Dose optimization of 2D X-ray image acquisition protocols in image-guided radiotherapy.

PURPOSE: In contemporary radiotherapy, patient positioning accuracy relies on kV imaging. This study aims at optimizing planar kV image acquisition protocols regarding patient dose without degrading image quality.

MATERIALS AND

METHODS

An image quality test-object was placed in-between PMMA plates, suitably arranged to model head or pelvis. Constructed phantoms were imaged using default protocols, the resultant image quality was assessed and the corresponding radiation dose was measured. The process was repeated using numerous kV/mAs combinations to identify those acquisition settings providing images at lower dose than the default protocols but without deterioration in image quality. Default and dose-optimized protocols were then tested on an anthropomorphic phantom and on 51 patients during two successive treatment sessions. Image quality was independently assessed by two readers. Organ and effective doses were estimated using a Monte Carlo simulation software.

RESULTS

Low-contrast detectability exhibited a stronger dependence on kV/mAs settings, compared to high-contrast resolution. Dose-optimized protocols resulted in significant dose reductions (anteroposterior-head 48.0 %, lateral-head 30.0 %, anteroposterior-pelvis 28.4 %, lateral-pelvis 27.0 %) compared to the default ones, without compromising image quality. Optimized protocols decreased effective doses by 54 % and 29.6 % in head and pelvic acquisitions, respectively. Regarding image quality, anthropomorphic and patient images acquired using the dose-optimized protocols were subjectively evaluated equivalent to those obtained with the corresponding default settings, indicating that the proposed protocols may be routinely used.

CONCLUSIONS

Given the potentially large number of radiotherapy fractions and the pertinent image acquisitions, dose-optimized protocols could significantly reduce patient dose associated with planar imaging without compromising positioning accuracy.