Functional Data Analysis of Dynamic PET Data.

One application of positron emission tomography (PET), a nuclear imaging technique, in neuroscience involves in vivo estimation of the density of various proteins (often, neuroreceptors) in the brain. PET scanning begins with the injection of a radiolabeled tracer that binds preferentially to the target protein; tracer molecules are then continuously delivered to the brain via the bloodstream. By detecting the radioactive decay of the tracer over time, dynamic PET data are constructed to reflect the concentration of the target protein in the brain at each time.

Nonlinear Mixed-Effects Models for PET Data.

Objective: The current state-of-the-art for compartment modeling of dynamic PET data can be described as a two-stage approach. In Stage 1, individual estimates of kinetic parameters are obtained by fitting models using standard techniques, such as nonlinear least squares, to each individual's data one subject at a time. Population-level effects, such as the difference between diagnostic groups, are analyzed in Stage 2 using standard statistical methods by treating the individual estimates as if they were observed data.

Variable Selection in Function-on-Scalar Regression.

For regression models with functional responses and scalar predictors, it is common for the number of predictors to be large. Despite this, few methods for variable selection exist for function-on-scalar models, and none account for the inherent correlation of residual curves in such models. By expanding the coefficient functions using a -spline basis, we pose the function-on-scalar model as a multivariate regression problem.

Effects of serelaxin in acute heart failure patients with renal impairment: results from RELAX-AHF.

Background: Serelaxin showed beneficial effects on clinical outcome and trajectories of renal markers in patients with acute heart failure. We aimed to study the interaction between renal function and the treatment effect of serelaxin.

Methods: In the current post hoc analysis of the RELAX-AHF trial, we included all patients with available estimated glomerular filtration rate (eGFR) at baseline (n = 1132).

Functional Data Classification: A Wavelet Approach.

In recent years, several methods have been proposed to deal with functional data classification problems (e.g., one-dimensional curves or two- or three-dimensional images).

fMRI response to negative words and SSRI treatment outcome in major depressive disorder: a preliminary study.

Clinically useful predictors of treatment outcome in major depressive disorder (MDD) remain elusive. We examined associations between functional magnetic resonance imaging (fMRI) blood oxygen level dependent (BOLD) signal during active negative word processing and subsequent selective serotonin reuptake inhibitor (SSRI) treatment outcome in MDD. Unmedicated MDD subjects (n=17) performed an emotional word processing fMRI task, and then received eight weeks of standardized antidepressant treatment with escitalopram.