Quantitation of the a priori dosimetric capabilities of spatial points in inverse planning and its significant implication in defining IMRT solution space
Creators
- 1. Department of Radiation Oncology, Stanford University, Stanford, CA 94305-5847 (United States)
- 2. Department of Mathematics, Stanford University, Stanford, CA 94305-2125 (United States)
Description
In inverse planning, the likelihood for the points in a target or sensitive structure to meet their dosimetric goals is generally heterogeneous and represents the a priori knowledge of the system once the patient and beam configuration are chosen. Because of this intrinsic heterogeneity, in some extreme cases, a region in a target may never meet the prescribed dose without seriously deteriorating the doses in other areas. Conversely, the prescription in a region may be easily met without violating the tolerance of any sensitive structure. In this work, we introduce the concept of dosimetric capability to quantify the a priori information and develop a strategy to integrate the data into the inverse planning process. An iterative algorithm is implemented to numerically compute the capability distribution on a case specific basis. A method of incorporating the capability data into inverse planning is developed by heuristically modulating the importance of the individual voxels according to the a priori capability distribution. The formalism is applied to a few specific examples to illustrate the technical details of the new inverse planning technique. Our study indicates that the dosimetric capability is a useful concept to better understand the complex inverse planning problem and an effective use of the information allows us to construct a clinically more meaningful objective function to improve IMRT dose optimization techniques
Availability note (English)
Available online at http://stacks.iop.org/0031-9155/50/1469/pmb5_7_010.pdf or at the Web site for the journal Physics in Medicine and Biology (ISSN 1361-6560) http://www.iop.org/Additional details
Identifiers
- URL
- http://stacks.iop.org/0031-9155/50/1469/pmb5_7_010.pdf; http://www.iop.org/;
- DOI
- 10.1088/0031-9155/50/7/010;
- PII
- S0031-9155(05)92274-4;
Publishing Information
- Journal Title
- Physics in Medicine and Biology
- Journal Volume
- 50
- Journal Issue
- 7
- Journal Page Range
- p. 1469-1482
- ISSN
- 0031-9155
- CODEN
- PHMBA7
INIS
- Country of Publication
- United Kingdom
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 36099398
- Subject category
- S62: RADIOLOGY AND NUCLEAR MEDICINE;
- Descriptors DEI
- ALGORITHMS; BEAMS; ITERATIVE METHODS; OPTIMIZATION; PATIENTS; PLANNING; RADIATION DOSES; RADIOTHERAPY
- Descriptors DEC
- CALCULATION METHODS; DOSES; MATHEMATICAL LOGIC; MEDICINE; NUCLEAR MEDICINE; RADIOLOGY; THERAPY