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- W4289528770 abstract "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." @default.
- W4289528770 created "2022-08-03" @default.
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- W4289528770 date "2023-02-01" @default.
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- W4289528770 title "Accurate and Early Metastases Diagnosis in Live Animals With Multimodal X-ray and Optical Imaging" @default.
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- W4289528770 doi "https://doi.org/10.1016/j.ijrobp.2022.07.1832" @default.
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