AbstractID: 6898 Title: A Maximum Entropy Method for Inverse Planning
Abstract: The maximum entropy method (MEM) is a powerful inverse analysis technique, which
has been used in many fields of science and engineering, such as image reconstruction, NMR
signal processing. Unlike other methods, MEM naturally incorporate a-priori knowledge of the
problem into the optimized cost function. This feature is especially important in radiotherapy
treatment planning since we usually have some knowledge about the stage of tumor development
and prescription doses (include some dose constraints to the surrounding normal organs), and the
nature of inverse parameter estimation of MEM inherently consists with the inverse planning. In
this work, we used Gull and Skilling’s entropy definition and construct an entropy function to
reach the homogeneity of dose distribution in planning target volume (PTV). Some dose
constraints on surrounding normal organs are imposed on this entropy function. A sequential
quadratic programming algorithm (SQP) is used to search for the optimization solution. We think
that this method can play an important role in the application of radiotherapy planning. Though
the example given in this paper was conformal external-beam treatment, we think the method can
be adopted in the optimization of intensity modulated radiation therapy.