Nano-scale simulation of neuronal damage by galactic cosmic rays.

The effects of realistic, deep space radiation environments on neuronal function remain largely unexplored.In silicomodeling studies of radiation-induced neuronal damage provide important quantitative information about physico-chemical processes that are not directly accessible through radiobiological experiments. Here, we present the first nano-scale computational analysis of broad-spectrum galactic cosmic ray irradiation in a realistic neuron geometry. We constructed thousands ofin silicorealizations of a CA1 pyramidal neuron, each with over 3500 stochastically generated dendritic spines. We simulated the entire 33 ion-energy beam spectrum currently in use at the NASA Space Radiation Laboratory galactic cosmic ray simulator (GCRSim) using the TOol for PArticle Simulation (TOPAS) and TOPAS-nBio Monte Carlo-based track structure simulation toolkits. We then assessed the resulting nano-scale dosimetry, physics processes, and fluence patterns. Additional comparisons were made to a simplified 6 ion-energy spectrum (SimGCRSim) also used in NASA experiments. For a neuronal absorbed dose of 0.5 Gy GCRSim, we report an average of 250 ± 10 ionizations per micrometer of dendritic length, and an additional 50 ± 10, 7 ± 2, and 4 ± 2 ionizations per mushroom, thin, and stubby spine, respectively. We show that neuronal energy deposition by proton andα-particle tracks declines approximately hyperbolically with increasing primary particle energy at mission-relevant energies. We demonstrate an inverted exponential relationship between dendritic segment irradiation probability and neuronal absorbed dose for each ion-energy beam. We also find that there are no significant differences in the average physical responses between the GCRSim and SimGCRSim spectra. To our knowledge, this is the first nano-scale simulation study of a realistic neuron geometry using the GCRSim and SimGCRSim spectra. These results may be used as inputs to theoretical models, aid in the interpretation of experimental results, and help guide future study designs.

18F-FDG Is a Superior Indicator of Cognitive Performance Compared to 18F-Florbetapir in Alzheimer's Disease and Mild Cognitive Impairment Evaluation: A Global Quantitative Analysis.

BACKGROUND: 18F-Fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) and 18F-florbetapir PET are approved neuroimaging biomarkers for the Alzheimer's disease (AD) and mild cognitive impairment (MCI). OBJECTIVES: This study aims to compare the efficacy of 18F-FDG and 18F-florbetapir PET at evaluating the cognitive performance of patients with AD, MCI, and normal controls (NC). METHODS: 63 subjects (36 male/27 female, mean age = 68.3) including 19 AD, 23 MCI, and 21 NC underwent 18F-FDG and 18F-florbetapir PET imaging. A global quantification approach was applied on supra-tentorial, frontal, parieto-occipital, temporal, and cerebellar brain regions by calculating the global SUVmean ratios (GSUVr) as the weighted average of all regional SUVmean. 18F-FDG and 18F-florbetapir GSUVr of each region were subsequently correlated with the Mini-Mental State Examination (MMSE). RESULTS: Subjects were studied in five categories as NC, MCI patients, AD patients, MCI and AD patients grouped together (MCI/AD), and a group including all the subjects (NC/MCI/AD). Both 18F-FDG and 18F-florbetapir could successfully detect subjects with dementia (p < 0.001). Studied in all regions and groups, the correlation analysis of 18F-FDG GSUVr with MMSE scores was significant in more regions and groups compared to that of 18F-florbetapir. We also demonstrated that the correlation of 18F-FDG GSUVr with MMSE is stronger than that of 18F-florbetapir in the supra-tentorial and temporal regions. CONCLUSIONS: This study reveals how 18F-FDG-PET global quantification is a superior indicator of cognitive performance in AD and MCI patients compared to 18F-florbetapir PET. Accordingly, we still recommend 18F-FDG-PET over amyloid imaging in the evaluation for AD and MCI.

Global temporal lobe asymmetry as a semi-quantitative imaging biomarker for temporal lobe epilepsy lateralization: A machine learning classification study.

OBJECTIVE: The purpose of this study was to evaluate the utility of global semi-quantitative analysis via fluorine-18-flurodeoxyglucose positron emission tomography (18F-FDG PET) at lateralizing seizure foci and diagnosing patients with unilateral temporal lobe epilepsy (TLE). METHODS: Seventeen patients with unilateral TLE (11 right TLE and 6 left TLE) were retrospectively selected for semi-quantitative 18F-FDG PET analysis. Twenty-three control subjects with a Mini Mental State Examination (MMSE) score of 29 or greater were selected for comparison. Globally averaged standardized uptake value (gSUVmean) was computed for each temporal lobe. Lateralization indices (LI) and the absolute value of lateralization indices (|LI|) were calculated to assess the degree of asymmetry in each subject. Logistic regression analyses were performed at a probability cutoff of 0.5 to classify TLE patients as left or right TLE and to discriminate patients from control subjects. Receiver operating characteristic (ROC) curves were generated to evaluate the utility of LI and |LI| as classification predictors. The Bland Altman test was used to evaluate the reproducibility of the measurements. RESULTS: There was a statistically significant difference in gSUVmean computed LI between left and right TLE patients (P<0.01). There was no statistically significant difference in |LI| between the patient and control groups (P=0.22). Logistic regression revealed that 82% of TLE patients were lateralized correctly using LI as the sole predictor. The area under the ROC curve (AUC) was 0.80. Logistic regression using |LI| on the combined patient/control population showed a diagnostic accuracy of 65% and an AUC of 0.44. Bland Altman analysis revealed an intra-observer reproducibility of 96% and an inter-observer reproducibility of 96% and 91% on successive trials. CONCLUSION: We conclude that gSUVmean computed LI is a reliable and reproducible measure for predicting seizure lateralization in unilateral TLE patients. However, gSUVmean computed |LI| does not appear to be particularly effective at diagnosing TLE patients from control subjects. Further studies with more patients should investigate other machine learning techniques that combine gSUVmean with other diagnostic predictors.

Novel assessment of global metabolism by 18F-FDG-PET for localizing affected lobe in temporal lobe epilepsy.

The aim of this study was to develop a novel method of global quantitative analysis for use in the diagnosis and treatment evaluation of temporal lobe epilepsy (TLE). We studied 16 patients diagnosed with TLE who underwent fluorine-18 fluorodeoxyglucose-PET (F-FDG-PET) and MRI at the Hospital of the University of Pennsylvania. To quantify temporal lobe hypometabolism, we averaged the mean standardized uptake value across regions of interest (ROIs) encompassing each lobe in its entirety and calculated the metabolic ratios and lateralization indices for each patient on the basis of global measurements. For comparison, we carried out a traditional 'punch biopsy' ROI analysis by averaging the mean standardized uptake value within 1 cm diameter ROIs across select slices. Both techniques were performed twice by the same rater to test intraobserver variability. An expert observer carried out visual analyses of both F-FDG-PET and MRI for reference. The global quantitative analysis identified a seizure focus lateralization in agreement with clinical evaluations for 91% of patients on both trials, with intraclass correlation coefficients of 0.97 and 0.92 for metabolic ratios and lateralization indices, respectively. The punch biopsy analysis was in agreement for 91 and 82% of patients on respective trials, with intraclass correlation coefficients of 0.90 and 0.75. Expert visual analyses carried out on F-FDG-PET and MRI were in agreement for 64 and 9% of patients, respectively. The global quantitative analysis proved to be the most accurate and reliable of the methods tested. This technique has the potential to improve metabolic analysis in TLE and other neuropsychiatric disorders.

Applications of global quantitative 18F-FDG-PET analysis in temporal lobe epilepsy.

Temporal lobe epilepsy (TLE) is a prevalent neurodegenerative disease associated with various neuropsychiatric disorders and decreased quality of life. Much has been said about the use of fluorine-18 fluorodeoxyglucose positron emission tomography (18F-FDG-PET), magnetic resonance imaging (MRI), and computed tomography in the qualitative assessment of TLE. However, research into the applications of quantitative measurements to treat and diagnose TLE is severely lacking in the literature. Global quantitative analysis using 18F-FDG-PET is a powerful tool in the metabolic assessment of TLE, and can more accurately identify seizure lateralization and the potential effects of treatment as compared with visual assessments and traditional biopsy region-of-interest quantification. Therefore, there is a pressing need to introduce these novel methods to the treatment of TLE. Although 18F-FDG-PET is most commonly used for visual assessments, qualitative analysis is associated with high levels of interobserver and intraobserver variability. Semiquantitative analysis using standardized uptake value is a more consistently accurate measure of the hypometabolic patterns seen in TLE patients. Novel methods of global quantitative analysis developed in our laboratory have the potential to improve TLE assessment by limiting variability and correcting for the partial volume effect. It is of great importance to adopt these techniques into the mainstream diagnosis and treatment of TLE in order to improve patient care worldwide.