Progress in the application of artificial intelligence in transpathology

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LIU Xi HAN Kaitai HUANG Mengyuan LIU Shitou GUO Qianjin

Cite this article as: LIU X, HAN K T, HUANG M Y, et al. Progress in the application of artificial intelligence in transpathology[J]. Chin J Magn Reson Imaging, 2023, 14(10): 195-202. DOI:10.12015/issn.1674-8034.2023.10.035.

Abstract

[Abstract] Transpathology is a new theory that is expected to revolutionize the future practice of pathology along with the molecular, digital and intelligent development of pathology. It primarily relies on cross-scale, non-invasive multi-modal molecular imaging technology, to visualize, characterize and measure the pathphysiology information of living organisms in temporal and spatial dimensions. Transpathology can not only solve the defects of invasive biopsy sampling and insufficient sampling in traditional pathology, but also comprehensively evaluate pathophysiological data and explore disease mechanism by combining morphological, structural, functional, metabolic and other multi-dimensional information. Transpathology reflects the fusion trend of molecular imaging and digitized pathology. Currently, transpathology is in a continuous phase of development and enhancement, in which artificial intelligence technology plays a pivotal role. The article begins by highlighting the significant role of transpathology in the evolution of pathology as a fusion of molecular imaging and digitalization. Subsequently, it reviewed the applications of artificial intelligence in the development of molecular imaging and digital pathology. Moreover, it provided examples to explore three potential artificial intelligence technologies that could drive transpathology practice. Finally, the challenges in the developmental trajectory of transpathology practice were summarized, along with a forward-looking perspective. This paper marks the inaugural comprehensive review delving into the potential of artificial intelligence technologies to propel transpathology development, with the aim of facilitating the translation of transpathology's foundational theories into clinical research and providing robust support for the realization of precision medicine.

[Keywords] transpathology；digital pathology；molecular imaging；magnetic resonance imaging；artificial intelligence；precision medicine

Contributor Information

LIU Xi HAN Kaitai HUANG Mengyuan LIU Shitou GUO Qianjin^*

Academy of Artificial Intelligence, Beijing Institute of Petrochemical Technology, Beijing 102617, China

Corresponding author: GUO Q J, E-mail: guoqianjin@bipt.edu.cn

Conflicts of interest None.

Publication Information

ACKNOWLEDGMENTS National Natural Science Foundation of China (No. 21673252).

Received 2023-04-22

Accepted 2023-09-14

DOI: 10.12015/issn.1674-8034.2023.10.035

Text

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