A natureza estatística dos processos físicos envolvidos nos exames de medicina nuclear faz com que o uso do método de Monte Carlo (MC) seja uma ferramenta útil para cálculos da energia depositada e da dose absorvida nos órgãos, principalmente para avaliação de risco-benefício. O objetivo deste trabalho é avaliar as potencialidades e limitações do uso do aplicativo de simulação de Monte Carlo GATE (Geant4 Application for Emission Tomography) no cálculo da dosimetria interna em testes simulados de imagem de Medicina Nuclear. Foram comparados cálculos analíticos e simulações de fontes emissoras de radiação em fontes pontuais de 99mTc e 18F, em objetos atenuadores com geometrias simples. Foi realizada uma análise da influência do tamanho dos elementos do mapa de dose (dosel), assim como o impacto de diferentes configurações das fontes radioativas. Os resultados concordam com dados já publicados. Para uma simulação mais realística do 18F para fins de dosimetria, deve-se utilizar os dois tipos de configuração da fonte, “back-to-back”, que simula os fótons de aniquilação, e “Fluor18”, que simula o espectro de emissão de pósitrons. Conclui-se que o aplicativo GATE é um ambiente confiável e amigável para a estimativa de dose em imagens de medicina nuclear.

This study aims to evaluate the dose sensitivity of MAGIC-f  gel irradiated by high-energy photon beams, comparing quantification using different MRI sequences. Irradiation was performed using 6 MV photons with 600 cGy/min dose rate, field size of 20x20 cm², and 94 cm source-to-surface distance. Two gel batches were produced on different days and placed in vials. In the first batch, doses of 0, 2, 4, 6, 8, 10, 20, and 40 Gy were planned. The second batch was irradiated with doses of 0, 2, 4, 6, 10, 12, 14, and 16 Gy. MR images were acquired with Spin Echo (SE, TR=3 s) and Multi Spin Echo (MSE, TR = 3s or 10s, turbo factor 24) sequences. The dose is assessed via changes in the transverse relaxation time in the irradiated gel. In MSE, dose sensitivity in the first batch was 0.27 (TR=3 s) and 0.28 Gy-1s-1  (TR=10 s) and in the second batch, 0.31 and 0.31 Gy-1s-1 (TR = 3 s and TR = 10 s, respectively). In the SE sequence, dose sensitivity was 0.42 for the first batch and 0.43 Gy-1s-1 for the second batch. Linearity of dose-response was only obtained for doses below 10 Gy. Comparing the dose sensitivity extracted from MSE and SE sequences using TR= 3s, differences around 30% were found. Thus, although MSE-MRI offers a faster protocol of imaging acquisition it is less precise for quantification of relaxation times, as TE is not a well-defined quantity. The performance of the gel as a dosimeter is consequently sequence dependent.

High-resolution structural magnetic resonance imaging (MRI) allows neurological investigation, especially when brain volumes must be carefully delineated to monitor neurodegeneration, such as in multiple sclerosis (MS). This study compares different segmentation techniques applied to brain MRI to measure the white matter (WM) and grey matter (GM) in healthy and MS brains. We propose to evaluate the reliability and how each segmentation method could potentially affect clinical trials in MS. Four segmentation software were evaluated: Statistical Parametric Mapping (SPM), Lesion Segmentation Tool (LST), Freesurfer, and Siena/X. We simulated healthy and MS brain MRI and compared the segmentation volumes with the ground truth. Our results showed that LST provides overall good segmentation with low variability. When SienaX spatially normalizes the images, the WM and GM volumes are overestimated. On the other hand, Freesurfer underestimates volumes. We conclude that the use of different segmentation software produces variability in GM and WM volumes, especially in challenging situations, such as small lesions and in the presence of noise. The best method was the automatic region growth algorithm implemented using the LST, which uses T1-weighted and T2-FLAIR MRI.

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