Friday, April 26, 2024
4/26/2024
Project Summary In this project, we propose to develop and optimize a novel X-ray fluorescence emission tomography system and reconstruction algorithm to image trace gold in biological samples. Gold nanoparticles (GNPs) play an important role in cancer therapy, serving as radiosensitizers in metal-meditated radiation therapy and as critical components to photothermal ablation therapy. These therapies offer a promising treatment for superficial lesions and are currently being explored in in vivo and clinical trials, but could see improved efficacy and decreased side effects if the location and concentrations of GNPs could be mapped accurately. However current metal-mapping methods do not provide the sensitivity or tissue penetration depth necessary to image relevant metal concentrations. For these therapies to be translated to the clinic, there needs to be a highly sensitive metal- mapping imaging modality that can image gold at the relevant concentrations and depths. In recent years, X-ray fluorescence tomography has emerged as a promising modality for metal-mapping. Specifically, X-ray fluorescence emission tomography (XFET) offers high sensitivity needed for imaging trace gold used in in vivo and clinical studies. Furthermore, XFET offers advantages over other x-ray fluorescence imaging modalities: it provides a direct measurement of the metal without noise-amplifying tomographic image reconstruction, and it does not require a full sinogram, which limits the tissue penetration depth of other modalities. In the proposed work, we will optimize the hardware acquisition parameters of an existing XFET system to maximize gold detectability. We will also optimize an XFET image reconstruction algorithm to jointly estimate metal maps as well as attenuation maps, providing a novel method for obtaining an attenuation map that would otherwise be obtained by an additional, dose-delivering computed tomography (CT) scan. The specific aims of this proposal are: 1) develop algorithms and a realistic forward model to jointly reconstruct metal distributions and attenuation maps of objects, 2) optimize XFET hardware acquisition parameters to maximize gold detectability at specified radiation dose levels, and 3) validate reconstruction methods and optimization strategies in mouse phantom models, assess minimum detectable gold concentration, and compare image quality metrics to CT. Upon completion, aim 1 will provide a method to map metals at low concentrations, and a novel method of obtaining an attenuation map using fluorescent emission data. Aim 2 will design a novel system geometry with parameters that maximize gold detectability. Aim 3 will demonstrate XFET sensitivity limits and compare image quality metrics to an existing system. These results will allow us to make predictions about this preclinical system’s capabilities in an eventual clinical scenario, paving the way for XFET to be used as a clinical imaging system capable of mapping therapeutic GNPs for safer treatment and fewer side effects in cancer therapies.
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