Research Project
10286795
SPECT with a Compton Camera for Thyroid Cancer Imaging ABSTRACT The thyroid gland is butterfly-shaped in the lower front of the neck, and secretes hormones for normal biological functions. The incidence of thyroid nodules increases with age, involving more than half of the population. Thyroid cancer is the most common type of endocrine-related cancer and the most common cancer in young women, with over 50K new cases per year in the United States. To detect and treat thyroid cancer, it is desired to characterize the nodule accurately. Currently, single photon emission computed tomography (SPECT) and computed tomography (CT) are used with radioiodine scintigraphy to evaluate patients with thyroid cancer. The gamma camera for SPECT contains a mechanical collimator that greatly compromises dose efficiency and limits diagnostic sensitivity. Fortunately, the Compton camera is emerging as an ideal approach for mapping the distribution of radiopharmaceuticals inside the thyroid. It is because the Compton camera requires no mechanical collimation and in principle rejects no gamma ray photon. Hence, radiation dose will be reduced by orders of magnitude in screening and follow-up scans of patients. In this R21 project, we will design a high-efficiency and high-quality tomographic imaging system with a Compton camera dedicated to thyroid cancer imaging, and develop an associated software package for Compton scattering based SPECT imaging. The major innovation lies in the deep learning empowered image reconstruction and the Timepix3-based Compton camera for thyroid cancer imaging. The proposed techniques help reduce radiation dose dramatically, improve the imaging speed, and enhance image quality and diagnostic performance, having a great potential for clinical translation. The three specific aims are defined as follows: (1) a Monte Carlo simulator will be developed for gamma ray Compton data synthesis; (b) deep reconstruction algorithms will be developed for Compton camera based SPECT, and (c) a SPECT system will be designed in numerical simulation and phantom experiments for ultra-low-dose thyroid imaging. Upon the completion of this project, the simulation and reconstruction software tools should have been developed for tomographic imaging of the radiotracer distribution in the human thyroid, and a point of care (POC) SPECT system will have been designed with the Compton camera and experimentally verified for a superior diagnostic performance at an ultra-low dose. The synergy among the deep learning techniques and the cutting-edge Timepix3 camera will have been demonstrated for a follow-up R01 proposal.
