Albert Cot

Serial dopamine transporter imaging of nigrostriatal function in patients with idiopathic rapid-eye-movement sleep behaviour disorder: a prospective study

BACKGROUND Serial dopamine transporter (DAT) imaging in patients with Parkinsons disease (PD) and other synucleinopathies shows progressive nigrostriatal dopaminergic dysfunction. Because idiopathic rapid-eye-movement (REM) sleep behaviour disorder (IRBD) can precede the classic symptoms of PD and other synucleinopathies, we postulated that serial DAT imaging in patients with IRBD could be used to detect decline in striatal tracer uptake, indicating progressive nigrostriatal cell degeneration. METHODS In a prospective study, 20 patients with IRBD (mean age 70·55 years [SD 6·02]) underwent serial DAT imaging with (123)I-2β-carbomethoxy-3β-(4-iodophenyl)-N-(3-fluoropropyl)-nortropane ((123)I-FP-CIT) SPECT at baseline and again after 1·5 years and 3 years; 20 age-matched and sex-matched control participants (69·50 years [6·77]) underwent imaging at baseline and 3 years. The striatum to occipital cortex uptake ratios were calculated for the putamen and caudate nucleus in each hemisphere. In patients, the ratio was judged to be reduced when it was less than two SD of the mean ratio in controls at the same timepoint. Differences in (123)I-FP-CIT uptake between patients and controls in each striatal region and rates of decline were assessed by use of multivariate ANOVA (MANOVA). FINDINGS Compared with controls, patients had significantly reduced mean (123)I-FP-CIT binding in all four striatal regions at baseline and after 3 years. Striatal (123)I-FP-CIT uptake was reduced compared with that in controls in ten patients at baseline and in 13 patients after 3 years. In patients, the mean reduction in (123)I-FP-CIT uptake from baseline to 3 years was 19·36% (95% CI 15·14 to 23·59) in the left putamen, 15·57% (10·87 to 20·28) in the right putamen, 10·81% (6·49 to 15·18) in the left caudate nucleus, and 7·14% (2·74 to 11·56) in the right caudate nucleus. After adjustment for the baseline (123)I-FP-CIT uptake ratios, the decline in (123)I-FP-CIT binding at baseline to 3 years was significantly greater in patients than in controls in the left putamen (9·78% difference between groups, 95% CI 3·22 to 16·32), right putamen (5·43%, 1·99 to 12·86), and left caudate nucleus (8·07%, 1·44 to 14·70), but not in the right caudate nucleus (4·16%, -3·00 to 11·34). At the 3-year assessment, three patients were diagnosed with PD. These patients had the lowest (123)I-FP-CIT uptake at baseline and a mean reduction in (123)I-FP-CIT uptake at 3 years of 32·81% in the left putamen, 30·40% in the right putamen, 26·51% in the left caudate nucleus, and 23·75% in the right caudate nucleus. INTERPRETATION In patients with IRBD, serial (123)I-FP-CIT SPECT shows decline in striatal tracer uptake that reflects progressive nigrostriatal dopaminergic dysfunction. Serial (123)I-FP-CIT SPECT can be used to monitor the progression of nigrostriatal deficits in patients with IRBD, and could be useful in studies of potential disease-modifying compounds in these patients. FUNDING Fondo de Investigaciones Sanitarias of Spain.

Quantification of dopaminergic neurotransmission SPECT studies with 123I-labelled radioligands. A comparison between different imaging systems and data acquisition protocols using Monte Carlo simulation

Purpose123I-labelled radioligands are commonly used for single-photon emission computed tomography (SPECT) imaging of the dopaminergic system to study the dopamine transporter binding. The aim of this work was to compare the quantitative capabilities of two different SPECT systems through Monte Carlo (MC) simulation.MethodsThe SimSET MC code was employed to generate simulated projections of a numerical phantom for two gamma cameras equipped with a parallel and a fan-beam collimator, respectively. A fully 3D iterative reconstruction algorithm was used to compensate for attenuation, the spatially variant point spread function (PSF) and scatter. A post-reconstruction partial volume effect (PVE) compensation was also developed.ResultsFor both systems, the correction for all degradations and PVE compensation resulted in recovery factors of the theoretical specific uptake ratio (SUR) close to 100%. For a SUR value of 4, the recovered SUR for the parallel imaging system was 33% for a reconstruction without corrections (OSEM), 45% for a reconstruction with attenuation correction (OSEM-A), 56% for a 3D reconstruction with attenuation and PSF corrections (OSEM-AP), 68% for OSEM-AP with scatter correction (OSEM-APS) and 97% for OSEM-APS plus PVE compensation (OSEM-APSV). For the fan-beam imaging system, the recovered SUR was 41% without corrections, 55% for OSEM-A, 65% for OSEM-AP, 75% for OSEM-APS and 102% for OSEM-APSV.ConclusionOur findings indicate that the correction for degradations increases the quantification accuracy, with PVE compensation playing a major role in the SUR quantification. The proposed methodology allows us to reach similar SUR values for different SPECT systems, thereby allowing a reliable standardisation in multicentric studies.

Assessment of SPM in Perfusion Brain SPECT Studies. A Numerical Simulation Study Using Bootstrap Resampling Methods

Statistical parametric mapping (SPM) has become the technique of choice to statistically evaluate positron emission tomography (PET), functional magnetic resonance imaging (fMRI), and single photon emission computed tomography (SPECT) functional brain studies. Nevertheless, only a few methodological studies have been carried out to assess the performance of SPM in SPECT. The aim of this paper was to study the performance of SPM in detecting changes in regional cerebral blood flow (rCBF) in hypo- and hyperperfused areas in brain SPECT studies. The paper seeks to determine the relationship between the group size and the rCBF changes, and the influence of the correction for degradations. The assessment was carried out using simulated brain SPECT studies. Projections were obtained with Monte Carlo techniques, and a fan-beam collimator was considered in the simulation process. Reconstruction was performed by using the ordered subsets expectation maximization (OSEM) algorithm with and without compensation for attenuation, scattering, and spatial variant collimator response. Significance probability maps were obtained with SPM2 by using a one-tailed two-sample f-test. A bootstrap resampling approach was used to determine the sample size for SPM to detect the between-group differences. Our findings show that the correction for degradations results in a diminution of the sample size, which is more significant for small regions and low-activation factors. Differences in sample size were found between hypo- and hyperperfusion. These differences were larger for small regions and low-activation factors, and when no corrections were included in the reconstruction algorithm.

Impact of scatter correction on D2 receptor occupancy measurements using 123I-IBZM SPECT: comparison to 11C-Raclopride PET.

Reported values of D(2) receptor occupancy (RO) achieved by antipsychotic drugs tend to be lower when measured with (123)I-IBZM SPECT than with (11)C-Raclopride PET. Image degrading factors such as attenuation, distance-dependent collimator response and scatter could account for this difference. While attenuation correction is routinely applied to SPECT images, the other degradations are not usually accounted for. The aim of this work was to assess the impact of scatter correction on D(2) RO quantification with (123)I-IBZM SPECT, and to compare the results of both corrected and un-corrected SPECT values with (11)C-Raclopride PET measurements. Phantom experiments as well as within-subject human data from a previous study were used for this purpose. SPECT images were reconstructed using filtered back-projection including attenuation correction (FBP(A)), ordered subsets expectation maximization including attenuation and point spread function corrections (OSEM(A+PSF)) and ordered subsets expectation maximization including attenuation, point spread function and scatter corrections (OSEM(A+PSF+SCT)). PET images were reconstructed using the FBP algorithm and corrected for attenuation, scatter, random coincidences and dead time. Quantification of receptor availability was performed using the tissue ratio at pseudoequilibrium for SPECT, and the simplified reference tissue model (SRTM) for PET. Analysis was performed using both occipital cortex (occ) and cerebellum (cer) as reference regions for both modalities. When images were reconstructed using FBP(A), SPECT D(2) RO values were significantly lower as compared with PET leading to a D(2) RO difference of -20% (CI(95%): -13, -27%) (occ) and -23% (CI(95%): -14, -31%) (cer). When images were reconstructed using OSEM(A+PSF), SPECT D(2) RO values were also lower as compared with PET leading to a D(2) RO difference of -21% (CI(95%): -14, -27%) (occ) and -24% (CI(95%): -18, -30%) (cer). When images were reconstructed using OSEM(A+PSF+SCT), the D(2) RO bias was reduced to -6% (CI(95%): 0, -13%) (occ) and -11% (CI(95%): -4, -18%) (cer). These data suggest that the scatter correction plays a major role in explaining the differences between D(2) RO measurements using (123)I-IBZM SPECT and (11)C-Raclopride PET.

Integration of advanced 3D SPECT modeling into the open-source STIR framework

PURPOSE The Software for Tomographic Image Reconstruction (STIR, http://stir.sourceforge.net) package is an open source object-oriented library implemented in C++. Although its modular design is suitable for reconstructing data from several modalities, it currently only supports Positron Emission Tomography (PET) data. In this work, the authors present results for Single Photon Emission Computed Tomography (SPECT) imaging. METHODS This was achieved by the complete integration of a 3D SPECT system matrix modeling library into STIR. RESULTS The authors demonstrate the flexibility of the combined software by reconstructing simulated and acquired projections from three different scanners with different iterative algorithms of STIR. CONCLUSIONS The extension of the open source STIR project with advanced SPECT modeling will enable the research community to study the performance of several algorithms on SPECT data, and potentially implement new algorithms by expanding the existing framework.

Effect of anatomical variability, reconstruction algorithms and scattered photons on the SPM output of brain PET studies.

Statistical parametric mapping (SPM) has become the standard technique to statistically evaluate differences between functional images. The aim of this paper was to assess the effect of anatomical variability of skull, the reconstruction algorithm and the scattering of photons in the brain on the output of an SPM analysis of brain PET studies. To this end, Monte Carlo simulation was used to generate suitable PET sinograms and bootstrap techniques were employed to increase the reliability of the conclusions. Activity distribution maps were obtained by segmenting thirty nine T1-weighted magnetic resonance images. Foci were placed on the posterior cingulate cortex (PCC) and the superior temporal cortex (STC) and activation factors ranging between -25% and +25% were simulated. Preprocessing of the reconstructed images and statistical analysis were performed using SPM2. Our findings show that intersubject anatomical differences can cause the minimum sample size to increase between 10 and 42% for posterior cingulate Cortex and between 40 and 80% for superior temporal cortex. Ideal scatter correction (ISC) allowed us to diminish the sample size up to 18% and fully 3D reconstruction reduced the minimum sample size between 8 and 33%. Detection sensitivity was higher for hypo-activation than for hyper-activation situations and higher for superior temporal cortex than for posterior cingulate cortex.

Modeling of high-energy contamination in SPECT imaging using Monte Carlo simulation

/sup 123/I is a commonly used radioisotope employed in neurotransmitter SPECT studies. In addition to an intense line at 159 keV, the decay scheme of this radioisotope includes a low yield (/spl sim/3%) of higher energy photons which make a non-negligible contribution to the final image when low-energy high-resolution (LEHR) collimators are used. This contribution of high-energy photons may reach /spl sim/28% of the total counts in the projections. The aim of this work is to model each energy component of the high-energy Point Spread Function (hPSF) for fan-beam LEHR collimators in order to develop fast Monte Carlo (MC) simulations of high-energy ray contamination. The modeling of hPSF was based on the results of simulating photons through the collimator-detector system using the MC code PENELOPE. Since low-energy PSFs models for fan-beam collimators tend to a Gaussian distribution, we use the same function for the hPSF modeling for high-energy photons. The parameters of these Gaussian functions (g(x,y)) were obtained by minimizing the root mean square error (RMS) using the sensitivity of the simulated hPSFs as a constraint. The hPSFs were parameterized for a range of energies between 350 keV and 538 keV. The RMS attained after fitting of g(x,y) to the simulated hPSFs was always smaller than /spl sim/2% of the mean sensitivity per pixel of the image. A strong dependence of the sensitivity on the type and thickness of the backscatter material behind the crystal was found. Our results indicate that Gaussian distributions approximate the hPSF responses for fan-beam collimators. This model will be an important tool to accelerate MC simulations of radiolabeled compounds which emit medium- or high-energy rays.

Neurotransmission SPECT and MR registration combining mutual and gradient information.

Purpose: Image registration is important in functional image analysis. In neurotransmission single photon emission tomography (nSPECT), specific uptake sites can be accurately localized by superimposing the SPECT study onto a high-resolution structural image such as a magnetic resonance(MR) of the subject. Mutual-information (MI)-based algorithms are usually employed for this purpose. Nevertheless, nSPECT/MR registration using MI is often limited by the low count rates present in nSPECT. Several works have proposed extensions of the MI measures to include gradient information (GI) from the images but their performance has not been evaluated in SPECT studies. Methods: In this work, the accuracy of the MI including gradient information (MIG) was compared with the standard MI using data from healthy volunteers and data simulating a specific uptake reduction using three different radioligands: I 123 -IBZM , I 123 -ADAM , I 123 -R 91150 . Results: The results showed that MIG-based registration yielded better accuracy than MI. The MIG-based similarity measures were less sensitive to sparse sampling and diminished computational time without a substantial decrease in registration accuracy. Conclusions: Accuracy of nSPECT/MR registration is improved when gradient information is included in the MI-based algorithm, which makes MIG-based registration potentially useful for clinical applications.

Validation of semi-quantitative methods for DAT SPECT: influence of anatomical variability and partial volume effect.

The aim of this work was to evaluate the influence of anatomical variability between subjects and of the partial volume effect (PVE) on the standardized Specific Uptake Ratio (SUR) in [(123)I]FP-bib SPECT studies. To this end, magnetic resonance (MR) images of 23 subjects with differences in the striatal volume of up to 44% were segmented and used to generate a database of 138 Monte Carlo simulated SPECT studies. Data included normal uptakes and pathological cases. Studies were reconstructed by filtered back projection (FBP) and the ordered-subset expectation-maximization algorithm. Quantification was carried out by applying a reference method based on regions of interest (ROIs) derived from the MR images and ROIs derived from the Automated Anatomical Labelling map. Our results showed that, regardless of anatomical variability, the relationship between calculated and true SUR values for caudate and putamen could be described by a multiple linear model which took into account the spill-over phenomenon caused by PVE (R² ≥ 0.963 for caudate and ≥0.980 for putamen) and also by a simple linear model (R(2) ≥ 0.952 for caudate and ≥0.973 for putamen). Calculated values were standardized by inverting both linear systems. Differences between standardized and true values showed that, although the multiple linear model was the best approach in terms of variability (X² ≥ 11.79 for caudate and ≤7.36 for putamen), standardization based on a simple linear model was also suitable (X² ≥ 12.44 for caudate and ≤12.57 for putamen).

Quantification of rat brain SPECT with (123)I-ioflupane: evaluation of different reconstruction methods and image degradation compensations using Monte Carlo simulation.

SPECT studies with (123)I-ioflupane facilitate the diagnosis of Parkinsons disease (PD). The effect on quantification of image degradations has been extensively evaluated in human studies but their impact on studies of experimental PD models is still unclear. The aim of this work was to assess the effect of compensating for the degrading phenomena on the quantification of small animal SPECT studies using (123)I-ioflupane. This assessment enabled us to evaluate the feasibility of quantitatively detecting small pathological changes using different reconstruction methods and levels of compensation for the image degrading phenomena. Monte Carlo simulated studies of a rat phantom were reconstructed and quantified. Compensations for point spread function (PSF), scattering, attenuation and partial volume effect were progressively included in the quantification protocol. A linear relationship was found between calculated and simulated specific uptake ratio (SUR) in all cases. In order to significantly distinguish disease stages, noise-reduction during the reconstruction process was the most relevant factor, followed by PSF compensation. The smallest detectable SUR interval was determined by biological variability rather than by image degradations or coregistration errors. The quantification methods that gave the best results allowed us to distinguish PD stages with SUR values that are as close as 0.5 using groups of six rats to represent each stage.