公开(公告)号：EP1352401A2

公开(公告)日：2003-10-15

申请号：EP01986871.0

申请日：2001-12-13

申请人： Elekta AB (publ)

发明人： ALBER, Markus

IPC分类号： G21K1/04

CPC分类号： A61N5/1031 ,  A61N5/1036 ,  G21K1/025

摘要： An optimisation method for a fluence pattern to be provided via a radiotherapeutic apparatus comprising a multi-leaf collimator comprises an iteration of a progressive solution (such as a gradient approach) of the fluence profile, at least some iterations including a weighted penalty function which varies between solutions favoured by the collimator design and solutions not so favoured, later iterations including the penalty function at a greater weight. Thus, the penalty function represents locally preferred solutions derived from the constraints of the multi-leaf collimator (MLC). As the iteration progresses, the greater weight assigned to the penalty function drives the method towards a solution which is possible given the MLC constraints. However, the lesser weight attached in the early stages of the iteration allows the method to settle towards a genuinely preferred solution. Overall, therefore, the method migrates towards a theoretically ideal solution and then diverts to a nearby practically possible solution. In this way, a solution is obtained which can be put into practice but is close to a theoretically ideal solution, i.e. a solution that would be preferred in the absence of MLC constraints.

公开(公告)号：EP1352401B1

公开(公告)日：2007-03-07

申请号：EP01986871.0

申请日：2001-12-13

申请人： Elekta AB (publ)

发明人： ALBER, Markus

IPC分类号： G21K1/04

CPC分类号： A61N5/1031 ,  A61N5/1036 ,  G21K1/025

摘要： An optimisation method for a fluence pattern to be provided via a radiotherapeutic apparatus comprising a multi-leaf collimator comprises an iteration of a progressive solution (such as a gradient approach) of the fluence profile, at least some iterations including a weighted penalty function which varies between solutions favoured by the collimator design and solutions not so favoured, later iterations including the penalty function at a greater weight. Thus, the penalty function represents locally preferred solutions derived from the constraints of the multi-leaf collimator (MLC). As the iteration progresses, the greater weight assigned to the penalty function drives the method towards a solution which is possible given the MLC constraints. However, the lesser weight attached in the early stages of the iteration allows the method to settle towards a genuinely preferred solution. Overall, therefore, the method migrates towards a theoretically ideal solution and then diverts to a nearby practically possible solution. In this way, a solution is obtained which can be put into practice but is close to a theoretically ideal solution, i.e. a solution that would be preferred in the absence of MLC constraints.