Biomedical subjects

C A Willemse

Publications and source records attributed to C A Willemse.

4 recordsLinked to original sources

PubMed1998

The indirect use of CT numbers to establish material properties needed for Monte Carlo calculation of dose distributions in patients.

A number of Monte Carlo codes are available, which can be used to calculate dose distributions n patients with high accuracy. Patient geometry can readily be derived with adequate spatial resolution from CT scans. To perform the Monte Carlo calculation with the same spatial resolution, it is necessary to enter the atomic composition and density of the tissue in each voxel of the CT image. This means entering 65,536 discrete values for a CT slice with a 256 x 256 matrix size. The need for automated methods of setting up the material data files is obvious. Because there is no direct unique relationship between CT numbers and material composition, the aim of our work was to devise a method whereby the atomic composition and density in each voxel could be assigned automatically by indirect derivation from the CT numbers. The set of all tissues types in the human body was divided into subsets that are dosimetrically equivalent, based on Monte Carlo calculated depth dose curves in homogeneous phantoms of each tissue. CT number ranges corresponding to each tissue subset were determined from the calibration curve linking electron density with CT number for the specific CT scanner. Further subdivision was found to be necessary for the lung and bone type tissues. This was done by keeping the atomic composition constant and varying the physical density. It was found that 57 distinct tissue subsets were needed to represent the 16 main tissue types in the body at a 1% dose level. Corresponding CT number intervals of 30 HU were needed in the lung and soft tissue region, whereas in the bone region the intervals could be increased to 100 HU. A computer algorithm was set up to convert automatically from CT number to corresponding equivalent material number for the Monte Carlo preprocessor code.

Algorithms↗

PubMed1996

Chelator effect on ion diffusion in ferrous-sulfate-doped gelatin gel dosimeters as analyzed by MRI.

Ferrous-sulfate-doped gelatin gel dosimeters are useful tools for the measurement of three-dimensional absorbed radiation dose distributions. The diffusion of ferric ions through these gels causes degradation with time of the dose distribution image. It would be useful to reduce ferric ion diffusion without decreasing gel sensitivity. The amount of ferric ion diffusion is a function of the time delay after radiation, the gel temperature, and the gel concentration. These effects can be quantified by measuring the ferric ion diffusion coefficient. Determination of the diffusion coefficient by irradiating the lower section of a cylinder of gel, which was then imaged repeatedly over time with a clinical magnetic resonance imager, is described. Analysis of the edge spread function formed at each of several times after irradiation by drawing a profile over the imaged junction between the irradiated and unirradiated halves of the cylinder, gave estimates of the variance of the edge spread function. These variances were used to obtain an estimate of the ferric ion diffusion coefficient for the gel. A method of reducing ferric ion diffusion by adding a chelator and the cross linkage agent formaldehyde is suggested. The chelators investigated were 1,10 phenanthroline, xylenol orange, and bathophenanthroline disulfonic acid. These reduced diffusion to varying extents, and influenced the gel sensitivity. The diffusion coefficient in gels containing xylenol orange was found to be 0.44 mm2h-1. The gel sensitivity was 0.0093 s-1Gy-1. This compared with a diffusion coefficient of 0.82 mm2h-1 for the base line gel that did not contain formaldehyde or chelators. The sensitivity of this base line gel was 0.0129 s-1Gy-1. The addition of xylenol orange produced the most improved gel dosimeter of the gels studied. This gel had a decreased ferric ion diffusion coefficient and a decreased sensitivity. It was still sensitive enough to be useful.

Biophysical Phenomena↗

PubMed1995

Technical note: computed tomography imaging with a radiotherapy simulator.

An inexpensive system for obtaining cross-sectional information and accurate body outlines of patients destined for radiotherapy, using a radiotherapy simulator without any major modifications, has been investigated. The image intensifier of the simulator was moved laterally and a narrow fan beam of X-rays passed through the phantom onto the intensifier. Several television (TV) lines of the video signal from the TV camera were digitized by a frame grabber and stored for reconstruction. Multiple projections were acquired by rotating the gantry of the simulator. The field of view was enlarged by increasing the offset distance of the image intensifier and taking two sets of projections. Reconstruction was carried out by using the convolution and back-projection method. The gradient between pixel values in the reconstructed images was used to detect the outlines of structures in the images. The accuracy of outline detection was evaluated with images of a Rando phantom. The outlines of the images were compared with the actual outlines of the phantom. The spatial resolution of the simulator computed tomography (CT) was measured to be 4.05 mm. Large inhomogeneities could be clearly seen. The average difference between the measured and the actual outlines was 3.0 mm with a maximum difference of 10.0 mm at sharp curves in the outline. The simulator CT provides an inexpensive, alternative method of obtaining body outlines and does not require any modifications to the simulator. Data acquisition, processing and display can be performed on a personal computer with image processing facilities.

Head↗

PubMedDate not supplied

Optimization of the wedge filter parameters for a radiotherapy treatment planning system.

When a treatment planning system uses an empirical or semianalytical approach to describe the influence of a wedge filter on a photon beam, a number of experimentally determined parameters are required. These may be found from direct measurement. However, if the beam model is sensitive to the parameters, it will be necessary to optimize the parameter values to obtain better correspondence between dose profiles calculated by the model and actual measured profiles. The procedure is time consuming if optimization is done manually. We have developed an optimization scheme, using a personal computer, to find the set of wedge parameters which will result in the best fit of calculated wedge profiles (using the beam model of the treatment planning system) to measured wedge profiles. The procedure is efficient and calculated profiles were found to match measured profiles to within 2% of the central axis value.

Filtration↗