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Multi-modality measurement and comprehensive analysis of hepatocellular carcinoma using synchrotron-based microscopy and spectroscopy

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Abstract

The visualization and data mining of tumor multidimensional information may play a major role in the analysis of the growth, metastasis, and microenvironmental changes of tumors while challenging traditional imaging and data processing techniques. In this study, a general trans-scale and multi-modality measurement method was developed for the quantitative diagnosis of hepatocellular carcinoma (HCC) using a combination of propagation-based phase-contrast computed tomography (PPCT), scanning transmission soft X-ray microscopy (STXM), and Fourier transform infrared micro-spectroscopy (FTIR). Our experimental results reveal the trans-scale micro-morphological HCC pathology and facilitate quantitative data analysis and comprehensive assessment. These results include some visualization features of PPCT-based tissue microenvironments, STXM-based cellular fine structures, and FTIR-based bio-macromolecular spectral characteristics during HCC tumor differentiation and proliferation. The proposed method provides multidimensional feature data support for constructing a high-accuracy machine learning algorithm based on a gray-level histogram, gray-gradient co-occurrence matrix, gray-level co-occurrence matrix, and back-propagation neural network model. Multi-dimensional information analysis and diagnosis revealed the morphological pathways of HCC pathological evolution and we explored the relationships between HCC-related feature changes in inflammatory microenvironments, cellular metabolism, and the stretching vibration peaks of biomolecules of lipids, proteins, and nucleic acids. Therefore, the proposed methodology has strong potential for the visualization of complex tumors and assessing the risks of tumor differentiation and metastasis.

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Acknowledgements

We thank the staff from the BL13HB beamline of the X-ray Imaging and Biomedical Center, BL08U1-A beamline of the Soft X-ray Spectro-Microscopy Center, BL06B beamline of the Dynamic Beamline: IR Branch at the Shanghai Synchrotron Radiation Facility, and BL01B beamline of the National Facility for Protein Science in Shanghai for their assistance with data collection.

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Author notes

  1. Gong-Xiang Wei and Sui-Xia Zhang have contributed equally.

Authors and Affiliations

  1. School of Physics and Optoelectronic Engineering, Shandong University of Technology, Zibo, 255000, China

    Gong-Xiang Wei, Zhao Li & Hui-Qiang Liu

  2. State Key Laboratory of Pathogenesis, Prevention, Treatment of Central Asian High Incidence Diseases, First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830054, China

    Sui-Xia Zhang & Hui-Qiang Liu

  3. Oncology Department, ZiBo Central Hospital, Zibo, 255000, China

    Fu-Li Wang

  4. SSRF, Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai, 201800, China

    Yan-Ling Xue & Te Ji

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  1. Gong-Xiang Wei
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Contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Gong-Xiang Wei, Sui-Xia Zhang, Fu-Li Wang, Zhao Li, Yan-Ling Xue, and Te Ji. The first draft of the manuscript was written by Gong-Xiang Wei and Hui-Qiang Liu and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Hui-Qiang Liu.

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This work was supported by the Natural Science Foundation of Shandong Province, China (No. ZR2020MA088), Natural Science Foundation of Xinjiang Uygur Autonomous Region, China (No. 2019D01C188), National Key Research and Development Program of China (No. 2018YFC1200204), and National Natural Science Foundation of China (No. 12175127).

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Wei, GX., Zhang, SX., Li, Z. et al. Multi-modality measurement and comprehensive analysis of hepatocellular carcinoma using synchrotron-based microscopy and spectroscopy. NUCL SCI TECH 32, 102 (2021). https://doi.org/10.1007/s41365-021-00927-6

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