SPM analysis of FDG rat PET scans

[Abstract] AMI Annual Conference 2002, October 23 - 27, San Diego, CaliforniaPublicad

Validation of SPM analysis of visual activation in rat brain pet studies

[Abstract] AMI Annual Conference 2004, March 27-31, Orlando, FloridaStatistical parametric mapping (SPM) is used to detect subtle activity changes in brain not requiring a priori assumptions about the expected activations. We adapt the methodology for analyzing rat brain positron emission tomography (PET) scansPublicad

PET and CT image registration of the rat brain and skull using the air algorithm

Proceeding of: 2000 IEEE Nuclear Science Symposium Conference Record, Lyon, France, October 15 - 20, 2000Spatially registered PET and CT images of the same small animal offer at .least three potential advantages .over PET alone. First, the CT images should' alIow accurate, nearly noise-free correction of the PET image data for attenuation. Second, the CT images snould permit more certain identification of structures evident in the PET images and third, the CT images provide a priori anatomical information that may be of use with resolution-improving image reconstruction algorithms that model the PET imaging process. Thus far, howeyer, image registration algorithms effective in human studies have not been characterized in the small animal setting. Accordingly,'we evaluated the ability of the AIR algorithm to accurately register PET F-18 fluoride and F-18 FDG images of the rat skull and brain, respectively, to CT images acquired following each PET imaging session. The AIR algorithm was able to register the bone-to-bone images with a maximum error of less than 1.0 mm. The registration error for the brain-to-brain study, however, was greater (2.4 mm) and required additional steps and. user.intervention to segment the brail1 from the head in both data sets before registration. These preliminary results suggest that the AIR algorithm can accurately combine PET and CT images in small animals when the data sets are nearly homologous, but may require additional segmentation steps with increased mis-registration errors when registering disparate, low contrast soft tissue structures

Detection of rat brain activation using statistical parametric mapping analysis in FDG-PET studies

[Abstract] AMI International Conference 2003, September 21 - 27, Madrid, Spain: High Resolution Molecular Imaging: from Basic Science to Clinical ApplicationsStatistical parametric mapping (SPM) is an analysis technique long been used in clinical research to detect subtle activity changes in brain; it is an excellent exploratory tool as it does not require a priori assumptions about the expected brain region activations. Research in animal imaging may also take benefit from this technique, if properly adapted to the new scenario. This is the case of brain activation studies in murine models using PET tracers and dedicated imaging devices. This work proposes the use of an SPM methodology adapted to the analysis of 2-deoxy-2-[18F] fluoro-D-Glucose (FDG) positron emission tomography (PET) scans of rat brains. Advantages over conventional region of interest (ROI) based analysis were assessed in an experiment addressing the detection of brain activation in of rats which underwent three different visual stimulation paradigmsPublicad

PET, CT, and MR image registration of the rat brain and skull

Spatially registered positron emission tomography (PET), computed tomography (CT), and magnetic resonance (MR) images of the same small animal offer potential advantages over PET alone: CT images should allow accurate, nearly noise-free correction of the PET image data for attenuation; the CT or MR images should permit more certain identification of structures evident in the PET images; and CT images provide a priori anatomical information that may be of use with resolution-improving image-reconstruction algorithms that model the PET imaging process. However, image registration algorithms effective in human studies have not been characterized in the small-animal setting. Accordingly, the authors evaluated the ability of the automated image registration (AIR) and mutual information (MI) algorithms to register PET images of the rat skull and brain to CT or MR images of the same animal. External fiducial marks visible in all three modalities were used to estimate residual errors after registration. The AIR algorithm registered PET bone-to-CT bone images with a maximum error of less than 1.0 mm, The registration errors for PET brain-to-CT brain images, however, were greater, and considerable user intervention was required prior to registration. The AIR algorithm either failed or required excessive user intervention to register PET and MR brain images. In contrast, the MI algorithm yielded smaller registration errors in all scenarios with little user intervention. The MI algorithm thus appears to be a more robust method for registering PET, CT, and MR images of the rat headPublicad

Exact positioning for OSEM reconstructions on the atlas depth-of-interaction small animal scanner

[Abstract] AMI Annual Conference 2002, October 23 - 27Publicad

Inhomogeneity correction of magnetic resonance images by minimization of intensity overlapping

Proceeding of: IEEE 2003 International Conference on Image Processing (ICIP), Barcelona, Spain, 14-17 Sept. 2003This work presents a new algorithm (NIC; Non uniform Intensity Correclion) for the correction of intensity inhomogeneities in magnetic resonance images. The algorithm has been validated by means of realistic phantom images and a set of 24 real images. Evaluation using previously proposed phantom images for inhomogeneity correction algorithms allowed us to obtain results fully comparable to the previous literature on the topic. This new algorithm was also compared, using a real image dataset, to other widely used methods which are freely available in the Internet (N3, SPM'99 and SPM2). Standard quality criteria have been used for determining the goodness of the different methods. The new algorithm showed better results removing the intensity inhomogeneities and did not produce degradation when used on images free from this artifact

Detection of visual activation in the rat brain using 2-deoxy-2-[18F]fluoro-D-glucose and statistical parametric mapping (SPM)

Purpose: This study was designed to assess changes in brain glucose metabolism in rats after visual stimulation. Materials and methods: We sought to determine whether visual activation in the rat brain could be detected using a small-animal positron emission tomography (PET) scanner and 2-deoxy-2- [18F]fluoro-D-glucose (FDG). Eleven rats were divided into two groups: (a) five animals exposed to ambient light and (b) six animals stimulated by stroboscopic light (10 Hz) with one eye covered. Rats were injected with FDG and, after 45 min of visual stimulation, were sacrificed and scanned for 90 min in a dedicated PET tomograph. Images were reconstructed by a threedimensional ordered subset expectation maximization algorithm (1.8 mm full width at half maximum). A region-of-interest (ROI) analysis was performed on 14 brain structures drawn on coronal sections. Statistical parametric mapping (SPM) adapted for small animals was also carried out. Additionally, the brains of three rats were sliced into 20-μm sections for autoradiography. Results: Analysis of ROI data revealed significant differences between groups in the right superior colliculus, right thalamus, and brainstem (p≤0.05). SPM detected the same areas as the ROI approach. Autoradiographs confirmed the existence of hyperactivation in the left superior colliculus and auditory cortex. Conclusions: To our knowledge, this is the first report that uses FDG-PET and SPM analysis to show changes in rat brain glucose metabolism after a visual stimulusThis work was supported by grants from the Ministerio de Ciencia y Tecnología (TEC2004-07052), Ministerio de Sanidad y Consumo (CIBERsam CB07/09/0031 and Plan Nacional sobre Drogas 2007/043), Ministerio de Industria (CDTEAM Project), and Fundación de Investigación Médica Mutua Madrileña. We thank Alexandra de Francisco for her assistance with the PET studies, the Atomic, Molecular, and Nuclear Physics Department of the Universidad Complutense in Madrid for reconstructing the PET images, and the National Institute of Health for facilitating the piPET system.Publicad

The knee prosthesis constraint dilemma: Biomechanical comparison between varus-valgus constrained implants and rotating hinge prosthesis. A cadaver study

The real degree of constriction of rotating hinge knee (RHK) and condylar constrained prostheses (CCK) is a matter of discussion in revision knee arthroplasty. The objectives of this study are to compare the tibial rotation of both implants and validate the use of inertial sensors with optical tracking system as movement measurement tools. A total of 16 cadaver knees were used. Eight knees were replaced using a RHK (Endomodel LINK), and the remaining eight received a CCK prosthesis (LCCK, Zimmer). Tibial rotation range of motion was measured in full extension and at 30°, 60°, and 90° of flexion, with four continuous waveforms for each measurement. Measurements were made using two inertial sensors with specific software and compared with measurements obtained using the gold standard technique - the motion capture camera. The comparison of the accuracy of both measurement methods showed no statistically significant differences between inertial sensors and motion capture cameras, with p > .1; the mean error for tibial rotation was 0.21°. Tibial rotation in the RHK was significantly greater than in the CCK (5.25° vs. 2.28°, respectively), p < .05. We have shown that RHK permit greater tibial rotation, being closer to physiological values than CCKs. Inertial sensors have been validated as an effective and accurate method of measuring knee movement. The clinical significance: RHK appears to represent a lower constriction degree than CCK systems.This study wassupported by Ministerio de Ciencia, Innovación y Universidades, Instituto de Salud Carlos III and European Regional Development Fund "Una manera de hacer Europa" (grant number PI18/01625

Algoritmo Level-set para segmentación hepática en TAC con Restricciones de curvatura local

Actas de: XXIX Congreso Anual de la Sociedad Espñaola de Ingeniería Biomédica (CASEIB 2011). Cáceres, 16-18 Noviembre 2011.La cirugía hepática avanzada requiere de una precisa planificación pre-operatoria en la que tanto la segmentación anatómica como la estimación del volumen hepático remanente tienen una importancia clave a la hora de evitar un fallo hepático postoperatorio. En este contexto, algoritmos basados en level-sets han logrado mejores resultados que otros, especialmente cuando se tratan casos con un parénquima hepático alterado o en hígados previamente resecados. Con el objetivo de mejorar las medidas de volumen hepático funcional, se proponen dos estrategias para completar y realzar algoritmos previos basados en level-sets: una estrategia optimizada multi-resolución con curvatura adaptativa y corrección/refinamiento de detalles, junto con un paso semiautomático adicional en el que se imponen restricciones de curvatura local. Los resultados muestran segmentaciones robustas y precisas, especialmente en estructuras alargadas, detectando lesiones internas y evitando fugas o escapes a estructuras proximales.Este trabajo está parcialmente apoyado por los proyectos de investigación PI09/91058, PI09/91065, ENTEPRASE PS-300000-2009-5, AMIT-CDTI, TEC2010-21619-C04 and PRECISION IPT-300000-2010-3, del Ministerio de Ciencia e Innovación de España, el proyecto ARTEMIS de la Comunidad de Madrid y la ayuda de los fondos FEDER de la Unión Europea.Publicad