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Accurate and Early Metastases Diagnosis in Live Animals With Multimodal X-ray and Optical Imaging

医学 断层摄影术 放射科 医学影像学 临床前影像学 转移 分子成像 光学成像 癌症 体内 光学 生物技术 内科学 生物 物理
作者
Jiahao Chen,Ning Zhao,Valeria A. Copello,Ruokun Yi,Kerry L. Burnstein,Yidong Yang
出处
期刊:International Journal of Radiation Oncology Biology Physics [Elsevier]
卷期号:115 (2): 511-517 被引量:1
标识
DOI:10.1016/j.ijrobp.2022.07.1832
摘要

In vivo optical imaging systems are essential to track disease progression and evaluate therapeutic efficacy in animal studies. However, current approaches are limited by their inability to accurately capture 3-dimensional (3-D) image information. To overcome this hindrance, we adopted x-ray computed tomography (CT) as a prior for 3-D optical image reconstruction and further challenged the multimodal imaging performance with a metastasis model.The iSMAART system, an integrated small animal research platform, features coregistered high-quality quantitative optical tomography and CT. In the synergistic dual-modality imaging, CT provides both 3-D anatomy information and animal structure mesh for optical tomography reconstruction, which is performed using bioluminescence projections acquired from 4 orthogonal angles. The multimodal imaging system was challenged with a prostate cancer metastasis model, and a double-blind histopathology diagnosis was obtained to validate the imaging results.The iSMAART located, visualized, and quantified early tumor metastases at the millimeter scale, and can accurately track deep tumors as small as 1.5 mm in live animals. Tumors metastasized into the liver, diaphragm, and tibia in 4 mice were all successfully diagnosed by the integrated tomographic imaging.Instead of roughly comparing surface-light intensities, as traditionally performed in 2-dimensional optical imaging, iSMAART provides accurate tumor imaging and quantitative assessment capabilities with integrated CT and optical tomography for cancer metastasis research. With the powerful 3-D optical/CT imaging capability, iSMAART has the potential to tackle more complex research needs with higher targeting accuracy.
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