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The paper presents the prototype of a Personal Health System (PHS) realized during the Smart Health 2.0 Project. This implementation, called 'LiSE', represents an evolution with respect to the Citizen's Personal Notebook, introduced and specified by the EHR Italian regulations. The PHR provides some features that simplify the relationships between key players in NHS, like health care workers and patients. The PHR tools, such as the clinical dossier, the virtual medical assistant, or the GP/patient communication system, make the patient 'closer' to the health system, improving the own knowledge about her/his illness and, consequently, making him/her part active and conscious in the care processes. The PHS is able to enrich the EHR with information on the patient's health state and, at the same time, to take advantage of information extracted from the EHR content and supplied in a language and a format accessible to the patient. The proposed PHS, equipped with its own business logic to support patient empowerment, is the key element for the construction of a health care model based on a patient-centered vision of the healthcare.

Most advanced radiotherapy planning can be optimized by incorporating the metabolic image of the tumour to be irradiated (Metabolic Target Volume). MTV can be properly obtained by in vivo molecular imaging studies as the volume of metabolically active tumour component. Positron EmissionTomography (PET) can provide MTV by in vivo measuring the glucose metabolism of a tumour. Aim of this work was to develop an innovative PET image segmentation method, based on an adaptive threshold of the image signal-to-noise ratio, for the estimation of the MTV. The proposed method was tested on a set of anthropomorphic phantoms proving its feasibility, operator-independency and accuracy in a clinical setting.

Fibroids are benign tumors growing in the uterus. Most of fibroids do not require treatment unless they are causing symptoms. Traditional surgery treatments, like myomectomy and hysterectomy, are very invasive therapeutic approaches which not always preserves reproductive potential of the woman. MRgFUS, performed with Insightec ExAblate 2100 equipment, is a new and noninvasive technique for uterine fibroids treatment, not requiring hospitalization and recovery time for patients. An initial assessment of MRgFUS treatment is made by computing the ablated volume of uterine fibroid. In this paper a semi-automatic approach, based on region-growing segmentation technique, is proposed. The implemented approach gives a quantitative and qualitative evaluation of the treatment providing the volume and the three-dimensional (3D) model of the treated fibroid area. Considering these characteristics, the proposed approach can be used as a tool to integrate the information used by a Medical Decision Support System (MDSS). As step in the MRgFUS treatment evaluation, the achieved results improve the current methodology based on the manual uterine fibroid ROT segmentation. © 2013 IEEE.

Specific genome copy number alterations, such as deletions and amplifications are an important factor in tumor development and progression, and are also associated with changes in gene expression. By combining analyses of gene expression and genome copy number we identified genes as candidate biomarkers of BC which were validated as prognostic factors of the disease progression. These results suggest that the proposed combined approach may become a valuable method for BC prognosis.

Purpose: Cardiac PET and SPECT images are known to suffer from degradation due to cardiac and respiratory motion. In this work we describe a dynamic heart phantom, that we designed and built, to simulate both these movements. The phantom can be used: (i) to study the degradation effects due to the heart motion on PET/SPECT images and (ii) to evaluate and optimize motion corrections/compensation techniques for PET/SPECT heart studies. Methods: The phantom consists of two main parts. The first one simulates the left ventricle and its contraction while the second one (a moving platform) simulate the respiratory motion. The phantom has been tested in a number of different acquisition configurations (no motion, with only respiratory or cardiac motion, with both cardiac and respiratory motion) to study the effects of heart motion on the reconstructed PET images. On the same set of data we tested the capability of single and double gated, acquisition and reconstruction techniques, to account and compensate for the heart motion. Results: The phantom was able to simulate well both cardiac and/or respiratory motion. In the PET studies we were able to assess the effects of motion on the image quality as well as on the quantitative accuracy of PET data. We found that double gated PET acquisition and reconstructions techniques were effective in recovering the true radioactivity distribution compared to that of the reference static condition (no motion). Conclusions: We have successfully designed and built a compact heart dynamic phantom capable of cardiac and respiratory motion. The phantom can be useful in the assessment of motion degradation on cardiac PET/SPECT images. Furthermore, the phantom can also be used in the evaluation and optimization of gating acquisition and reconstruction techniques as well as in the evaluation of corrections techniques aiming to account and compensate for heart motion

Decision support systems for the assisted medical diagnosis offer the main feature of giving assessments which are poorly affected from arbitrary clinical reasoning. Aim of this work was to assess the feasibility of a decision support system for the assisted diagnosis of brain cancer, such approach presenting potential for early diagnosis of tumors and for the classification of the degree of the disease progression. For this purpose, a supervised learning algorithm combined with a pattern recognition method was developed and cross-validated in 18F-FDG PET studies of a model of a brain tumour implantation.

Removal of interplane septa in a PET scanner en- ables acquisition of all possible lines of response (3-D mode) in an effort to maximize the available number of detected events. One problem with this method at high count rates, however, is a markedly increased deadtime and randoms rate, which has a deleterious effect on data quality. The noise-equivalent count- rate (NEC) performance of a neuro-PET scanner has been de- termined with and without interplane septa on uniform cylin- drical phantoms of differing radii and in human studies to assess the optimum count rate conditions that realise the maximum gain. In the brain, the effective gain in NEC performance for 3-D ranges from >5 at low count rates to ~3.3 at 200 kcps (equivalent to 37 kcps in 2-D). The gains of the 3-D method assessed by this analysis are significant, and are shown to be highly dependent on count rate and object dimensions. I. INTRODUCTION OMPARISONS of count rate performance between C different positron emission tomography (PET) scan- ners, or a single scanner operating under different condi- tions, are difficult to make because of the vastly different strategies for handling physical effects such as scattered events and random (accidental) coincidences. A naive as- sessment of acquired coincidences will fail to examine the numbers of scattered or random events included in this figure. Differences in design, composition of detectors and septa together with methods for handling corrections ne- cessitates a method for analysing such data that includes these effects and their contribution in degrading image quality. The noise-equivalent count rate (NEC) method proposed by Strother et a/. (I) provides a means for mak- ing meaningful intercomparisons that incorporate these ef- fects. This analysis technique has been applied to a neuro- PET scanner (953B, Siemens-CTI, Knoxville, TN) which can operate with or without interplane septa. The scanner utilizes block technology detectors and contains 16 indi- vidual rings each 6.5 mm thick axially, which results in

At Ferrara University the authors have built a dedicated 3-D PET scanner (YAPPET) with a very high spatial resolution and sensitivity as necessary for radiopharmaceutical studies on rats and mice. In collaboration with the Institute H.S. Raffaele in Milano the authors have performed both distribution and dynamical uptake studies of various radioactive tracers in rats. They have performed tomographic studies after injecting live rats with FDG and FESP labeled with /sup 18/F, with FE-CIT and Flumazenil labeled with /sup 11/C, and with /sup 18/F. The /sup 18/F-FDG, /sup 18/F-FESP and /sup 11/C-FE-CIT images show the different distribution of the various tracers in the rat brain. The /sup 18/F was injected for imaging the rat skeleton. In addition, the authors studied the uptake and washout curve of /sup 11/C Flumazenil in the rat brain from tomographic images.

A nonlinear regularizing least-square reconstruction criterion is proposed for simultaneously estimating a single-photon emission computed tomography (SPECT) emission distribution corrected for attenuation together with its degree of regularization. Only a regularization trend has to be defined and tuned once for all on a reference study. Given this regularization trend, the precise regularization weight, which is usually fixed a priori, is automatically computed for each data set to adapt to the noise content of the data. We demonstrate that this adaptive process yields better results when the noise conditions change than when the regularization weight is kept constant. This adaptation is illustrated on simulated cardiac data for noise variations due to changes in the acquisition duration, background intensity, and attenuation map.

The accurate correlation of complementary structural and functional images of the human brain (brain mapping) is now an essential component of studies of brain functional anatomy. This paper describes a generalized validation procedure for multi-modal image registration in an individual subject. We first measured the distortions of the magnetic resonance imaging (MRI) and positron emission tomography (PET) scanners used for structural and functional imaging, and implemented distortion corrections. We then designed and built a multi-modal validation phantom with markers that are visible in MRI, PET, and SPECT. We scanned the phantom in MRI and PET, corrected the resulting images for distortion, correlated the images using a well-known registration algorithm, and determined the accuracy of the resulting fit. The procedure is general enough for validating most single-subject, multi-modal correlation protocols, and the results are useful in designing automated correlation procedures.