bluuebunny/crossref_metadata_2025_split huggingface dataset:
Large breast compressions: Observations and evaluation of simulations
Authors: Tanner Christine , White Mark , Guarino Salvatore , Hall‐Craggs Margaret A. , Douek Michael , Hawkes David J. 
Published: February 2011

Purpose:Several methods have been proposed to simulate large breast compressions such as those occurring during x‐ray mammography. However, the evaluation of these methods against real data is rare. The aim of this study is to learn more about the deformation behavior of breasts and to assess a simulation method.Methods:Magnetic resonance (MR) images of 11 breasts before and after applying a relatively largein vivo compression in the medial direction were acquired. Nonrigid registration was employed to study the deformation behavior. Optimal material properties for finite element modeling were determined and their prediction performance was assessed. The realism of simulated compressions was evaluated by comparing the breast shapes on simulated and real mammograms.Results:Following image registration, 19 breast compressions from 8 women were studied. An anisotropic deformation behavior, with a reduced elongation in the anterior‐posterior direction and an increased stretch in the inferior‐superior direction was observed. Using finite element simulations, the performance of isotropic and transverse isotropic material models to predict the displacement of internal landmarks was compared. Isotropic materials reduced the mean displacement error of the landmarks from 23.3 to 4.7 mm, on average, after optimizing material properties with respect to breast surface alignment and image similarity. Statistically significantly smaller errors were achieved with transverse isotropic materials (4.1 mm,). Homogeneous material models performed substantially worse (transverse isotropic: 5.5 mm; isotropic: 6.7 mm). Of the parameters varied, the amount of anisotropy had the greatest influence on the results. Optimal material properties varied less when grouped by patient rather than by compression magnitude (mean: 0.72 vs 1.44). Employing these optimal materials for simulating mammograms from ten MR breast images of a different cohort resulted in more realistic breast shapes than when using established material models.Conclusions:Breasts in the prone position exhibited an anisotropic compression behavior. Transverse isotropic materials with an increased stiffness in the anterior‐posterior direction improved the prediction of these deformations and produced more realistic mammogram simulations from MR images.
A comparison of four skull models for independent dose calculations for Gamma Knife® PERFEXION™
Authors: Wright G. , Bownes P. , Reiner B. 
Published: February 2011

Purpose:It is recommended to have a method for independently verifying planned doses in stereotactic radiosurgery. The problem is one of how to model the geometry of a skull sampled by a limited number of points and how to subsequently calculate numerous attenuation pathlengths through the modeled skull. While methods of verification have been previously published for model B and C Gamma Knife® units, the aims of the current work were to apply the principles of these previously published techniques for the verification of plans for Gamma Knife® PERFEXION™, to present a new method of verification, and to compare all methods in terms of their agreement with GammaPlan®.Methods:Four algorithms were implemented: the previously published spherical approximation method (SAM) and bubble helmet skull (BHS), plus a modified BHS named interpolated BHS (IBHS) and a newly developed variable radius SAM (VRSAM). Reference point doses calculated by the four algorithms were compared to those reported by GammaPlan® for 54 simple test plans and for 35 targets in 20 recent patient plans.Results:For test plans, the mean (standard deviation) discrepancies against GammaPlan®‐reported doses were 0.3(1.3)%, 0.3(1.3)%, −1.6(3.4)%, and −0.4(1.0)% for SAM, VRSAM, BHS, and IBHS, respectively. For patient plans both the VRSAM and IBHS showed insignificant ( and ) discrepancies against GammaPlan® of 0.38(1.86)% and −0.11(1.86)%, respectively. More significant discrepancies against GammaPlan® of 2.64(2.98)% and −4.43(3.39)% were observed for the SAM and BHS.Conclusions:The SAM can lead to large discrepancies against GammaPlan® when a sphere is a poor approximation of the true skull surface, and in peripheral locations can lead to nonreal solutions to the attenuation pathlength calculations. While the BHS does not suffer the same geometric assumptions of the SAM, it can underestimate dose for peripherally located shots. The IBHS exhibits better agreement with GammaPlan® than does the BHS, but requires two‐dimensional interpolation that was found to be impractical to implement in the Excel‐based software used in the current work. Combining aspects of both the previously published SAM and BHS algorithms, the newly presented VRSAM exhibits comparable results to the IBHS but without the need for interpolation and is therefore considered the preferred technique of the four implemented.
Performance evaluation of real‐time motion tracking using positron emission fiducial markers
Authors: Chamberland Marc , Wassenaar Richard , Spencer Benjamin , Xu Tong 
Published: February 2011

Purpose:Tumor motion due to patient breathing is a factor that limits the accuracy of dose distribution in radiotherapy. One of the methods to improve the accuracy is by applying respiratory gating or tumor tracking. Both techniques require a precise determination of the spatial location of the tumor. We present an experimental evaluation of the performance of PeTrack, a technique that can track internal fiducial markers in real‐time for tumor trackingMethods:PeTrack uses position sensitive detectors to record annihilation coincidence gamma rays from fiducial positron emission markers implanted in or around the tumor. It uses an expectation‐maximization clustering algorithm to track the position of the markers. A normalized least mean square adaptive filter was used to predict the position of the markers 100 and 200 ms in the future. We evaluated the performance of the tracking and of the prediction by using a dynamic anthropomorphic thorax phantom to generate three‐dimensional (3D) motion of three fiducial markers. The algorithm was run with four different data sets. In the first run, the motion of the markers was based on a sinusoidal model of respiratory motion. Three additional runs were done with motion based on patient breathing data.Results:In the case of the sinusoidal model, the average 3D root mean square error for all markers was 0.44 mm. For the three runs based on patient breathing data, the precision of the 3D localization was 0.49 mm. At a latency of 100 ms, the average 3D prediction error was for the sinusoidal model and for the three patient breathing runs. At a latency of 200 ms, the average 3D prediction errors were for the sinusoidal model and for the breathing runs.Conclusions:We conclude that PeTrack can track multiple fiducial markers in real‐time with an accuracy and precision smaller than 2 mm. PeTrack can have a direct application in tumor tracking for radiation therapy.
A multiple points method for 4D CT image sorting
Authors: Gianoli Chiara , Riboldi Marco , Spadea Maria Francesca , Travaini Laura Lavinia , Ferrari Mahila , Mei Riccardo , Orecchia Roberto , Baroni Guido 
Published: February 2011

Purpose:Artifacts affect 4D CT images due to breathing irregularities or incorrect breathing phase identification. The purpose of this study is the reduction of artifacts in sorted 4D CT images. The assumption is that the use of multiple respiratory related signals may reduce uncertainties and increase robustness in breathing phase identification.Methods:Multiple respiratory related signals were provided by infrared 3D localization of a configuration of markers placed on the thoracoabdominal surface. Multidimensional K‐means clustering was used for retrospective 4D CT image sorting, which was based on multiple marker variables, in order to identify clusters representing different breathing phases. The proposed technique was tested on computational simulations, phantom experimental acquisitions, and clinical data coming from two patients. Computational simulations provided a controlled and noise‐free condition for testing the clustering technique on regular and irregular breathing signals, including baseline drift, time variant amplitude, time variant frequency, and end‐expiration plateau. Specific attention was given to cluster initialization. Phantom experiments involved two moving phantoms fitted with multiple markers. Phantoms underwent 4D CT acquisition while performing controlled rigid motion patterns and featuring end‐expiration plateau. Breathing cycle period and plateau duration were controlled by means of weights leaned upon the phantom during repeated 4D CT scans. The implemented sorting technique was applied to clinical 4D CT scans acquired on two patients and results were compared to conventional sorting methods.Results:For computational simulations and phantom studies, the performance of the multidimensional clustering technique was evaluated by measuring the repeatability in identifying the breathing phase among adjacent couch positions and the uniformity in sampling the breathing cycle. When breathing irregularities were present, the clustering technique consistently improved breathing phase identification with respect to conventional sorting methods based on monodimensional signals. In patient studies, a qualitative comparison was performed between corresponding breathing phases of 4D CT images obtained by conventional sorting methods and by the described clustering technique. Artifact reduction was clearly observable on both data set especially in the lower lung region.Conclusions:The implemented multiple point method demonstrated the ability to reduce artifacts in 4D CT imaging. Further optimization and development are needed to make the most of the availability of multiple respiratory related variables and to extend the method to 4D CT‐PET hybrid scan.
CT image artifacts from brachytherapy seed implants: A postprocessing 3D adaptive median filter
Authors: Basran Parminder S. , Robertson Andrew , Wells Derek 
Published: February 2011

Purpose:To design a postprocessing 3D adaptive median filter that minimizes streak artifacts and improves soft‐tissue contrast in postoperative CT images of brachytherapy seed implantations.Methods:The filter works by identifying voxels that are likely streaks and estimating more reflective voxel intensity by using voxel intensities in adjacent CT slices and applying a median filter over voxels not identified as seeds. Median values are computed over a region of interest (ROI) within the CT volume. An acrylic phantom simulating a clinical seed implant arrangement and containing nonradioactive seeds was created. Low contrast subvolumes of tissuelike material were also embedded in the phantom. Pre‐ and postprocessed image quality metrics were compared using the standard deviation of ROIs between the seeds, the CT numbers of low contrast ROIs embedded within the phantom, the signal to noise ratio (SNR), and the contrast to noise ratio (CNR) of the low contrast ROIs. The method was demonstrated with a clinical postimplant CT dataset.Results:After the filter was applied, the standard deviation of CT values in streak artifact regions was significantly reduced from 76.5 to 7.2 HU. Within the observable low contrast plugs, the mean of all ROI standard deviations was significantly reduced from 60.5 to 3.9 HU, SNR significantly increased from 2.3 to 22.4, and CNR significantly increased from 0.2 to 4.1 (all). The mean CT in the low contrast plugs remained within 5 HU of the original values.Conclusion:An efficient postprocessing filter that does not require access to projection data, which can be applied irrespective of CT scan parameters has been developed, provided the slice thickness and spacing is 3 mm or less.
A planning quality evaluation tool for prostate adaptive IMRT based on machine learning
Authors: Zhu Xiaofeng , Ge Yaorong , Li Taoran , Thongphiew Danthai , Yin Fang‐Fang , Wu Q Jackie 
Published: February 2011

Purpose:To ensure plan quality for adaptive IMRT of the prostate, we developed a quantitative evaluation tool using a machine learning approach. This tool generates dose volume histograms (DVHs) of organs‐at‐risk (OARs) based on prior plans as a reference, to be compared with the adaptive plan derived from fluence map deformation.Methods:Under the same configuration using seven‐field 15 MV photon beams, DVHs of OARs (bladder and rectum) were estimated based on anatomical information of the patient and a model learned from a database of high quality prior plans. In this study, the anatomical information was characterized by the organ volumes and distance‐to‐target histogram (DTH). The database consists of 198 high quality prostate plans and was validated with 14 cases outside the training pool. Principal component analysis (PCA) was applied to DVHs and DTHs to quantify their salient features. Then, support vector regression (SVR) was implemented to establish the correlation between the features of the DVH and the anatomical information.Results:DVH/DTH curves could be characterized sufficiently just using only two or three truncated principal components, thus, patient anatomical information was quantified with reduced numbers of variables. The evaluation of the model using the test data set demonstrated its accuracy in prediction and effectiveness in improving ART planning quality.Conclusions:An adaptive IMRT plan quality evaluation tool based on machine learning has been developed, which estimates OAR sparing and provides reference in evaluating ART.
The impact of anthropometric patient‐phantom matching on organ dose: A hybrid phantom study for fluoroscopy guided interventions
Authors: Johnson Perry B. , Geyer Amy , Borrego David , Ficarrotta Kayla , Johnson Kevin , Bolch Wesley E. 
Published: February 2011

Purpose:To investigate the benefits and limitations of patient‐phantom matching for determining organ dose during fluoroscopy guided interventions.Methods:In this study, 27 CT datasets representing patients of different sizes and genders were contoured and converted into patient‐specific computational models. Each model was matched, based on height and weight, to computational phantoms selected from the UF hybrid patient‐dependent series. In order to investigate the influence of phantom type on patient organ dose, Monte Carlo methods were used to simulate two cardiac projections (PA/left lateral) and two abdominal projections (RAO/LPO). Organ dose conversion coefficients were then calculated for each patient‐specific and patient‐dependent phantom and also for a reference stylized and reference hybrid phantom. The coefficients were subsequently analyzed for any correlation between patient‐specificity and the accuracy of the dose estimate. Accuracy was quantified by calculating an absolute percent difference using the patient‐specific dose conversion coefficients as the reference.Results:Patient‐phantom matching was shown most beneficial for estimating the dose to heavy patients. In these cases, the improvement over using a reference stylized phantom ranged from approximately 50% to 120% for abdominal projections and for a reference hybrid phantom from 20% to 60% for all projections. For lighter individuals, patient‐phantom matching was clearly superior to using a reference stylized phantom, but not significantly better than using a reference hybrid phantom for certain fields and projections.Conclusions:The results indicate two sources of error when patients are matched with phantoms: Anatomical error, which is inherent due to differences in organ size and location, and error attributed to differences in the total soft tissue attenuation. For small patients, differences in soft tissue attenuation are minimal and are exceeded by inherent anatomical differences. For large patients, difference in soft tissue attenuation can be large. In these cases, patient‐phantom matching proves most effective as differences in soft tissue attenuation are mitigated. With increasing obesity rates, overweight patients will continue to make up a growing fraction of all patients undergoing medical imaging. Thus, having phantoms that better represent this population represents a considerable improvement over previous methods. In response to this study, additional phantoms representing heavier weight percentiles will be added to the UFHADM and UFHADF patient‐dependent series.
Four‐dimensional cone‐beam computed tomography and digital tomosynthesis reconstructions using respiratory signals extracted from transcutaneously inserted metal markers for liver SBRT
Authors: Park Justin C. , Park Sung Ho , Kim Jong Hoon , Yoon Sang Min , Kim Su Ssan , Kim Jin Sung , Liu Zhaowei , Watkins Tyler , Song William Y. 
Published: February 2011

Purpose: Respiration‐induced intrafraction target motion is a concern in liver cancer radiotherapy, especially in stereotactic body radiotherapy (SBRT), and therefore, verification of its motion is necessary. An effective means to localize the liver cancer is to insert metal fiducial markers to or near the tumor with simultaneous imaging using cone‐beam computed tomography (CBCT). Utilizing the fiducial markers, the authors have demonstrated a method to generate breath‐induced motion signal of liver for reconstructing 4D digital tomosynthesis (4DDTS) and 4DCBCT images based on phasewise and/or amplitudewise sorting of projection data.Methods:The marker extraction algorithm is based on template matching ofa prior known marker image and has been coded to optimally extract marker positions in CBCT projections from the On‐Board Imager (Varian Medical Systems, Palo Alto, CA). To validate the algorithm, multiple projection images of moving thorax phantom and five patient cases were examined. Upon extraction of the motion signals from the markers, 4D image sorting and image reconstructions were subsequently performed. In the case of incomplete signals due to projections with missing markers, the authors have implemented signal profiling to replace the missing portion.Results:The proposed marker extraction algorithm was shown to be very robust and accurate in the phantom and patient cases examined. The maximum discrepancy of the algorithm predicted marker location versus operator selected location was, with the overall average of , for 500 projections. The resulting 4DDTS and 4DCBCT images showed clear reduction in motion‐induced blur of the markers and the anatomy for an effective image guidance. The signal profiling method was useful in replacing missing signals.Conclusions:The authors have successfully demonstrated that motion tracking of fiducial markers and the subsequent 4D reconstruction of CBCT and DTS are possible. Due to the significant reduction in motion‐induced image blur, it is anticipated that such technology will be useful in image‐guided liver SBRT treatments.
Performance measurements for the PET/CT Discovery‐600 using NEMA NU 2‐2007 standards
Authors: De Ponti E. , Morzenti S. , Guerra L. , Pasquali C. , Arosio M. , Bettinardi V. , Crespi A. , Gilardi M. C. , Messa C. 
Published: February 2011

Purpose:The aim of this study was to assess the performance measurements of the new PET/CT system Discovery‐600 (D‐600, GEMS, Milwaukee, WI).Methods:Performance measures were obtained with the National Electrical Manufacturers Association (NEMA) NU 2‐2007 procedures.Results:The transverse (axial) spatial resolution FWHMs were 4.9 (5.6) mm and 5.6 (6.4) mm at 1 and 10 cm off axis, respectively. The sensitivity (average at 0 and 10 cm) was 9.6 cps/kBq. The scatter fraction was 36.6% (low energy threshold: 425 keV). The NEC peak rate was 75.2 kcps at 12.9 kBq/cc. The hot contrasts for 10, 13, 17, and 22 mm spheres were 41%, 51%, 62%, and 73% and the cold contrasts for 28 and 37 mm spheres were 68% and 72%.Conclusions:The Discovery‐600 has good performance for the NEMA NU 2‐2007 parameters, particularly in improved sensitivity compared to the scanners of the same Discovery family, D‐ST and D‐STE.
A Systems Biology Approach to Infectious Disease Research: Innovating the Pathogen-Host Research Paradigm
Authors: Aderem Alan , Adkins Joshua N. , Ansong Charles , Galagan James , Kaiser Shari , Korth Marcus J. , Law G. Lynn , McDermott Jason G. , Proll Sean C. , Rosenberger Carrie , Schoolnik Gary , Katze Michael G. 
Published: February 2011

ABSTRACT
The twentieth century was marked by extraordinary advances in our understanding of microbes and infectious disease, but pandemics remain, food and waterborne illnesses are frequent, multidrug-resistant microbes are on the rise, and the needed drugs and vaccines have not been developed. The scientific approaches of the past—including the intense focus on individual genes and proteins typical of molecular biology—have not been sufficient to address these challenges. The first decade of the twenty-first century has seen remarkable innovations in technology and computational methods. These new tools provide nearly comprehensive views of complex biological systems and can provide a correspondingly deeper understanding of pathogen-host interactions. To take full advantage of these innovations, the National Institute of Allergy and Infectious Diseases recently initiated the Systems Biology Program for Infectious Disease Research. As participants of the Systems Biology Program, we think that the time is at hand to redefine the pathogen-host research paradigm.
Tectonic style and structural analysis of the Puebla de Guzmán Antiform (Iberian Pyrite Belt, South Portuguese Zone, SW Spain)
Authors: Mantero Elena M. , Alonso-Chaves Francisco M. , García-Navarro Encarnación , Azor Antonio 
Published: February 2011

Abstract

In the South Portuguese Zone (Iberian Massif), thin-skinned tectonics linked to the collision with the Ossa-Morena Zone produced the inversion of previous extensional basins in Carboniferous times. Its central domain, namely the Iberian Pyrite Belt, underwent two deformation phases at mostly low-grade metamorphic conditions linked to a progressive deformation migrating upwards from a basal detachment and from north to south. The Puebla de Guzmán Antiform is one of the most outstanding cartographic structures in the Iberian Pyrite Belt, representing a imbricate fan thrust system developed during the second regional deformation phase. In the Puebla de Guzmán Antiform, the first deformation phase gave rise to a penetrative slaty cleavage (S
1
), which is also recognized in the whole Iberian Pyrite Belt and constitutes the main foliation all over the region. Its genesis is possibly linked to the coetaneous development of thrusts at deeper crustal levels and SSW-vergent folds at all levels above these thrusts. First phase structures were deformed by large-scale imbricated thrust systems with lateral (NNE–SSW) and frontal (WNW–ESE) ramps, which constitute the most relevant regional cartographic structures. This second deformation phase generated thrusts, two set of folds with WNW–ESE and NNE–SSW-oriented axes, as well as two related axial plane crenulation cleavages. These relatively brittle to ductile-brittle second phase structures have been identified in many areas of the Iberian Pyrite Belt, and especially in the southern limb of the Puebla de Guzmán Antiform. The second phase thrusts reported from the Puebla de Guzmán Antiform have not been folded according to both the geological map of the area and the analysis of maximum shortening and stretching axes.