High-resolution x-ray luminescence computed tomography

Michael C. Lun; Changqing Li

doi:10.1117/12.2544493

28 February 2020 High-resolution x-ray luminescence computed tomography

Michael C. Lun, Changqing Li

Proceedings Volume 11317, Medical Imaging 2020: Biomedical Applications in Molecular, Structural, and Functional Imaging; 113171D (2020) https://doi.org/10.1117/12.2544493
Event: SPIE Medical Imaging, 2020, Houston, Texas, United States

Abstract

High-resolution imaging modalities play a critical role for advancing biomedical sciences. Recently, x-ray luminescence computed tomography (XLCT) imaging was introduced as a hybrid molecular imaging modality that combines the highspatial resolution of x-ray imaging and molecular sensitivity of optical imaging. The narrow x-ray beam based XLCT imaging has been demonstrated to achieve high spatial resolution, even at depth, with great molecular sensitivity. Using a focused x-ray beam as the excitation source, orders of magnitude of increased sensitivity has been verified compared with previous methods with a collimated x-ray beam. In this work, we demonstrate the high-spatial resolution capabilities of our focused x-ray beam based XLCT imaging system by scanning two sets of targets, differing in the target size, embedded inside of two tissue-mimicking cylindrical phantoms. Gd2O2S:Eu3+ targets of 200 μm and 150 μm diameters were created and embedded with the same edge-to-edge distances as their diameters respectively. We scanned and reconstructed a single transverse section and successfully demonstrated that a focused x-ray beam with an average dual-cone size of 125 μm could separate the targets in both phantoms with good shape and location accuracy. We have also improved the current XLCT imaging system to make it feasible for fast three-dimensional XLCT scanning.

Conference Presentation

Citation Download Citation

Michael C. Lun and Changqing Li "High-resolution x-ray luminescence computed tomography", Proc. SPIE 11317, Medical Imaging 2020: Biomedical Applications in Molecular, Structural, and Functional Imaging, 113171D (28 February 2020); https://doi.org/10.1117/12.2544493

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