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The aim of this work was to assess lesion detectability and quantification in whole body oncological [sup.18]F-FDG studies performed by a state-of-the-art integrated Positron Emission Tomograph/computed tomography (PET/CT) system. Lesion detectability and quantification were assessed by a Monte Carlo (MC) simulation approach as a function of different physical factors (e.g., attenuation and scatter), image counting statistics, lesion size and position, lesion-to-background radioactivity concentration ratio (L/B), and reconstruction algorithms. The results of this work brought to a number of conclusions. * The MC code PET-electron gamma shower (EGS) was accurate in simulating the physical response of the considered PET/CT scanner (> 90%). * PET-EGS and patient-derived phantoms can be used in [simulating.sup.18] F-FDG PET oncological studies. * Counting statistics is a dominant factor in lesion detectability. * Correction for scatter (from both inside and outside the field of view) is needed to improve lesion detectability. * Iterative reconstruction and attenuation correction must be used to interpret clinical images. * Re-binning algorithms are appropriate for whole-body oncological data. * A MC-based method for correction of partial volume effect is feasible. For the considered PET/CT system, limits in lesion detectability were determined in situations comparable to those of real oncological studies: at a L/B = 3 for lesions of 12 mm diameter and at a L/B = 4 for lesions of 8 mm diameter. Index Terms--Lesion detectability, Monte Carlo, PET/CT.

This work presents a new model, developed by Monte Carlo methods, to estimate noise components (scatter and random coincidences) in three-dimensional (3-D) positron emission tomography (PET). The model allows the amount, spatial, and temporal distribution of true, scattered, and random coincidences to be estimated independently for any radioactive source (both phantoms and real patients), taking proper account of system dead time. The model was applied to a 3-D NaI(TI) current-generation PET scanner for which there are no currently available methods for estimating scatter and random components in whole-body studies. The quantitative accuracy of the developed noise model was tested by comparing simulated and measured PET data in terms of physical parameters, count-rate curves, and spatial distribution profiles. Scatter and random components were assessed for phantoms representing brain, abdomen, and whole-body studies. Evidence was found of high scatter and random contribution in 3-D PET clinical studies. The clinical response of the PET system, in terms of signal-to-noise ratio, was assessed and optimized, confirming the suitability of the default energy window, although suggesting a possible improvement by setting a lower energy threshold higher than the current default. The proposed noise model applies to any current generation 3-D PET scanner and has been included in the Monte Carlo software package PET-EGS, devoted to 3-D PET and freely available from the authors. Index Terms--Monte Carlo methods, noise, positron emission tomography (PET).