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Pascal R M Storchi

Publications and source records attributed to Pascal R M Storchi.

3 recordsLinked to original sources

Computer optimization of noncoplanar beam setups improves stereotactic treatment of liver tumors.

PURPOSE: To investigate whether computer-optimized fully noncoplanar beam setups may improve treatment plans for the stereotactic treatment of liver tumors. METHODS: An algorithm for automated beam orientation and weight selection (Cycle) was extended for noncoplanar stereotactic treatments. For 8 liver patients previously treated in our clinic using a prescription isodose of 65%, Cycle was used to generate noncoplanar and coplanar plans with the highest achievable minimum planning target volume (PTV) dose for the clinically delivered isocenter and mean liver doses, while not violating the clinically applied hard planning constraints. The clinical and the optimized coplanar and noncoplanar plans were compared, with respect to D(PTV,99%), the dose received by 99% of the PTV, the PTV generalized equivalent uniform dose (gEUD), and the compliance with the clinical constraints. RESULTS: For each patient, the ratio between D(PTV,99%) and D(isoc), and the gEUD(-5) and gEUD(-20) values of the optimized noncoplanar plan were higher than for the clinical plan with an average increase of respectively 18.8% (range, 7.8-24.0%), 6.4 Gy (range, 3.4-11.8 Gy), and 10.3 Gy (range, 6.7-12.5). D(PTV,99%)/D(isoc), gEUD(-5), and gEUD(-20) of the optimized noncoplanar plan was always higher than for the optimized coplanar plan with an average increase of, respectively, 4.5% (range, 0.2-9.7%), 2.7 Gy (range, 0.6-9.7 Gy), and 3.4 Gy (range, 0.6-9.9 Gy). All plans were within the imposed hard constraints. On average, the organs at risk were better spared with the optimized noncoplanar plan than with the optimized coplanar plan and the clinical plan. CONCLUSIONS: The use of automatically generated, fully noncoplanar beam setups results in plans that are favorable compared with coplanar techniques. Because of the automation, we found that the planning workload can be decreased from 1 to 2 days to 1 to 2 h.

Algorithms↗

Fast, multiple optimizations of quadratic dose objective functions in IMRT.

Inverse treatment planning for intensity-modulated radiotherapy may include time consuming, multiple minimizations of an objective function. In this paper, methods are presented to speed up the process of (repeated) minimization of the well-known quadratic dose objective function, extended with a smoothing term that ensures generation of clinically acceptable beam profiles. In between two subsequent optimizations, the voxel-dependent importance factors of the quadratic terms will generally be adjusted, based on an intermediate plan evaluation. The objective function has been written in matrix-vector format, facilitating the use of a recently published, fast quadratic minimization algorithm, instead of commonly applied gradient-based methods. This format also reduces the calculation time in between subsequent minimizations, related to adjustment of the voxel-dependent importance factors. Sparse matrices are used to limit the required amount of computer memory. For three patients, comparisons have been made with a gradient method. Mean speed improvements of up to a factor of 37 have been achieved.

Algorithms↗

Automated selection of beam orientations and segmented intensity-modulated radiotherapy (IMRT) for treatment of oesophagus tumors.

BACKGROUND AND PURPOSE: For some treatment sites, there is evidence in the literature that five to nine equi-angular input beam directions are enough for generating IMRT plans. For oesophagus cancer, there is a report showing that going from four to nine beams may even result in lower quality plans. In this paper, our previously published algorithm for automated beam angle selection (Cycle) has been extended to include segmented IMRT. For oesophagus cancer patients, we have investigated whether automated orientation selection from a large number of equi-angular input beam directions (up to thirty-six) for IMRT optimisation can result in improved lung sparing. MATERIALS AND METHODS: CT-data from five oesophagus patients treated recently in our institute were used for this study. For a prescribed mean PTV dose of 55 Gy, Cycle was used in an iterative procedure to minimise the mean lung dose under the following hard constraints: standard deviation for PTV dose inhomogeneity 2% (1,1 Gy), maximum spinal cord dose 45 Gy. Conformal radiotherapy (CFRT) and IMRT plans for a standard four field oesophagus beam configuration were compared with IMRT plans generated by automated selection from nine or thirty-six equi-angular input beam orientations. Comparisons were also made with dose distributions generated with our commercial treatment planning system (TPS), and with observations in the literature. RESULTS: Using Cycle, automated orientation selection from nine or thirty-six input beam directions resulted in improved lung sparing compared to the four field set-ups. Compared to selection from nine input orientations, selection from thirty-six directions did always result in lower mean lung doses, sometimes with even fewer non-zero weight beams. On average only seven beams with a non-zero weight were enough for obtaining the lowest mean lung dose, yielding clinically feasible plans even in case of thirty-six input directions for the optimisation process. With our commercial TPS we observed the same contra-intuitive, unfavourable results as reported in the literature; nine field equi-angular IMRT plans had substantially higher mean lung doses than plans for the conventional four field set-ups. For all cases, the Cycle plans generated from nine equi-angular input directions were superior compared to similar plans generated with our commercial TPS. CONCLUSIONS: For the studied oesophagus cancer patients the best plans for IMRT were obtained with Cycle, using automated beam orientation selection from thirty-six input beam directions. The lowest mean lung doses could be obtained with, on average, a selection of only seven beams with non-zero weight.

Algorithms↗