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Intelligent SERS Navigation System Guiding Brain Tumor Surgery by Intraoperatively Delineating the Metabolic Acidosis

Authors :
Ziyi Jin
Qi Yue
Wenjia Duan
An Sui
Botao Zhao
Yinhui Deng
Yuting Zhai
Yuwen Zhang
Tao Sun
Guang‐Ping Zhang
Limei Han
Ying Mao
Jinhua Yu
Xiao‐Yong Zhang
Cong Li
Source :
Advanced Science, Vol 9, Iss 7, Pp n/a-n/a (2022)
Publication Year :
2022
Publisher :
Wiley, 2022.

Abstract

Abstract Surgeons face challenges in intraoperatively defining margin of brain tumors due to its infiltrative nature. Extracellular acidosis caused by metabolic reprogramming of cancer cells is a reliable marker for tumor infiltrative regions. Although the acidic margin‐guided surgery shows promise in improving surgical prognosis, its clinical transition is delayed by having the exogenous probes approved by the drug supervision authority. Here, an intelligent surface‐enhanced Raman scattering (SERS) navigation system delineating glioma acidic margins without administration of exogenous probes is reported. With assistance of this system, the metabolites at the tumor cutting edges can be nondestructively transferred within a water droplet to a SERS chip with pH sensitivity. Homemade deep learning model automatically processes the Raman spectra collected from the SERS chip and delineates the pH map of tumor resection bed with increased speed. Acidity correlated cancer cell density and proliferation level are demonstrated in tumor cutting edges of animal models and excised tissues from glioma patients. The overall survival of animal models post the SERS system guided surgery is significantly increased in comparison to the conventional strategy used in clinical practice. This SERS system holds the promise in accelerating clinical transition of acidic margin‐guided surgery for solid tumors with infiltrative nature.

Details

Language :
English
ISSN :
21983844 and 20210493
Volume :
9
Issue :
7
Database :
Directory of Open Access Journals
Journal :
Advanced Science
Publication Type :
Academic Journal
Accession number :
edsdoj.23508dd9799d4215a23df81097ad1d27
Document Type :
article
Full Text :
https://doi.org/10.1002/advs.202104935