{"doi":"10.1002/hbm.26529","title":"Structural, static, and dynamic functional <scp>MRI</scp> predictors for conversion from mild cognitive impairment to Alzheimer's disease: Inter‐cohort validation of Shanghai Memory Study and <scp>ADNI</scp>","abstract":"Mild cognitive impairment (MCI) is a critical prodromal stage of Alzheimer's disease (AD), and the mechanism underlying the conversion is not fully explored. Construction and inter-cohort validation of imaging biomarkers for predicting MCI conversion is of great challenge at present, due to lack of longitudinal cohorts and poor reproducibility of various study-specific imaging indices. We proposed a novel framework for inter-cohort MCI conversion prediction, involving comparison of structural, static, and dynamic functional brain features from structural magnetic resonance imaging (sMRI) and resting-state functional MRI (fMRI) between MCI converters (MCI_C) and non-converters (MCI_NC), and support vector machine for construction of prediction models. A total of 218 MCI patients with 3-year follow-up outcome were selected from two independent cohorts: Shanghai Memory Study cohort for internal cross-validation, and Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort for external validation. In comparison with MCI_NC, MCI_C were mainly characterized by atrophy, regional hyperactivity and inter-network hypo-connectivity, and dynamic alterations characterized by regional and connectional instability, involving medial temporal lobe (MTL), posterior parietal cortex (PPC), and occipital cortex. All imaging-based prediction models achieved an area under the curve (AUC) > 0.7 in both cohorts, with the multi-modality MRI models as the best with excellent performances of AUC > 0.85. Notably, the combination of static and dynamic fMRI resulted in overall better performance as relative to static or dynamic fMRI solely, supporting the contribution of dynamic features. This inter-cohort validation study provides a new insight into the mechanisms of MCI conversion involving brain dynamics, and paves a way for clinical use of structural and functional MRI biomarkers in future.","journal":"Human Brain Mapping","year":2023,"id":329086,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":21,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.948,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":834214,"name":"Keliang Chen","orcid":"0000-0001-9275-3007","position":1,"is_corresponding":false},{"id":828688,"name":"Yuxin Li","orcid":"0000-0003-2107-6744","position":2,"is_corresponding":false},{"id":1051692,"name":"Daoying Geng","orcid":"0000-0002-3585-6883","position":3,"is_corresponding":false},{"id":460585,"name":"Xiantao Li","orcid":"0000-0002-9760-7292","position":4,"is_corresponding":false},{"id":1048014,"name":"Xiaoniu Liang","orcid":null,"position":5,"is_corresponding":false},{"id":1052335,"name":"Huimeng Lu","orcid":null,"position":6,"is_corresponding":false},{"id":1048016,"name":"Saineng Ding","orcid":null,"position":7,"is_corresponding":false},{"id":888410,"name":"Zhenxu Xiao","orcid":"0000-0002-6598-0367","position":8,"is_corresponding":false},{"id":1051693,"name":"Xiaoxi Ma","orcid":"0000-0001-7403-3700","position":9,"is_corresponding":false},{"id":1051694,"name":"Li Zheng","orcid":"0000-0003-1151-8676","position":10,"is_corresponding":false},{"id":888409,"name":"Ding Ding","orcid":"0000-0002-0352-0883","position":11,"is_corresponding":false},{"id":328761,"name":"Qianhua Zhao","orcid":"0000-0001-5655-158X","position":12,"is_corresponding":false},{"id":1051695,"name":"Liqin Yang","orcid":"0000-0003-1823-4756","position":13,"is_corresponding":false},{"id":300139,"name":"for the Alzheimer's Disease Neuroimaging Initiative","orcid":null,"position":14,"is_corresponding":false},{"id":297491,"name":"Zhihan Chen","orcid":"0000-0002-0237-7501","position":0,"is_corresponding":true}],"reference_count":79,"raw_metadata":null,"created_at":"2026-07-19T01:09:01.509601Z","pmid":"37991144","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}