Improved correction for the tissue fraction effect in lung PET/CT imaging

Recently, there has been an increased interest in imaging different pulmonary disorders using PET techniques. Previous work has shown, for static PET/CT, that air content in the lung influences reconstructed image values and that it is vital to correct for this 'tissue fraction effect' (TFE). In this paper, we extend this work to include the blood component and also investigate the TFE in dynamic imaging. CT imaging and PET kinetic modelling are used to determine fractional air and blood voxel volumes in six patients with idiopathic pulmonary fibrosis. These values are used to illustrate best and worst case scenarios when interpreting images without correcting for the TFE. In addition, the fractional volumes were used to determine correction factors for the SUV and the kinetic parameters. These were then applied to the patient images. The kinetic parameters K1 and Ki along with the static parameter SUV were all found to be affected by the TFE with both air and blood providing a significant contribution to the errors. Without corrections, errors range from 34-80% in the best case and 29-96% in the worst case. In the patient data, without correcting for the TFE, regions of high density (fibrosis) appeared to have a higher uptake than lower density (normal appearing tissue), however this was reversed after air and blood correction. The proposed correction methods are vital for quantitative and relative accuracy. Without these corrections, images may be misinterpreted

Extension of the GATE Monte-Carlo simulation package to model bioluminescence and fluorescence imaging

International audienceThe Geant4 Application for Emission Tomography (GATE) is an advanced open-source software dedicated to Monte-Carlo (MC) simulations in medical imaging involving photon transportation (Positron emission tomography, single photon emission computed tomography, computed tomography) and in particle therapy. In this work, we extend the GATE to support simulations of optical imaging, such as bioluminescence or fluo-rescence imaging, and validate it against the MC for multilayered media standard simulation tool for biomedical optics in simple geometries. A full simulation setup for molecular optical imaging (bioluminescence and fluo-rescence) is implemented in GATE, and images of the light distribution emitted from a phantom demonstrate the relevance of using GATE for optical imaging simulations

Density variation during respiration affects PET quantitation in the lung

PET quantitation depends on the accuracy of the CT-derived attenuation correction map. In the lung, respiration leads to both positional and density mismatches, causing PET quantitation errors at lung borders but also within the whole lung. The aim of this work is to determine the extent of the associated errors on the measured time activity curves (TACs) and the corresponding kinetic parameter estimates. 5 patients with idiopathic pulmonary fibrosis underwent dynamic 18 F-FDG PET and cine-CT imaging as part of an ongoing study. The cine-CT was amplitude gated using PCA techniques to produce end expiration (EXP), end inspiration (INS) and mid-breathing cycle (MID) gates representative of a short clinical CT acquisition. The ungated PET data were reconstructed with each CT gate and the TACs and kinetic parameters compared. Patient representative XCAT simulations with varying lung density, both with and without motion, were also produced to represent the above study allowing comparison of true to measured results. In all cases, the obtained PET TACs differed with each CT gate. For ROIs internal to the lung, the effect was dominated by changes in density, as opposed to motion. The errors in the TACs varied with time, providing evidence that errors due to attenuation mismatch depend on activity distribution. In the simulations, some kinetic parameters were over- and under-estimated by a factor of 2 in the INS and EXP gates respectively. For the patients, the maximum variation in kinetic parameters was 20%. Our results show that whole lung density changes during the respiratory cycle have a significant impact on PET quantitation. This is especially true of the kinetic parameter estimates as the extent of the error is dependent on tracer distribution which varies with time. It is therefore vital to use matched PET/CT for attenuation correction

Experimental and analytical comparative study of optical coefficient of fresh and frozen rat tissues

International audienceOptical properties of fresh and frozen tissues of rat heart, kidney, brain, liver, and muscle were measured in the 450-to 700-nm range. The total reflectance and transmittance were measured using a well-calibrated integral sphere setup. Absorption coefficient μ a and reduced scattering coefficient μ 0 s were derived from the experimental measurements using the inverse adding doubling technique. The influence of cryogenic processing on optical properties was studied. Interindividual and intraindividual variations were assessed. These new data aim at filling the lack of validated optical properties in the visible range especially in the blue-green region of particular interest for fluorescence and optogenetics preclinical studies. Furthermore, we provide a unique comparison of the optical properties of different organs obtained using the same measurement setup for fresh and frozen tissues as well as an estimate of the intraindividual and interindividual variability

A Demonstration of STIR-GATE-Connection

We present the first open-source version of STIR-GATE-Connection, a project that aims to provide an easy-to-use pipeline to simulate realistic PET data using GATE, followed by quantitative reconstruction using STIR. Monte Carlo simulations and image reconstruction are powerful research tools for emission tomography that can assist with the design of new medical imaging devices as well as the evaluation of novel image reconstruction algorithms and various correction techniques. STIR-GATE-Connection is a collection of scripts that aid with the: (i) setup of a realistic GATE simulation of a voxelised phantom using a user selected scanner configuration, (ii) conversion of the output list mode data into STIR compatible sinograms, and (iii) computation of additive and multiplicative data corrections for Poisson image reconstruction using STIR. In this work, we demonstrate example usage of these steps. A public release of STIR-GATE-Connection, licensed under the Apache 2.0 License, can be downloaded at: http://www.github.com/UCL/STIR-GATE-Connection

Four-point correlator constraints on electromagnetic chiral parameters and resonance effective Lagrangians

We pursue the analysis of a set of generalized DGMLY sum rules for the electromagnetic chiral parameters at order $e^2p^2$ and discuss implications for effective Lagrangians with resonances. We exploit a formalism in which charge spurions are introduced and treated as sources. We show that no inconsistency arises from anomalies up to quadratic order in the spurions. We focus on the sum rules associated with QCD 4-point correlators which were not analyzed in detail before. Convergence properties of the sum rules are deduced from a general analysis of the form of the counterterms in the presence of electromagnetic spurions. Following the approach in which vector and axial-vector resonances are described with antisymmetric tensor fields and have a chiral order, we show that the convergence constraints are violated at chiral order four and can be satisfied by introducing a set of terms of order six. The relevant couplings get completely and uniquely determined from a set of generalized Weinberg sum-rule relations. An update on the corrections to Dashen's low-energy theorem is given.Comment: 42 pages, 1 figure. v2: references adde

Issues in quantification of registered respiratory gated PET/CT in the lung

PET/CT quantification of lung tissue is limited by several difficulties: the lung density and local volume changes during respiration, the anatomical mismatch between PET and CT and the relative contributions of tissue, air and blood to the PET signal (the tissue fraction effect). Air Fraction Correction (AFC) has been shown to improve PET image quantification in the lungs. Methods to correct for the movement and anatomical mismatch involve respiratory gating and image registration techniques. While conventional registration methods only account for spatial mismatch, the Jacobian determinant of the deformable registration transformation field can be used to estimate local volume changes and could therefore potentially be used to correct (i.e. Jacobian Correction, JC) the PET signal for changes in concentration due to local volume changes. This work aims to investigate the relationship between variations in the lung due to respiration, specifically density, tracer concentration and local volume changes. In particular, we study the effect of AFC and JC on PET quantitation after registration of respiratory gated PET/CT patient data. Six patients suffering from lung cancer with solitary pulmonary nodules underwent 18F-FDG PET/cine-CT. The PET data were gated into six respiratory gates using displacement gating based on an RPM signal and reconstructed with matched gated CT. The PET tracer concentration and tissue density were extracted from registered gated PET and CT images before and after corrections (AFC or JC) and compared to the values from the reference images. Before correction, we observed a linear correlation between the PET tracer concentration values and density. Across all gates and patients, the maximum relative change in PET tracer concentration before (after) AFC was found to be 16.2% (4.1%) and the maximum relative change in tissue density and PET tracer concentration before (after) JC was found to be 17.1% (5.5%) and 16.2% (6.8%) respectively. Overall our results show that both AFC or JC largely explain the observed changes in PET tracer activity over the respiratory cycle. We also speculate that a second order effect is related to change in fluid content but this needs further investigation. Consequently, either AFC or JC is recommended when combining lung PET images from different gates to reduce noise

Detection of Lung Density Variations With Principal Component Analysis in PET

Respiratory motion generates lung volume changes during the breathing cycle. These affect the lung tissue density and therefore influence both the attenuation effect and the radiotracer concentration in PET imaging. To detect and correct for these effects could improve the quantitative accuracy of lung PET imaging. In this work we propose the use of Principal Component Analysis (PCA) to detect respiratory-induced lung density changes in the upper lung, where motion is expected to be minimal. The method is firstly applied to simulation data, specifically generated to simulate density changes only and no motion. Secondly, it is applied on the upper lung bed position of 15 lung cancer patients datasets. The total number of counts in time is also evaluated. The results show that the PCA signal is highly correlated to the respiratory trace obtained from an external device, and also to the variation of total counts in time. As the bed positions taken into account do not include moving organs, the results suggest that PCA is successful in detecting respiratory-induced density changes in the upper lung