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1.
Phys Med Biol ; 64(16): 165001, 2019 08 14.
Artigo em Inglês | MEDLINE | ID: mdl-31252419

RESUMO

Dose reporting is a matter of concern in the preclinical field as the different dose descriptors dose-to-water-in-medium [Formula: see text] and dose-to-medium-in-medium [Formula: see text] coexist. For kV photons differences between both quantities are expected to be amplified due to photon energy absorption coefficients differences for different media, and could represent a limiting factor for accurate translation of pre-clinical research into clinical trials. The main goal of this study was to analyse the relationship between [Formula: see text] and [Formula: see text] for kV irradiation of small animals, using different flavours of the intermediate cavity theory (ICT). Irradiations of mathematical phantoms and a mouse CT scan, both with different voxel sizes and materials, were investigated. A modified version of the Monte Carlo code DOSXYZnrc was used to derive [Formula: see text] and convert to [Formula: see text] using ICT. Local photon spectra were generated in different regions of the mouse. Depending on energy and cavity size, which we equate to the voxel size, [Formula: see text] ranged from 0.68 to 4.37 times [Formula: see text]. Higher kV energy combined with very small cavity sizes yielded decreased [Formula: see text] in comparison to [Formula: see text]; this behaviour was reversed for larger cavities combined with lower kV energies. Hence, the impact of the cavity dimensions on estimated [Formula: see text] is significant on pre-clinical kV beams. [Formula: see text] and [Formula: see text] in the ex vivo male mouse were found to differ by -29% to 286%. Caution is advised when using the ICT due to a lack of consensus on weighting factor (d-parameter) deriving methods; for the same irradiation conditions, different d-values affected [Formula: see text] up to 20%. Pre-clinically, such divergence between dose descriptors could enable biological damage. The abiding debate over which quantity to favour is foreseen to linger while it is unclear which quantity correlates better with the biological effects of ionizing irradiation: preclinical radiotherapy might represent an ideal platform for measurement-based studies to settle this fundamental question. Finally, dose distribution comparisons require caution and should use the same reporting quantity.


Assuntos
Imagens de Fantasmas , Fótons/uso terapêutico , Tomografia Computadorizada por Raios X/métodos , Água/química , Animais , Camundongos , Método de Monte Carlo , Doses de Radiação , Irradiação Corporal Total , Raios X
2.
J Magn Reson ; 238: 115-25, 2014 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-24334098

RESUMO

To adjust pulse sequences that produce diffusion-weighted MRI signals for increased sensitivity to nucleus size, the impulse-propagator method in q-space is applied to a spherical geometry that would describe each member of a collection of cells and their nuclei, with several possible representations of the extracellular space. The method is extended to allow propagation between nucleus, cytoplasm, and extracellular space through semi-permeable membranes, using an approximate adjustment of intra-compartment propagators. Diffraction patterns are first calculated for the three compartments separately, for PGSE and OGSE pulse sequences, and verified by comparison with Monte Carlo simulations. The detailed patterns from the separate compartments determine the q value for maximum contrast in the total signal between large and small nuclei, an optimization that is not accurate in a Gaussian Phase Distribution (GPD) approximation. Then diffraction patterns are calculated for the case of linked compartments with semi-permeable membranes. The treatment of permeability adequately estimates pulse-sequence parameters for maximum contrast in calculated signal as nucleus size varies.


Assuntos
Núcleo Celular/ultraestrutura , Células/ultraestrutura , Imagem de Difusão por Ressonância Magnética/métodos , Algoritmos , Permeabilidade da Membrana Celular , Simulação por Computador , Humanos , Processamento de Imagem Assistida por Computador , Membranas , Modelos Biológicos , Método de Monte Carlo
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