z-logo
Premium
Practical dose point‐based methods to characterize dose distribution in a stationary elliptical body phantom for a cone‐beam C‐arm CT system
Author(s) -
Choi JangHwan,
Constantin Dragos,
Ganguly Arundhuti,
Girard Erin,
Morin Richard L.,
Dixon Robert L.,
Fahrig Rebecca
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 - 10.1118/1.4927257
Subject(s) - imaging phantom , cone beam computed tomography , cone beam ct , dosimetry , physics , medical imaging , distribution (mathematics) , point (geometry) , beam (structure) , nuclear medicine , optics , computed tomography , medical physics , mathematics , geometry , medicine , mathematical analysis , radiology
Purpose: To propose new dose point measurement‐based metrics to characterize the dose distributions and the mean dose from a single partial rotation of an automatic exposure control‐enabled, C‐arm‐based, wide cone angle computed tomography system over a stationary, large, body‐shaped phantom. Methods: A small 0.6 cm 3 ion chamber (IC) was used to measure the radiation dose in an elliptical body‐shaped phantom made of tissue‐equivalent material. The IC was placed at 23 well‐distributed holes in the central and peripheral regions of the phantom and dose was recorded for six acquisition protocols with different combinations of minimum kVp (109 and 125 kVp) and z ‐collimator aperture (full: 22.2 cm; medium: 14.0 cm; small: 8.4 cm). Monte Carlo (MC) simulations were carried out to generate complete 2D dose distributions in the central plane ( z = 0). The MC model was validated at the 23 dose points against IC experimental data. The planar dose distributions were then estimated using subsets of the point dose measurements using two proposed methods: (1) the proximity‐based weighting method (method 1) and (2) the dose point surface fitting method (method 2). Twenty‐eight different dose point distributions with six different point number cases (4, 5, 6, 7, 14, and 23 dose points) were evaluated to determine the optimal number of dose points and their placement in the phantom. The performances of the methods were determined by comparing their results with those of the validated MC simulations. The performances of the methods in the presence of measurement uncertainties were evaluated. Results: The 5‐, 6‐, and 7‐point cases had differences below 2%, ranging from 1.0% to 1.7% for both methods, which is a performance comparable to that of the methods with a relatively large number of points, i.e., the 14‐ and 23‐point cases. However, with the 4‐point case, the performances of the two methods decreased sharply. Among the 4‐, 5‐, 6‐, and 7‐point cases, the 7‐point case (1.0% [±0.6%] difference) and the 6‐point case (0.7% [±0.6%] difference) performed best for method 1 and method 2, respectively. Moreover, method 2 demonstrated high‐fidelity surface reconstruction with as few as 5 points, showing pixelwise absolute differences of 3.80 mGy (±0.32 mGy). Although the performance was shown to be sensitive to the phantom displacement from the isocenter, the performance changed by less than 2% for shifts up to 2 cm in the x ‐ and y ‐axes in the central phantom plane. Conclusions: With as few as five points, method 1 and method 2 were able to compute the mean dose with reasonable accuracy, demonstrating differences of 1.7% (±1.2%) and 1.3% (±1.0%), respectively. A larger number of points do not necessarily guarantee better performance of the methods; optimal choice of point placement is necessary. The performance of the methods is sensitive to the alignment of the center of the body phantom relative to the isocenter. In body applications where dose distributions are important, method 2 is a better choice than method 1, as it reconstructs the dose surface with high fidelity, using as few as five points.

This content is not available in your region!

Continue researching here.

Having issues? You can contact us here