bluuebunny/crossref_metadata_2025_split huggingface dataset:
WE‐H‐BRA‐07: Mechanistic Modelling of the Relative Biological Effectiveness of Heavy Charged Particles
Authors: McMahon S , McNamara A , Schuemann J , Prise K , Paganetti H 
Published: July 2016

Purpose Uncertainty in the Relative Biological Effectiveness (RBE) of heavy charged particles compared to photons remains one of the major uncertainties in particle therapy. As RBEs depend strongly on clinical variables such as tissue type, dose, and radiation quality, more accurate individualised models are needed to fully optimise treatments. MethodsWe have developed a model of DNA damage and repair following X‐ray irradiation in a number of settings, incorporating mechanistic descriptions of DNA repair pathways, geometric effects on DNA repair, cell cycle effects and cell death. Our model has previously been shown to accurately predict a range of biological endpoints including chromosome aberrations, mutations, and cell death. This model was combined with nanodosimetric models of individual ion tracks to calculate the additional probability of lethal damage forming within a single track. These lethal damage probabilities can be used to predict survival and RBE for cells irradiated with ions of different Linear Energy Transfer (LET). ResultsBy combining the X‐ray response model with nanodosimetry information, predictions of RBE can be made without cell‐line specific fitting. The model's RBE predictions were found to agree well with empirical proton RBE models (Mean absolute difference between models of 1.9% and 1.8% for cells with α/β ratios of 9 and 1.4, respectively, for LETs between 0 and 15 keV/µm). The model also accurately recovers the impact of high‐LET carbon ion exposures, showing both the reduced efficacy of ions at extremely high LET, as well as the impact of defects in non‐homologous end joining on RBE values in Chinese Hamster Ovary cells.ConclusionOur model is predicts RBE without the inclusion of empirical LET fitting parameters for a range of experimental conditions. This approach has the potential to deliver improved personalisation of particle therapy, with future developments allowing for the calculation of individualised RBEs.SJM is supported by a Marie Curie International Outgoing Fellowship from the European Commission's FP7 program (EC FP7 MC‐IOF‐623630)
WE‐H‐BRA‐09: Application of a Modified Microdosimetric‐Kinetic Model to Analyze Relative Biological Effectiveness of Ions Relevant to Light Ion Therapy Using the Particle Heavy Ion Transport System
Authors: Butkus M , Palmer T 
Published: July 2016

Purpose:To evaluate the dose and biological effectiveness of various ions that could potentially be used for actively scanned particle therapy.Methods:The PHITS Monte Carlo code paired with a microscopic analytical function was used to determine probability distribution functions of the lineal energy in 0.3µm diameter spheres throughout a water phantom. Twenty million primary particles for 1H beams and ten million particles for 4He, 7Li, 10B, 12C, 14N, 16O, and 20Ne were simulated for 0.6cm diameter pencil beams. Beam energies corresponding to Bragg peak depths of 50, 100, 150, 200, 250, and 300mm were used and evaluated transversely every millimeter and radially in annuli with outer radius of 1.0, 2.0, 3.0, 3.2, 3.4, 3.6, 4.0, 5.0, 10.0, 15.0, 20.0 and 25.0mm. The acquired probability distributions were reduced to dose‐mean lineal energies and applied to the modified microdosimetric kinetic model for five different cell types to calculate relative biological effectiveness (RBE) compared to 60Co beams at the 10% survival threshold. The product of the calculated RBEs and the simulated physical dose was taken to create biological dose and comparisons were then made between the various ions.Results:Transversely, the 10B beam was seen to minimize relative biological dose in both the constant and accelerated dose change regions, proximal to the Bragg Peak, for all beams traveling greater than 50mm. For the 50mm beam, 7Li was seen to provide the most optimal biological dose profile. Radially small fluctuations (<4.2%) were seen in RBE while physical dose was greater than 1% for all beams.Conclusion:Even with the growing usage of 12C, it may not be the most optimal ion in all clinical situations. Boron was calculated to have slightly enhanced RBE characteristics, leading to lower relative biological doses.
WE‐H‐202‐02: Biomechanical Modeling of Anatomical Response Over the Course of Therapy
Authors: Brock K. 
Published: July 2016

Deformable image registration has now been commercially available for several years, with solid performance in a number of sites and for several applications including contour and dose mapping. However, more complex applications have arisen, such as assessing response to radiation therapy over time, registering images pre‐ and post‐surgery, and auto‐segmentation from atlases. These applications require innovative registration algorithms to achieve accurate alignment. The goal of this session is to highlight emerging registration technology and these new applications. The state of the art in image registration will be presented from an engineering perspective. Translational clinical applications will also be discussed to tie these new registration approaches together with imaging and radiation therapy applications in specific diseases such as cervical and lung cancers.

Learning Objectives:
To understand developing techniques and algorithms in deformable image registration that are likely to translate into clinical tools in the near future.
To understand emerging imaging and radiation therapy clinical applications that require such new registration algorithms.Research supported in part by the National Institutes of Health under award numbers P01CA059827, R01CA166119, and R01CA166703. Disclosures: Phillips Medical systems (Hugo), Roger Koch (Christensen) support, Varian Medical Systems (Brock), licensing agreements from Raysearch (Brock) and Varian (Hugo).; K. Brock, Licensing Agreement ‐ RaySearch Laboratories. Research Funding ‐ Varian Medical Systems; G. Hugo, Research grant from National Institutes of Health, award number R01CA166119.; G. Christensen, Research support from NIH grants CA166119 and CA166703 and a gift from Roger Koch. There are no conflicts of interest.
WE‐H‐207A‐01: Computational Evaluation of High‐Resolution 18F Positron Imaging Using Radioluminescence Microscopy with Lu2O3: Eu Thin‐Film Scintillator
Authors: Wang Q , Sengupta D , Pratx G 
Published: July 2016

Purpose:Radioluminescence microscopy, an emerging and powerful tool for high resolution beta imaging, has been applied to molecular imaging of cellular metabolism to understand tumor biology. A novel thin‐film (10 µm thickness) scintillator made of Lu2O3: Eu has been developed to enhance the system performance. However the advances of radioluminescence imaging with Lu2O3scintillator compared with that using conventional scintillator have not been explored theoretically to date. To validate the advantages of the thin‐film scintillator, this study uses a novel computational simulation framework to evaluate the performance of radioluminescence microscopy using both conventional and thin‐film scintillators.Methods:Numerical models for different stages of positron imaging are established. Positron from 18F passing through the scintillator and its neighbor structures are modeled by Monte‐Carlo simulation using Geant4. The propagation and focus of photons by the microscope are modeled by convolution with a depth‐varying point spread function generated by the Gibson‐Lanni model. Photons focused on the detector plane are then captured and converted into electronic signals by an electron multiplication (EM) CCD camera, which is described by a photosensor model considering various noises and charge amplification.Results:The performance metrics of radioluminescence imaging with a thin‐film Lu2O3 and conventional CdWO4 scintillator are compared, including spatial resolution, sensitivity, positron track area and intensity. The spatial resolution of Lu2O3 system can achieve 10 µm maximally, a 12 µm enhancement from that obtained from CdWO4 system. Meanwhile, the system with Lu2O3 scintillator can provide a higher mean sensitivity: 40% compared with that (21.5%) obtained from CdWO4 system. Moreover, the simulation results are in good agreement with previous experimental measurements.Conclusion:This study provides a new theoretical understanding of our imaging system and has the potential to promote the development of radioluminescence microscopy for more reliable and robust application on the functional imaging of delicate biological structures.The authors acknowledge funding from NIH grant R01CA186275 and SBIR grant 1R43GM110888‐01.
WE‐H‐207A‐03: The Universality of the Lognormal Behavior of [F‐18]FLT PET SUV Measurements
Authors: Scarpelli M , Eickhoff J , Perlman S , Jeraj R 
Published: July 2016

Purpose:Log transforming [F‐18]FDG PET standardized uptake values (SUVs) has been shown to lead to normal SUV distributions, which allows utilization of powerful parametric statistical models. This study identified the optimal transformation leading to normally distributed [F‐18]FLT PET SUVs from solid tumors and offers an example of how normal distributions permits analysis of non‐independent/correlated measurements.Methods:Forty patients with various metastatic diseases underwent up to six FLT PET/CT scans during treatment. Tumors were identified by nuclear medicine physician and manually segmented. Average uptake was extracted for each patient giving a global SUVmean (gSUVmean) for each scan. The Shapiro‐Wilk test was used to test distribution normality. One parameter Box‐Cox transformations were applied to each of the six gSUVmean distributions and the optimal transformation was found by selecting the parameter that maximized the Shapiro‐Wilk test statistic. The relationship between gSUVmean and a serum biomarker (VEGF) collected at imaging timepoints was determined using a linear mixed effects model (LMEM), which accounted for correlated/non‐independent measurements from the same individual.Results:Untransformed gSUVmean distributions were found to be significantly non‐normal (p<0.05). The optimal transformation parameter had a value of 0.3 (95%CI: −0.4 to 1.6). Given the optimal parameter was close to zero (which corresponds to log transformation), the data were subsequently log transformed. All log transformed gSUVmean distributions were normally distributed (p>0.10 for all timepoints). Log transformed data were incorporated into the LMEM. VEGF serum levels significantly correlated with gSUVmean (p<0.001), revealing log‐linear relationship between SUVs and underlying biology.Conclusion:Failure to account for correlated/non‐independent measurements can lead to invalid conclusions and motivated transformation to normally distributed SUVs. The log transformation was found to be close to optimal and sufficient for obtaining normally distributed FLT PET SUVs. These transformations allow utilization of powerful LMEMs when analyzing quantitative imaging metrics.
WE‐H‐207A‐04: Impact of Lesion Location On the Repeatability of 18F‐NaF PET/CT
Authors: Lin C , Perk T , Harmon S , Perlman S , Liu G , Jeraj R 
Published: July 2016

Purpose:Quantifying the repeatability of imaging biomarkers is critical for assessing therapeutic response. While 18F‐NaF PET/CT has shown to be a repeatable imaging method, research has not shown which factors may influence its repeatability. The purpose of this study was to evaluate whether the location of the lesion impacts the repeatability of quantitative 18F‐NaF PET‐derived SUV metrics.Methods:Metastatic castrate‐resistant prostate cancer patients with multiple bone lesions received whole‐body test‐retest NaF PET/CT scans. Malignant bone lesions of PET‐defined volume greater than 1.5 cm3 were identified by a nuclear medicine physician and automatically delineated using a SUV>15 threshold. The maximum (SUVmax), average (SUVmean), and total (SUVtotal) SUV were extracted from each lesion. Atlas‐based segmentation was used to divide each patient skeleton into 25 skeletal regions. Test‐retest repeatability of each SUV metric was assessed with coefficient of variation (CV).Results:A total of 265 malignant bone lesions from 18 patients were identified by nuclear medicine physician. The largest proportion of bone lesions were localized to the spine (41%), with 41% of those lesions localized to the thoracic spine. One‐way ANOVA showed that measurement differences differed significantly for all three metrics across locations (p<0.01 for each metrics). Overall, CV was smallest for SUVmean at 5.3%, followed by SUVmax at 11.5% and SUVtotal at 20.4%. Lesions in the pubis were consistently the most repeatable (CV(SUVmax)= 5.6%, CV(SUVmean)= 0.6%, CV(SUVtotal)= 2.9%). According to SUVmean, repeatability was poorest in the cervical spine (CV = 6.2%), whereas according to SUVmax and SUVtotal, repeatability was poorest in the ribs (CV(SUVmax)= 15.0%, CV(SUVtotal)= 29.8%).Conclusion:Location of the lesion affects the repeatability of 18F‐NaF PET/CT, with the ribs and cervical spine having the lowest repeatability and the pubis having the highest repeatability. These results can be used to establish location‐specific response criteria for NaF PET‐based treatment response assessment.
WE‐H‐207A‐05: Spatial Co‐Localization of F‐18 NaF Vs. F‐18 FDG Defined Disease Volumes
Authors: Ferjancic P , Harmon S , Chen S , Simoncic U , Jeraj R 
Published: July 2016

Purpose:Both [F‐18]NaF and [F‐18]FDG show promise for quantitative PET/CT assessment in metastatic prostate cancer to bone. Broad agreement between the tracers has been shown but voxel‐wise correspondence has not been explored in depth. This study evaluates the spatial co‐localization of [F‐18]NaF PET and [F‐18]FDG PET in bone lesions.Methods:Seventy‐three lesion contours were identified in six patients receiving dynamic NaF PET/CT and FDG PET/CT scans two hours apart using identical fields‐of‐view. Tracer uptake (SUV) reflecting 60 minutes post‐injection was modeled from kinetic parameters. Lesions were segmented by a physician separately on NaF PET and FDG PET. PET images were rigidly aligned using skeletal references on CT images. Lesion size, degree of overlap, voxel‐wise tracer uptake values (SUV), and CT density distributions were compared using Dice coefficient, Positive Predictive Value (PPV), and Spearman rank correlation tests.Results:Across all patients, 42 lesions were identified on NaF PET (median 1.4 cm3, range <1–204 cm3) compared to 31 using FDG PET (median 1.8 cm3, range <1–244 cm3). Spatial cooccurrence was found in 25 lesion pairs. Lesions on NaF PET had PPV of 0.91 and on FDG a PPV of 0.65. Overall, NaF‐defined lesions were 47% (±24%) larger by volume with moderate overlap to FDG, resulting in mean Dice coefficient of 34% (±22%). In areas of overlap, voxel‐wise correlation of NaF and FDG SUV was moderate (ρ=0.56). Expanding to regions of non‐spatial overlap, voxels contained in FDG‐only contours were almost exclusively low HU (median 118), compared to dense regions of NaF‐only voxels (median 250). In sclerotic sub‐volumes (HU > 300) NaF‐defined contours encompassed 83% of total FDG volume.Conclusion:Moderate voxel‐wise correlation of FDG and NaF PET/CT uptake was observed. Spatial discrepancies in FDG and NaF PET/CT imaging of boney metastases could be influenced by poor sensitivity of FDG PET/CT in sclerotic regions.Funded by Prostate Cancer Foundation
WE‐H‐207A‐06: Hypoxia Quantification in Static PET Images: The Signal in the Noise
Authors: Keller H , Kueng R , Shek T , Driscoll B , Yeung I , Milosevic M , Jaffray D 
Published: July 2016

Purpose:Quantification of hypoxia from PET images is of considerable clinical interest. In the absence of dynamic PET imaging the hypoxic fraction (HF) of a tumor has to be estimated from voxel values of activity concentration of a radioactive hypoxia tracer. This work is part of an effort to standardize quantification of tumor hypoxic fraction from PET images.Methods:A simple hypoxia imaging model in the tumor was developed. The distribution of the tracer activity was described as the sum of two different probability distributions, one for the normoxic (and necrotic), the other for the hypoxic voxels. The widths of the distributions arise due to variability of the transport, tumor tissue inhomogeneity, tracer binding kinetics, and due to PET image noise. Quantification of HF was performed for various levels of variability using two different methodologies: a) classification thresholds between normoxic and hypoxic voxels based on a non‐hypoxic surrogate (muscle), and b) estimation of the (posterior) probability distributions based on maximizing likelihood optimization that does not require a surrogate. Data from the hypoxia imaging model and from 27 cervical cancer patients enrolled in a FAZA PET study were analyzed.Results:In the model, where the true value of HF is known, thresholds usually underestimate the value for large variability. For the patients, a significant uncertainty of the HF values (an average intra‐patient range of 17%) was caused by spatial non‐uniformity of image noise which is a hallmark of all PET images. Maximum likelihood estimation (MLE) is able to directly optimize for the weights of both distributions, however, may suffer from poor optimization convergence. For some patients, MLE‐based HF values showed significant differences to threshold‐based HF‐values.Conclusion:HF‐values depend critically on the magnitude of the different sources of tracer uptake variability. A measure of confidence should also be reported.
WE‐H‐207A‐07: Image‐Based Versus Atlas‐Based Internal Dosimetry
Authors: Fallahpoor M , Abbasi M , Parach A , Kalantari F 
Published: July 2016

Purpose:Monte Carlo (MC) simulation is known as the gold standard method for internal dosimetry. It requires radionuclide distribution from PET or SPECT and body structure from CT for accurate dose calculation. The manual or semi‐automatic segmentation of organs from CT images is a major obstacle. The aim of this study is to compare the dosimetry results based on patient's own CT and a digital humanoid phantom as an atlas with pre‐specified organs.Methods:SPECT‐CT images of a 50 year old woman who underwent bone pain palliation with Samarium‐153 EDTMP for osseous metastases from breast cancer were used. The anatomical date and attenuation map were extracted from SPECT/CT and three XCAT digital phantoms with different BMIs (i.e. matched (38.8) and unmatched (35.5 and 36.7) with patient's BMI that was 38.3). Segmentation of patient's organs in CT image was performed using itk‐SNAP software. GATE MC Simulator was used for dose calculation. Specific absorbed fractions (SAFs) and S‐values were calculated for the segmented organs.Results:The differences between SAFs and S‐values are high using different anatomical data and range from −13% to 39% for SAF values and −109% to 79% for S‐values in different organs. In the spine, the clinically important target organ for Samarium Therapy, the differences in the S‐values and SAF values are higher between XCAT phantom and CT when the phantom with identical BMI is employed (53.8% relative difference in S‐value and 26.8% difference in SAF). However, the whole body dose values were the same between the calculations based on the CT and XCAT with different BMIs.Conclusion:The results indicated that atlas‐based dosimetry using XCAT phantom even with matched BMI for patient leads to considerable errors as compared to image‐based dosimetry that uses the patient's own CT Patient‐specific dosimetry using CT image is essential for accurate results.
WE‐H‐207A‐08: Characterization of a Broad‐Spectrum Cancer Targeted MRI Contrast Agent
Authors: Brunnquell C , Zhang R , Pinchuk A , Weichert J 
Published: July 2016

Purpose:To characterize the relaxation properties and tumor targeting capabilities of a novel alkylphosphocholine (APC) analog MR contrast agent, Gd‐DO3A‐404.Methods:Relaxivities were measured via T1 and T2 mapping of Gd‐DO3A‐404 with inversion recovery and spin echo pulse sequences, respectively. Uptake was characterized in flank xenograft models of non‐small cell lung cancer (A549) and glioma (U87) and compared with uptake of Dotarem. Mice (N=3 per model per agent) were delivered 2.34 moles contrast intravenously. T1‐weighted MRI and T1 maps were acquired pre‐contrast and at multiple time points up to seven days post‐contrast. For Dotarem imaging, T1‐weighted MRI was performed at multiple time points from one minute to one day.Results:Relaxivities of Gd‐DO3A‐404 in plasma were r1=5.74 and r2=20.4 s‐1/mm at 4.7T, comparing favorably to clinical contrast agent Dotarem (r1=3.3, r2=4.7). Specific, sustained uptake of Gd‐DO3A‐404 was observed in U87 and A549. The ratio of tumor:muscle T1‐weighted signal increased from 1.24 pre‐contrast to 2.12 twenty‐four hours post‐contrast in U87 and from 1.14 to 2.16 (same time points) in A549. Significant signal enhancement was maintained until 7 and 4 days post‐contrast in U87 and A549, respectively. In comparison, uptake and washout of Dotarem in U87 occurred over the course of fifteen minutes. The ratio of tumor:muscle T1‐weighted signal increased only 59% as much as Gd‐DO3A‐404, ranging from 1.15 pre‐contrast to a maximum of 1.67 five minutes post‐contrast. Significant signal enhancement from Dotarem was not sustained beyond one hour post‐contrast.Conclusion:These results indicate that with favorable relaxation characteristics and sustained signal‐enhancing uptake in multiple tumor models, Gd‐DO3A‐404 has great potential as a tumor‐targeting MR contrast agent. As part of a library of APC analogs labeled with PET/optical tracers and therapeutic radionuclides, Gd‐DO3A‐404 further expands theranostic capabilities. Future work will investigate applications in orthotopic glioma imaging, simultaneous PET/MR, and neutron capture therapy.
WE‐H‐207B‐04: Strategies for Adaptive RT
Authors: Green O. 
Published: July 2016

In recent years, steady progress has been made towards the implementation of MRI in external beam radiation therapy for processes ranging from treatment simulation to in‐room guidance. Novel procedures relying mostly on MR data are currently implemented in the clinic. This session will cover topics such as (a) commissioning and quality control of the MR in‐room imagers and simulators specific to RT, (b) treatment planning requirements, constraints and challenges when dealing with various MR data, (c) quantification of organ motion with an emphasis on treatment delivery guidance, and (d) MR‐driven strategies for adaptive RT workflows. The content of the session was chosen to address both educational and practical key aspects of MR guidance.

Learning Objectives:
Good understanding of MR testing recommended for in‐room MR imaging as well as image data validation for RT chain (e.g. image transfer, filtering for consistency, spatial accuracy, manipulation for task specific);
Familiarity with MR‐based planning procedures: motivation, core workflow requirements, current status, challenges;
Overview of the current methods for the quantification of organ motion;
Discussion on approaches for adaptive treatment planning and delivery.T. Stanescu ‐ License agreement with Modus Medical Devices to develop a phantom for the quantification of MR image system‐related distortions.; T. Stanescu, N/A