Abstract
Introduction: New medical technologies must be tested across diverse populations to ensure efficacy for all patients. In the last decade, a novel technique for imaging in vivo radiation dose was developed to mitigate clinical radiotherapy (RT) incidents. Named Cherenkov imaging (CI), this technology captures the inherent light emission from ionizing radiation interacting with tissue during RT and allows for spatial verification of dose across a patient surface compared to their plan. Recent efforts have been made to use CI to quantitatively assess the true dose delivered across a patient’s surface in real-time, but many patient-specific factors prevent developing a direct Cherenkov-to-dose calibration until addressed. Melanin, a known absorber of light including Cherenkov wavelengths, is the most influential. Early phantom studies showed a near 45% change in emission across a range of skin tones for the same dose. Up until now, further investigation into this effect has been limited to phantoms due to a low number of in vivo CI studies and predominantly Caucasian catchment area demographics. We present a first detailed analysis of imaging patients with a wider range of skin tones and quantifying the effect that it has on dose estimation errors. Methods: A multi-institutional partnership was developed to expand patient demographics and increase diverse skin tone representation. All CI was completed with time-gated iCMOS cameras that capture the low light emission from tissue during RT. Cherenkov images were normalized by absolute planned dose and bulk tissue heterogeneities to minimize non-linear effects outside of skin tone. Patients were initially categorized by ethnicity and their skin tones were quantified by analysis of calibrated color photography. Average Cherenkov light intensity per dose was compared across various skin tones towards developing a calibration system for quantifying dose from the corrected signals. Results: In vivo Cherenkov images exhibit a nearly 220% decrease in signal across a range of skin tones, from White to Black/African American patients, greatly affecting the Cherenkov-to-dose calibration. However, a linear correlation exists between quantitative skin luminosity and dose-normalized Cherenkov emission. Thus, quantifying skin luminosity provides a method to normalize out the effect of skin tone and minimize the in vivo dose estimation errors across diverse patient demographics. Conclusion: This study addresses the critically important issue of developing optical tools that are appropriately calibrated for all skin tones. In vivo CI must be calibrated by skin tone for dosimetric assessments. We have shown that it is not only feasible to image dark skin patients, but possible to quantify the effect that a range of skin tones has on CI for a given dose. Using this information, we can develop a skin tone normalization algorithm to minimize dose estimation errors. Future work will focus on expanding our patient dataset to even darker skin tones through active recruitment efforts in the participating clinics.
Citation Format: Savannah Decker, Jacqueline Andreozzi, Diego Hernandez, Daniel Alexander, Vihan Wickramasinghe, Ibrahim Oraiqat, Erli Chen, Iman Washington, Rongxiao Zhang, Lesley Jarvis, Petr Bruza, David Gladstone, Brian Pogue. Radiation dose estimates via live, optical imaging are highly dependent upon patient skin tone [abstract]. In: Proceedings of the 16th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2023 Sep 29-Oct 2;Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(12 Suppl):Abstract nr PR001.