P. Almeida

Absolute quantitation of iodine-123 epidepride kinetics using single-photon emission tomography : comparison with carbon-11 epidepride and positron emission tomography

Abstract. Epidepride labelled with iodine-123 is a suitable probe for the in vivo imaging of striatal and extrastriatal dopamine D2 receptors using single-photon emission tomography (SPET). Recently, this molecule has also been labelled with carbon-11. The goal of this work was to develop a method allowing the in vivo quantification of radioactivity uptake in baboon brain using SPET and to validate it using positron emission tomography (PET). SPET studies were performed in Papio anubis baboons using 123I-epidepride. Emission and transmission measurements were acquired on a dual-headed system with variable head angulation and low-energy ultra-high resolution (LEUHR) collimation. The imaging protocol consisted of one transmission measurement (24 min, heads at 90°), obtained with two sliding line sources of gadolinium-153 prior to injection of 0.21–0.46 GBq of 123I-epidepride, and 12 emission measurements starting 5 min post injection. For scatter correction (SC) we used a dual-window method adapted to 123I. Collimator blurring correction (CBC) was done by deconvolution in Fourier space and attenuation correction (AT) was applied on a preliminary (CBC) filtered back-projection reconstruction using 12 iterations of a preconditioned, regularized minimal residual algorithm. For each reconstruction, a calibration factor was derived from a uniform cylinder filled with a 123I solution of a known radioactivity concentration. Calibration and baboon images were systematically built with the same reconstruction parameters. Uncorrected (UNC) and (AT), (SC+AT) and (SC+CBC+AT) corrected images were compared. PET acquisitions using 0.11–0.44 GBq of 11C-epidepride were performed on the same baboons and used as a reference. The radioactive concentrations expressed in percent of the injected dose per 100 ml (%ID/100 ml) obtained after (SC+CBC+AT) in SPET are in good agreement with those obtained with PET and 11C-epidepride. A method for the in vivo absolute quantitation of 123I-epidepride uptake using SPET has been developed which can be directly applied to other 123I-labelled molecules used in the study of the dopamine system. Further work will consist in using PET to model the radioligand-receptor interactions and to derive a simplified model applicable in SPET.

Comparison of clinical data sets acquired on different tomographs using 6-18F-l-dopa

Abstract.Longitudinal positron emission tomography (PET) studies of 6-18F-l-dopa uptake in the striatum are used to assess the progression of Parkinson’s disease or the survival of neuronal cells grafted in parkinsonian patients. These studies are performed over several years, and data analysis may suffer from the change from old tomographs to new machines with better sensitivity and spatial resolution. Furthermore, such studies on parkinsonian patients may be accomplished in either 2D or 3D acquisition mode. The aforementioned improvements offer great benefits for the study of neurodegenerative diseases, especially those affecting the striatum. However, direct comparison of data is not straightforward owing to variation in scanner characteristics. In this study, we assessed the feasibility of comparing the 6-18F-l-dopa striatal uptake values (Kc) measured in two groups of healthy subjects using two tomographs of different generations.We re-studied and compared acquisitions performed on 14 healthy subjects using 6-18F-l-dopa. Half of these studies had been performed in 2D acquisition mode using an ECAT 953B. The other half had been performed in 3D acquisition mode using an ECAT EXACT HR+. Different reconstruction protocols were used and the Kc values obtained were statistically compared.The results showed that lowering the transverse spatial resolution of images obtained with the scanner having the better spatial resolution, so that it more closely matched that of the other machine, allowed similar Kc values to be obtained in healthy subjects.This study shows that quantitative results of 6-18F-l-dopa scans can be matched between different scanners with different intrinsic resolutions. This can be accomplished using adequate modifications of the reconstruction parameters. Such modifications can be used to help in the longitudinal monitoring of parkinsonian patients using different tomographs.

Reconstruction of Clear-PEM data with STIR

The Clear-PEM scanner is a device based on planar detectors that is currently under development within the Crystal Clear Collaboration, at CERN. The basis for 3D image reconstruction in Clear-PEM is the software for tomographic image reconstruction (STIR). STIR is an open source object-oriented library that efficiently deals with the 3D positron emission tomography data sets. This library was originally designed for the traditional cylindrical scanners. In order to make its use compatible with planar scanner data, new functionalities were introduced into the librarys framework. In this work, Monte Carlo simulations of the Clear-PEM scanner acquisitions were used as input for image reconstruction with the 3D OSEM algorithm available in STIR. The results presented indicate that dual plate PEM data can be accurately reconstructed using the enhanced STIR framework.

Maximum a Posteriori Reconstruction using PRESTO and PET/MR data acquired Simultaneously with the 3TMR-BrainPET

In this paper, a Maximum a Posteriori Reconstruction algorithm is applied for the first time to the Siemens 3TMR BrainPET scanner. The implementation of this algorithm is done in the PET REconstruction Software TOolkit. This software is able to cope with 3D PET listmode data and can deal with the specificities of the Siemens 3TMR BrainPET scanner. Simulated data was used to assess the performance of the algorithm. Several a priori distributions were tested and the results are compared to OSEM reconstruction. Simultaneously acquired PET and MR data of a human patient was used to show the feasibility of the Maximum a Posteriori algorithm. The results are promising and expected to improve clinical applications.

Breast cancer imaging studies by Monte Carlo simulation with Clear-PEM

Positron emission mammography (PEM) is a functional imaging technique for breast cancer detection. The development of dedicated systems with high sensitivity and spatial resolution, are a valuable resource for early breast cancer diagnosis and onset of an efficient therapy. In this paper, we report on the performance indicators of the Clear-PEM imaging system. In particular, we evaluate, the detection sensitivity, system count rates and breast lesion detection by means of Monte Carlo simulation.

List-mode maximum-likelihood reconstruction for the ClearPEM system

A dedicated implementation of list-mode maximum-likelihood expectation-maximization (MLEM) reconstruction for the ClearPEM system is presented. The system is composed of two face-to-face detectors, which can be rotated to acquire data from different angular positions. Due to the specific design with irregular sampling and depth of interaction capability, the possible number of lines of response (LOR) is significantly greater than the number of detected events in a standard clinical study. Because reconstruction methods based on data histogramming to sinogram lead to a high computational cost and/or a loss of the intrinsical system resolution, it is necessary to consider the processing of events in list-mode during the reconstruction. The presented method adopted EM algorithm to maximize the logarithmic likelihood function that is expressed in list-mode. The voxel efficiency is corrected by pre-calculated efficiency maps based on flood phantom acquisitions. The method is also implemented with parallelization by distributing the calculation of the acquired events into different threads for significantly increasing computational speed. The results of a Derenzo phantom study show that the presented algorithm can achieve a similar result as 3D-OSEM reconstruction based on data histogramming with significantly lower reconstruction time (6 times faster with one thread, 20 times faster with 8 threads distributed in 8 CPU cores). In clinical studies with lower acquired events, the acceleration ratio can be even higher. The result from a breast phantom study shows that lesions with 15 mm in diameter, each, as well as a small lesion with 5 mm in diameter are clearly visible and can be characterized. The mouse imaging studies show also great potential of the system in small animal applications.

Clear-PEM: Monte Carlo performance and image reconstruction studies

The Clear-PEM prototype under development aims to improve early stage breast cancer diagnostics. The proposed device is based on cerium doped lutetium crystal matrices developed by the Crystal Clear Collaboration, as well as on modern data acquisition techniques. A series of Monte Carlo studies were performed to evaluate detection sensitivity, background rate and intrinsic spatial resolution in order to optimize the final detector concept. A description of the developed GEANT4 based simulation framework and PEM image reconstruction software is also presented in this paper. First simulation results indicates that Clear-PEM design significantly increases detection sensitivity in comparison with conventional PET cameras for breast cancer diagnostics. Count-rate simulation results are within operation limits for the data acquisition system, able to read 1 MHz event rate, allowing to take full profit of the large detector acceptance.

Optimization of 2D image reconstruction for positron emission mammography using IDL

The Clear-PEM system is a prototype machine for Positron Emission Mammography (PEM) under development within the Portuguese PET-Mammography consortium. We have embedded 2D image reconstruction algorithms implemented in IDL within the prototypes image analysis package. The IDL implementation of these algorithms proved to be accurate and computationally efficient. In this paper, we present the implementation of the MLEM, OSEM and ART 2D iterative image reconstruction algorithms for PEM using IDL. C and IDL implementations are compared using realistic Monte Carlo simulated data. We show that IDL can be used for the easy implementation of image reconstruction algorithms for emission tomography.

An overview of the Clear-PEM breast imaging scanner

We present an overview of the Clear-PEM breast imaging scanner. Clear-PEM is a unique dual-head Positron Emission Mammography scanner using APD-based detector modules that are capable of measuring depth-of-interaction (DOI) with a resolution of 2 mm in 20 mm long LYSO:Ce crystals. Such capability leads to an image spatial resolution of 1.2 mm and a high efficiency, foreseeing the detection of 3 mm breast lesions in less than 7 minutes exams. The full system comprises 192 detector modules in a total of 6144 LYSO:Ce crystals and 384 32-pixel APD arrays readout by ASICs with 192 input channels that represents an unprecedented level of integration in PET systems. Throughout the project and besides the detector module, we had developed dedicated Frontend and Data Acquisition electronics, the mechanical design and construction of the detector heads and the robotic gantry, as well as all the software that include calibration (energy, time and DOI), normalization and image reconstruction algorithms. In this work we will discuss the developments and present the commissioning results of the detector before the beginning of the clinical trials program, scheduled for the end of the present year.

System matrix calculation for Clear-PEM using ART and linograms

The Clear-PEM device is a positron emission mammography (PEM) unit based on planar detectors and is currently under development. We have developed a 2D algebraic reconstruction technique (ART) algorithm using linograms to reconstruct Clear-PEM data. In this work we evaluate three different methods of calculating the system matrix used by the ART algorithm, which we designate as the pixel-, ray- and tube-driven methods, respectively. The methods were tested using Monte Carlo simulated data. The results obtained show that ART algorithm allows, for these cases, accurate image reconstruction and indicate that a more accurate modeling of the image system matrix using tubes of response (TORs) provides the best image evaluation indexes.