Deconvolution-based partial volume correction in Raclopride-PET and Monte Carlo comparison to MR-based method

In this work, we evaluated three iterative deconvolution algorithms and compared their performance to partial volume (PV) correction based on structural imaging in brain positron emission tomography (PET) using a database of Monte Carlo-simulated images. We limited our interest to quantitative radioligand PET imaging, particularly to (11)C-Raclopride and striatal imaging. The studied deconvolution methods included Richardson-Lucy, reblurred Van Cittert, and reblurred Van Cittert with the total variation regularization. We studied the bias and variance of the regional estimates of binding potential (BP) values and the accuracy of regional TACs as a function of the applied image processing. The resolution/noise tradeoff in parametric BP images was addressed as well. The regional BP values and TACs obtained by deconvolution were almost as accurate than those by structural imaging-based PV correction (GTM method) when the ideal volumes of interests (VOIs) were used to extract TACs from the images. For deconvolution methods, the ideal VOIs were slightly eroded from the exact anatomical VOI to limit the bias due to tissue fraction effect which is not corrected for by deconvolution-based methods. For the GTM method, the ideal VOIs were the exact anatomical VOIs. The BP values and TACs by deconvolution were less affected by segmentation and registration errors than those with the GTM-based PV correction. The BP estimates and TACs with deconvolution-based PV correction were more accurate than BPs and TACs derived without PV correction. The parametric images obtained by the deconvolution-based PV correction showed considerably improved resolution with only slightly increased noise level compared to the case with no PV correction. The reblurred Van Cittert method was the best of the studied deconvolution methods. We conclude that the deconvolution is an interesting alternative to structural imaging-based PV correction as it leads to quantification results of similar accuracy, and it is less prone to registration and segmentation errors than structural imaging-based PV correction. Moreover, PV-corrected parametric images can be readily computed based on deconvolved dynamic images.     

Improved quantification of amyloid burden and associated biomarker cut-off points: results from the first amyloid Singaporean cohort with overlapping cerebrovascular disease

European Journal of Nuclear Medicine and Molecular Imaging - The analysis of the [11C]PiB-PET amyloid images of a unique Asian cohort of 186 participants featuring overlapping vascular diseases...     

A deficit in post-graphemic writing processes: Evidence for a graphomotor buffer

ABSTRACT

Post-graphemic writing processes transform abstract letter representations into representations of writing movements. We describe an individual with an acquired post-graphemic writing deficit. NGN is normal in spelling words aloud, but impaired in writing words to dictation, with most errors involving letter substitutions (e.g., RUMOR written as BUMOR). NGN’s deficit affects graphic motor plans, which specify the writing strokes for producing letters. Analyses of writing speed, fluency, and stroke patterns suggest that NGN’s errors result from incomplete motor-plan activation. NGN’s error rate is high for the first letter in a word, and declines across subsequent positions. On the basis of this serial position effect and other results, we propose that post-graphemic writing mechanisms include a graphomotor buffer, a writing-specific working memory that holds activated graphic motor plans bound to specific serial positions. We suggest that NGN’s graphomotor buffer is damaged such that early serial positions are affected most severely. Finally, we present results speaking to the roles and capabilities of the graphomotor buffer, and the structure of graphic motor plans.     

Motion correction of multi-frame PET data in neuroreceptor mapping: Simulation based validation

Patient motion during positron emission tomography scanning can affect the accuracy of the data analysis in two ways: 1) movement occurring during emission data acquisition alters the time activity curves (TACs), measured at a voxel or region of interest (ROI), and hence introduces errors in the parameter estimates derived from kinetic modeling; 2) emission–transmission mismatches introduce errors during attenuation and scatter correction, and hence in the radioactivity distribution estimates for each time frame of the scan. With the aim of designing an algorithm-based frame realignment method, we first conducted investigations that aimed at optimizing the parameters of a coregistration method, such as the choice of the target volume and the similarity criterion. Based on these results we designed a novel frame realignment strategy in a multi-step algorithm using uncorrected reconstructed images, cross-correlation similarity criteria for the determination of inter-frame motion parameters and emission-transmission mismatch for each frame. Features and validation results are reported here based on a multi-subject simulated [¹¹C]raclopride dynamic PET scan database incorporating intra-frame movements of various magnitudes and with various times of occurrence. Performances of the proposed algorithm were evaluated at regional and voxel-based level for binding potential parametric images.     

A PET imaging study of 5-HT(1A) receptors in cat brain after acute and chronic fluoxetine treatment

Immuno-electron microscopic and beta-microprobe studies have demonstrated that the internalization of serotonin 5-HT(1A) autoreceptors, after acute treatment with the selective 5-HT(1A) receptor agonist 8-OH-DPAT or with the specific serotonin reuptake inhibitor (SSRI) fluoxetine, is associated with a marked decrease in the in vivo binding of [(18)F]MPPF in the nucleus raphe dorsalis (NRD) of rat. To determine whether this event might be amenable to brain imaging, the present [(18)F]MPPF positron emission tomographic (PET) study was carried out in anesthetized cats given or not a single dose (5 mg/kg, i.v.) or chronically treated with fluoxetine (5 mg/kg, s.c. for 21 days). Compared to control, [(18)F]MPPF binding potential was considerably (and visibly) decreased in the cat NRD after acute fluoxetine treatment, while it remained unchanged in other brain regions. Unexpectedly, after chronic fluoxetine treatment, [(18)F]MPPF binding potential was not affected in any brain region. In parallel immuno-electron microscopic experiments carried out in rat, the density of 5-HT(1A) autoreceptors on the plasma membrane of NRD dendrites was comparable to control after chronic fluoxetine treatment. If the decrease in [(18)F]MPPF binding at the onset of SSRI treatment was detectable by PET imaging, it could potentially serve as a biological index of efficacy.     

Test-retest reproducibility of 18F-MPPF PET in healthy humans: a reliability study.

The aim of this study was to assess the reliability of 2'-methoxyphenyl-(N-2'-pyridinyl)-p-18F-fluoro-benzamidoethylpiperazine (18F-MPPF) PET binding parameter's quantification via a test-retest study over a long-term period. METHODS: Ten healthy volunteers underwent 2 dynamic 18F-MPPF PET scans in an interval of 6 mo. As a methodologic control, 10 simulated datasets, including interindividual functional and anatomic variabilities, were also used to assess the measurement variations in the absence of intraindividual variability. Indices of tracer binding were computed using 2 different models: (a) the simplified reference tissue model (SRTM) and (b) the Logan graphical model. The SRTM allows computing the binding potential (BP) index and plasma-to-brain transport constants (R1, k2). The Logan model evaluates the distribution volume (DV). For both methods, cerebellum was taken as the reference region. From both models, binding indices were calculated with time-activity curves extracted from regions of interest, on one hand, and for each voxel to perform parametric images on the other hand. RESULTS: Reliability indices--that is, bias, variability, and intraclass correlation (ICC)--indicated a good reproducibility: the BP percentage change in mean between test and retest is close to 1% in rich regions and 2% in poor regions. The typical error is around 7%. Mean ICC is over 0.70. The DV percentage change in the mean is +/-2.5%, with a typical error close to 6% and an ICC over 0.60. CONCLUSION: Our results show a good reliability, with a reasonable level of intraindividual biologic variability that allows crossover studies with 18F-MPPF in which small percentage changes are expected between test and retest measurements, in group studies and for single subject assessment.     

Simulation-based evaluation of OSEM iterative reconstruction methods in dynamic brain PET studies

The reconstruction of dynamic PET data is usually performed using filtered backprojection algorithms (FBP). This method is fast, robust, linear and yields reliable quantitative results. However, the use of FBP for low count data, such as dynamic PET data, generally results in poor visual image quality, exhibiting high noise, disturbing streak artifacts and low contrast. These signal-to-noise ratio and contrast in the reconstructed images may alter the quantification of physiological indexes, such as the regional Binding Potential (BP) obtained from kinetic modeling. Iterative reconstruction methods are often presented as viable alternatives to FBP reconstruction. In this study, we investigated the characteristics of the UW-OSEM and the ANW-OSEM iterative reconstruction methods in the context of ligand-receptor PET studies with low counts. The assessment was conducted using replicates of simulated [18F]MPPF acquisitions. The quantitative accuracy obtained with the iterative and analytical methods was compared. The results show that analytical methods are more robust to the low count data than iterative methods, and therefore enable a better estimate of the regional activity values and binding potential. The positivity constraint in MLEM-based algorithms leads to overestimations of the activity in regions with low activity concentration, typically the cerebellum. This overestimation results in significant bias in BP estimates with iterative reconstruction methods. The bias is confirmed from the reconstruction of real PET data.     

Breast cancer incidence and hormone replacement therapy: results from the MISSION study, prospective phase.

BACKGROUND: The MISSION Study (Menopause: Risk of Breast Cancer, Morbidity and Prevalence) is a historical-prospective study with random patient selection to determine breast cancer incidence in postmenopausal women with or without hormone replacement therapy (HRT). The first prospective follow-up phase started on 5 January 2004 and the cut-off date for data collection was 30 June 2006. PARTICIPANTS: Patients were divided into two groups: an 'exposed group' of women on HRT regimens commonly prescribed in France or who had stopped < or =5 years previously; and an 'unexposed group' of women who had never received HRT or stopped >5 years previously. In total 6755 patients were included; and prospective data were available for 4949 patients: 2693 in the exposed group and 2256 in the unexposed group. Women in the exposed group were younger, less overweight, and had fewer first-degree family histories of breast cancer than women of the unexposed group. Mean duration of HRT exposure was 8.3 years, with 31% being exposed for > or =10 years. RESULTS: The incidence of new breast cancer cases was 0.64% in the exposed group and 0.70% in the unexposed group (relative risk RR(exposed/unexposed) = 0.914, 95% confidence interval = 0.449-1.858; not modified when adjusted for age). Mean age at breast cancer diagnosis was similar in both groups. Breast cancer incidence in the exposed group was not significantly affected by the route of estradiol administration (cutaneous 0.69%; oral 0.52%) or HRT type (estradiol alone 0.28%; estradiol + progesterone 0.40%; estradiol + synthetic progestin 0.94%). CONCLUSION: No evidence was found for an increased risk of breast cancer in women exposed to HRT compared with non-exposed women.     

Validation of PET-SORTEO Monte Carlo simulations for the geometries of the MicroPET R4 and Focus 220 PET scanners

PET-SORTEO is a Monte Carlo-based simulator that enables the fast generation of realistic PET data for the geometry of the ECAT EXACT HR+ scanner. In order to address the increasing need for simulation models of animal PET imaging systems, our aim is to adapt and configure this simulation tool for small animal PET scanners, especially for the widely distributed microPET R4 and Focus 220 systems manufactured by Siemens Preclinical Solutions. We propose a simulation model that can produce realistic rodent images in order to evaluate and optimize acquisition and reconstruction protocols. The first part of this study presents the validation of SORTEO against the geometries of the R4 and the Focus 220 systems. This validation is carried out against actual measurements performed on the R4 scanner at the Montreal Neurological Institute in Canada and on the Focus 220 system of the department of radiopharmaceuticals of the Austrian Research Center in Seibersdorf. The comparison of simulated and experimental performance measurements includes spatial resolution, energy spectra, scatter fraction and count rates. In the second part of the study, we demonstrate the ability to rapidly generate realistic whole-body radioactive distributions using the MOBY phantom and give comparative example case studies of the same rodent model simulated with PET-SORTEO for the R4 and Focus 220 systems.     

Longitudinal trajectory of Amyloid‐related hippocampal subfield atrophy in nondemented elderly

Hippocampal atrophy and abnormal β‐Amyloid (Aβ) deposition are established markers of Alzheimer's disease (AD). Nonetheless, longitudinal trajectory of Aβ‐associated hippocampal subfield atrophy prior to dementia remains unclear. We hypothesized that elevated Aβ correlated with longitudinal subfield atrophy selectively in no cognitive impairment (NCI), spreading to other subfields in mild cognitive impairment (MCI). We analyzed data from two independent longitudinal cohorts of nondemented elderly, including global PET‐Aβ in AD‐vulnerable cortical regions and longitudinal subfield volumes quantified with a novel auto‐segmentation method (FreeSurfer v.6.0). Moreover, we investigated associations of Aβ‐related progressive subfield atrophy with memory decline. Across both datasets, we found a converging pattern that higher Aβ correlated with faster CA1 volume decline in NCI. This pattern spread to other hippocampal subfields in MCI group, correlating with memory decline. Our results for the first time suggest a longitudinal focal‐to‐widespread trajectory of Aβ‐associated hippocampal subfield atrophy over disease progression in nondemented elderly.