Analysis of Variance in Neuroreceptor Ligand Imaging Studies

Radioligand positron emission tomography (PET) with dual scan paradigms can provide valuable insight into changes in synaptic neurotransmitter concentration due to experimental manipulation. The residual t-test has been utilized to improve the sensitivity of the t-test in PET studies. However, no further development of statistical tests using residuals has been proposed so far to be applied in cases when there are more than two conditions. Here, we propose the residual f-test, a one-way analysis of variance (ANOVA), and examine its feasibility using simulated [11C]raclopride PET data. We also re-visit data from our previously published [11C]raclopride PET study, in which 10 individuals underwent three PET scans under different conditions. We found that the residual f-test is superior in terms of sensitivity than the conventional f-test while still controlling for type 1 error. The test will therefore allow us to reliably test hypotheses in the smaller sample sizes often used in explorative PET studies

Genetic Diversity in the SIR Model of Pathogen Evolution

We introduce a model for assessing the levels and patterns of genetic diversity in pathogen populations, whose epidemiology follows a susceptible-infected-recovered model (SIR). We model the population of pathogens as a metapopulation composed of subpopulations (infected hosts), where pathogens replicate and mutate. Hosts transmit pathogens to uninfected hosts. We show that the level of pathogen variation is well predicted by analytical expressions, such that pathogen neutral molecular variation is bounded by the level of infection and increases with the duration of infection. We then introduce selection in the model and study the invasion probability of a new pathogenic strain whose fitness (R0(1+s)) is higher than the fitness of the resident strain (R0). We show that this invasion probability is given by the relative increment in R0 of the new pathogen (s). By analyzing the patterns of genetic diversity in this framework, we identify the molecular signatures during the replacement and compare these with those observed in sequences of influenza A

Partial volume correction strategies for quantitative FDG PET in oncology

Purpose: Quantitative accuracy of positron emission tomography (PET) is affected by partial volume effects resulting in increased underestimation of the standardized uptake value (SUV) with decreasing tumour volume. The purpose of the present study was to assess accuracy and precision of different partial volume correction (PVC) methods. Methods: Three methods for PVC were evaluated: (1) inclusion of the point spread function (PSF) within the reconstruction, (2) iterative deconvolution of PET images and (3) calculation of spill-in and spill-out factors based on tumour masks. Simulations were based on a mathematical phantom with tumours of different sizes and shapes. Phantom experiments were performed in 2-D mode using the National Electrical Manufacturers Association (NEMA) NU2 image quality phantom containing six differently sized spheres. Clinical studies (2-D mode) included a test-retest study consisting of 10 patients with stage IIIB and IV non-small cell lung cancer and a response monitoring study consisting of 15 female breast cancer patients. In all studies tumour or sphere volumes of interest (VOI) were generated using VOI based on adaptive relative thresholds. Results: Simulations and experiments provided similar results. All methods were able to accurately recover true SUV within 10% for spheres equal to and larger than 1 ml. Reconstruction-based recovery, however, provided up to twofold better precision than image-based methods. Cl

Image-Derived Input Function for Human Brain Using High Resolution PET Imaging with [11C](R)-rolipram and [11C]PBR28

The aim of this study was to test seven previously published image-input methods in state-of-the-art high resolution PET brain images. Images were obtained with a High Resolution Research Tomograph plus a resolution-recovery reconstruction algorithm using two different radioligands with different radiometabolite fractions. Three of the methods required arterial blood samples to scale the image-input, and four were blood-free methods. values was quantified using a scoring system. Using the image input methods that gave the most accurate results with Logan analysis, we also performed kinetic modelling with a two-tissue compartment model.)-rolipram, which has a lower metabolite fraction. Compartment modeling gave less reliable results, especially for the estimation of individual rate constants.C]PBR28), the more difficult it is to obtain a reliable image-derived input function; and 4) in association with image inputs, graphical analyses should be preferred over compartmental modelling

Carotid Plaque Imaging with SPECT/CT and PET/CT

A major contributor to the occurrence of ischemic stroke is the existence of carotid atherosclerosis. A vulnerable carotid atherosclerotic plaque may rupture or erode, thus causing a thrombotic event. Currently, clinical decision-making with regard to carotid endarterectomy or stenting is still primarily based on the extent of luminal stenosis, estimated with CT angiography and/or (duplex) ultrasonography. However, there is growing evidence that the anatomic impact of stenosis alone has limited value in predicting the exact consequences of plaque vulnerability. Various molecular processes have, independently of degree of stenosis, shown to be importantly associated with the plaque's capability to cause thrombotic events. These molecular processes can be visualized with nuclear medicine techniques allowing the identification of vulnerable patients by non-invasive in vivo SPECT(/CT) and PET(/CT) imaging. This chapter provides an overview of SPECT(/CT) and PET(/CT) imaging with specific radiotracers that have been evaluated for the detection of plaques together with a future perspective in this field of imaging.</p