A kinetics-based approach to amyloid PET semi-quantification.

PURPOSE: To develop and validate a semi-quantification method (time-delayed ratio, TDr) applied to amyloid PET scans, based on tracer kinetics information. METHODS: The TDr method requires two static scans per subject: one early (~ 0-10 min after the injection) and one late (typically 50-70 min or 90-100 min after the injection, depending on the tracer). High perfusion regions are delineated on the early scan and applied onto the late scan. A SUVr-like ratio is calculated between the average intensities in the high perfusion regions and the late scan hotspot. TDr was applied to a naturalistic multicenter dataset of 143 subjects acquired with [18F]florbetapir. TDr values are compared to visual evaluation, cortical-cerebellar SUVr, and to the geometrical semi-quantification method ELBA. All three methods are gauged versus the heterogeneity of the dataset. RESULTS: TDr shows excellent agreement with respect to the binary visual assessment (AUC = 0.99) and significantly correlates with both validated semi-quantification methods, reaching a Pearson correlation coefficient of 0.86 with respect to ELBA. CONCLUSIONS: TDr is an alternative approach to previously validated ones (SUVr and ELBA). It requires minimal image processing; it is independent on predefined regions of interest and does not require MR registration. Besides, it takes advantage on the availability of early scans which are becoming common practice while imposing a negligible added patient discomfort.

Trafficking and homing of systemically administered stem cells: the need for appropriate analysis tools of radionuclide images.

AIM: Despite its enormous relevance, homing of hematopoietic stem cells (SCs) remains relatively uncertain due to the limitations of measuring small number of systemically administered cells in the different organs. Despite its high sensitivity, radionuclide detection has been relatively underutilized to this purpose since it cannot differentiate hematopietic SCs recruited by target tissues from those circulating in the blood pool. Our study aims to verify the potential of tracer kinetic approaches in estimating the recruitment of labeled SCs after their systemic administration. METHODS: Twenty-four Lewis rats underwent administration of 2 millions cells labeled with 37 MBq of 99mTc-exametazime. Animals were divided into 2 groups according to administered cells: hematopoietic SCs or cells obtained from a line of rat hepatoma. Cell injection was performed during a planar dynamic acquisition. Regions of interest were positioned to plot time activity curves on heart, lungs, liver and spleen. Blood cell clearance was evaluated according to common stochastic analysis approach. Either fraction of dose in each organ at the end of the experiment or computing the slope of regression line provided by Patlak or Logan graphical approach estimated cell recruitment. At the end of the study, animals were sacrificed and the number of cells retained in the same organs was estimated by in vitro counting. RESULTS: Cell number, documented by the dose fraction retained in each organ at imaging was consistently higher with respect to the "gold standard" in vitro counting in all experiments. An inverse correlation was observed between degree of overestimation and blood clearance of labeled cells (r=-0.56, P<0.05). Logan plot analysis consistently provided identifiable lines, whose slope values closely agreed with the "in vitro" estimation of hepatic and splenic cell recruitment. CONCLUSION: The simple evaluation of organ radioactivity concentration does not provide reliable estimates of local recruitment of systemically administered cells. Yet, the combined analysis of temporal trends of tracer (cell) tissue accumulation and blood clearance can provide quantitative estimations of cell homing in the different organs.

Role of quantitative myocardial perfusion PET as a clinical translation research tool.

In biology and medicine, "translational research" indicates the "translation" from the language of molecular biology in animal experiments to human physiology in order to improve our insight into the molecular mechanisms underlying the progression of cardiac diseases and to verify the mechanism of action or the potential of newly developed drugs. Positron emission tomography (PET) plays a major role in this setting due to four major characteristics: 1) extremely high sensitivity; 2) excellent temporal resolution; 3) the possibility to label molecules without altering their chemical properties and 4) the short half live of isotopes. These features make PET as an unique method able to display in the same image format different variables related to the physiology of the myocardium under different pathophysiological states, thus allowing a more precise geographical correlation of the different processes underlying disease or drug effect. This paper will review the literature available about the utilization of PET in the setting of cardiovascular pathophysiology and drug development. This task will be accomplished by describing the theory and practice of methods available to measure myocardial blood flow and to characterize myocardial metabolism in order to obtain a more precise clarification of disease phenotype. Similarly the potential of this method in defining drug effectiveness in clinical trial will be discussed, in order to offer an overview of the potential for the noninvasive measurement of physiological variables in the modern medicine.

Features extraction from time-varying cortical networks adopting a theoretical graph approach.

In this work, a novel approach is proposed in order to capture relevant features related to the structure and organization of the functional brain networks estimated in the time-frequency domain. To achieve this, we used a cascade of computational tools able to estimate first the electrical activity of the cortical surface by using high resolution EEG techniques. Then, on the cortical signals from different regions of interests we estimated the time-varying functional connectivity patterns by means of the adaptive Partial Directed Coherence. Such time-varying connectivity estimation returns a series of causality patterns evolving during the examined task which can be summarized and interpreted with the aid of mathematical indexes based on the graph theory. The combination of all these methods is demonstrated on a set of high resolution EEG data recorded from a healthy subject performing a simple foot movement.