Wavelet-based methodology for [15O]-H20 PET brain activation assessment

[Abstract] AMI International Conference 2003, September 21-27, Madrid, Spain: "High Resolution Molecular Imaging: from Basic Science to Clinical Applications"Statistical parametric mapping (SPM) is a voxel-byvoxel analysis method commonly used for the detection of brain activation patterns. An alternative approach is the use of multiscale information by means of wavelet analysis. In this study, we have compared the detection of brain activations using conventional SPM and a statistical wavelet analysis in a set of realistic simulated [15O]-H20 positron emission tomography (PET) phantomsPublicad

Effect of different interpolation methods on the accuracy of the reconstruction of spiral k-space trajectories in MRI

[Poster] 4th European Molecular Imaging Meeting, Barcelona, Spain, May 27 - 30, 2009This work is supported in part by the projects CdTeaM (CeniT-ingenio 2010), Ministerio de Ciencia e innovación, and Ciber Cb07/09/0031 CiberSaM, Ministerio de Sanidad y Consumo.Publicad

FDG-PET studies of the effect of MDMA in rat brain

[Abstract] The 10th International Conference on Functional Mapping of the Human Brain, June 13-17, 2004, Budapest, HungaryAlterations of the human brain due to MDMA use are a focus of ongoing research. MDMA abuse produces both short and long-term effects on brain; MDMA-induced functional alterations of the serotonergic system are reported to alter local energy metabolism of cortical and subcortical structures. Presently, there are no FDG-PET experimental studies reported in animals. The aim of this study is to assess these brain glucose metabolism changes after a single dose of MDMA in rats by using FDG-PETPublicad

Detection of small murine lung tumours by FDG-PET

[Abstract] AMI International Conference 2003, September 21 - 27, Madrid, Spain: "High Resolution Molecular Imaging: from Basic Science to Clinical Applications"The functional information provided by 2-deoxy-2- [18F]fluoro-D-Glucose (FDG) positron emission tomography (PET) is commonly used to detect primary tumours and metastases in clinical studies. The aim of this work is to assess the possibilities of FDG-PET studies to detect small lung tumour lesions in mice, using a dedicated small animal PET scannerPublicad

Fat composition assessment by 1H and 13C spectroscopy in mice

Proceeding of: 17th Scientific Meeting, International Society for Magnetic Resonance in Medicine, 18-24 April, 2009, Honolulu, Hawai, US

Optimization of 2-DEOXY-2-[18F] FLUORO-D-GLUCOSE positron emission tomography thorax imaging of laboratory small animals

[Abstract] AMI Annual Conference 2005, March 18-23, Orlando, FloridaThe search of oncologic lesions in thorax may be hindered by the high uptake of organs such as the heart or back muscles that prevent the proper visualization of neighbor organs. The aim of this study is to analyze to what extent glucose metabolism can be modulated to obtain an optimal thorax image in micePublicad

Unsupervised CT Lung Image Segmentation of a Mycobacterium Tuberculosis Infection Model

Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis that produces pulmonary damage. Radiological imaging is the preferred technique for the assessment of TB longitudinal course. Computer-assisted identification of biomarkers eases the work of the radiologist by providing a quantitative assessment of disease. Lung segmentation is the step before biomarker extraction. In this study, we present an automatic procedure that enables robust segmentation of damaged lungs that have lesions attached to the parenchyma and are affected by respiratory movement artifacts in a Mycobacterium Tuberculosis infection model. Its main steps are the extraction of the healthy lung tissue and the airway tree followed by elimination of the fuzzy boundaries. Its performance was compared with respect to a segmentation obtained using: (1) a semi-automatic tool and (2) an approach based on fuzzy connectedness. A consensus segmentation resulting from the majority voting of three experts' annotations was considered our ground truth. The proposed approach improves the overlap indicators (Dice similarity coefficient, 94\% +/- 4\%) and the surface similarity coefficients (Hausdorff distance, 8.64 mm +/- 7.36 mm) in the majority of the most difficult-to-segment slices. Results indicate that the refined lung segmentations generated could facilitate the extraction of meaningful quantitative data on disease burden.We thank Estibaliz Gomez de Mariscal, Paula Martin Gonzalez and Mario Gonzalez Arjona for helping with the manual lung annotation. The research leading to these results received funding from the Innovative Medicines Initiative (www.imi.europa.eu) Joint Undertaking under grant agreement no. 115337, whose resources comprise funding from the European Union's Seventh Framework Programme (FP7/2007-2013) and EFPIA companies' in kind contribution. This work was partially funded by projects TEC2013-48552-C2-1-R, RTC-2015-3772-1, TEC2015-73064-EXP and TEC2016-78052-R from the Spanish Ministerio de Economia, Industria y Competitividad, TOPUS S2013/MIT-3024 project from the regional government of Madrid and by the Department of Health, UK.S