Positron Emission Tomography Template Research Articles

Poor sleep quality is associated with decreased regional brain glucose metabolism in healthy middle-aged adults

Sleep disturbance is associated with the development of neurodegenerative disease. We aimed to address the effects of sleep quality on brain glucose metabolism measured by 18F-Fl uorodeoxyglucose (18F-FDG) positron emission tomography (PET) in healthy middle-aged adults. A total of 378 healthy men (mean age: 42.8±3.6 years) were included in this study. Participants underwent brain 18F-FDG PET and completed the Korean version of the Pittsburgh Sleep Quality Index (PSQI-K). Additionally, anthropometric measurements were obtained. PETs were spatially normalized to MNI space using PET templates from SPM5 with PMOD. The Automated Anatomical Labeling 2 atlas was used to define regions of interest (ROIs). The mean uptake of each ROI was scaled to the mean of the global cortical uptake of each individual and defined as the standardized uptake value ratio (SUVR). After the logarithmic transformation of the regional SUVR, the effects of the PSQI-K on the regional SUVR were investigated using Bayesian hierarchical modeling. Brain glucose metabolism of the posterior cingulate, precuneus, and thalamus showed a negative association with total PSQI-K scores in the Bayesian model ROI-based analysis. Voxel-based analysis using statistical parametric mapping revealed a negative association between the total PSQI-K scores and brain glucose metabolism of the precuneus, postcentral gyrus, posterior cingulate, and thalamus. Poor sleep quality is negatively associated with brain glucose metabolism in the precuneus, posterior cingulate, and thalamus. Therefore, the importance of sleep should not be overlooked, even in healthy middle-aged adults.

Feasibility of 18F‐florzolotau Quantification in Patients with Alzheimer’s Disease Based on an MRI‐free Tau PET Template

AbstractBackgroundQuantification of tau accumulation using positron emission tomography (PET) is critical for the diagnosis of Alzheimer’s disease (AD). This study aimed to evaluate the feasibility of 18F‐florzolotau quantification in patients with AD using a magnetic resonance imaging (MRI)‐free tau PET template, since individual high‐resolution MRI is costly and not always available in practice.Method 18F‐florzolotau PET and MRI scans were obtained in a discovery cohort including 1) patients within the AD continuum (n = 87), 2) cognitively impaired patients with non‐AD (n = 32), and 3) cognitively unimpaired subjects (n = 24). The validation cohort comprised 24 patients with AD. Following MRI‐dependent spatial normalization (standard approach) in randomly selected subjects (n = 40) to cover the entire spectrum of cognitive function, selected PET images were averaged to create the 18F‐florzolotau‐specific template. Standardized uptake value ratios (SUVRs) were calculated in five predefined regions of interest (ROIs) including entorhinal cortex, inferior temporal cortex, temporal meta‐ROI, temporoparietal cortex, and neocortical areas. MRI‐free and MRI‐dependent methods were compared in terms of continuous and dichotomous agreement, diagnostic performances, and associations with specific cognitive domains.ResultMRI‐free SUVRs had high continuous and dichotomous agreement with MRI‐dependent measures for all ROIs (intraclass correlation coefficient ≥ 0.980; agreement ≥ 94.5%). Similar findings were observed for AD‐related effect sizes, diagnostic performances with respect to categorization across the cognitive spectrum, and associations with cognitive domains. The robustness of the MRI‐free approach was confirmed in the validation cohort.ConclusionThe use of an 18F‐florzolotau‐specific template is a valid alternative to MRI‐dependent spatial normalization, improving the clinical generalizability of this second‐generation tau tracer.

Feasibility of 18F-florzolotau quantification in patients with Alzheimer's disease based on an MRI-free tau PET template.

Quantification of tau accumulation using positron emission tomography (PET) is critical for the diagnosis of Alzheimer's disease (AD). This study aimed to evaluate the feasibility of 18F-florzolotau quantification in patients with AD using a magnetic resonance imaging (MRI)-free tau PET template, since individual high-resolution MRI is costly and not always available in practice. 18F-florzolotau PET and MRI scans were obtained in a discovery cohort including (1) patients within the AD continuum (n = 87), (2) cognitively impaired patients with non-AD (n = 32), and (3) cognitively unimpaired subjects (n = 26). The validation cohort comprised 24 patients with AD. Following MRI-dependent spatial normalization (standard approach) in randomly selected subjects (n = 40) to cover the entire spectrum of cognitive function, selected PET images were averaged to create the 18F-florzolotau-specific template. Standardized uptake value ratios (SUVRs) were calculated in five predefined regions of interest (ROIs). MRI-free and MRI-dependent methods were compared in terms of continuous and dichotomous agreement, diagnostic performances, and associations with specific cognitive domains. MRI-free SUVRs had a high continuous and dichotomous agreement with MRI-dependent measures for all ROIs (intraclass correlation coefficient ≥ 0.980; agreement ≥ 94.5%). Similar findings were observed for AD-related effect sizes, diagnostic performances with respect to categorization across the cognitive spectrum, and associations with cognitive domains. The robustness of the MRI-free approach was confirmed in the validation cohort. The use of an 18F-florzolotau-specific template is a valid alternative to MRI-dependent spatial normalization, improving the clinical generalizability of this second-generation tau tracer. • Regional 18F-florzolotau SUVRs reflecting tau accumulation in the living brains are reliable biomarkers for the diagnosis, differential diagnosis, and assessment of disease severity in patients with AD. • The 18F-florzolotau-specific template is a valid alternative to MRI-dependent spatial normalization, improving the clinical generalizability of this second-generation tau tracer.

Neurotransmitter receptor densities are associated with changes in regional Cerebral blood flow during clinical ongoing pain.

Arterial spin labelling (ASL) plays an increasingly important role in neuroimaging pain research but does not provide molecular insights regarding how regional cerebral blood flow (rCBF) relates to underlying neurotransmission. Here, we integrate ASL with positron emission tomography (PET) and brain transcriptome data to investigate the molecular substrates of rCBF underlying clinically relevant pain states. Two data sets, representing acute and chronic ongoing pain respectively, were utilised to quantify changes in rCBF; one examining pre-surgical versus post-surgical pain, and the second comparing patients with painful hand Osteoarthritis to a group of matched controls. We implemented a whole-brain spatial correlation analysis to explore associations between change in rCBF (ΔCBF) and neurotransmitter receptor distributions derived from normative PET templates. Additionally, we utilised transcriptomic data from the Allen Brain Atlas to inform distributions of receptor expression. Both datasets presented significant correlations of ΔCBF with the μ-opioid and dopamine-D2 receptor expressions, which play fundamental roles in brain activity associated with pain experiences. ΔCBF also correlated with the gene expression distributions of several receptors involved in pain processing. Overall, this is the first study illustrating the molecular basis of ongoing pain ASL indices and emphasises the potential of rCBF as a biomarker in pain research.

Spatial normalization and quantification approaches of PET imaging for neurological disorders.

Quantification approaches of positron emission tomography (PET) imaging provide user-independent evaluation of pathophysiological processes in living brains, which have been strongly recommended in clinical diagnosis of neurological disorders. Most PET quantification approaches depend on spatial normalization of PET images to brain template; however, the spatial normalization and quantification approaches have not been comprehensively reviewed. In this review, we introduced and compared PET template-based and magnetic resonance imaging (MRI)-aided spatial normalization approaches. Tracer-specific and age-specific PET brain templates were surveyed between 1999 and 2021 for 18F-FDG, 11C-PIB, 18F-Florbetapir, 18F-THK5317, and etc., as well as adaptive PET template methods. Spatial normalization-based PET quantification approaches were reviewed, including region-of-interest (ROI)-based and voxel-wise quantitative methods. Spatial normalization-based ROI segmentation approaches were introduced, including manual delineation on template, atlas-based segmentation, and multi-atlas approach. Voxel-wise quantification approaches were reviewed, including voxel-wise statistics and principal component analysis. Certain concerns and representative examples of clinical applications were provided for both ROI-based and voxel-wise quantification approaches. At last, a recipe for PET spatial normalization and quantification approaches was concluded to improve diagnosis accuracy of neurological disorders in clinical practice.

Advanced quantitative evaluation of PET systems using the ACR phantom and NiftyPET software.

PurposeA novel phantom‐imaging platform, a set of software tools, for automated and high‐precision imaging of the American College of Radiology (ACR) positron emission tomography (PET) phantom for PET/magnetic resonance (PET/MR) and PET/computed tomography (PET/CT) systems is proposed.MethodsThe key feature of this platform is the vector graphics design that facilitates the automated measurement of the knife‐edge response function and hence image resolution, using composite volume of interest templates in a 0.5 mm resolution grid applied to all inserts of the phantom. Furthermore, the proposed platform enables the generation of an accurate μ‐map for PET/MR systems with a robust alignment based on two‐stage image registration using specifically designed PET templates. The proposed platform is based on the open‐source NiftyPET software package used to generate multiple list‐mode data bootstrap realizations and image reconstructions to determine the precision of the two‐stage registration and any image‐derived statistics. For all the analyses, iterative image reconstruction was employed with and without modeled shift‐invariant point spread function and with varying iterations of the ordered subsets expectation maximization (OSEM) algorithm. The impact of the activity outside the field of view (FOV) was assessed using two acquisitions of 30 min each, with and without the activity outside the FOV.ResultsThe utility of the platform has been demonstrated by providing a standard and an advanced phantom analysis including the estimation of spatial resolution using all cylindrical inserts. In the imaging planes close to the edge of the axial FOV, we observed deterioration in the quantitative accuracy, reduced resolution (FWHM increased by 1–2 mm), reduced contrast, and background uniformity due to the activity outside the FOV. Although it slows convergence, the PSF reconstruction had a positive impact on resolution and contrast recovery, but the degree of improvement depended on the regions. The uncertainty analysis based on bootstrap resampling of raw PET data indicated high precision of the two‐stage registration.ConclusionsWe demonstrated that phantom imaging using the proposed methodology with the metric of spatial resolution and multiple bootstrap realizations may be helpful in more accurate evaluation of PET systems as well as in facilitating fine tuning for optimal imaging parameters in PET/MR and PET/CT clinical research studies.

Population-specific brain [18F]-FDG PET templates of Chinese subjects for statistical parametric mapping

Statistical Parametric Mapping (SPM) is a computational approach for analysing functional brain images like Positron Emission Tomography (PET). When performing SPM analysis for different patient populations, brain PET template images representing population-specific brain morphometry and metabolism features are helpful. However, most currently available brain PET templates were constructed using the Caucasian data. To enrich the family of publicly available brain PET templates, we created Chinese-specific template images based on 116 [18F]-fluorodeoxyglucose ([18F]-FDG) PET images of normal participants. These images were warped into a common averaged space, in which the mean and standard deviation templates were both computed. We also developed the SPM analysis programmes to facilitate easy use of the templates. Our templates were validated through the SPM analysis of Alzheimer’s and Parkinson’s patient images. The resultant SPM t-maps accurately depicted the disease-related brain regions with abnormal [18F]-FDG uptake, proving the templates’ effectiveness in brain function impairment analysis.

Serotonin 1B receptor density mapping of the human brainstem using positron emission tomography and autoradiography

The serotonin 1B (5-HT1B) receptor has lately received considerable interest in relation to psychiatric and neurological diseases, partly due to findings based on quantification using Positron Emission Tomography (PET). Although the brainstem is an important structure in this regard, PET radioligand binding quantification in brainstem areas often shows poor reliability. This study aims to improve PET quantification of 5-HT1B receptor binding in the brainstem. Volumes of interest (VOIs) were selected based on a 3D [3H]AZ10419369 Autoradiography brainstem model, which visualized 5-HT1B receptor distribution in high resolution. Two previously developed VOI delineation methods were tested and compared to a conventional manual method. For a method based on template data, a [11C]AZ10419369 PET template was created by averaging parametric binding potential (BPND) images of 52 healthy subjects. VOIs were generated based on a predefined volume and BPND thresholding and subsequently applied to test-retest [11C]AZ10419369 parametric BPND images of 8 healthy subjects. For a method based on individual subject data, VOIs were generated directly on each individual parametric image. Both methods showed improved reliability compared to a conventional manual VOI. The VOIs created with [11C]AZ10419369 template data can be automatically applied to future PET studies measuring 5-HT1B receptor binding in the brainstem.

Cross-validation of Quantitative Analytical Software Using 18F-florbetapir PET Imaging

18F-florbetapir is an amyloid β (Aβ) -targeted 18F-labeled positron emission tomography (PET) tracer for the clinical diagnosis of Alzheimer's disease. The standardized uptake value ratio (SUVR) serves as a tool with which to differentially diagnose. The present study aimed to cross-validate and compare SUVR derived from Amygo neuro and MIMneuro software. We injected 40 individuals with 18F-florbetapir and then acquired PET images from 50 to 60 minutes later. All images were separately normalized to the standard 18F-florbetapir PET template using Amygo neuro and MIMneuro. Volumes of interest (VOIs) were automatically placed on six target regions each in Amygo neuro and MIMneuro. The composite SUVR (cSUVR) and regional SUVR (rSUVR) were calculated from mean values measured in VOI. A cSUVR of>1.10 was defined as representing Aβ positivity. Correlation coefficients were calculated in the two types of software. A cSUVR>1.10 was determined by Amygo neuro and MIMneuro in 15 of the 40 individuals. The rSUVR in the posterior cingulate, parietal lobe, precuneus, and temporal lobe significantly differed between Amygo neuro and MIMneuro, whereas the cSUVR did not. The SUVR calculated by the two types of software closely correlated to each other (R=0.89-0.96, P<0.05). The cSUVR was not different between Amygo neuro and MIMneuro. We suggest that Amygo neuro is comparable to MIMneuro in quantitative analysis using SUVR for 18F-florbetapir imaging, thus facilitating the use of standardized quantitative approaches to amyloid PET imaging.

MR-based spatial normalization improves [18F]MNI-659 PET regional quantification and detectability of disease effect in the Q175 mouse model of Huntington’s disease

The positron emission tomography (PET) tracer [18F]MNI-659, selective for phosphodiesterase 10A (PDE10A), is a promising tool to assess an early biomarker for Huntington’s disease (HD). In this study we investigated [18F]MNI-659 uptake in the Q175 mouse model of HD. Given the focal striatal distribution of PDE10A as well as the striatal atrophy occurring in HD, the spatial normalization approach applied during the processing could sensibly affect the accuracy of the regional quantification. We compared the use of a magnetic resonance images (MRI) template based on individual MRI over a PET and CT templates for regional quantification and spatial normalization of [18F]MNI-659 PET images. We performed [18F]MNI-659 PET imaging in six months old heterozygous (HET) Q175 mice and wild-type (WT) littermates, followed by X-ray computed tomography (CT) scan. In the same week, individual T2-weighted MRI were acquired. Spatial normalization and regional quantification of the PET/CT images was performed on MRI, [18F]MNI-659 PET, or CT template and compared to binding potential (BPND) using volumes manually delineated on the individual MR images. Striatal volume was significantly reduced in HET mice (-7.7%, p<0.0001) compared to WT littermates. [18F]MNI-659 BPND in striatum of HET animals was significantly reduced (p<0.0001) when compared to WT littermates using all three templates. However, BPND values were significantly higher for HET mice using the PET template compared to the MRI and CT ones (p<0.0001), with an overestimation at lower activities. On the other hand, the CT template spatial normalization introduced larger variability reducing the effect size. The PET and CT template-based approaches resulted in a lower accuracy in BPND quantification with consequent decrease in the detectability of disease effect. This study demonstrates that for [18F]MNI-659 brain PET imaging in mice the use of an MRI-based spatial normalization is recommended to achieve accurate quantification and fully exploit the detectability of disease effect.

The Effect of Endogenous Adenosine on Neuronal Activity in Rats: An FDG PET Study

ABSTRACT2–18F‐fluorodeoxy‐D‐glucose (FDG) is a glucose analog that is taken up by cells and phosphorylated. The amount of FDG accumulated by cells is a measure of the rate of glycolysis, which reflects cellular activity. As the levels and actions of the neuromodulator adenosine are dynamically regulated by neuronal activity, this study was designed to test whether endogenous adenosine affects tissue accumulation of FDG as assessed by positron emission tomography (PET) or by postmortem analysis of tissue radioactivity. Rats were given an intraperitoneal injection of the adenosine A1 receptor antagonist 8‐cyclopentyl‐1,3‐dipropyl‐xanthine (DPCPX, 3 mg/kg), the adenosine kinase inhibitor ABT‐702 (3 mg/kg), or vehicle 10 minutes prior to an intravenous injection of FDG (15.4 ± 0.7 MBq per rat). Rats were then subjected to a 15 minute static PET scan. Reconstructed images were normalized to FDG PET template for rats and standard uptake values (SUVs) were calculated. To examine the regional effect of active treatment compared to vehicle, statistical parametric mapping analysis was performed. Whole‐brain FDG uptake was not affected by drug treatment. Significant regional hypometabolism was detected, particularly in cerebellum, of DPCPX‐ and ABT‐702 treated rats, relative to vehicle‐treated rats. Thus, endogenous adenosine can affect FDG accumulation although this effect is modest in quiescent rats.

Feasibility of Computed Tomography-Guided Methods for Spatial Normalization of Dopamine Transporter Positron Emission Tomography Image.

BackgroundSpatial normalization is a prerequisite step for analyzing positron emission tomography (PET) images both by using volume-of-interest (VOI) template and voxel-based analysis. Magnetic resonance (MR) or ligand-specific PET templates are currently used for spatial normalization of PET images. We used computed tomography (CT) images acquired with PET/CT scanner for the spatial normalization for [18F]-N-3-fluoropropyl-2-betacarboxymethoxy-3-beta-(4-iodophenyl) nortropane (FP-CIT) PET images and compared target-to-cerebellar standardized uptake value ratio (SUVR) values with those obtained from MR- or PET-guided spatial normalization method in healthy controls and patients with Parkinson’s disease (PD).MethodsWe included 71 healthy controls and 56 patients with PD who underwent [18F]-FP-CIT PET scans with a PET/CT scanner and T1-weighted MR scans. Spatial normalization of MR images was done with a conventional spatial normalization tool (cvMR) and with DARTEL toolbox (dtMR) in statistical parametric mapping software. The CT images were modified in two ways, skull-stripping (ssCT) and intensity transformation (itCT). We normalized PET images with cvMR-, dtMR-, ssCT-, itCT-, and PET-guided methods by using specific templates for each modality and measured striatal SUVR with a VOI template. The SUVR values measured with FreeSurfer-generated VOIs (FSVOI) overlaid on original PET images were also used as a gold standard for comparison.ResultsThe SUVR values derived from all four structure-guided spatial normalization methods were highly correlated with those measured with FSVOI (P < 0.0001). Putaminal SUVR values were highly effective for discriminating PD patients from controls. However, the PET-guided method excessively overestimated striatal SUVR values in the PD patients by more than 30% in caudate and putamen, and thereby spoiled the linearity between the striatal SUVR values in all subjects and showed lower disease discrimination ability. Two CT-guided methods showed comparable capability with the MR-guided methods in separating PD patients from controls and showed better correlation between putaminal SUVR values and the parkinsonian motor severity than the PET-guided method.ConclusionCT-guided spatial normalization methods provided reliable striatal SUVR values comparable to those obtained with MR-guided methods. CT-guided methods can be useful for analyzing dopamine transporter PET images when MR images are unavailable.

Deformation field correction for spatial normalization of PET images

Spatial normalization of positron emission tomography (PET) images is essential for population studies, yet the current state of the art in PET-to-PET registration is limited to the application of conventional deformable registration methods that were developed for structural images. A method is presented for the spatial normalization of PET images that improves their anatomical alignment over the state of the art. The approach works by correcting the deformable registration result using a model that is learned from training data having both PET and structural images. In particular, viewing the structural registration of training data as ground truth, correction factors are learned by using a generalized ridge regression at each voxel given the PET intensities and voxel locations in a population-based PET template. The trained model can then be used to obtain more accurate registration of PET images to the PET template without the use of a structural image. A cross validation evaluation on 79 subjects shows that the proposed method yields more accurate alignment of the PET images compared to deformable PET-to-PET registration as revealed by 1) a visual examination of the deformed images, 2) a smaller error in the deformation fields, and 3) a greater overlap of the deformed anatomical labels with ground truth segmentations.

Monoaminergic PET imaging and histopathological correlation in unilateral and bilateral 6-hydroxydopamine lesioned rat models of Parkinson's disease: A longitudinal in-vivo study

Carbon-11 labeled dihydrotetrabenazine (11C-DTBZ) binds to the vesicular monoamine transporter 2 and has been used to assess nigro-striatal integrity in animal models and patients with Parkinson's disease. Here, we applied 11C-DTBZ positron emission tomography (PET) to obtain longitudinally in-vivo assessment of striatal dopaminergic loss in the classic unilateral and in a novel bilateral 6-hydroxydopamine (6-OHDA) lesion rat model. Forty-four Sprague–Dawley rats were divided into 3 sub-groups: 1. 6-OHDA-induced unilateral lesion in the medial forebrain bundle, 2. bilateral lesion by injection of 6-OHDA in the third ventricle, and 3. vehicle injection in either site. 11C-DTBZ PET studies were investigated in the same animals successively at baseline, 1, 3 and 6weeks after lesion using an anatomically standardized volumes-of-interest approach. Additionally, 12 rats had PET and Magnetic Resonance Imaging to construct a new 11C-DTBZ PET template. Behavior was characterized by rotational, catalepsy and limb-use asymmetry tests and dopaminergic striatal denervation was validated post-mortem by immunostaining of the dopamine transporter (DAT). 11C-DTBZ PET showed a significant decrease of striatal binding (SB) values one week after the unilateral lesion. At this point, there was a 60% reduction in SB in the affected hemisphere compared with baseline values in 6-OHDA unilaterally lesioned animals. A 46% symmetric reduction over baseline SB values was found in bilaterally lesioned rats at the first week after lesion. SB values remained constant in unilaterally lesioned rats whereas animals with bilateral lesions showed a modest (22%) increase in binding values at the 3rd and 6th weeks post-lesion. The degree of striatal dopaminergic denervation was corroborated histologically by DAT immunostaining. Statistical analysis revealed a high correlation between 11C-DTBZ PET SB and striatal DAT immunostaining values (r=0.95, p<0.001). The data presented here indicate that 11C-DTBZ PET may be used to ascertain changes occurring in-vivo throughout the evolution of nigro-striatal dopaminergic neurodegeneration, mainly in the unilateral 6-OHDA lesion rat.

A Standardized [18F]-FDG-PET Template for Spatial Normalization in Statistical Parametric Mapping of Dementia

[18F]-fluorodeoxyglucose (FDG) Positron Emission Tomography (PET) is a widely used diagnostic tool that can detect and quantify pathophysiology, as assessed through changes in cerebral glucose metabolism. [18F]-FDG PET scans can be analyzed using voxel-based statistical methods such as Statistical Parametric Mapping (SPM) that provide statistical maps of brain abnormalities in single patients. In order to perform SPM, a "spatial normalization" of an individual's PET scan is required to match a reference PET template. The PET template currently used for SPM normalization is based on [15O]-H2O images and does not resemble either the specific metabolic features of [18F]-FDG brain scans or the specific morphological characteristics of individual brains affected by neurodegeneration. Thus, our aim was to create a new [18F]-FDG PET aging and dementia-specific template for spatial normalization, based on images derived from both age-matched controls and patients. We hypothesized that this template would increase spatial normalization accuracy and thereby preserve crucial information for research and diagnostic purposes. We investigated the statistical sensitivity and registration accuracy of normalization procedures based on the standard and new template-at the single-subject and group level-independently for subjects with Mild Cognitive Impairment (MCI), probable Alzheimer's Disease (AD), Frontotemporal lobar degeneration (FTLD) and dementia with Lewy bodies (DLB). We found a significant statistical effect of the population-specific FDG template-based normalisation in key anatomical regions for each dementia subtype, suggesting that spatial normalization with the new template provides more accurate estimates of metabolic abnormalities for single-subject and group analysis, and therefore, a more effective diagnostic measure.

Comparison of PET template-based and MRI-based image processing in the quantitative analysis of C11-raclopride PET

BackgroundQuantitative measures of 11C-raclopride receptor binding can be used as a correlate of postsynaptic D2 receptor density in the striatum, allowing 11C-raclopride positron emission tomography (PET) to be used for the differentiation of Parkinson’s disease from atypical parkinsonian syndromes. Comparison with reference values is recommended to establish a reliable diagnosis. A PET template specific to raclopride may facilitate direct computation of parametric maps without the need for an additional MR scan, aiding automated image analysis.MethodsSixteen healthy volunteers underwent a dynamic 11C-raclopride PET and a high-resolution T1-weighted MR scan of the brain. PET data from eight healthy subjects was processed to generate a raclopride-specific PET template normalized to standard space. Subsequently, the data processing based on the PET template was validated against the standard magnetic resonance imaging (MRI)-based method in 8 healthy subjects and 20 patients with suspected parkinsonian syndrome. Semi-quantitative image analysis was performed in Montreal Neurological Institute (MNI) and in original image space (OIS) using VOIs derived from a probabilistic brain atlas previously validated by Hammers et al. (Hum Brain Mapp, 15:165–174, 2002).ResultsThe striatal-to-cerebellar ratio (SCR) of 11C-raclopride uptake obtained using the PET template was in good agreement with the MRI-based image processing method, yielding a Lin’s concordance coefficient of 0.87. Bland-Altman analysis showed that all measurements were within the ±1.96 standard deviation range. In all 20 patients, the PET template-based processing was successful and manual volume of interest optimization had no further impact on the diagnosis of PD in this patient group. A maximal difference of <5% was found between the measured SCR in MNI space and OIS.ConclusionsThe PET template-based method for automated quantification of postsynaptic D2 receptor density is simple to implement and facilitates rapid, robust and reliable image analysis. There was no significant difference between the SCR values obtained with either PET- or MRI-based image processing. The method presented alleviates the clinical workflow and facilitates automated image analysis.

Deformation field correction for spatial normalization of PET images using a population-derived partial least squares model.

Spatial normalization of positron emission tomography (PET) images is essential for population studies, yet work on anatomically accurate PET-to-PET registration is limited. We present a method for the spatial normalization of PET images that improves their anatomical alignment based on a deformation correction model learned from structural image registration. To generate the model, we first create a population-based PET template with a corresponding structural image template. We register each PET image onto the PET template using deformable registration that consists of an affine step followed by a diffeomorphic mapping. Constraining the affine step to be the same as that obtained from the PET registration, we find the diffeomorphic mapping that will align the structural image with the structural template. We train partial least squares (PLS) regression models within small neighborhoods to relate the PET intensities and deformation fields obtained from the diffeomorphic mapping to the structural image deformation fields. The trained model can then be used to obtain more accurate registration of PET images to the PET template without the use of a structural image. A cross validation based evaluation on 79 subjects shows that our method yields more accurate alignment of the PET images compared to deformable PET-to-PET registration as revealed by 1) a visual examination of the deformed images, 2) a smaller error in the deformation fields, and 3) a greater overlap of the deformed anatomical labels with ground truth segmentations.

A computed tomography-based spatial normalization for the analysis of [18F] fluorodeoxyglucose positron emission tomography of the brain.

ObjectiveWe developed a new computed tomography (CT)-based spatial normalization method and CT template to demonstrate its usefulness in spatial normalization of positron emission tomography (PET) images with [18F] fluorodeoxyglucose (FDG) PET studies in healthy controls.Materials and MethodsSeventy healthy controls underwent brain CT scan (120 KeV, 180 mAs, and 3 mm of thickness) and [18F] FDG PET scans using a PET/CT scanner. T1-weighted magnetic resonance (MR) images were acquired for all subjects. By averaging skull-stripped and spatially-normalized MR and CT images, we created skull-stripped MR and CT templates for spatial normalization. The skull-stripped MR and CT images were spatially normalized to each structural template. PET images were spatially normalized by applying spatial transformation parameters to normalize skull-stripped MR and CT images. A conventional perfusion PET template was used for PET-based spatial normalization. Regional standardized uptake values (SUV) measured by overlaying the template volume of interest (VOI) were compared to those measured with FreeSurfer-generated VOI (FSVOI).ResultsAll three spatial normalization methods underestimated regional SUV values by 0.3-20% compared to those measured with FSVOI. The CT-based method showed slightly greater underestimation bias. Regional SUV values derived from all three spatial normalization methods were correlated significantly (p < 0.0001) with those measured with FSVOI.ConclusionCT-based spatial normalization may be an alternative method for structure-based spatial normalization of [18F] FDG PET when MR imaging is unavailable. Therefore, it is useful for PET/CT studies with various radiotracers whose uptake is expected to be limited to specific brain regions or highly variable within study population.

Perfusion-like template and standardized normalization-based brain image analysis using 18F-florbetapir (AV-45/Amyvid) PET

Amyloid positron emission tomography (PET) is an important noninvasive method for detecting amyloid burden in Alzheimer's disease (AD) patients. As amyloid PET images have limited anatomical information, magnetic resonance (MR) imaging is usually acquired to perform reliable spatial normalization needed for large-scale analysis. This work proposed and evaluated the performance of new MR-free spatial normalization methods using a perfusion-like template for amyloid PET imaging. Amyloid PET and MR images were collected in 35 subjects (cohort 1: 8 AD patients and 6 controls; cohort 2: 15 AD patients and 6 controls). Three ligand-related templates (AD, control, mixed group) and a perfusion-like template (pAV-45) from early time frames of amyloid PET images were constructed from cohort 1. The variations of (18)F-AV-45 standardized uptake value ratios (SUVRs) among AD patients, controls, and all subjects were tested with repeated two-way (template × brain region) analysis of variance (ANOVA) in cohort 2. (18)F-AV-45 SUVRs by region of interest analysis and voxelwise analysis between MR-based and MR-free approaches were compared and correlated to clinical and image parameters. Effect size (group mean SUVR difference between AD and control/standard deviation) was also evaluated for each template method. Significantly different (18)F-AV-45 SUVRs between MR-free spatial normalization and MR-based reference images were found among AD patients, controls, and all subjects by the effect of template and brain regions. The highest correlation (r=0.991) of (18)F-AV-45 SUVR to MR-based reference was found in the pAV-45 group. The SUVR percentage difference to MR-based reference showed the least variation and bias (control: -1.31±3.47 %; AD: -0.36±2.50 %) in the pAV-45 group as well. The voxelwise analysis showed the smallest t statistic value in pAV-45 followed by mixed, control, and AD groups when compared to MR-based reference images. Moreover, an overall larger effect size but compatible to that of MR-based reference result was observed in the pAV-45 group as compared to those of the other MR-free template. The novel MR-free template based on the early-phase perfusion images pAV-45 approach for amyloid imaging showed significantly better performance in quantitation accuracy, effect size, and stability when compared with other MR-free PET templates and thus has potential for large-scale clinical applications.

Comparison of MRI based and PET template based approaches in the quantitative analysis of amyloid imaging with PIB-PET

[(11)C]Pittsburgh compound-B (PIB) has been the most widely used positron emission tomography (PET) imaging agent for brain amyloid. Several longitudinal studies evaluating the progression of Alzheimer's disease (AD), and numerous therapeutic intervention studies are underway using [(11)C]PIB PET as an AD biomarker. Quantitative analysis of [(11)C]PIB data requires the definition of regional volumes of interest. This investigation systematically compared two data analysis routes both using a probabilistic brain atlas with 11 bilateral regions. Route 1 used individually segmented structural magnetic resonance images (MRI) for each subject while Route 2 used a standardised [(11)C]PIB PET template. A total of 54 subjects, 20 with probable Alzheimer's disease (AD), 14 with amnestic Mild Cognitive Impairment (MCI) and 20 age-matched healthy controls, were scanned at two imaging centres either in London (UK) or in Turku (Finland). For all subjects structural volumetric MRI and [(11)C]PIB PET scans were acquired. Target-to-cerebellum ratios 40 min to 60 min post injection were used as outcome measures. Regional read outs for grey matter target regions were generated for both routes. Based on a composite neocortical, frontal, posterior cingulate, combined posterior cingulate and frontal cortical regions, scans were categorised into either 'PIB negative' (PIB-) or 'PIB positive' (PIB+) using previously reported cut-off target-to-cerebellar ratios of 1.41, 1.5 and 1.6, respectively. Target-to-cerebellum ratios were greater when defined with a [(11)C]PIB PET template than with individual MRIs for all cortical regions regardless of diagnosis. This difference was highly significant for controls (p<0.001, paired samples t-test), less significant for MCIs and borderline for ADs. Assignment of subjects to raised or normal categories was the same with both routes with a 1.6 cut-off while with lower cut off using frontal cortex, and combined frontal cortex and posterior cingulate demonstrated similar results, while posterior cingulate alone demonstrated significantly higher proportion of controls as amyloid positive by Route 2. Definition of cortical grey matter regions is more accurate when individually segmented MRIs (Route 1) were used rather than a population-based PET template (Route 2). The impact of this difference depends on the grey-to-white matter contrast in the PET images; specifically seen in healthy controls with high white matter and low grey matter uptake. When classifying AD, MCI and control subjects as normal or abnormal using large cortical regions; discordance was found between the MRI and template approach for those few subjects who presented with cortex-to-cerebellum ratios very close to the pre-assigned cut-off. However, posterior cingulate alone demonstrated significant discordance in healthy controls using template based approach. This study, therefore, demonstrates that the use of a [(11)C]PIB PET template (Route 2) is adequate for clinical diagnostic purposes, while MRI based analysis (Route 1) remains more appropriate for clinical research.