Tight glycemic control results in increased global glucose uptake and an increased cerebral metabolic crisis after traumatic brain injury. The mechanisms leading to the enhancement of metabolic crisis are unclear, but delivery of more glucose through mild hyperglycemia may be necessary after traumatic brain injury.

PurposeSubcortical white matter is known to be relatively unaffected by amyloid deposition in Alzheimer’s disease (AD). We investigated the use of subcortical white matter as a reference region to quantify [18F]FDDNP binding in the human brain.MethodsDynamic [18F]FDDNP PET studies were performed on 7 control subjects and 12 AD patients. Population efflux rate constants () from subcortical white matter (centrum semiovale) and cerebellar cortex were derived by a simplified reference tissue modeling approach incorporating physiological constraints. Regional distribution volume ratio (DVR) estimates were derived using Logan and simplified reference tissue approaches, with either subcortical white matter or cerebellum as reference input. Discriminant analysis with cross-validation was performed to classify control subjects and AD patients.ResultsThe population estimates of in subcortical white matter did not differ significantly between control subjects and AD patients but the variability of individual estimates of determined in white matter was lower than that in cerebellum. Logan DVR showed dependence on the efflux rate constant in white matter. The DVR estimates in the frontal, parietal, posterior cingulate, and temporal cortices were significantly higher in the AD group (p<0.01). Incorporating all these regional DVR estimates as predictor variables in discriminant analysis yielded accurate classification of control subjects and AD patients with high sensitivity and specificity, and the results agreed well with those using the cerebellum as the reference region.ConclusionSubcortical white matter can be used as a reference region for quantitative analysis of [18F]FDDNP with the Logan method which allows more accurate and less biased binding estimates, but a population efflux rate constant has to be determined a priori.

Head movement during a PET scan (especially a dynamic scan) can affect both the qualitative and the quantitative aspects of an image, making it difficult to accurately interpret the results. The primary objective of this study was to develop a retrospective image-based movement correction (MC) method and evaluate its implementation on dynamic 2-(1-f6-[(2-18 F-fluoroethyl)(methyl)amino]-2-naphthylgethylidene)-malononitrile ( 18 F-FDDNP) PET images of cognitively intact controls and patients with Alzheimer's disease (AD). Methods: Dynamic 18 F-FDDNP PET images, used for in vivo imaging of b-amyloid plaques and neurofibrillary tangles, were obtained from 12 AD patients and 9 age-matched controls. For each study, a transmission scan was first acquired for attenuation correction. An accurate retrospective MC method that corrected for transmission-emission and emission-emission misalignments was applied to all studies. No restriction was assumed for zero movement between the transmission scan and the first emission scan. Logan analysis, with the cerebellum as the reference region, was used to estimate various regional distribution volume ratio (DVR) values in the brain before and after MC. Discriminant analysis was used to build a predictive model for group membership, using data with and without MC. Results: MC improved the image quality and quantitative values in 18 F-FDDNP PET images. In this subject population, no significant difference in DVR value was observed in the medial temporal (MTL) region of controls and patients with AD before MC. However, after MC, significant differences in DVR values in the frontal, parietal, posterior cingulate, MTL, lateral temporal (LTL), and global regions were seen between the 2 groups (P , 0.05). In controls and patients with AD, the variability of regional DVR values (as measured by the coefficient of variation) decreased on average by more than 18% after MC. Mean DVR separation between controls and patients with AD was higher in frontal, MTL, LTL, and global regions after MC. Group classification by discriminant analysis based on 18 F-FDDNP DVR values was markedly improved after MC. Conclusion: The streamlined and easy-to-use MC method presented in this work significantly improves the image quality and the measured tracer kinetics of 18 F-FDDNP PET images. The proposed MC method has the potential to be applied to PET studies on patients having other disorders (e.g., Down syndrome and Parkinson's disease) and to brain PET scans with other molecular imaging probes.

The authors have developed a rationale to improve plan quality and consistency, by evolving the plan quality criteria from institution-specific experience, complementary to national standards. The validity of the proposed method was demonstrated with a prototype system on prostate stereotactic body radiotherapy (SBRT) cases. The current study uses direct and indirect DVH endpoints for plan quality evaluation, but the infrastructure proposed here applies to general outcome data as well. The authors expect forward evaluation together with intelligent update based on evidence-based learning, which will evolve the clinical practice for improved efficiency, consistency, and ultimately better treatment outcome.

Many considerations, involving understanding and selection of multiple experimental parameters, are required to perform MicroPET studies properly. The large number of these parameters/ variables and their complicated interdependence make their optimal choice nontrivial. We have a developed kinetic imaging system (KIS), an integrated software system, to assist the planning, design, and data analysis of MicroPET studies. The system serves multiple functions-education, virtual experimentation, experimental design, and image analysis of simulated/experimental dataand consists of four main functional modules-"Dictionary," "Virtual Experimentation," "Image Analysis," and "Model Fitting." The "Dictionary" module provides didactic information on tracer kinetics, pharmacokinetic, MicroPET imaging, and relevant biological/pharmacological information. The "Virtual Experimentation" module allows users to examine via computer simulations the effect of biochemical/pharmacokinetic parameters on tissue tracer kinetics. It generates dynamic MicroPET images based on the user's assignment of kinetics or kinetic parameters to different tissue organs in a 3-D digital mouse phantom. Experimental parameters can be adjusted to investigate the design options of a MicroPET experiment. The "Image Analysis" module is a full-fledged image display/manipulation program. The "Model Fitting" module provides model-fitting capability for measured/simulated tissue kinetics. The system can be run either through the Web or as a stand-alone process. With KIS, radiotracer characteristics, administration method, dose level, imaging sequence, and image resolution-to-noise tradeoff can be evaluated using virtual experimentation. KIS is designed for biology/pharmaceutical scientists to make learning and applying tracer kinetics fun and easy.