bluuebunny/crossref_metadata_2025_split huggingface dataset:
MO‐G‐BRF‐07: Anomalously Fast Diffusion of Carbon Nanotubes Carriers in 3D Tissue Model
Authors: Wang Y , Bahng J , Kotov N 
Published: July 2014

Purpose:We aim to investigate and understand diffusion process of carbon nanotubes (CNTs) and other nanoscale particles in tissue and organs.Methods:In this research, we utilized a 3D model tissue of hepatocellular carcinoma (HCC)cultured in inverted colloidal crystal (ICC) scaffolds to compare the diffusivity of CNTs with small molecules such as Rhodamine and FITC in vitro, and further investigated the transportation of CNTs with and without targeting ligand, TGFβ1. The real‐time permeation profiles of CNTs in HCC tissue model with high temporal and spatial resolution was demonstrated by using standard confocal microscopy. Quantitative analysis of the diffusion process in 3D was carried out using luminescence intensity in a series of Z‐stack images obtained for different time points of the diffusion process after initial addition of CNTs or small molecules to the cell culture and the image data was analyzed by software ImageJ and Mathematica.Results:CNTs display diffusion rate in model tissues substantially faster than small molecules of the similar charge such as FITC, and the diffusion rate of CNTs are significantly enhanced with targeting ligand, TGFβ1.Conclusion:In terms of the advantages of in‐vitro model, we were able to have access to measuring the rate of CNT penetration at designed conditions with variable parameters. And the findings by using this model, changed our understanding about advantages of CNTs as nanoscale drug carriers and provides design principles for making new drug carriers for both treatment and diagnostics. Additionally the fast diffusion opens the discussion of the best possible drug carriers to reach deep parts of cancerous tissues, which is often a prerequisite for successful cancer treatment.This work was supported by the Center for Photonic and Multiscale Nanomaterials funded by National Science Foundation Materials Research Science and Engineering Center program DMR 1120923. The work was also partially supported by NSF grant ECS‐0601345; EFRI‐BSBA 0938019; CBET 0933384; CBET 0932823; CBET 1036672, AFOSR MURI 444286‐P061716 and NIH 1R21CA121841‐01A2.
MO‐G‐17A‐02: Computer Simulation Studies for On‐Board Functional and Molecular Imaging of the Prostate Using a Robotic Multi‐Pinhole SPECT System
Authors: Cheng L , Bowsher J , Yan S , Yin F 
Published: July 2014

Purpose:To investigate prostate imaging onboard radiation therapy machines using a novel robotic, 49‐pinhole Single Photon Emission Computed Tomography (SPECT) system.Methods:Computer‐simulation studies were performed for region‐of‐interest (ROI) imaging using a 49‐pinhole SPECT collimator and for broad cross‐section imaging using a parallel‐hole SPECT collimator. A male XCAT phantom was computersimulated in supine position with one 12mm‐diameter tumor added in the prostate. A treatment couch was added to the phantom. Four‐minute detector trajectories for imaging a 7cm‐diameter‐sphere ROI encompassing the tumor were investigated with different parameters, including pinhole focal length, pinhole diameter and trajectory starting angle. Pseudo‐random Poisson noise was included in the simulated projection data, and SPECT images were reconstructed by OSEM with 4 subsets and up to 10 iterations. Images were evaluated by visual inspection, profiles, and Root‐Mean‐ Square‐Error (RMSE).Results:The tumor was well visualized above background by the 49‐pinhole SPECT system with different pinhole parameters while it was not visible with parallel‐hole SPECT imaging. Minimum RMSEs were 0.30 for 49‐pinhole imaging and 0.41 for parallelhole imaging. For parallel‐hole imaging, the detector trajectory from rightto‐ left yielded slightly lower RMSEs than that from posterior to anterior. For 49‐pinhole imaging, near‐minimum RMSEs were maintained over a broader range of OSEM iterations with a 5mm pinhole diameter and 21cm focal length versus a 2mm diameter pinhole and 18cm focal length. The detector with 21cm pinhole focal length had the shortest rotation radius averaged over the trajectory.Conclusion:On‐board functional and molecular prostate imaging may be feasible in 4‐minute scan times by robotic SPECT. A 49‐pinhole SPECT system could improve such imaging as compared to broadcross‐section parallel‐hole collimated SPECT imaging. Multi‐pinhole imaging can be improved by considering pinhole focal length, pinhole diameter, and trajectory starting angle.The project is supported by the NIH grant 5R21‐CA156390.
MO‐G‐17A‐04: Internal Dosimetric Calculations for Pediatric Nuclear Imaging Applications, Using Monte Carlo Simulations and High‐Resolution Pediatric Computational Models
Authors: Papadimitroulas P , Loudos G , Kagadis GC 
Published: July 2014

Purpose:Our purpose is to evaluate the administered absorbed dose in pediatric, nuclear imaging studies. Monte Carlo simulations with the incorporation of pediatric computational models can serve as reference for the accurate determination of absorbed dose. The procedure of the calculated dosimetric factors is described, while a dataset of reference doses is created.Methods:Realistic simulations were executed using the GATE toolkit and a series of pediatric computational models, developed by the “IT' IS Foundation”. The series of the phantoms used in our work includes 6 models in the range of 5–14 years old (3 boys and 3 girls). Pre‐processing techniques were applied to the images, to incorporate the phantoms in GATE simulations. The resolution of the phantoms was set to 2 mm3. The most important organ densities were simulated according to the GATE “Materials Database”. Several used radiopharmaceuticals in SPECT and PET applications are being tested, following the EANM pediatric dosage protocol. The biodistributions of the several isotopes used as activity maps in the simulations, were derived by the literature.Results:Initial results of absorbed dose per organ (mGy) are presented in a 5 years old girl from the whole body exposure to 99mTc – SestaMIBI, 30 minutes after administration. Heart, kidney, liver, ovary, pancreas and brain are the most critical organs, in which the S‐factors are calculated. The statistical uncertainty in the simulation procedure was kept lower than 5%. The Sfactors for each target organ are calculated in Gy/(MBq*sec) with highest dose being absorbed in kidneys and pancreas (9.29*1010 and 0.15*1010 respectively).Conclusion:An approach for the accurate dosimetry on pediatric models is presented, creating a reference dosage dataset for several radionuclides in children computational models with the advantages of MC techniques. Our study is ongoing, extending our investigation to other reference models and evaluating the results with clinical estimated doses.
MO‐G‐17A‐06: Kernel Based Dosimetry for 90Y Microsphere Liver Therapy Using 90Y Bremsstrahlung SPECT/CT
Authors: Mikell J , Siman W , Mahvash A , Mourtada F , Kappadath S 
Published: July 2014

Purpose:90Y microsphere therapy in liver presents a situation where beta transport is dominant and the tissue is relatively homogenous. We compare voxel‐based absorbed doses from a 90Y kernel to Monte Carlo (MC) using quantitative 90Y bremsstrahlung SPECT/CT as source distribution.Methods:Liver, normal liver, and tumors were delineated by an interventional radiologist using contrast‐enhanced CT registered with 90Y SPECT/CT scans for 14 therapies. Right lung was segmented via region growing. The kernel was generated with 1.04 g/cc soft tissue for 4.8 mm voxel matching the SPECT. MC simulation materials included air, lung, soft tissue, and bone with varying densities. We report percent difference between kernel and MC (%Δ(K,MC)) for mean absorbed dose, D70, and V20Gy in total liver, normal liver, tumors, and right lung. We also report %Δ(K,MC) for heterogeneity metrics: coefficient of variation (COV) and D10/D90. The impact of spatial resolution (0, 10, 20 mm FWHM) and lung shunt fraction (LSF) (1,5,10,20%) on the accuracy of MC and kernel doses near the liver‐lung interface was modeled in 1D. We report the distance from the interface where errors become <10% of unblurred MC as d10(side of interface, dose calculation, FWHM blurring, LSF).Results:The %Δ(K,MC) for mean, D70, and V20Gy in tumor and liver was <7% while right lung differences varied from 60–90%. The %Δ(K,MC) for COV was <4.8% for tumor and liver and <54% for the right lung. The %Δ(K,MC) for D10/D90 was <5% for 22/23 tumors. d10(liver,MC,10,1–20) awere <9mm and d10(liver,MC,20,1–20) awere <15mm; both agreed within 3mm to the kernel. d10(lung,MC,10,20), d10(lung,MC,10,1), d10(lung,MC,20,20), and d10(lung,MC,20,1) awere 6, 25, 15, and 34mm, respectively. Kernel calculations on blurred distributions in lung had errors > 10%.Conclusions:Liver and tumor voxel doses with 90Y kernel and MC agree within 7%. Large differences exist between the two methods in right lung.Research reported in this publication was supported by the National Cancer Institute of the National Institutes of Health under Award Number R01CA138986. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
MO‐G‐18C‐05: Real‐Time Prediction in Free‐Breathing Perfusion MRI
Authors: Song H , Liu W , Ruan D , Jung S , Gach M 
Published: July 2014

Purpose:The aim is to minimize frame‐wise difference errors caused by respiratory motion and eliminate the need for breath‐holds in magnetic resonance imaging (MRI) sequences with long acquisitions and repeat times (TRs). The technique is being applied to perfusion MRI using arterial spin labeling (ASL).Methods:Respiratory motion prediction (RMP) using navigator echoes was implemented in ASL. A least‐square method was used to extract the respiratory motion information from the 1D navigator. A generalized artificial neutral network (ANN) with three layers was developed to simultaneously predict 10 time points forward in time and correct for respiratory motion during MRI acquisition. During the training phase, the parameters of the ANN were optimized to minimize the aggregated prediction error based on acquired navigator data. During realtime prediction, the trained ANN was applied to the most recent estimated displacement trajectory to determine in real‐time the amount of spatialResults:The respiratory motion information extracted from the least‐square method can accurately represent the navigator profiles, with a normalized chi‐square value of 0.037±0.015 across the training phase. During the 60‐second training phase, the ANN successfully learned the respiratory motion pattern from the navigator training data. During real‐time prediction, the ANN received displacement estimates and predicted the motion in the continuum of a 1.0 s prediction window. The ANN prediction was able to provide corrections for different respiratory states (i.e., inhalation/exhalation) during real‐time scanning with a mean absolute error of < 1.8 mm.Conclusion:A new technique enabling free‐breathing acquisition during MRI is being developed. A generalized ANN development has demonstrated its efficacy in predicting a continuum of motion profile for volumetric imaging based on navigator inputs. Future work will enhance the robustness of ANN and verify its effectiveness with human subjects.Research supported by National Institutes of Health National Cancer Institute Grant R01 CA159471‐01
TU‐A‐9A‐04: Development of a Thermally Stable Phantom for Photoacoustic and Magnetic Resonance Temperature Imaging
Authors: Dextraze K , MacLellan C , Mitcham T , Melancon M , Bouchard R 
Published: July 2014

Purpose:Photoacoustic‐ultrasonic (PAUS) imaging, which utilizes an ultrasound transducer to provide co‐registered photoacoustic and pulse‐echo ultrasound images, is capable of measuring temperature non‐invasively while simultaneously providing anatomical images. The sub‐millimeter resolution and centimeter‐order penetration depths achievable with PAUS imaging have the potential to deliver active monitoring of both a targeted tumor microenvironment and nearby healthy tissue during thermal ablation. These characteristics make PAUS imaging a promising new technique for guidance and monitoring during photothermal ablations of solid tumors. In order to assess the potential clinical role of PAUS imaging, the technique was validated against the clinically accepted magnetic resonance thermal imaging approach (MRTI).Methods:To facilitate co‐registration between modalities, the phantom had inclusions of gold nanoshells encapsulating super‐paramagnetic iron oxide (SPIO) particles, where gold enhances the PA signal and SPIOs provide negative contrast on MRI. Several phantom designs were assessed for resilience to heating. PA images were acquired on a Vevo LAZR (FUJIFILM VisualSonics Inc., Toronto, Ontario) PAultrasound small‐animal imaging system (21MHz) operating at 710nm. MRTI experiments were performed using a 6‐channel flex coil (GE Healthcare, Waukesha, WI) on a 3T MRI scanner (Discovery MR750, GE Healthcare, Waukesha, WI) using a fast multi gradient echo acquisition (16 echoes, 128×128 acquisition matrix, 25.6×25.6cm field of view, 3mm slice thickness, 60ms TR, 20° flip angle, 2.9ms minimum TE and 1.6ms echo spacing). The accuracy and spatio‐temporal resolution of PA thermography was cross‐validated with both MRTI and a fluoroptic temperature sensor (LumaSense Technologies, Santa Clara, CA) in the custom‐designed phantom.Results:A thermally stable, dual‐modality phantom was created for cross‐validation of photoacoustic thermography and MRTI. Axial and lateral resolutions of PA images were sub‐millimeter with a temporal resolution of 0.2s, which will accommodate precise real‐time guidance and monitoring.Conclusion:These results indicate that a PA thermography technique offers tremendous promise for real‐time thermal monitoring of ablative therapy.Funding support provided by Cancer Prevention Research Institute of Texas and Julia Jones Matthews family. No disclosures or conflicts of interest.
TU‐A‐12A‐12: Improved Airway Measurement Accuracy for Low Dose Quantitative CT (qCT) Using Statistical (ASIR), at Reduced DFOV, and High Resolution Kernels in a Phantom and Swine Model
Authors: Yadava G , Imai Y , Hsieh J 
Published: July 2014

Purpose:Quantitative accuracy of Iodine Hounsfield Unit (HU) in conventional single‐kVp scanning is susceptible to beam‐hardening effect. Dual‐energy CT has unique capabilities of quantification using monochromatic CT images, but this scanning mode requires the availability of the state‐of‐the‐art CT scanner and, therefore, is limited in routine clinical practice. Purpose of this work was to develop a beam‐hardening‐correction (BHC) for single‐kVp CT that can linearize Iodine projections at any nominal energy, apply this approach to study Iodine response with respect to keV, and compare with dual‐energy based monochromatic images obtained from material‐decomposition using 80kVp and 140kVp.Methods:Tissue characterization phantoms (Gammex Inc.), containing solid‐Iodine inserts of different concentrations, were scanned using GE multi‐slice CT scanner at 80, 100, 120, and 140 kVp. A model‐based BHC algorithm was developed where Iodine was estimated using re‐projection of image volume and corrected through an iterative process. In the correction, the re‐projected Iodine was linearized using a polynomial mapping between monochromatic path‐lengths at various nominal energies (40 to 140 keV) and physically modeled polychromatic path‐lengths. The beam‐hardening‐corrected 80kVp and 140kVp images (linearized approximately at effective energy of the beam) were used for dual‐energy material‐decomposition in Water‐Iodine basis‐pair followed by generation of monochromatic images. Characterization of Iodine HU and noise in the images obtained from singlekVp with BHC at various nominal keV, and corresponding dual‐energy monochromatic images, was carried out.Results:Iodine HU vs. keV response from single‐kVp with BHC and dual‐energy monochromatic images were found to be very similar, indicating that single‐kVp data may be used to create material specific monochromatic equivalent using modelbased projection linearization.Conclusion:This approach may enable quantification of Iodine contrast enhancement and potential reduction in injected contrast without using dual‐energy scanning. However, in general, dual‐energy scanning has unique value in material characterization and quantification, and its value cannot be discounted.GE Healthcare Employee
TU‐C‐12A‐06: Computerized Analysis of Diffusion‐Weighted Images in Breast Cancer Diagnosis
Authors: White T , Weiss W , Giger M 
Published: July 2014

Purpose:Diffusion‐weighted imaging (DWI) for breast MRI is a non‐invasive technique which maps the diffusion process of water molecules, with the use of Brownian motion, in biological tissues, yielding apparent diffusion coefficients (ADC). Quantitative image analyses of the resulting images can yield information about the surrounding tissues in vivo. In this study, we investigated computerized image analyses of DWI images, including automated lesion segmentation, calculation of ADC values, and assessment of tumor heterogeneity, on a dataset of malignant and benign breast lesions.Method and Database:The IRB‐approved, retrospectively collected dataset included 46 breast lesions ‐‐ 36 malignant and 10 benign. The DW images had been acquired during clinical breast MRI on a high‐field 1.5 T echo‐planar system using five b values [b = 0, 500, 1000, 1500, and 2000 s/mm2]. Seed‐point‐initiated 3D Gaussian‐based lesion segmentation was conducted to yield the lesion margins, and within the margin and after b‐value fitting, ADC values were calculated. Average ADC values and various measures of heterogeneity were calculated for benign and malignant lesions.Results:Our findings showed that malignant lesions tended, as expected, to have lower ADC values relative to benign lesions with average ADC values for benign and malignant lesions being 1.70 +/− 0.50 × 10(−3) and 1.07 +/− 0.37 × 10(−3), respectively. In addition, malignant lesions showed higher heterogeneity. In the task of distinguishing between benign and malignant lesions, ROC analysis, from histogram analysis, yielded AUC values of 0.86 +/− 0.07 and 0.88 +/− 0.06 for average ADC values and standard deviation of ADC values, respectively.Conclusion:DWI exhibits potential for differentiating between benign and malignant lesions, and inclusion of computerized quantitative image analysis methods allow for more objectives and efficient calculations of the ADC values and their variations, for potential use in decision making.M. L. Giger is a stockholder in R2 Technology/Hologic, is a shareholder/investor in Quantitative Insights, Qview Medical,receives royalties from Hologic, GE Medical Systems, MEDIAN Technologies, Riverain Medical, Mitsubishi and Toshiba.
TU‐C‐12A‐10: BEST IN PHYSICS (IMAGING) – Correlating 4DCT‐Ventilation with Clinical Pulmonary Function Test Data
Authors: Vinogradskiy Y , Castillo R , Castillo E , Guerrero T , Miften M , Kavanagh B , Martel M , Schubert L 
Published: July 2014

Purpose:4DCT‐ventilation is an emerging form of lung function imaging calculated from 4DCT data. Because 4DCTs are acquired as part of routine care, the lung function information comes at no extra monetary or dosimetric cost to the patient. Studies are needed that compare 4DCT‐ventilation with clinical data. Pulmonary function tests (PFT) provide an established method of evaluating lung function. Our study performed a clinical validation by comparing 4DCT‐ventilation with PFT data.Methods:63 patients with pre‐treatment PFTs and 4DCT data were used for the study. Standard PFT metrics used to diagnose tumor‐based obstructive lung disease were recorded for each patient, including forced expiratory volume in 1 second (FEV1), and the ratio between FEV1 and the forced vital capacity (FEV1/FVC). A PFT value of 70% was used to delineate normal versus abnormal lung function for modeling. 4DCT data sets were input into a density‐change based model to compute 4DCT‐ventilation. The 4DCT‐ventilation maps were reduced to single metrics intended to reflect the degree of ventilation obstruction and heterogeneity. The coefficient of variation (CoV) defined as the ratio of standard deviation over mean ventilation and the ventilation‐V20 (volume of lung <20% ventilation) were computed. Ventilation metrics were compared to PFT data using correlation coefficients and logistic regression modeling methods.Results:The 4DCT‐ventilation metrics correlated well with PFT data. Ventilation‐V20 had correlation values of 0.75 and 0.71 with FEV1 and FEV1/FVC respectively. A probit model as a function of the ventilationderived CoV was fit and able to significantly (p<0.01) predict for normal versus abnormal PFT‐based lung function.Conclusions:The current study validates 4DCT‐ventilation with a clinically established end‐point. Our data demonstrate good agreement between PFTs and ventilation data, indicating that 4DCT‐ventilation can reliably demonstrate oncologic‐based obstructive lung disease. We present important results that support integration of 4DCT‐based pre‐treatment lung function assessment into clinical practice.This work was partially supported by the NIH Director's new Innovator award (TG, EC, RC) and NIH research scientist development award (RC)
TU‐F‐16A‐01: Communicating Risk
Authors: McCollough C , Wagner L , Kofler J , Brateman L 
Published: July 2014

The radiobiological risks associated with medical imaging are generally considered to be small, if existent. However, the public view of the risk of medical radiation at diagnostic levels can be substantially different from the clinical reality. Radiation science is not taught to the general public, and so perception of radiation risks can be based on a variety sources, including some that may be misleading, incorrect, or sensationalized. Consequently, patients can have significant concerns about procedures they or their loved ones might have had or that might be needed in their medical care. It is the responsibility of the physicist to be able to communicate risk in a manner that is clear, understandable, and respectful. This session will present a number of real life scenarios of patient or family concern about radiation risks. The panel will, through demonstration or discussion, present various options for handling each situation. The audience will be involved in discussion and critique of the approaches presented.Learning Objectives:

To gain insight to the patients perspective on radiation risk and how to respond professionally to their concerns.
To learn basic principles for effectively communicating with patients about radiation risk.
To gain tools and approaches for addressing a wide range of patient concerns.
TU‐F‐19A‐01: New Member Symposium
Authors: Sherouse G , Miller R 
Published: July 2014

As a new member of the AAPM, it’s easy to feel overwhelmed by the size and complexity of the association and to be unaware of the benefits and opportunities available to members. At this year’s AAPM annual meeting in Austin, we will host a New Member Symposium where you can learn more about the organization, member resources, and opportunities to get involved.Learning Objectives:

Welcome, introduction to, and overview of AAPM organization
Introduction to medical physics profession
Registered attendees will receive a raffle ticket for a drawing at the symposium to win a complimentary registration for the 2015 Annual Meeting in Anaheim!In addition, all new members who register for the Symposium will receive a drink ticket, good for one complimentary soda or beer served during the social following.