Remote dose imaging from Cherenkov light using spatially resolved CT calibration in breast radiotherapy

Purpose Imaging Cherenkov light during radiotherapy allows the visualization and recording of frame-by-frame relative maps of the dose being delivered to the tissue at each control point used throughout treatment, providing one of the most complete real-time means of treatment quality assurance. In non-turbid media, the intensity of Cherenkov light is linear with surface dose deposited, however the emission from patient tissue is well-known to be reduced by absorbing tissue components such as hemoglobin, fat, water, and melanin, and diffused by the scattering components of tissue. Earlier studies have shown that bulk correction could be achieved by using the patient planning computed tomography (CT) scan for attenuation correction. Methods In this study, CT maps were used for correction of spatial variations in emissivity. Testing was completed on Cherenkov images from radiotherapy treatments of post-lumpectomy breast cancer patients (n = 13), combined with spatial renderings of the patient radiodensity (CT number) from their planning CT scan. Results The correction technique was shown to provide a pixel-by-pixel correction that suppressed many of the inter- and intra-patient differences in the Cherenkov light emitted per unit dose. This correction was established from a calibration curve that correlated Cherenkov light intensity to surface-rendered CT number (R6MV2=0.70$R_{6{\rm{MV}}}<^>2 = 0.70$ and R10MV2=0.72$R_{10{\rm{MV}}}<^>2 = 0.72$). The corrected Cherenkov intensity per unit dose standard error was reduced by nearly half (from similar to 30% to similar to 17%). Conclusions This approach provides evidence that the planning CT scan can mitigate some of the tissue-specific attenuation in Cherenkov images, allowing them to be translated into near surface dose images.

Automated summary

This study investigates the correction of spatial variations in Cherenkov images using CT maps. The results show that this approach can effectively reduce inter- and intra-patient differences, providing a more accurate near surface dose image.