Positron Emission Tomography (PET) Tumor Segmentation and Quantification: Development of New Algorithms

Tumor functional volume (FV) and its mean activity concentration (mAC) are the quantities derived from positron emission tomography (PET). These quantities are used for estimating radiation dose for a therapy, evaluating the progression of a disease and also use it as a prognostic indicator for predicting outcome. PET images have low resolution, high noise and affected by partial volume effect (PVE). Manually segmenting each tumor is very cumbersome and very hard to reproduce. To solve the above problem I developed an algorithm, called iterative deconvolution thresholding segmentation (IDTS) algorithm; the algorithm segment the tumor, measures the FV, correct for the PVE and calculates mAC. The algorithm corrects for the PVE without the need to estimate camera’s point spread function (PSF); also does not require optimizing for a specific camera. My algorithm was tested in physical phantom studies, where hollow spheres (0.5-16 ml) were used to represent tumors with a homogeneous activity distribution. It was also tested on irregular shaped tumors with a heterogeneous activity profile which were acquired using physical and simulated phantom. The physical phantom studies were performed with different signal to background ratios (SBR) and with different acquisition times (1-5 min). The algorithm was applied on ten clinical data where the results were compared with manual segmentation and fixed percentage thresholding method called T50 and T60 in which 50% and 60% of the maximum intensity respectively is used as threshold. The average error in FV and mAC calculation was 30% and -35% for 0.5 ml tumor. The average error FV and mAC calculation were ~5% for 16 ml tumor. The overall FV error was ~10% for heterogeneous tumors in physical and simulated phantom data. The FV and mAC error for clinical image compared to manual segmentation was around -17% and 15% respectively. In summary my algorithm has potential to be applied on data acquired from different cameras as its not dependent on knowing the camera’s PSF. The algorithm can also improve dose estimation and treatment planning.

PROGRAMA SAÚDE DA FAMÍLIA NO MUNICÍPIO DE PIRAPORA – NORTE DE MINAS GERAIS - BRASIL: POSSIBILIDADES E LIMITES EM SAÚDE

A saúde é vista como direito do cidadão e dever do estado. Sendo assim, deve ir além das propostas vigentes sancionadas a saúde, mas, sobretudo resolver os problemas e desafios impostos por ela. Neste sentido, o presente estudo objetiva analisar a importância do Programa Saúde da Família para a população da cidade de Pirapora – Norte de Minas Gerais - Brasil, em especial no bairro Nossa Senhora Aparecida e Santo Antônio. Os procedimentos metodológicos consistiram em levantamento bibliográfico e documental, observação in loco e entrevistas à moradores das áreas e microáreas adscrita pelo Programa Saúde da Família - PSF. Com a implantação do PSF ocorreram significativas mudanças no sistema de saúde brasileiro, já que sua proposta é a inversão do modelo de saúde de hospitalocentrico para assistenciocêntrico, ou seja, promoção e prevenção, onde o cidadão participa do processo de mudanças sendo ator da transformação e do cuidado com a própria saúde. Dessa forma, observamos a importância do Programa em mobilizar  e incentivar  a participação da comunidade em torno de um interesse comum, de modo que os agentes de saúde  e a comunidade  criem um elo de possibilidades que estabeleça vínculos para desenvolver trabalhos que beneficie toda a comunidade.