A Mixed-Effects Model with Time Reparametrization for Longitudinal Univariate Manifold-Valued Data.

Mixed-effects models provide a rich theoretical framework for the analysis of longitudinal data. However, when used to analyze or predict the progression of a neurodegenerative disease such as Alzheimer's disease, these models usually do not take into account the fact that subjects may be at different stages of disease progression and the interpretation of the model may depend on some implicit reference time. In this paper, we propose a generative statistical model for longitudinal data, described in a univariate Riemannian manifold setting, which estimates an average disease progression model, subject-specific time shifts and acceleration factors. The time shifts account for variability in age at disease-onset time. The acceleration factors account for variability in speed of disease progression. For a given individual, the estimated time shift and acceleration factor define an affine reparametrization of the average disease progression model. This statistical model has been used to analyze neuropsychological assessments scores and cortical thickness measurements from the Alzheimer's Disease Neuroimaging Initiative database. The numerical results showed that we can distinguish between slow versus fast progressing and early versus late-onset individuals.

A method based on Monte Carlo simulations and voxelized anatomical atlases to evaluate and correct uncertainties on radiotracer accumulation quantitation in beta microprobe studies in the rat brain.

The beta-microprobe is a simple and versatile technique complementary to small animal positron emission tomography (PET). It relies on local measurements of the concentration of positron-labeled molecules. So far, it has been successfully used in anesthetized rats for pharmacokinetics experiments and for the study of brain energetic metabolism. However, the ability of the technique to provide accurate quantitative measurements using (18)F, (11)C and (15)O tracers is likely to suffer from the contribution of 511 keV gamma rays background to the signal and from the contribution of positrons from brain loci surrounding the locus of interest. The aim of the present paper is to provide a method of evaluating several parameters, which are supposed to affect the quantification of recordings performed in vivo with this methodology. We have developed realistic voxelized phantoms of the rat whole body and brain, and used them as input geometries for Monte Carlo simulations of previous beta-microprobe reports. In the context of realistic experiments (binding of (11)C-Raclopride to D2 dopaminergic receptors in the striatum; local glucose metabolic rate measurement with (18)F-FDG and H(2)O(15) blood flow measurements in the somatosensory cortex), we have calculated the detection efficiencies and corresponding contribution of 511 keV gammas from peripheral organs accumulation. We confirmed that the 511 keV gammas background does not impair quantification. To evaluate the contribution of positrons from adjacent structures, we have developed beta-Assistant, a program based on a rat brain voxelized atlas and matrices of local detection efficiencies calculated by Monte Carlo simulations for several probe geometries. This program was used to calculate the 'apparent sensitivity' of the probe for each brain structure included in the detection volume. For a given localization of a probe within the brain, this allows us to quantify the different sources of beta signal. Finally, since stereotaxic accuracy is crucial for quantification in most microprobe studies, the influence of stereotaxic positioning error was studied for several realistic experiments in favorable and unfavorable experimental situations (binding of (11)C-Raclopride to D2 dopaminergic receptors in the striatum; binding of (18)F-MPPF to 5HT1A receptors in the dorsal raphe nucleus).

The Minnesota project: a focused approach to ambulatory quality assessment.

With national HMO quality assurance requirements pending for Medicare risk contracts, three HMOs in Minnesota established a working group with the state Department of Health to develop and test a new methodology proposed for quality of care review. A two-tiered system was developed for ambulatory chart review based on 15 hospitalization diagnoses having a potential for inadequate prehospital care. This system was applied to 796 cases from the HMOs (2% of admissions). Technical problems limited actual review to 673 of these cases. Although 304 (45%) of reviewed cases failed initial screening, physician review found only 22% of such failures (10% of reviewed cases) to represent probable quality of care problems. The approach appears to be feasible and unusually efficient. Although there is considerable variability that limits its potential use for interhealth plan comparison, the approach holds promise for quality assurance within an individual health plan.