Cherenkov Excited Short-Wavelength Infrared Fluorescence Imaging in vivo with External Beam Radiation

Cherenkov emission induced by external beam radiation therapy from a clinical linear accelerator (LINAC) can be used to excite phosphors deep in biological tissues. As with all luminescence imaging, there is a desire to minimize the spectral overlap between the excitation light and emission wavelengths, here between the Cherenkov and the phosphor. Cherenkov excited short-wavelength infrared (SWIR, 1000 to 1700 nm) fluorescence imaging has been demonstrated for the first time, using long Stokes-shift fluorophore PdSe quantum dots (QD) with nanosecond lifetime and an optimized SWIR detection. The 1  /  λ2 intensity spectrum characteristic of Cherenkov emission leads to low overlap of this into the fluorescence spectrum of PdSe QDs in the SWIR range. Additionally, using a SWIR camera itself inherently ignores the stronger Cherenkov emission wavelengths dominant across the visible spectrum. The SWIR luminescence was shown to extend the depth sensitivity of Cherenkov imaging, which could be used for applications in radiotherapy sensing and imaging in human tissue with targeted molecular probes

Fast-MC-PET: A Novel Deep Learning-aided Motion Correction and Reconstruction Framework for Accelerated PET

Patient motion during PET is inevitable. Its long acquisition time not only increases the motion and the associated artifacts but also the patient's discomfort, thus PET acceleration is desirable. However, accelerating PET acquisition will result in reconstructed images with low SNR, and the image quality will still be degraded by motion-induced artifacts. Most of the previous PET motion correction methods are motion type specific that require motion modeling, thus may fail when multiple types of motion present together. Also, those methods are customized for standard long acquisition and could not be directly applied to accelerated PET. To this end, modeling-free universal motion correction reconstruction for accelerated PET is still highly under-explored. In this work, we propose a novel deep learning-aided motion correction and reconstruction framework for accelerated PET, called Fast-MC-PET. Our framework consists of a universal motion correction (UMC) and a short-to-long acquisition reconstruction (SL-Reon) module. The UMC enables modeling-free motion correction by estimating quasi-continuous motion from ultra-short frame reconstructions and using this information for motion-compensated reconstruction. Then, the SL-Recon converts the accelerated UMC image with low counts to a high-quality image with high counts for our final reconstruction output. Our experimental results on human studies show that our Fast-MC-PET can enable 7-fold acceleration and use only 2 minutes acquisition to generate high-quality reconstruction images that outperform/match previous motion correction reconstruction methods using standard 15 minutes long acquisition data.Comment: Accepted at Information Processing in Medical Imaging (IPMI 2023

Cherenkov Imaging in Linac Quality Assurance and Total Skin Electron Therapy Dose Studies

Radiation therapy is widely used for treating cancer, and the linear accelerator (Linac) is the main tool to delivery this. Linac quality assurance (QA), treatment planning, and dosimetry are important tasks that are done to make sure that the radiation doses delivered to patients are appropriate and safe. This thesis covers the development of novel Cherenkov imaging methods for Linac QA, as well as for dosimetry verification in total skin electron therapy. Basic Linac radiation field QA checks must be completed to confirm that the field shape precisely matches expectations based on configuration. These field checks were efficiently performed using remote Cherenkov imaging on a flat board. The agreement between the dose, the light field projected by the Linac, and the Cherenkov imaging validated that this type of imaging could be a surrogate dosimetry tool. The major benefit of using Cherenkov was that it is a video rate imaging approach, so that arbitrary shapes and entire treatment plans can be imaged without entering the treatment room. Imaging Cherenkov light as a correlate of dose in total skin electron therapy (TSET) was examined for patients getting treatment following the Stanford technique, where 6 different patient positions are used during irradiation, with supplemental 3D measurement of the patient’s body. This dose distribution was projected onto the 3D body model of each position and recorded as a 2D surface texture map. The cumulative dose distribution was calculated by summing up the texture maps of all positions and displayed back on the body model. Statistical analysis was conducted to determine the overall dose uniformity throughout the whole delivery. A comparison of treatments in the Stanford and rotary techniques was done to compare the dose uniformity, using an angle-dose relationship based upon Monte Carlo simulations of TSET dosimetry. A treatment plan type simulation predicted the relative dose distributions on the body surface. 3D visualization and statistical analysis of these distributions showed that there is better dose uniformity in the rotational technique. Imaging of a number of patients undergoing TSET at the University of Pennsylvania allowed for visual confirmation of the ability to image dose with Cherenkov imaging. The approach to visualization and display of Cherenkov with 3D modelling animation makes it more efficient to allow both TSET treatment planning and TSET dosimetry verification

Cherenkov imaging for total skin electron therapy (TSET)

BackgroundTotal skin electron therapy (TSET) utilizes high-energy electrons to treat malignancies on the entire body surface. The otherwise invisible radiation beam can be observed via the optical Cherenkov photons emitted from interactions between the high-energy electron beam and tissue.Methods and materialsWith a time-gated intensified camera system, the Cherenkov emission can be used to evaluate the dose uniformity on the surface of the patient in real time. Fifteen patients undergoing TSET in various conditions (whole body and half body) were imaged and analyzed. Each patient was monitored during TSET via in vivo detectors (IVD) in nine locations. For accurate Cherenkov imaging, a comparison between IVD and Cherenkov profiles was conducted using a polyvinyl chloride board to establish the perspective corrections.Results and discussionWith proper corrections developed in this study including the perspective and inverse square corrections, the Cherenkov imaging provided two-dimensional maps proportional to dose and projected on patient skin. The results of ratio between chest and umbilicus points were in good agreement with in vivo point dose measurements, with a standard deviation of 2.4% compared to OSLD measurements.ConclusionsCherenkov imaging is a viable tool for validating patient-specific dose distributions during TSET