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Rapid and sensitive acute leukemia classification and diagnosis platform using deep learning-assisted SERS detection

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资源类型：
Pubmed体系：
作者：
Zhang Dongjie[1,2,3,4] * ; Cheng Zhaoyang[1,2] * ; Song Yali[5] * ; Li Huandi[1,2] ; Shi Lin[1,2] ; Wang Nan[1,2] ; Peng Yingwen[1,2,3] ; Chen Renan[6] ; Sun Nianzheng[7,8] ; Han Min[9] ; Hu Fengjiao[10] ; Zong Chuntao[6] ; Zhang Rui[8] ; Chen Si[5] ; Zhu Conghui[6] ; Zhang Xiaoli[6] ; Li Xiaobo[11] ; Ma Xiaopeng[12] ; Shi Changbei[13] ; Zhang Xiaofei[14] ; Liu Rui[1,2] ; Ren Ziqi[1,2] ; Wang Lin[15] ; Zeng Qi[1,2] ; Zeng Tingting[5,10] ; Chen Xueli[1,2,3,4] ;
机构： [1]Center for Biomedical-photonics and Molecular Imaging, Advanced Diagnostic-Therapy Technology and Equipment Key Laboratory of [2]Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education & Xi’an Key Laboratory of Intelligent Sensing and [3]Bi-optoelectronic-integration and Medical Instrumentation Laboratory, Guangzhou Institute of Technology, Xidian University, Guangzhou, [4]State Key Laboratory of Electromechanical Integrated Manufacturing of High-Performance Electronic Equipment, Xidian University, Xi’an, [5]Department of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China [6]Department of Hematology, Xi’an Daxing Hospital affiliated to Yan’an University, Xi ’an, Shaanxi 710082, China [7]Department of Pediatrics, Qilu Hospital of Shandong University, Jinan, Shandong 250012, China [8]Department of Hematology, Qilu Hospital of Shandong University Dezhou Hospital, Dezhou, Shandong 253000, China [9]Department of Neurosurgery, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, [10]Department of Laboratory Medicine, Chengdu Shangjin Nanfu Hospital/Shangjin Branch of West China Hospital, Sichuan University, [11]Shaanxi Key Laboratory of High-Orbits-Electron Materials and Protection Technology for Aerospace, School of Advanced Materials and [12]School of Control Science and Engineering, Shandong University, Jinan, Shandong 150061, China [13]Shaanxi Provincial Cancer Hospital, Xi’an, Shaanxi 710061, China [14]Key Laboratory of Basic and New Drug Research of Tradinonal Chinese Medicine, Shaanxi Universily of Chinese Medicine, Xianyang, [15]School of Computer Science and Engineering, Xi’an University of Technology, Xi’an, Shaanxi 710048, China
出处：
DOI： 10.1016/j.xcrm.2025.102320

摘要：
Rapid identification and accurate diagnosis are critical for individuals with acute leukemia (AL). Here, we propose a combined deep learning and surface-enhanced Raman scattering (DL-SERS) classification strategy to achieve rapid and sensitive identification of AL with various subtypes and genetic abnormalities. More than 390 of cerebrospinal fluid (CSF) samples are collected as targets, encompassing healthy control, AL patients, and individuals with other diseases. Sensitive SERS detection could be achieved within 5 min, using only 0.5 μL volume of CSF. Through integrated feature fusion (1D spectra and 2D image) with a transformer model, the classification method is developed to screen and diagnose AL patients, demonstrating exceptional classification performances of accuracy, sensitivity, specificity, or reliability. Also, this approach demonstrates remarkable versatility and could be extended to the classifications of meningitis diseases. The sensitive DL-SERS classification platform has the potential to be a powerful auxiliary in vitro diagnostic tool.Copyright © 2025 The Author(s). Published by Elsevier Inc. All rights reserved.

基金：
This work has been supported by the National Natural Science Foundation of China, grants 32201133 (D.Z.), 62275210 (X.C.), and 82302632 (Y.S.); the National Leading Talent Program (X.C.); the National Young Talent Program (X.C.); the Shaanxi Young Top-notch Talent Program (X.C.); the Young Talent Fund of Association for Science and Technology in Shaanxi, grant 20230222 (D.Z.); the Science and Technology Projects in Guangzhou, grant 2023A04J1509 (D.Z.); the Guangdong Basic and Applied Basic Research Foundation, grant 2025A1515010789 (D.Z.); the 1⋅3⋅5 project for disciplines of excellence, West China Hospital, Sichuan University, grant ZYJC21067 (T.Z.); the Sichuan Science and Technology Program, grant 2022YFS0214 (T.Z.); the Natural Science Foundation of Sichuan Province, grant 2022NSFSC1305 (Y.S.); the Fundamental Research Funds for the Central Universities, grants ZYTS25098 (D.Z.) and QTZX25113 (X.C.); the Xidian University Specially Funded Project for Interdisciplinary Exploration, grant TZJH2024036 (N.W.); and the Opening Foundation of Shanxi Key Laboratory of Ferroelectric Physical Micro-nano Devices and Systems, grant TDWL- 202501 (D.Z.)
语种：
外文
PubmedID：
中科院(CAS)分区：
出版当年[2025]版：
大类 | 1 区 医学
小类 | 1 区 医学：研究与实验 2 区 细胞生物学
最新[2025]版：
大类 | 1 区 医学
小类 | 1 区 医学：研究与实验 2 区 细胞生物学
第一作者：
第一作者机构： [1]Center for Biomedical-photonics and Molecular Imaging, Advanced Diagnostic-Therapy Technology and Equipment Key Laboratory of [2]Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education & Xi’an Key Laboratory of Intelligent Sensing and [3]Bi-optoelectronic-integration and Medical Instrumentation Laboratory, Guangzhou Institute of Technology, Xidian University, Guangzhou, [4]State Key Laboratory of Electromechanical Integrated Manufacturing of High-Performance Electronic Equipment, Xidian University, Xi’an,
共同第一作者：
通讯作者：
通讯机构： [1]Center for Biomedical-photonics and Molecular Imaging, Advanced Diagnostic-Therapy Technology and Equipment Key Laboratory of [2]Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education & Xi’an Key Laboratory of Intelligent Sensing and [3]Bi-optoelectronic-integration and Medical Instrumentation Laboratory, Guangzhou Institute of Technology, Xidian University, Guangzhou, [4]State Key Laboratory of Electromechanical Integrated Manufacturing of High-Performance Electronic Equipment, Xidian University, Xi’an, [5]Department of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China [7]Department of Pediatrics, Qilu Hospital of Shandong University, Jinan, Shandong 250012, China [8]Department of Hematology, Qilu Hospital of Shandong University Dezhou Hospital, Dezhou, Shandong 253000, China [10]Department of Laboratory Medicine, Chengdu Shangjin Nanfu Hospital/Shangjin Branch of West China Hospital, Sichuan University,
推荐引用方式(GB/T 7714)：
Zhang Dongjie,Cheng Zhaoyang,Song Yali,et al.Rapid and sensitive acute leukemia classification and diagnosis platform using deep learning-assisted SERS detection[J].Cell Reports. Medicine.2025,6(9):102320.doi:10.1016/j.xcrm.2025.102320.
APA：
Zhang Dongjie,Cheng Zhaoyang,Song Yali,Li Huandi,Shi Lin...&Chen Xueli.(2025).Rapid and sensitive acute leukemia classification and diagnosis platform using deep learning-assisted SERS detection.Cell Reports. Medicine,6,(9)
MLA：
Zhang Dongjie,et al."Rapid and sensitive acute leukemia classification and diagnosis platform using deep learning-assisted SERS detection".Cell Reports. Medicine 6..9(2025):102320

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