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Sparse proportional re-scanning with hadron beams

Published:September 07, 2019DOI:https://doi.org/10.1016/j.ejmp.2019.07.022

      Highlights

      • The novel sparse proportional re-scanning method reduces the treatment time.
      • The advantage is quantified using Eclipse treatment plans of 54 proton fields.
      • It is proven that the time “reduction factor” depends only on the number N of re-scannings.
      • The reduction factor does not depend on the shape and volume of the target, the numbers of layers or on the spot grid.
      • The same reduction factors apply also to carbon ion treatments.

      Abstract

      Spot Scanning is a well-established technique to deliver the dose with hadron therapy systems. For many years re-scanning (called also re-painting) has been used to achieve uniform dose distribution in particular for moving organs, although it leads to an increase of the treatment time. Reducing this time is a major focus of present research. In this paper, after reviewing the current re-scanning techniques, sparse proportional re-scanning is defined and applied to 29 proton patient cases for a total of 54 fields. In this technique, only the highest weighted spot in the whole target is visited a number of times that is equal to the number N of re-scans. The number of visits of the beam spot to all remaining spots is scaled down proportionally to their weight. Sparse proportional re-scanning is advantageous especially in volumetric re-scanning. In order to quantify the potential advantages of this technique in terms of treatment time, a reduction factor of the number of scanned spots has been introduced, evaluated and analysed for 54 proton fields. The conclusion is that the reduction factor is a function of N (having values equal to 2.8 ± 0.3 and 3.6 ± 0.4 for N = 5 and N = 12 respectively) and does not depend either on the shape and volume of the target or on the distance between the scanned layers and the spot grid. The same values are approximately valid also for carbon ion treatments.

      Keywords

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