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Several advances have been made toward understanding the biology of cancer and most of them are due to robust genetic studies that led to the scientific recognition that although many patients have the same type of cancer their tumors may have harbored different molecular alterations. Personalized therapy and the development of advanced techniques of preclinical imaging and new murine models of disease are emerging concepts that are allowing mapping of disease markers in vivo and in some cases also receptor targeted therapy. Aim of this review is to illustrate some emerging models of disease that allow patient tumor implantation in mice for subsequent drug testing and advanced approaches for therapy mediated by preclinical imaging. In particular we discuss targeted therapy mediated by high frequency ultrasound and magnetic resonance, two emerging techniques in molecular preclinical therapy.

A computer-aided detection (CAD) system for the selection of lung nodules in computer tomography (CT) images is presented. The system is based on region growing (RG) algorithms and a new active contour model (ACM), implementing a local convex hull, able to draw the correct contour of the lung parenchyma and to include the pleural nodules. The CAD consists of three steps: (1) the lung parenchymal volume is segmented by means of a RG algorithm; the pleural nodules are included through the new ACM technique; (2) a RG algorithm is iteratively applied to the previously segmented volume in order to detect the candidate nodules; (3) a double-threshold cut and a neural network are applied to reduce the false positives (FPs). After having set the parameters on a clinical CT, the system works on whole scans, without the need for any manual selection. The CT database was recorded at the Pisa center of the ITALUNG-CT trial, the first Italian randomized controlled trial for the screening of the lung cancer. The detection rate of the system is 88.5% with 6.6 FPs/CT on 15 CT scans (about 4700 sectional images) with 26 nodules: 15 internal and 11 pleural. A reduction to 2.47 FPs/CT is achieved at 80% efficiency. [ABSTRACT FROM AUTHOR]

The mammography is the most effective procedure for an early diagnosis of the breast cancer. In this paper, an algorithm for detecting masses in mammographic images will be presented. The database consists of 3762 digital images acquired in several hospitals belonging to the MAGIC-5 collaboration (Medical Applications on a Grid Infrastructure Connection). A reduction of the whole image's area under investigation is achieved through a segmentation process, by means of a ROI Hunter algorithm, without loss of meaningful information. In the following classification step, feature extraction plays a fundamental role: some features give geometrical information, other ones provide shape parameters. Once the features are computed for each ROI, they are used as inputs to a supervised neural network with momentum. The output neuron provides the probability that the ROI is pathological or not. Results are provided in terms of ROC and FROC curves: the area under the ROC curve was found to be AZ = 0.862 ± 0.007, and we get a 2.8 FP/Image at a sensitivity of 82%. This software is included in the CAD station actually working in the hospitals belonging to the MAGIC-5 Collaboration. [ABSTRACT FROM AUTHOR]

X-ray radiography and x-ray tomography are important tools for noninvasive characterization of materials. Historically, the contrast mechanism used with these techniques has been absorption. However, for any given sample there are x-ray energies for which absorption contrast is poor. Alternatively, when good contrast can be obtained, radiation damage from an excessive dose may become an issue. Consequently, phase-contrast methods have in recent years been implemented at both synchrotron and laboratory facilities. A range of radiographic and tomographic demonstrations have now been made, typically utilizing the coherent flux from an insertion device at a synchrotron or a microfocus laboratory source. In this paper we demonstrate that useful results may be obtained using a bending magnet source at a synchrotron. In particular we show that the same beamline can be used to make and characterize a sample made by x-ray lithographic methods. [ABSTRACT FROM AUTHOR]