Implementation of a new reference values database for semiquantification in123I-FP-CIT brain single emission tomography

Brain dopamine transporters imaging by Single Emission Tomography (SPECT) with 123I-FP-CIT (DaTScanTM) has become an important tool in the diagnosis and evaluation of Parkinson syndromes.This diagnostic method allows the visualization of a portion of the striatum – where healthy pattern resemble two symmetric commas - allowing the evaluation of dopamine presynaptic system, in which dopamine transporters are responsible for dopamine release into the synaptic cleft, and their reabsorption into the nigrostriatal nerve terminals, in order to be stored or degraded. In daily practice for assessment of DaTScan TM, it is common to rely only on visual assessment for diagnosis. However, this process is complex and subjective as it depends on the observer’s experience and it is associated with high variability intra and inter observer. Studies have shown that semiquantification can improve the diagnosis of Parkinson syndromes. For semiquantification, analysis methods of image segmentation using regions of interest (ROI) are necessary. ROIs are drawn, in specific - striatum - and in nonspecific – background – uptake areas. Subsequently, specific binding ratios are calculated. Low adherence of semiquantification for diagnosis of Parkinson syndromes is related, not only with the associated time spent, but also with the need of an adapted database of reference values for the population concerned, as well as, the examination of each service protocol. Studies have concluded, that this process increases the reproducibility of semiquantification. The aim of this investigation was to create and validate a database of healthy controls for Dopamine transporters with DaTScanTM named DBRV. The created database has been adapted to the Nuclear Medicine Department’s protocol, and the population of Infanta Cristina’s Hospital located in Badajoz, Spain.

Desenvolvimento de modelo de primeiros princípios para simulação dinâmica de uma coluna de destilação contínua

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Química e Biológica

Deep structure of the Santos basin-São Paulo plateau system, SE Brazil

The structure and nature of the crust underlying the Santos Basin-São Paulo Plateau System (SSPS), in the SE Brazilian margin, are discussed based on five wide-angle seismic profiles acquired during the Santos Basin (SanBa) experiment in 2011. Velocity models allow us to precisely divide the SSPS in six domains from unthinned continental crust (Domain CC) to normal oceanic crust (Domain OC). A seventh domain (Domain D), a triangular shape region in the SE of the SSPS, is discussed by Klingelhoefer et al. (2014). Beneath the continental shelf, a similar to 100km wide necking zone (Domain N) is imaged where the continental crust thins abruptly from similar to 40km to less than 15km. Toward the ocean, most of the SSPS (Domains A and C) shows velocity ranges, velocity gradients, and a Moho interface characteristic of the thinned continental crust. The central domain (Domain B) has, however, a very heterogeneous structure. While its southwestern part still exhibits extremely thinned (7km) continental crust, its northeastern part depicts a 2-4km thick upper layer (6.0-6.5km/s) overlying an anomalous velocity layer (7.0-7.8km/s) and no evidence of a Moho interface. This structure is interpreted as atypical oceanic crust, exhumed lower crust, or upper continental crust intruded by mafic material, overlying either altered mantle in the first two cases or intruded lower continental crust in the last case. The deep structure and v-shaped segmentation of the SSPS confirm that an initial episode of rifting occurred there obliquely to the general opening direction of the South Atlantic Central Segment.

ECG biometrics using a dissimilarity space representation

Electrocardiogram (ECG) biometrics are a relatively recent trend in biometric recognition, with at least 13 years of development in peer-reviewed literature. Most of the proposed biometric techniques perform classifi-cation on features extracted from either heartbeats or from ECG based transformed signals. The best representation is yet to be decided. This paper studies an alternative representation, a dissimilarity space, based on the pairwise dissimilarity between templates and subjects' signals. Additionally, this representation can make use of ECG signals sourced from multiple leads. Configurations of three leads will be tested and contrasted with single-lead experiments. Using the same k-NN classifier the results proved superior to those obtained through a similar algorithm which does not employ a dissimilarity representation. The best Authentication EER went as low as 1:53% for a database employing 503 subjects. However, the employment of extra leads did not prove itself advantageous.