Biomedical subjects

J Tervo

Publications and source records attributed to J Tervo.

4 recordsLinked to original sources

PubMed2005

Modelling the transport of ionizing radiation using the finite element method.

Radiation therapy treatment planning is based on the calculation of the absorbed dose in the patient domain. For exact dose calculations, the solution of three coupled Boltzmann transport equations (BTEs) is needed to cover the transport of photons, electrons and positrons. In many situations, however, two coupled systems for photons and electrons are enough. The use of numerical methods in finding the exact solution of the unknown particle fluxes is necessary. In the stationary case, the BTE has six variables, three spatial, two directional and one energy variable. In this paper, we describe an approach in which the finite element method (FEM) is used to solve the six-dimensional problem. For the coupled photon-electron system, the variational formulation and the existence and uniqueness of the solution are derived. We simulate the solution of two coupled BTEs describing the travelling of photons and electrons in two spatial dimensions. The results are compared to Monte Carlo calculations with good agreement.

Animals↗

PubMed2003

Simulations for inverse radiation therapy treatment planning using a dynamic MLC algorithm.

The inverse radiation treatment planning model for a dynamic multileaf collimator (MLC) is used to find the optimal solution of planning problem. The model for dynamic MLC is explained in Tervo et al (2003 Appl. Math. Comput. 135 227-50). The advantage of this model is that it optimizes leaf velocity parameters directly. Our algorithm uses a gradient-based local optimization method. Two patient cases, prostate carcinoma and tonsilla carcinoma, are studied. Field arrangements are pre-selected and velocity parameters for MLC leaves are optimized to obtain the prescribed dose in the patient space. In both simulated cases, high dose distribution conforms the planning target volume well and organs-at-risk are saved in most parts. Simulations show that the model has its functionality in patient treatments, although it is still formal and needs further development.

Algorithms↗

PubMed1998

Use of the Cimmino algorithm and continuous approximation for the dose deposition kernel in the inverse problem of radiation treatment planning.

An approximate continuous data fitting model for the dose deposition kernel was developed. The model uses a discrete Fourier transform to interpolate dose values in patient space and intensity distribution in treatment space. The continuous kernel was applied to the inverse problem of radiation treatment planning. In the problem a prescribed dose distribution was to be created using intensity modulation of several fields. The Cimmino algorithm suitable for solving large systems of inequalities was adapted. Upper and lower dose constraints for planning target volume (PTV) and organs at risk (OAR) can be implemented into the algorithm. Using continuous and discrete kernels an intensity modulation was computed in a two-dimensional phantom with a PTV and low-dose region, and in the real three-dimensional patient planning. Intensity modulations obtained using continuous and discrete kernels were in good agreement.

Algorithms↗

PubMed1987

A cyclic isomer of 2-hydroxymelatonin: a novel metabolite of melatonin.

A previously unknown melatonin metabolite was isolated by chloroform extraction and reverse phase HPLC from human and rat urine after administration of synthetic melatonin and characterized by mass spectroscopy and proton magnetic resonance spectroscopy to 1-acetyl-1,2,3,3a,8,8a-hexahydro-8a-hydroxy-5-methoxypyrrolo[2,3-b ]indole, a cyclic isomer of 2-hydroxymelatonin. This isolation was based on the fact that our melatonin antibody (a-MT-K1) cross-reacted against this novel metabolite at a level of 0.1% (melatonin 100%). In our HPLC program for indoles the cyclic 2-hydroxymelatonin eluted at 25 min, separately from synthetic indoles, between 6-hydroxymelatonin (19 min) and melatonin (35 min). In [3H] melatonin studies it was found to be present (at 25 min in our HPLC), accounting for 5% of the urinary metabolites of melatonin in the rat. Since beta-glucuronidase-arylsulfatase treatment of rat urine did not liberate the cyclic 2-hydroxymelatonin this would appear to be excreted into urine as the free form.

Adult↗