Some recent developments in treatment planning software and methodology for BNCT Page: 4 of 7
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Once the region outlines for all image slices are established, these
representations are then mathematically combined to produce detailed equations
describing the 3-D surfaces that enclose each volume of interest. The
surface equations generated in the B-spline region reconstructions, in
conjunction with appropriate region material descriptions, completely describe
the problem and are subsequently used in a Monte Carlo radiation transport
calculation performed by a specialized module incorporated into BNCT-rtpe.
The ray-trace algorithm for the Monte Carlo calculation is based on searching
nested hierarchies of bounding volumes enclosing the points of intersection of
particles (neutrons or photons) with each reconstructed geometric NURBS
surface describing a particular compartment of the patient anatomy. The
spline surfaces can be combined with geometric primitive surfaces to further
specify the calculational geometry, if needed. Any type of tomographic
medical image data can be input to BNCT rtpe. The radiation transport
computational module within BNCTrtpe will also accept parallelpiped arrays
constructed using the so-called "voxel reconstruction" technique , if
Figure 2 illustrates some typical computed total physical dose contours
registered on the original MR image of Figure 1, which was used to construct
the computational model. These results are based on the assumption that the
patient is treated using the Brookhaven Medical Research Reactor (BMRR)
epithermal-neutron beam as it was configured at the initiation of human
studies in September, 1994. In the display the boron concentration is assumed
to be 15 parts per million (ppm), uniformly distributed throughout the brain.
The contours are thus representative of what would be seen by the normal
tissue. The total dose includes the boron dose at 15 ppm as well as the
contributions from the fast neutron component of the beam, the incident and
capture photon components, the nitrogen component, as well as a fifth
component that includes a few other small contributions from various other
neutron interactions. The 100% contour corresponds to approximately 9.1 cGy
per minute per megawatt of BMRR reactor power. Although BPA-f is typically
present in the normal brain at about the same concentration as in the blood,
this agent tends to concentrate in the malignant tissue at a level that is
roughly 3-4 times the blood concentration for most patients. Thus the tumor
dose includes all of the background components as well as a significantly
higher boron dose corresponding to the higher tumor boron concentration. The
tumor dose contours can also be displayed since the actual treatment plan is
based on tumor dose, constrained by normal tissue tolerance, just as in photon
therapy. Dose-volume histograms for each defined volume of interest can also
be constructed as needed.
Efforts to include much faster, albeit approximate, dose computation
methods in BNCTrtpe are underway. An algorithm based on multidimensional
parameter fitting from precomputed kernel functions (closely-related to the
so-called "pencil-beam" methods) has been incorporated and has proven to be
quite effective for use in dose optimization studies prior to performing a
Monte Carlo calculation for the final optimized plan for each patient. This
capability should prove to be especially useful as clinical application of
BNCT moves into the more complicated realm of multi-port irradiations. In
addition, an informal collaboration has been established with The Ohio State
University to explore the utility of incorporating a computational option
based on removal-diffusion theory . Finally, it may be noted that the
basic physics modules have been significantly upgraded to allow incident
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Nigg, D.W.; Wheeler, F.J.; Wessol, D.E.; Wemple, C.A.; Babcock, R. & Capala, J. Some recent developments in treatment planning software and methodology for BNCT, article, December 31, 1996; Idaho Falls, Idaho. (https://digital.library.unt.edu/ark:/67531/metadc686613/m1/4/: accessed April 21, 2019), University of North Texas Libraries, Digital Library, https://digital.library.unt.edu; crediting UNT Libraries Government Documents Department.