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Quantifying the performance of in vivo portal dosimetry in detecting four types of treatment parameter variations
Author(s) -
Bojechko C.,
Ford E. C.
Publication year - 2015
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 - 10.1118/1.4935093
Subject(s) - multileaf collimator , isocenter , dosimetry , nuclear medicine , receiver operating characteristic , image guided radiation therapy , radiation treatment planning , mathematics , radiation therapy , medical imaging , biomedical engineering , computer science , medicine , artificial intelligence , statistics , radiology , imaging phantom
Purpose: To quantify the ability of electronic portal imaging device (EPID) dosimetry used during treatment ( in vivo ) in detecting variations that can occur in the course of patient treatment. Methods: Images of transmitted radiation from in vivo EPID measurements were converted to a 2D planar dose at isocenter and compared to the treatment planning dose using a prototype software system. Using the treatment planning system (TPS), four different types of variability were modeled: overall dose scaling, shifting the positions of the multileaf collimator (MLC) leaves, shifting of the patient position, and changes in the patient body contour. The gamma pass rate was calculated for the modified and unmodified plans and used to construct a receiver operator characteristic (ROC) curve to assess the detectability of the different parameter variations. The detectability is given by the area under the ROC curve (AUC). The TPS was also used to calculate the impact of the variations on the target dose–volume histogram. Results: Nine intensity modulation radiation therapy plans were measured for four different anatomical sites consisting of 70 separate fields. Results show that in vivo EPID dosimetry was most sensitive to variations in the machine output, AUC = 0.70 − 0.94, changes in patient body habitus, AUC = 0.67 − 0.88, and systematic shifts in the MLC bank positions, AUC = 0.59 − 0.82. These deviations are expected to have a relatively small clinical impact [planning target volume (PTV) D 99 change <7%]. Larger variations have even higher detectability. Displacements in the patient's position and random variations in MLC leaf positions were not readily detectable, AUC < 0.64. The D 99 of the PTV changed by up to 57% for the patient position shifts considered here. Conclusions: In vivo EPID dosimetry is able to detect relatively small variations in overall dose, systematic shifts of the MLC's, and changes in the patient habitus. Shifts in the patient's position which can introduce large changes in the target dose coverage were not readily detected.