{
    "abstract": "The heterogeneity of cerebral small vessel disease (CSVD) with mild cognitive impairment (MCI) presents a challenge for diagnosis and classification. This study aims to propose a multimodal magnetic resonance imaging (MRI)-based machine learning framework to effectively classify MCI and NCI in CSVD patients. We enrolled 165 CSVD patients, categorized into NCI (n\u2009=\u200981) and MCI (n\u2009=\u200984) groups based on neurocognitive assessments. Multimodal MRI data, including T1-weighted, resting-state functional MRI, and diffusion tensor images, were collected. Image preprocessing, feature extraction and selection were applied to obtain MRI features from three modalities. The AutoGluon platform was utilized for model development, and traditional machine learning algorithms were applied for comparison. The models were validated using a validation cohort of 83 CSVD patients, and their performance was assessed via receiver operating characteristic curve analysis. The AutoGluon model to distinguish MCI from NCI based on multimodal MRI features demonstrated high area under the curve (AUC), accuracy, sensitivity, specificity, precision, balanced accuracy, and F1-score in the training cohort (0.926, 88.48%, 88.10%, 88.89%, 89.16%, 88.50%, and 88.63%, respectively) and validation cohort (0.878, 81.93%, 86.36%, 76.92%, 80.85%, 81.64%, and 83.51%, respectively). Other traditional machine learning models had AUCs of 0.755-0.831, and their prediction accuracies were significantly lower than that of AutoGluon model (P\u2009<\u20090.001). Our study provides a multimodal MRI-based machine learning framework, utilizing the AutoGluon platform, that outperforms traditional algorithms in classifying MCI and NCI, offering a promising tool for the early prediction of MCI in CSVD.",
    "authors": [
        {
            "affiliation": "Zhejiang Key Laboratory of Imaging and Interventional Medicine, Zhejiang Engineering Research Csaenter of Interventional Medicine Engineering and Biotechnology, Key Laboratory of Precision Medicine of Lishui City, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, 323000, Zhejiang, China.",
            "firstname": "Guihan",
            "initials": "G",
            "lastname": "Lin"
        },
        {
            "affiliation": "Zhejiang Key Laboratory of Imaging and Interventional Medicine, Zhejiang Engineering Research Csaenter of Interventional Medicine Engineering and Biotechnology, Key Laboratory of Precision Medicine of Lishui City, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, 323000, Zhejiang, China.",
            "firstname": "Weiyue",
            "initials": "W",
            "lastname": "Chen"
        },
        {
            "affiliation": "School of Life Science and Technology, Changchun University of Science and Technology, Changchun, 130000, China.",
            "firstname": "Yongkang",
            "initials": "Y",
            "lastname": "Geng"
        },
        {
            "affiliation": "Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China.",
            "firstname": "Bo",
            "initials": "B",
            "lastname": "Peng"
        },
        {
            "affiliation": "Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China.",
            "firstname": "Surui",
            "initials": "S",
            "lastname": "Liu"
        },
        {
            "affiliation": "Zhejiang Key Laboratory of Imaging and Interventional Medicine, Zhejiang Engineering Research Csaenter of Interventional Medicine Engineering and Biotechnology, Key Laboratory of Precision Medicine of Lishui City, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, 323000, Zhejiang, China.",
            "firstname": "Minjiang",
            "initials": "M",
            "lastname": "Chen"
        },
        {
            "affiliation": "School of Life Science and Technology, Changchun University of Science and Technology, Changchun, 130000, China.",
            "firstname": "Chunying",
            "initials": "C",
            "lastname": "Pang"
        },
        {
            "affiliation": "Zhejiang Key Laboratory of Imaging and Interventional Medicine, Zhejiang Engineering Research Csaenter of Interventional Medicine Engineering and Biotechnology, Key Laboratory of Precision Medicine of Lishui City, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, 323000, Zhejiang, China.",
            "firstname": "Pengjun",
            "initials": "P",
            "lastname": "Chen"
        },
        {
            "affiliation": "Zhejiang Key Laboratory of Imaging and Interventional Medicine, Zhejiang Engineering Research Csaenter of Interventional Medicine Engineering and Biotechnology, Key Laboratory of Precision Medicine of Lishui City, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, 323000, Zhejiang, China.",
            "firstname": "Chenying",
            "initials": "C",
            "lastname": "Lu"
        },
        {
            "affiliation": "Wenzhou Key Laboratory of Structural and Functional Imaging, Wenzhou, 325000, China.",
            "firstname": "Zhihan",
            "initials": "Z",
            "lastname": "Yan"
        },
        {
            "affiliation": "Zhejiang Key Laboratory of Imaging and Interventional Medicine, Zhejiang Engineering Research Csaenter of Interventional Medicine Engineering and Biotechnology, Key Laboratory of Precision Medicine of Lishui City, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, 323000, Zhejiang, China.",
            "firstname": "Shuiwei",
            "initials": "S",
            "lastname": "Xia"
        },
        {
            "affiliation": "Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China. daiyk@sibet.ac.cn.",
            "firstname": "Yakang",
            "initials": "Y",
            "lastname": "Dai"
        },
        {
            "affiliation": "Zhejiang Key Laboratory of Imaging and Interventional Medicine, Zhejiang Engineering Research Csaenter of Interventional Medicine Engineering and Biotechnology, Key Laboratory of Precision Medicine of Lishui City, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, 323000, Zhejiang, China. jjstcty@wmu.edu.cn.",
            "firstname": "Jiansong",
            "initials": "J",
            "lastname": "Ji"
        }
    ],
    "conclusions": null,
    "copyrights": "\u00a9 2025. The Author(s).",
    "doi": "10.1038/s41598-025-97552-9",
    "journal": "Scientific reports",
    "keywords": [
        "AutoGluon",
        "Cerebral small vessel disease",
        "Cognitive impairment",
        "Machine learning",
        "Multimodal MRI"
    ],
    "methods": null,
    "publication_date": "2025-04-17",
    "pubmed_id": "40240809\n32224755\n31142635\n33630769\n23596414\n32896599\n26687324\n15481073\n34607584\n25686760\n30068634\n17620494\n18465744\n11118237\n17599699\n15103435\n30637462\n34518686\n31901155\n28435046\n11771995\n27075850\n19059349\n28952937\n26481672\n8661285\n8130344\n16790051\n8606814\n35166416\n16520329\n34414301\n20610345",
    "results": null,
    "title": "A multimodal MRI-based machine learning framework for classifying cognitive impairment in cerebral small vessel disease.",
    "xml": "<Element 'PubmedArticle' at 0x78850394e890>"
}