Advances in PET Methodology

Textural properties of microglial activation in Alzheimer's disease as measured by (R)-[11C]PK11195 PET

Alzheimer's disease is the most common form of dementia worldwide, accounting for 60-70% of diagnosed cases. According to the current understanding of molecular pathogenesis, the main hallmarks of this disease are the abnormal accumulation of amyloid plaques and neurofibrillary tangles. Therefore, biomarkers reflecting these underlying biological mechanisms are recognized as valid tools for an early diagnosis of Alzheimer's disease. Inflammatory mechanisms, such as microglial activation, are known to be involved in Alzheimer's disease onset and progression. This activated state of the microglia is associated with increased expression of the translocator protein 18 kDa. On that account, PET tracers capable of measuring this signature, such as (R)-[¹¹C]PK11195, might be instrumental in assessing the state and evolution of Alzheimer's disease. This study aims to investigate the potential of Gray Level Co-occurrence Matrix-based textural parameters as an alternative to conventional quantification using kinetic models in (R)-[¹¹C]PK11195 PET images. To achieve this goal, kinetic and textural parameters were computed on (R)-[¹¹C]PK11195 PET images of 19 patients with an early diagnosis of Alzheimer's disease and 21 healthy controls and submitted separately to classification using a linear support vector machine. The classifier built using the textural parameters showed no inferior performance compared to the classical kinetic approach, yielding a slightly larger classification accuracy (accuracy of 0.7000, sensitivity of 0.6957, specificity of 0.7059 and balanced accuracy of 0.6967). In conclusion, our results support the notion that textural parameters may be an alternative to conventional quantification using kinetic models in (R)-[¹¹C]PK11195 PET images. The proposed quantification method makes it possible to use simpler scanning procedures, which increase patient comfort and convenience. We further speculate that textural parameters may also provide an alternative to kinetic analysis in (R)-[¹¹C]PK11195 PET neuroimaging studies involving other neurodegenerative disorders. Finally, we recognize that the potential role of this tracer is not in diagnosis but rather in the assessment and progression of the diffuse and dynamic distribution of inflammatory cell density in this disorder as a promising therapeutic target.

Translating a radiolabeled imaging agent to the clinic

Molecular Imaging is entering the most fruitful, exciting period in its history with many new agents under development, and several reaching the clinic in recent years. While it is unusual for just one laboratory to take an agent from initial discovery through to full clinical approval the steps along the way are important to understand for all interested participants even if one is not involved in the entire process. Here, we provide an overview of these processes beginning at discovery and preclinical validation of a new molecular imaging agent and using as an exemplar a low molecular weight disease-specific targeted positron emission tomography (PET) agent. Compared to standard drug development requirements, molecular imaging agents may benefit from a regulatory standpoint from their low mass administered doses, they nonetheless still need to go through a series of well-defined steps before they can be considered for Phase 1 human testing. After outlining the discovery and preclinical validation approaches, we will also discuss the nuances of Phase 1, Phase 2 and Phase 3 studies that may culminate in an FDA general use approval. Finally, some post-approval aspects of novel molecular imaging agents are considered.

What Has Neuroimaging Taught Us on the Neurobiology of Yoga? A Review

Yoga is becoming increasingly popular worldwide, with several implicated physical and mental benefits. Here we provide a comprehensive and critical review of the research generated from the existing neuroimaging literature in studies of yoga practitioners. We reviewed 34 international peer-reviewed neuroimaging studies of yoga using magnetic resonance imaging (MRI), positron emission tomography (PET), or single-photon emission computed tomography (SPECT): 11 morphological and 26 functional studies, including three studies that were classified as both morphological and functional. Consistent findings include increased gray matter volume in the insula and hippocampus, increased activation of prefrontal cortical regions, and functional connectivity changes mainly within the default mode network. There is quite some variability in the neuroimaging findings that partially reflects different yoga styles and approaches, as well as sample size limitations. Direct comparator groups such as physical activity are scarcely used so far. Finally, hypotheses on the underlying neurobiology derived from the imaging findings are discussed in the light of the potential beneficial effects of yoga.

Correlations of Neuropsychological and Metabolic Brain Changes in Parkinson's Disease and Other α-Synucleinopathies

Cognitive impairment is a common feature in Parkinson's disease (PD) and other α-synucleinopathies as 80% of PD patients develop dementia within 20 years. Early cognitive changes in PD patients present as a dysexecutive syndrome, broadly characterized as a disruption of the fronto-striatal dopamine network. Cognitive deficits in other domains (recognition memory, attention processes and visuospatial abilities) become apparent with the progression of PD and development of dementia. In dementia with Lewy bodies (DLB) the cognitive impairment develops early or even precedes parkinsonism and it is more pronounced in visuospatial skills and memory. Cognitive impairment in the rarer α-synucleinopathies (multiple system atrophy and pure autonomic failure) is less well studied. Metabolic brain imaging with positron emission tomography and [¹⁸F]-fluorodeoxyglucose (FDG-PET) is a well-established diagnostic method in neurodegenerative diseases, including dementias. Changes in glucose metabolism precede those seen on structural magnetic resonance imaging (MRI). Reduction in glucose metabolism and atrophy have been suggested to represent consecutive changes of neurodegeneration and are linked to specific cognitive disorders (e.g., dysexecutive syndrome, memory impairment, visuospatial deficits etc.). Advances in the statistical analysis of FDG-PET images enabling a network analysis broadened our understanding of neurodegenerative brain processes. A specific cognitive pattern related to PD was identified by applying voxel-based network modeling approach. The magnitude of this pattern correlated significantly with patients' cognitive skills. Specific metabolic brain changes were observed also in patients with DLB as well as in a prodromal phase of α-synucleinopathy: REM sleep behavior disorder. Metabolic brain imaging with FDG-PET is a reliable biomarker of neurodegenerative brain diseases throughout their course, precisely reflecting their topographic distribution, stage and functional impact.