Optimal radiation beam profiles considering uncertainties in beam patient alignment.

The often large uncertainties that exist in beam patient alignment during radiation therapy may require modification of the incident beams to ensure an optimal delivered dose distribution to the target volume. This problem becomes increasingly severe when the required dose distribution of the incident beams becomes more heterogeneous. A simple analytical formula is derived for the case when the fraction number is high, and the desired relative dose variations are small. This formula adjusts the fluence distribution of the incident beam so that the resultant dose distribution will be as close as possible to the desired one considering the uncertainties in beam patient alignment. When sharp dose gradients are important, for instance at the border of the target volume, the problem is much more difficult. It is shown here that, if the tumor is surrounded by organs at risk, it is generally best to open up the field by about one standard deviation of the positional uncertainty--that is sigma/2 on each side of the target volume. In principle it is simultaneously desirable to increase the prescribed dose by a few per cent compared to the case where the positional uncertainty is negligible, in order to compensate for the rounded shoulders of the delivered dose distribution. When the tissues surrounding the tumor no longer are dose limiting even larger increases in field size may be advantageous. For more critical clinical situations the positional uncertainty may even limit the success of radiotherapy. In such cases one generally wants to create a steeper dose distribution than the underlying random Gaussian displacement process allows. The problem is then best handled by quantifying the treatment outcome under the influence of the stochastic process of patient misalignment. Either the coincidence with the desired dose distribution, or the expectation value of the probability of achieving complication-free tumor control is maximized under the influence of this stochastic process. It is shown that the most advantageous treatment is to apply beams that are either considerably widened or slightly widened and over flattened near the field edges for small and large fraction numbers respectively.

[1]  Jörg W. Müller Some second thoughts on error statements , 1979 .

[2]  A Brahme,et al.  Correction of a measured distribution for the finite extension of the detector. , 1981, Strahlentherapie.

[3]  Michael Goitein,et al.  Nonstandard deviations: Communications , 1983 .

[4]  T E Schultheiss,et al.  Models in radiotherapy: volume effects. , 1983, Medical physics.

[5]  A B Wolbarst,et al.  Optimization of radiation therapy II: the critical-voxel model. , 1984, International journal of radiation oncology, biology, physics.

[6]  A Brahme,et al.  Dosimetric precision requirements in radiation therapy. , 1984, Acta radiologica. Oncology.

[7]  G J Kutcher,et al.  Clinical experience with a computerized record and verify system. , 1985, International journal of radiation oncology, biology, physics.

[8]  A. Brahme,et al.  Optimal dose distribution for eradication of heterogeneous tumours. , 1987, Acta oncologica.

[9]  H. Withers,et al.  Biologic basis of radiation therapy , 1987 .

[10]  J. Leong,et al.  Implementation of random positioning error in computerised radiation treatment planning systems as a result of fractionation. , 1987, Physics in medicine and biology.

[11]  A Brahme,et al.  Shaping of arbitrary dose distributions by dynamic multileaf collimation. , 1988, Physics in medicine and biology.

[12]  B Kihlén,et al.  Reproducibility of field alignment in radiation therapy. A large-scale clinical experience. , 1989, Acta oncologica.

[13]  A. Kellerer A Generalised Formulation of Microdosimetric Quantities , 1990 .

[14]  B. Lind Properties of an algorithm for solving the inverse problem in radiation therapy , 1990 .

[15]  A Brahme,et al.  Optimization of uncomplicated control for head and neck tumors. , 1990, International journal of radiation oncology, biology, physics.

[16]  L Lindborg,et al.  Influence of microdosimetric quantities on observed dose-response relationships in radiation therapy. , 1990, Radiation research.

[17]  M Goitein,et al.  Calculation of normal tissue complication probability and dose-volume histogram reduction schemes for tissues with a critical element architecture. , 1991, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[18]  R Mohan,et al.  The role of uncertainty analysis in treatment planning. , 1991, International journal of radiation oncology, biology, physics.

[19]  Bengt K. Lind,et al.  Radiation therapy planning and optimization studied as inverse problems , 1991 .

[20]  M. Goitein,et al.  Tolerance of normal tissue to therapeutic irradiation. , 1991, International journal of radiation oncology, biology, physics.

[21]  A Brahme,et al.  Photon field quantities and units for kernel based radiation therapy planning and treatment optimization , 1992, Physics in medicine and biology.

[22]  A Brahme,et al.  Tumour and normal tissue responses to fractionated non-uniform dose delivery. , 1992, International journal of radiation biology.

[23]  A Brahme,et al.  An algorithm for maximizing the probability of complication-free tumour control in radiation therapy , 1992, Physics in medicine and biology.