Carole Lartizien

GATE: a simulation toolkit for PET and SPECT.

Monte Carlo simulation is an essential tool in emission tomography that can assist in the design of new medical imaging devices, the optimization of acquisition protocols and the development or assessment of image reconstruction algorithms and correction techniques. GATE, the Geant4 Application for Tomographic Emission, encapsulates the Geant4 libraries to achieve a modular, versatile, scripted simulation toolkit adapted to the field of nuclear medicine. In particular, GATE allows the description of time-dependent phenomena such as source or detector movement, and source decay kinetics. This feature makes it possible to simulate time curves under realistic acquisition conditions and to test dynamic reconstruction algorithms. This paper gives a detailed description of the design and development of GATE by the OpenGATE collaboration, whose continuing objective is to improve, document and validate GATE by simulating commercially available imaging systems for PET and SPECT. Large effort is also invested in the ability and the flexibility to model novel detection systems or systems still under design. A public release of GATE licensed under the GNU Lesser General Public License can be downloaded at http:/www-lphe.epfl.ch/GATE/. Two benchmarks developed for PET and SPECT to test the installation of GATE and to serve as a tutorial for the users are presented. Extensive validation of the GATE simulation platform has been started, comparing simulations and measurements on commercially available acquisition systems. References to those results are listed. The future prospects towards the gridification of GATE and its extension to other domains such as dosimetry are also discussed.

Computer-aided diagnosis of prostate cancer in the peripheral zone using multiparametric MRI

This study evaluated a computer-assisted diagnosis (CADx) system for determining a likelihood measure of prostate cancer presence in the peripheral zone (PZ) based on multiparametric magnetic resonance (MR) imaging, including T2-weighted, diffusion-weighted and dynamic contrast-enhanced MRI at 1.5 T. Based on a feature set derived from grey-level images, including first-order statistics, Haralick features, gradient features, semi-quantitative and quantitative (pharmacokinetic modelling) dynamic parameters, four kinds of classifiers were trained and compared: nonlinear support vector machine (SVM), linear discriminant analysis, k-nearest neighbours and naïve Bayes classifiers. A set of feature selection methods based on t-test, mutual information and minimum-redundancy-maximum-relevancy criteria were also compared. The aim was to discriminate between the relevant features as well as to create an efficient classifier using these features. The diagnostic performances of these different CADx schemes were evaluated based on a receiver operating characteristic (ROC) curve analysis. The evaluation database consisted of 30 sets of multiparametric MR images acquired from radical prostatectomy patients. Using histologic sections as the gold standard, both cancer and nonmalignant (but suspicious) tissues were annotated in consensus on all MR images by two radiologists, a histopathologist and a researcher. Benign tissue regions of interest (ROIs) were also delineated in the remaining prostate PZ. This resulted in a series of 42 cancer ROIs, 49 benign but suspicious ROIs and 124 nonsuspicious benign ROIs. From the outputs of all evaluated feature selection methods on the test bench, a restrictive set of about 15 highly informative features coming from all MR sequences was discriminated, thus confirming the validity of the multiparametric approach. Quantitative evaluation of the diagnostic performance yielded a maximal area under the ROC curve (AUC) of 0.89 (0.81-0.94) for the discrimination of the malignant versus nonmalignant tissues and 0.82 (0.73-0.90) for the discrimination of the malignant versus suspicious tissues when combining the t-test feature selection approach with a SVM classifier. A preliminary comparison showed that the optimal CADx scheme mimicked, in terms of AUC, the human experts in differentiating malignant from suspicious tissues, thus demonstrating its potential for assisting cancer identification in the PZ.

PET-SORTEO: a Monte Carlo-based Simulator with high count rate capabilities

Monte Carlo-based PET simulators are powerful tools for accurately generating projections of tracer distributions for given scanner specifications and attenuating media distributions. High activity-related phenomena, such as the randoms contribution as well as block and system deadtimes constitute a large source of artefact and must therefore be integrated within the simulation model along with the /spl gamma/-ray interaction within the tissue or the scanner material. We present here the features of a Monte Carlo simulator, dedicated to full ring tomographs, which is able to generate scattered, unscattered, and randoms distributions from voxelized phantom descriptions, and which accounts for the data losses due to system deadtime. Simulations of the count rate performance of the ECAT Exact HR/sup +/ operating in 2-D and 3-D modes were found to be in good agreement with experimental measurements obtained for a wide range of activity levels and distributions.

Simulating whole-body PET scanning with rapid analytical methods

Presents a 3D whole-body PET simulator that generates multiple, yet statistically accurate, realizations of projection data within a computation time that is short enough to enable the measurement of the task performance of image reconstruction algorithms. The whole-body simulator takes into account the following effects: the separate amounts of statistical noise contributed by true, scattered, and random coincidences, activity outside the field of view, activity decay between bed positions, detector efficiencies and resolution, and noise arising from the transmission scan. The principle of the simulation is to analytically calculate projections based on the geometrical specification of the emission and attenuation objects that comprise the MCAT phantom. A pre-determined level of statistical noise is then added to the projection data, which is then inputted to the same data correction and image reconstruction procedures used in practice. The authors compare the results of multiple realizations of simulated and measured phantom studies at statistical noise levels similar to those encountered in 3D whole-body PET scanning. They obtain comparable statistical noise properties for the fully corrected emission sinograms, and also show that a simple model accurately predicts the statistical noise added by random and scattered coincidences generated by activity outside the field of view.

A Virtual Imaging Platform for Multi-Modality Medical Image Simulation

This paper presents the Virtual Imaging Platform (VIP), a platform accessible at http://vip.creatis.insa-lyon.fr to facilitate the sharing of object models and medical image simulators, and to provide access to distributed computing and storage resources. A complete overview is presented, describing the ontologies designed to share models in a common repository, the workίow template used to integrate simulators, and the tools and strategies used to exploit computing and storage resources. Simulation results obtained in four image modalities and with different models show that VIP is versatile and robust enough to support large simulations. The platform currently has 200 registered users who consumed 33 years of CPU time in 2011.

Incorporating Patient-Specific Variability in the Simulation of Realistic Whole-Body

The purpose of the work described in this paper was the development of a framework for the creation of a realistic positron emission tomography (PET) simulated database incorporating patient-specific variability. The ground truth used was therefore based on clinical PET/computed tomography (CT) data of oncology patients. In the first step, the NURBS-based cardiac-torso phantom was adapted to the patients CT acquisitions to reproduce their specific anatomy while the corresponding PET acquisitions were used to derive the activity distribution of each organ of interest. Secondly, realistic tumor shapes with homogeneous or heterogeneous activity distributions were modeled based on segmentation of the PET tumor volume and incorporated in the patient-specific models obtained at the first step. Lastly, patient-specific respiratory motion was also modeled. The derived patient-specific models were subsequently combined with the PET SORTEO Monte Carlo simulation tool for the simulation of the whole-body PET acquisition process. The accuracy of the simulated datasets was assessed in comparison to the original clinical patient images. In addition, a couple of applications for such simulated images were also demonstrated. Future work will focus on the creation of a comprehensive database of simulated raw data and reconstructed whole-body images, facilitating the rigorous evaluation of image-processing algorithms in PET for oncology applications.

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The goal of this project is to determine if there is a difference between planar and volumetric numerical observers. The motivation comes from the use of a volumetric (3D) display of image data (i.e. three orthogonal views through a volume image) to assess whole-body PET images in most, if not all, clinical PET centers. Studies of correlations between numerical observers and human observers (e.g. using receiver operating characteristic (ROC) detection analysis), however, typically use a planar (2D) display and analysis methodology. For images where axial noise correlations exist, Wells et al. [IEEE-TNS, 47:037-1044, 2000] have shown significant differences between single-slice and multi-slice ROC studies, implying that ROC-type studies utilizing a volumetric image display will also yield different results from a single or multi-slice image displays. In particular, planar implementations of the non-prewhitening matched filter (NPWMF) and the channelized Hotelling observer (CHO) have been extensively investigated as surrogates for measuring human detection task performance. To determine if there is a difference between planar and volumetric numerical observers, we analyzed the behavior of 2D and 3D implementations of the NPWMF and CHO numerical observers with multiple realizations of images with noise properties similar to those of whole-body PET oncology imaging. Initial results indicate that there is a significant difference increase in SNR or delectability of volumetric numerical observers relative to planar observers. This implies that volumetric and planar numerical observers may have different strengths of correlation with human observer performance, and that these correlations should be determined prior to using numerical observers to optimize algorithm or protocol performance for whole-body PET imaging.The goal of this project is to determine if there is a difference between planar and volumetric numerical observers. The motivation comes from the use of a volumetric (3-D) display of image data (i.e., three orthogonal views through a volume image) to assess whole-body PET images in most, if not all, clinical PET centers. Studies of correlations between numerical observers and human observers (e.g., using receiver operating characteristic (ROC) detection analysis), however, typically use a planar (2-D) display and analysis methodology. In particular, planar implementations of the nonprewhitening matched filter (NPWMF) and the channelized Hotelling observer (CHO) have been extensively investigated as surrogates for measuring human detection task performance. To determine if there is a difference between planar and volumetric numerical observers, we analyzed the behavior of 2-D and 3-D implementations of the NPWMF and CHO numerical observers with multiple realizations of images with noise properties similar to those of whole-body PET oncology imaging. The results indicate that there is a significant increase in SNR or detectability of volumetric numerical observers relative to planar observers. This implies that volumetric and planar numerical observers may have different strengths of correlation with human observer performance, and that these correlations should be determined prior to using numerical observers to optimize algorithm or protocol performance for whole-body PET imaging. When axial smoothing is applied, however, to impose isotropic target resolution or to simulate fully 3-D PET data, the detectabilities of planar numerical observers are increased and the differences between planar and volumetric numerical observers become less significant.

Distributions for Oncology Applications

We report on results of a localization ROC (LROC) study that evaluated several multiclass model observers as predictors of human tumor-detection performance. The study used image slices extracted from simulated whole-body FDG-PET volumes. Lesions were located in the liver, lungs, and soft tissue of a mathematical phantom, and the data simulation modeled a full-3D acquisition mode with an ECAT HR+ scanner. Reconstructions were performed with the FORE+AWOSEM algorithm. In the LROC study, observers read separate sets consisting of either coronal, sagittal, or transverse slices from the same set of cases. Multiclass versions of the channelized nonprewhitening observer demonstrated good agreement with the human observers

A comparison of planar versus volumetric numerical observers for detection task performance in whole-body PET imaging

We implemented a hybrid scatter-correction method for 3D PET that combines two scatter-correction methods in a complementary way. The implemented scheme uses a method based on the discrimination of the energy of events (the estimation of trues method (ETM)) and an auxiliary method (the single scatter simulation method (SSS1) or the convolution–subtraction method (CONV)) in an attempt to increase the accuracy of the correction over a wider range of acquisitions. The ETM takes into account the scatter from outside the field-of-view (FOV), which is not estimated with the auxiliary method. On the other hand, the auxiliary method accounts for events that have scattered with small angles, which have an energy that cannot be discriminated from that of unscattered events using the ETM. The ETM uses the data acquired in an upper energy window above the photopeak (550–650 keV) to obtain a noisy estimate of the unscattered events in the standard window (350–650 keV). Our implementation uses the auxiliary method to correct the residual scatter in the upper window. After appropriate scaling, the upper window data are subtracted from the total coincidences acquired in the standard window, resulting in the final scatter estimate, after smoothing. In this work we compare the hybrid method with the corrections used by default in the 2D and 3D modes of the ECAT EXACT HR+ using phantom measurements. Generally, the contrast was better with the hybrid method, although the relative errors of quantification were similar. We conclude that hybrid techniques such as the one implemented in this work can provide an accurate, general-purpose and practical way to correct the scatter in 3D PET, taking into account the scatter from outside the FOV.

Evaluation of multiclass model observers in PET LROC studies

Contents. Preface S. Tavernier.-A Look at Medical Imaging Trends through the Eyes of a Medical Doctor S.S. Makeyev.- Introduction.-Historical Aspect of Nuclear Medicine.-Nowadays in Nuclear Medicine.-Perspectives of Nuclear Medicine Imaging.- New Trends in X-Ray CT Imaging R. Deych and E. Dolazza.- Present Status of X-Ray CT.-Detector Instrumentation in Medical CT.- Scintillator.-Photodetectors.-Future Evolution of Data Measurement Systems.- The Evolution of Spect- from Anger to Today and Beyond W.W. Moses, A. Gektin et al.- Introduction.-General Considerations.-SPECT.- The Anger Camera.-Optimizing Positioning in Anger Cameras.- Collimators.-Scintillators for Spect.- Recently Developed Scintillator Materials.- Conclusion.- New Trends in PET Detector Developments P.Lecoq.- Introduction.-PET Based Molecular Imaging.-Improving Sensitivity.- Improving Spatial and Temporal Resolution.-Multimodaility and Multifunctionality.-New Conversion Materials.- New Photodetectors.-Highly Integrated and Low Noise Electronics.-Intelligent and Triggerable Data Acquisition Systems.-Simulation Software.-New Reconstruction and Visualisation Algorithms.-Conclusion.-Semiconductor Detectors in Radiation Medicine: Radiotherapy and related Applcations A.B. Rosenfeld.- Introduction.-Integral Semiconductor Dosimetry in Radiation Therapy.-Mosfet Detectors.-Semiconductor Radiation Detectors in Hadron Therapy.- Semiconductor Radiation Detectors for Microdosimetry in Radiation Therapy.-Application of Scintillator Based Detector in Radiation Therapy.-Conclusion.-First Results with the ClearPET small Animal PET Scanners S. Tavernier et al.- Introduction.-Description of the ClearPET Scanners.-Measured Performance and Comparison with Monte Carlo Simulations.- Image Reconstruction.-Conclusions.-Investigation of Crystal Identification Methods for ClearPETTM Phoswich Detector D. Wisniewski et al.- Introduction.-Measurement Setup.-Crystal Identification Methods.- Experimental Results.- Conclusions.- Directions in Scintillation Materials Research P. Dorenbos.- Introduction.-Historic Developments.- Fundamental Limits.- Directions in Scintillation Materials Research.-Summary and Conclusions.-Scintillation Detectors for Medical and Biology Applications: Materials, Design and Light Collection Conditions M. Globus, B. Grinyov.- Introduction.-2. Some Features and Regularities of Light Collection in Scintillators.- Medical Diagnostics Instrumentation.- Thin Scintillation Films for Biological Microtomography. Conclusions.- Current and Future Use of LSO: CE Scintillators in PET C.L. Melcher et al.- Introduction.-Physical Properties.- Scintillation Properties.-Crystal Growth.-Detector Design.- Future Uses of LSO: CE in PET.-Conclusion.-Inorganic Scintillators in Positron Emission Tomography C.W.E. van Eijk.- Introduction.-Inorganic Scintillators.- Position Resolution and Depth of Interaction.-Coincidence-Time Resolution, Random Coincidences, Time of Flight and Dead Time.-Conclusion.-Crystal Fibers and thin Films for Imaging Applications C. Pedrini and C. Dujardin.-. Introduction.-Single Crystal Fibers.- Scintillating Thin Films Deposited on Substrate.- Scintillation thin Layers created by Irradiation.-Conclusions. Non-Proportionality and Energy Resolution of Scintillation Detectors M. Moszynski.-Introduction.-Outline of the Problem.Study of Energy Resolution and Non-Proportionality.- Discussion and Conclusions.