{"doi":"10.1101/2020.09.03.280636","title":"Single-vessel cerebral blood flow fMRI to map blood velocity by phase-contrast imaging","abstract":"Abstract Current approaches to high-field fMRI provide two means to map hemodynamics at the level of single vessels in the brain. One is through changes in deoxyhemoglobin in venules, i.e., blood oxygenation level-dependent (BOLD) fMRI, while the second is through changes in arteriole diameter, i.e., cerebral blood volume (CBV) fMRI. Here we introduce cerebral blood flow (CBF)-fMRI, which uses high-resolution phase-contrast MRI to form velocity measurements of flow and demonstrate CBF-fMRI in single penetrating microvessels across rat parietal cortex. In contrast to the venule-dominated BOLD and arteriole-dominated CBV fMRI signal, the phase-contrast -based CBF signal changes are highly comparable from both arterioles and venules. Thus, we have developed a single-vessel fMRI platform to map the BOLD, CBV, and CBF from penetrating microvessels throughout the cortex. This high-resolution single-vessel fMRI mapping scheme not only enables the vessel-specific hemodynamic mapping in diseased animal models but also presents a translational potential to map vascular dementia in diseased or injured human brains with ultra-high field fMRI. Summary We established a high-resolution PC-based single-vessel velocity mapping method using the high field MRI. This PC-based micro-vessel velocity measurement enables the development of the single-vessel CBF-fMRI method. In particular, in contrast to the arteriole-dominated CBV and venule-dominated BOLD responses, the CBF-fMRI shows similar velocity changes in penetrating arterioles and venules in activated brain regions. Thus, we have built a noninvasive single-vessel fMRI mapping scheme for BOLD, CBV, and CBF hemodynamic parameter measurements in animals.","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2020,"id":127301,"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":1,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9616,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2020-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":575980,"name":"Yuanyuan Jiang","orcid":"0000-0001-7758-7450","position":1,"is_corresponding":false},{"id":575981,"name":"Sangcheon Choi","orcid":"0000-0001-7327-1344","position":2,"is_corresponding":false},{"id":384840,"name":"R Pohmann","orcid":"0000-0002-6137-9590","position":3,"is_corresponding":false},{"id":384838,"name":"Klaus Scheffler","orcid":"0000-0001-6316-8773","position":4,"is_corresponding":false},{"id":227038,"name":"David Kleinfeld","orcid":"0000-0001-9797-4722","position":5,"is_corresponding":false},{"id":251801,"name":"Xin Yu","orcid":"0000-0001-9890-5489","position":6,"is_corresponding":false},{"id":575979,"name":"Xuming Chen","orcid":"0000-0002-1876-4573","position":0,"is_corresponding":true}],"reference_count":40,"raw_metadata":null,"created_at":"2026-07-18T23:15:30.930746Z","pmid":null,"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":[]}