No abstract

The accuracy of the Leksell GammaPlan, the dose planning system of the Gamma Knife Model-B, was evaluated near tissue inhomogeneities, using the gel dosimetry method. The lack of electronic equilibrium around the small-diameter gamma beams can cause dose calculation errors in the neighborhood of an air-tissue interface. An experiment was designed to investigate the effects of inhomogeneity near the paranosal sinuses cavities. The homogeneous phantom was a spherical glass balloon of 16 cm diameter, filled with MAGIC gel; i.e., the normoxic polymer gel. Two hollow PVC balls of 2 cm radius, filled with N2 gas, represented the air cavities inside the inhomogeneous phantom. For dose calibration purposes, 100 ml gel-containing vials were irradiated at predefined doses, and then scanned in a MR unit. Linearity was observed between the delivered dose and the reciprocal of the T2 relaxation time constant of the gel. Dose distributions are the results of a single shot of irradiation, obtained by collimating all 201 cobalt sources to a known target in the phantom. Both phantoms were irradiated at the same dose level at the same coordinates. Stereotactic frames and fiducial markers were attached to the phantoms prior to MR scanning. The dose distribution predicted by the Gamma Knife planning system was compared with that of the gel dosimetry. As expected, for the homogeneous phantom the isodose diameters measured by the gel dosimetry and the GammaPlan differed by 5% at most. However, with the inhomogeneous phantom, the dose maps in the axial, coronal and sagittal planes were spatially different. The diameters of the 50% isodose curves differed 43% in the X axis and 32% in the Y axis for the Z =90 mm axial plane; by 44% in the X axis and 24% in the Z axis for the Y=90 mm coronal plane; and by 32% in the Z axis and 42% in the Y axis for the X=92 mm sagittal plane. The lack of ability of the GammaPlan to predict the rapid dose fall off, due to the air cavities behind or near the lesion led to an overestimation of the dose that was actually delivered. Clinically, this can result in underdosing of lesions near tissue inhomogeneities in patients under treatment.

No abstract

MRA enables excluding voxels on the MCA during cluster analysis, and avoiding the risk of shape distortions.

Segmentation of tissues in magnetic resonance images is essential especially for a radiologist to be able to identify a disease, tumors, or any tissue. I n any magnetic resonance image there exists many different types of tissues each with characteristic TI and T2 decay times and proton densities. If these parameters of tissues can be calculated from the regular magnetic resonance images, the type of tissue could also be determined on any M R image independent of M R hardware characteristics. One such important hardware limitation is the varying sensitivity of an imaging coil spatially. Segmentation algorithms can not distinguish between an intensity variation caused by the imaging coil sensitivity or a variation by tissue change. Calculated TI, T2, and PD images provide consistent pixel intensity corresponding to the same tissue therefore easier to utilize in conventional segmentation algorithms. To be able to calculate true TI and PD parameters, a slice of human head were imaged sixteen times by holding TE fixed and changing T R each time. Levenberg-Marquardt Method is applied to the data and TI and PD values were estimated. The true TI and true PD images were produced. The maximum likelihood classification is then applied successfully to four M R images of different slices of human head and the robustness of this method in segmenting CSF, WM, and GM is illustrated.