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Prof. Kaiyu Cui develop and obtain approval for the first group standard of spectral pathology diagnosis

Pathological diagnosis serves as the "gold standard" for the diagnosis of most diseases, especially tumor-related conditions. By analyzing biopsy or surgically excised human tissue samples, it provides the terminal diagnosis that can not be replaced by any other method at present. The introduction of spectral dimension material information allows for more accurate differentiation between cancerous and normal cells, thereby significantly reducing the subjectivity in pathological diagnosis, enhancing diagnostic accuracy, and increasing the degree of intelligence and automation in the diagnostic process. This advancement holds promise for the realization and popularization of early cancer screening. Real-time pathological auxiliary diagnosis results based on spectral imaging can be provided to doctors during surgery, along with operational feedback. This creates a new detection technology for intraoperative pathology, addressing the long-standing clinical challenge of real-time determination of intraoperative tumor margins.

In response to the significant national needs concerning people's health, Prof. Kaiyu Cui initiated and organized collaboration among Tsinghua Changgung Hospital, Chinese People's Liberation Army General Hospital, Chinese Academy of Medical Sciences Cancer Hospital, and other institutions to develop and obtain approval for the world's first group standard for spectral pathology diagnosis "Technical Requirements for Spectral Pathology Assisted Diagnosis System" (T/CIE 275-2024).

During the standard approval process, the experts evaluated that the standard stipulated the general scheme and technical requirements for using spectral information for pathologically assisted diagnosis, and extensively solicited opinions from various aspects of production, academia, research and application, providing important guidance for the development of related technologies in spectral pathologically assisted diagnosis.

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2024年12月30日

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