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TU‐A‐211A‐01: Margins in Radiation Therapy
Author(s) -
Low D,
Litzenberg D
Publication year - 2009
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.3182306
Subject(s) - margin (machine learning) , population , position (finance) , dosimetry , computer science , medical physics , medicine , nuclear medicine , machine learning , environmental health , finance , economics
Conformal radiation therapy has historically used margins to account for geometrical uncertainties in the position of a target volume. The margins, in their simplest form, are simply expansions to the diameter of a treatment beam, to ensure that dosimetric planning criteria are met in the presence of inter‐ and intra‐fraction setup variations. Historically, the size of the margin in a given treatment site was difficult to determine due to the available technology and the time and effort required to obtaining accurate data. Consequently, margins were estimated to accommodate a population of patients. As new technologies have emerged, target volume position errors have become easier to measure, their accuracy has increased, and the measurements can be made much more frequently. As the quantity and quality of data has increased for patient populations, and even for individual patients, the conceptual basis of employing margins has evolved. Strategies for ensuring dosimetric coverage may now be individualized to a specific patient's geometric uncertainty characteristics with customized margins, or they may incorporate geometric correction based on predefined action levels. Other strategies may incorporate continuous monitoring to gate or modify the beam. And finally, other strategies seek to eliminate margins by including the estimated geometrical uncertainty into the development of the dose distribution. Learning Objectives: 1. To provide an educational review of the technologies and methods of measuring target volume positioning errors. 2. To review methods of determining population margins from measured data. 3. To review corrective and intervention strategies for patients with individualized margins. 4. To review planning strategies which seek to eliminate margins.

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