This report investigates methods of optimization to make treatment plans in radiosurgery robust to spatial uncertainty, and attempts to determine whether they could be used with bene t in a Gamma Knife context. To make the problem mathematically feasible, regions of interest (ROIs) are approximated to move in a pre-computed static dose cloud, which in turn is estimated by methods of linear interpolation and linear approximation. The movements of ROIs are modeled by transforms, of which rigid, general affine, and a special case of non-affine transforms are treated. Of these, the rigid transforms are used to flexibly assess various properties of the robust optimization model; the a ne transforms to model the total geometric error of the Gamma Knife, excluding ROI delineation; and the non-affine transforms for initial modeling of the important delineation uncertainty. For the geometric errors, traditionally seen as small for the Gamma Knife, the robust treatment plans are seen to compare favorably to those obtained by non-robust optimization. Delineation errors are found to need careful modeling in order to avoid excessively conservative plans, which may harm normal tissue.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:kth-156415 |
| Date | January 2014 |
| Creators | Josefsson, Marcus |
| Publisher | KTH, Optimeringslära och systemteori |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | TRITA-MAT-E ; 2014:64 |
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