Robustness of post-reconstruction and direct kinetic parameter estimates under rigid head motion in dynamic brain PET imaging.

OBJECTIVE: Dynamic PET imaging is extensively used in brain imaging to estimate parametric maps. Inter-frame motion can substantially disrupt the voxel-wise time-activity curves (TACs), leading to erroneous maps during kinetic modelling. Therefore, it is important to characterize the robustness of kinetic parameters under various motion and kinetic model related factors. METHODS: Fully 4D brain simulations ([15O]H2O and [18F]FDG dynamic datasets) were performed using a variety of clinically observed motion patterns. Increasing levels of head motion were investigated as well as varying temporal frames of motion initiation. Kinetic parameter estimation was performed using both post-reconstruction kinetic analysis and direct 4D image reconstruction to assess bias from inter-frame emission blurring and emission/attenuation mismatch. RESULTS: Kinetic parameter bias heavily depends on the time point of motion initiation. Motion initiated towards the end of the scan results in the most biased parameters. For the [18F]FDG data, k4 is the more sensitive parameter to positional changes, while K1 and blood volume were proven to be relatively robust to motion. Direct 4D image reconstruction appeared more sensitive to changes in TACs due to motion, with parameter bias spatially propagating and depending on the level of motion. CONCLUSION: Kinetic parameter bias highly depends upon the time frame at which motion occurred, with late frame motion-induced TAC discontinuities resulting in the least accurate parameters. This is of importance during prolonged data acquisition as is often the case in neuro-receptor imaging studies. In the absence of a motion correction, use of TOF information within 4D image reconstruction could limit the error propagation.

In vivo imaging of brain microglial activity in antipsychotic-free and medicated schizophrenia: a [11C](R)-PK11195 positron emission tomography study.

Positron emission tomography (PET) imaging of the 18 kDa translocator protein (TSPO) has been used to investigate whether microglial activation, an indication of neuroinflammation, is evident in the brain of adults with schizophrenia. Interpretation of these studies is confounded by potential modulatory effects of antipsychotic medication on microglial activity. In the first such study in antipsychotic-free schizophrenia, we have used [11C](R)-PK11195 PET to compare TSPO availability in a predominantly antipsychotic-naive group of moderate-to-severely symptomatic unmedicated patients (n=8), similarly symptomatic medicated patients with schizophrenia taking risperidone or paliperidone by regular intramuscular injection (n=8), and healthy comparison subjects (n=16). We found no evidence for increased TSPO availability in antipsychotic-free patients compared with healthy controls (mean difference 4%, P=0.981). However, TSPO availability was significantly elevated in medicated patients (mean increase 88%, P=0.032) across prefrontal (dorsolateral, ventrolateral, orbital), anterior cingulate and parietal cortical regions. In the patients, TSPO availability was also strongly correlated with negative symptoms measured using the Positive and Negative Syndrome Scale across all the brain regions investigated (r=0.651-0.741). We conclude that the pathophysiology of schizophrenia is not associated with microglial activation in the 2-6 year period following diagnosis. The elevation in the medicated patients may be a direct effect of the antipsychotic, although this study cannot exclude treatment resistance and/or longer illness duration as potential explanations. It also remains to be determined whether it is present only in a subset of patients, represents a pro- or anti-inflammatory state, its association with primary negative symptoms, and whether there are significant differences between antipsychotics.

Regional neuronal network failure and cognition in late-onset sporadic Alzheimer disease.

BACKGROUND AND PURPOSE: The severe cognitive deficits in Alzheimer disease are associated with structural lesions in gray and white matter in addition to changes in synaptic function. The current investigation studied the breakdown of the structure and function in regional networks involving the Papez circuit and extended neocortical association areas. MATERIALS AND METHODS: Cortical volumetric and diffusion tensor imaging (3T MR imaging), positron-emission tomography with (18)F fluorodeoxyglucose on a high-resolution research tomograph, and comprehensive neuropsychological assessments were performed in patients with late-onset sporadic Alzheimer disease, those with mild cognitive impairment, and elderly healthy controls. RESULTS: Atrophy of the medial temporal lobes was the strongest and most consistent abnormality in patients with mild cognitive impairment and Alzheimer disease. Atrophy in the temporal, frontal, and parietal regions was most strongly related to episodic memory deficits, while deficits in semantic cognition were also strongly related to reductions of glucose metabolism in the posterior cingulate cortex and temporoparietal regions. Changes in fractional anisotropy within white matter tracts, particularly in the left cingulum bundle, uncinate fasciculus, superior longitudinal fasciculus, and inferior fronto-occipital fasciculus, were significantly associated with the cognitive deficits in multiple regression analyses. Posterior cingulate and orbitofrontal metabolic deficits appeared to be related to microstructural changes in projecting white matter tracts. CONCLUSIONS: Many lesioned network components within the Papez circuit and extended neocortical association areas were significantly associated with cognitive dysfunction in both mild cognitive impairment and late-onset sporadic Alzheimer disease. Hippocampal atrophy was the most prominent lesion, with associated impairment of the uncinate and cingulum white matter microstructures and hippocampal and posterior cingulate metabolic impairment.

Optimization of methods for quantification of rCBF using high-resolution [¹5O]H2O PET images.

This study aimed to derive accurate estimates of regional cerebral blood flow (rCBF) from noisy dynamic [¹5O]H2O PET images acquired on the high-resolution research tomograph, while retaining as much as possible the high spatial resolution of this brain scanner (2-3 mm) in parametric maps of rCBF. The PET autoradiographic method and generalized linear least-squares (GLLS), with fixed or extended to include spatially variable estimates of the dispersion of the measured input function, were compared to nonlinear least-squares (NLLS) for rCBF estimation. Six healthy volunteers underwent two [¹5O]H2O PET scans with continuous arterial blood sampling. rCBF estimates were obtained from three image reconstruction methods (one analytic and two iterative, of which one includes a resolution model) to which a range of post-reconstruction filters (3D Gaussian: 2, 4 and 6 mm FWHM) were applied. The optimal injected activity was estimated to be around 11 MBq kg⁻¹ (800 MBq) by extrapolation of patient-specific noise equivalent count rates. Whole-brain rCBF values were found to be relatively insensitive to the method of reconstruction and rCBF quantification. The grey and white matter rCBF for analytic reconstruction and NLLS were 0.44 ± 0.03 and 0.15 ± 0.03 mL min⁻¹ cm⁻³, respectively, in agreement with literature values. Similar values were obtained from the other methods. For generation of parametric images using GLLS or the autoradiographic method, a filter of ≥ 4 mm was required in order to suppress noise in the PET images which otherwise produced large biases in the rCBF estimates.