Cherenkov light emission occurs in patient tissues during radiation therapy, and the development of imaging systems to selectively capture this signal has paved a way to visualize the treatment delivery in real time.^{1 – 4} The ability to visualize the beam shape is well documented, although the interpretation of the emitted intensity is much more complex because of the range of factors that influence the observed signal intensity.^5,6 While several studies have examined the influence of tissue optical properties, few have systematically examined the nature of the radiation beam itself in affecting the observed emitted Cherenkov signal intensity. In particular, there has always been a mystery about why the intensity of Cherenkov light emitted from patients undergoing radiation therapy does not appear to be a strong function of beam energy, despite the fact that it is well known that the basic production of Cherenkov light is a strong function of particle energy⁷ (Fig. 1). Cherenkov light is continuously emitted from secondary electrons as they scatter inside tissue and are emitted over a range of angles. In this paper, both analytic theory and experimental validation studies are used to interpret the diffuse Cherenkov radiant emission from tissue, relevant to changes in radiation therapy beam characteristics and interactions with tissue optical properties.

The gastric pathogen, Helicobacter pylori bacteria have to swim across a pH gradient from 2 to 7 in the mucus layer to colonize the gastric epithelium. Previous studies from our group have shown that porcine gastric mucin (PGM) gels at an acidic pH < 4, and H. pylori bacteria are unable to swim in the gel, although their flagella rotate. Changing pH impacts both the rheological properties of gastric mucin and also influences the proton (H+)-pumped flagellar motors of H. pylori as well as their anti-pH sensing receptors. To unravel these intertwined effects of acidic pH on both the viscoelastic properties of the mucin-based mucus as well as the flagellar motors and chemo-receptors of the bacterium, we compared the motility of H. pylori in PGM with that in Brucella broth (BB10) at different pH values using phase contrast microscopy to track the motion of the bacteria. The results show that the distribution of swimming speeds and other characteristics of the bacteria trajectories exhibit pH-dependent differences in both media. The swimming speed exhibits a peak at pH 4 in BB10, and a less pronounced peak at a higher pH of 5 in PGM. At all pH values, the bacteria swam faster and had a longer net displacement in BB10 compared to PGM. While the bacteria were stuck in PGM gels at pH < 4, they swam at these acidic pH values in BB10, although with reduced speed. Decreasing pH leads to a decreased fraction of motile bacteria, with a decreased contribution of the faster swimmers to the distributions of speeds and net displacement of trajectories. The body rotation rate is weakly dependent on pH in BB10, whereas in PGM bacteria that are immobilized in the low pH gel are capable of mechano-sensing and rotate faster. Bacteria can be stuck in the gel in various ways, including the flagella getting entangled in the fibers of the gel or the cell body being stuck to the gel. Our results show that in BB10, swimming is optimized at pH4, reflecting the combined effects of pH sensing by anti-pH tactic receptors and impact on H+ pumping of flagellar motors, while the increase in viscosity of PGM with decreasing pH and gelation below pH 4 lead to further reduction in swimming speed, with optimal swimming at pH 5 and immobilization of bacteria below pH 4.

SignificanceHigh-energy x-ray delivery from a linear accelerator results in the production of spectrally continuous broadband Cherenkov light inside tissue. In the absence of attenuation, there is a linear relationship between Cherenkov emission and deposited dose; however, scattering and absorption result in the distortion of this linear relationship. As Cherenkov emission exits the absorption by tissue dominates the observed Cherenkov emission spectrum. Spectroscopic interpretation of this effects may help to better relate Cherenkov emission to ionizing radiation dose delivered during radiotherapy.AimIn this study, we examined how color Cherenkov imaging intensity variations are caused by absorption from both melanin and hemoglobin level variations, so that future Cherenkov emission imaging might be corrected for linearity to delivered dose.ApproachA custom, time-gated, three-channel intensified camera was used to image the red, green, and blue wavelengths of Cherenkov emission from tissue phantoms with synthetic melanin layers and varying blood concentrations. Our hypothesis was that spectroscopic separation of Cherenkov emission would allow for the identification of attenuated signals that varied in response to changes in blood content versus melanin content, because of their different characteristic absorption spectra.ResultsCherenkov emission scaled with dose linearly in all channels. Absorption in the blue and green channels increased with increasing oxy-hemoglobin in the blood to a greater extent than in the red channel. Melanin was found to absorb with only slight differences between all channels. These spectral differences can be used to derive dose from measured Cherenkov emission.ConclusionsColor Cherenkov emission imaging may be used to improve the optical measurement and determination of dose delivered in tissues. Calibration for these factors to minimize the influence of the tissue types and skin tones may be possible using color camera system information based upon the linearity of the observed signals.

Objectives: Examine the responses of multiple image similarity metrics to detect patient positioning errors in radiotherapy observed through Cherenkov imaging, which may be used to optimize automated incident detection. Methods: An anthropomorphic phantom mimicking patient vasculature, a biological marker seen in Cherenkov images, was simulated for a breast radiotherapy treatment. The phantom was systematically shifted in each translational direction, and Cherenkov images were captured during treatment delivery at each step. The responses of mutual information (MI) and the γ passing rate (%GP) were compared to that of existing field-shape matching image metrics, the Dice coefficient, and mean distance to conformity (MDC). Patient images containing other incidents were analyzed to verify the best detection algorithm for different incident types. Results: Positional shifts in all directions were registered by both MI and %GP, degrading monotonically as the shifts increased. Shifts in intensity, which may result from erythema or bolus-tissue air gaps, were detected most by %GP. However, neither metric detected beam-shape misalignment, such as that caused by dose to unintended areas, as well as currently employed metrics (Dice and MDC). Conclusions: This study indicates that different radiotherapy incidents may be detected by comparing both inter- and intrafractional Cherenkov images with a corresponding image similarity metric, varying with the type of incident. Future work will involve determining appropriate thresholds per metric for automatic flagging. Advances in knowledge: Classifying different algorithms for the detection of various radiotherapy incidents allows for the development of an automatic flagging system, eliminating the burden of manual review of Cherenkov images.