitudinal analyses were also developed, including image registration (provided by directly linked Insight Toolkit executables), ordinal and logistic regression analyses (utilizing a link with R), and a scripting framework.Results:QUATTRO has been successfully implemented and employed in a number of longitudinal phantom studies and quantitative imaging applications. Moreover, the software has facilitated the development and associated feasibility studies of a voxel‐by‐voxel statistical response model capable of generating probabilistic response maps by incorporating multiparametric quantitative imaging data.Conclusion:An open‐source software package, QUATTRO, has been developed for applications in assessing treatment response incorporating quantitative imaging. An intuitive GUI provides a front‐end tool for utilizing built‐in QUATTRO capabilities, while the API facilitates rapid prototyping of future applications, e.g., novel multimodality analyses, and links to the highly developed libraries of ITK and R enable development of advanced image processing and statistical tools, respectively.
SU‐E‐QI‐19: Evaluation of a Clinical 1.5T MRI for Prostate Cancer MRS Imaging Using a In Vivo Tumor Model
Authors: Chen X , Chen L , Hensley H , Cvetkovic D , Zhang C , Fan J , Ma C 
Published: July 2014

Purpose:Magnetic resonance spectroscopic (MRS) imaging may provide important bio‐markers to distinguish normal/cancerous prostate tissue. While MRS imaging requires a high uniform magnetic field, the ability of a clinical 1.5T MRI to achieve a comparable MRS signal is of interest for radiation treatment planning/assessment. This study is to evaluate the MRS imaging of a 1.5T clinical MRI for prostate cancers by comparing with a small animal 7T MRS scanner.Methods:A tumor model was developed by implanting LNCaP tumor cells in nude mice prostates. Tumor was monitored 3 weeks after implantation using MRI, and MRS imaging was performed on the tumor area when the tumor reached around 1cm in diameter. The 1.5T GE clinical MR scanner and the 7T Bruker small animal MR scanner were used for each mouse. MR spectrums acquired with these scanners were analyzed and compared. The signals of Choline and Citrate were considered.Results:The prostate tumor MR spectrum under the 1.5T clinical MRI showed a similar spectrum pattern to that acquired using the 7T animal MRI. The Choline signal (3.2ppm) is clear and there is no clear peak for Citrate (2.6ppm). However, the signal magnitude for Choline is not dominant compared to the background signal under 1.5T MRI. Typical cancerous prostate tissue MR spectrum with an increased Choline signal and a reduced Citrate signal was observed. In addition, signal variation is noticeable between repeated spectrum scans. The average of these scans showed a comparable and consistent spectrum to those under 7T MRI.Conclusion:The clinical 1.5T MRI is able to acquire a MR spectrum for prostate cancer comparable to those acquired using a dedicated 7T MRS scanner. However, to achieve a consistent and reliable spectrum, multiple repeated scans were necessary to get a statistical result and reduce the noise‐induced artifact.This work was supported in part by the National Cancer Institute Grant R21 CA131979 and R01CA172638.
SU‐E‐QI‐20: A Review of Advanced PET and CT Image Features for the Evaluation of Tumor Response
Authors: Lu W 
Published: July 2014

Purpose:To review the literature in using quantitative PET and CT image features for the evaluation of tumor response.Methods:We reviewed and summarized more than fifty papers that use advanced, quantitative PET/CT image features for the evaluation of tumor response. We also discussed future works on extracting disease‐specific features, combining multiple and complementary features in response modeling, delineating tumor in multimodality images, and exploring biological explanations of these advanced features.Results:Advanced PET image features considering spatial information, such as tumor volume, tumor shape, total glycolytic volume, histogram distance, and texture features (characterizing spatial distribution of FDG uptake) have been found more informative than the traditional SUVmax for the prediction of tumor response. Advanced CT features, including volumetric, attenuation, morphologic, structure, and texture descriptors, have also been found advantage over the traditional RECIST and WHO criteria in certain tumor types.Conclusions:Advanced, quantitative FDG PET/CT image features have been shown promising for the evaluation of tumor response. With the emerging multi‐modality imaging performed at multiple time points for each patient, it becomes more important to analyze the serial images quantitatively, select and combine both complementary and contradictory information from various sources, for accurate and personalized evaluation of tumor response to therapy.
SU‐E‐QI‐21: Iodinated Contrast Agent Time Course In Human Brain Metastasis: A Study For Stereotactic Synchrotron Radiotherapy Clinical Trials
Authors: Obeid L , Tessier A , Balosso J , Esteve F , Adam J 
Published: July 2014

Purpose:Synchrotron stereotactic radiotherapy (SSRT) is an innovative treatment combining the selective accumulation of heavy elements in tumors with stereotactic irradiations using monochromatic medium energy x‐rays from a synchrotron source. Phase I/II clinical trials on brain metastasis are underway using venous infusion of iodinated contrast agents. The radiation dose enhancement depends on the amount of iodine in the tumor and its time course. In the present study, the reproducibility of iodine concentrations between the CT planning scan day (Day 0) and the treatment day (Day 10) was assessed in order to predict dose errors.Methods:For each of days 0 and 10, three patients received a biphasic intravenous injection of iodinated contrast agent (40 ml, 4 ml/s, followed by 160 ml, 0.5 ml/s) in order to ensure stable intra‐tumoral amounts of iodine during the treatment. Two volumetric CT scans (before and after iodine injection) and a multi‐slice dynamic CT of the brain were performed using conventional radiotherapy CT (Day 0) or quantitative synchrotron radiation CT (Day 10). A 3D rigid registration was processed between images. The absolute and relative differences of absolute iodine concentrations and their corresponding dose errors were evaluated in the GTV and PTV used for treatment planning.Results:The differences in iodine concentrations remained within the standard deviation limits. The 3D absolute differences followed a normal distribution centered at zero mg/ml with a variance (∼1 mg/ml) which is related to the image noise.Conclusion:The results suggest that dose errors depend only on the image noise. This study shows that stable amounts of iodine are achievable in brain metastasis for SSRT treatment in a 10 days interval.
SU‐E‐CAMPUS‐T‐01: Automation of the Winston‐Lutz Test for Stereotactic Radiosurgery
Authors: Litzenberg D , Irrer J , Keranen W , Kessler M , Lam K 
Published: July 2014

Purpose:To optimize clinical efficiency and shorten patient wait time by minimizing the time and effort required to perform the Winston‐Lutz test before stereotactic radiosurgery (SRS) through automation of the delivery, analysis, and documentation of results.Methods:The radiation fields of the Winston‐Lutz (WL) test were created in a “machine‐QA patient” saved in ARIA for use before SRS cases. Images of the BRW target ball placed at mechanical isocenter are captured with the portal imager for each of four, 2cm×2cm, MLC‐shaped beams. When the WL plan is delivered and closed, this event is detected by in‐house software called EventNet which automates subsequent processes with the aid of the ARIA web services. Images are automatically retrieved from the ARIA database and analyzed to determine the offset of the target ball from radiation isocenter. The results are posted to a website and a composite summary image of the results is pushed back into ImageBrowser for review and authenticated documentation.Results:The total time to perform the test was reduced from 20‐25 minutes to less than 4 minutes. The results were found to be more accurate and consistent than the previous method which used radiochromic film. The images were also analyzed with DoseLab for comparison. The difference between the film and automated WL results in the X and Y direction and the radius were (−0.17 +/− 0.28) mm, (0.21 +/− 0.20) mm and (−0.14 +/− 0.27) mm, respectively. The difference between the DoseLab and automated WL results were (−0.05 +/− 0.06) mm, (−0.01 +/− 0.02) mm and (0.01 +/− 0.07) mm, respectively.Conclusions:This process reduced patient wait times by 15–20 minutes making the treatment machine available to treat another patient. Accuracy and consistency of results were improved over the previous method and were comparable to other commercial solutions. Access to the ARIA web services is made possible through an Eclipse co‐development agreement with Varian Medical Systems.
SU‐E‐CAMPUS‐T‐02: Exploring Radiation Acoustics CT Dosimeter Design Aspects for Proton Therapy
Authors: Alsanea F , Moskvin V , Stantz K 
Published: July 2014

Purpose:Investigate the design aspects and imaging dose capabilities of the Radiation Acoustics Computed Tomography (RA CT) dosimeter for Proton induced acoustics, with the objective to characterize a pulsed pencil proton beam. The focus includes scanner geometry, transducer array, and transducer bandwidth on image quality.Methods:The geometry of the dosimeter is a cylindrical water phantom (length 40cm, radius 15cm) with 71 ultrasound transducers placed along the length and end of the cylinder to achieve a weighted set of projections with spherical sampling. A 3D filtered backprojection algorithm was used to reconstruct the dosimetric images and compared to MC dose distribution. First, 3D Monte Carlo (MC) Dose distributions for proton beam energies (range of 12cm, 16cm, 20cm, and 27cm) were used to simulate the acoustic pressure signal within this scanner for a pulsed proton beam of 1.8×107 protons, with a pulse width of 1 microsecond and a rise time of 0.1 microseconds. Dose comparison within the Bragg peak and distal edge were compared to MC analysis, where the integrated Gaussian was used to locate the 50% dose of the distal edge. To evaluate spatial fidelity, a set of point sources within the scanner field of view (15×15×15cm3) were simulated implementing a low‐pass bandwidth response function (0 to 1MHz) equivalent to a multiple frequency transducer array, and the FWHM of the point‐spread‐function determined.Results:From the reconstructed images, RACT and MC range values are within 0.5mm, and the average variation of the dose within the Bragg peak are within 2%. The spatial resolution tracked with transducer bandwidth and projection angle sampling, and can be kept at 1.5mm.Conclusion:This design is ready for fabrication to start acquiring measurements. The 15 cm FOV is an optimum size for imaging dosimetry. Currently, simulations comparing transducer sensitivity, bandwidth, and proton beam parameters are being evaluated to assess signal‐to‐noise.