{"doi":"10.1101/2022.09.26.509366","title":"Concurrent measurement of perfusion parameters related to small blood and lymphatic vessels in the human brain using dynamic dual-spin-echo perfusion (DDSEP) MRI","abstract":"Abstract PURPOSE Accumulating evidence from recent studies has indicated the importance of studying the interaction between the microvascular and lymphatic systems in the brain. To date, most imaging methods can only measure blood or lymphatic vessels separately, such as dynamic-susceptibility-contrast (DSC) MRI for blood vessels and DSC MRI in the CSF (cDSC MRI) for lymphatic vessels. An approach that can measure both blood and lymphatic vessels in a single scan will offer the advantages such as halved scan time and contrast dosage. Based on previous works on DSC and cDSC MRI, this study proposes an MRI approach for concurrent measurement of perfusion parameters related to small blood and lymphatic vessels in the brain within one single scan. METHODS Bloch simulations were performed to optimize a dual-echo sequence for the measurement of gadolinium(Gd)-induced blood and CSF signal changes using a short and a long echo time, respectively. MRI experiments were performed in healthy subjects to evaluate the dual-echo approach by comparing it with existing separate methods. RESULTS The proposed method showed consistent results in human brains as previous studies using separate methods. Signal changes from small blood vessels occurred faster than lymphatic vessels after intravenous Gd-injection. CONCLUSION Gd-induced signal changes in blood and CSF can be detected simultaneously in healthy subjects with the proposed sequence. To the best of our knowledge, this may be the first study in which the temporal difference in Gd-induced signal changes from small blood and lymphatic vessels after intravenous Gd-injection was measured in the same human subjects.","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2022,"id":311612,"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":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9569,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2022-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1007773,"name":"Yuanqi Sun","orcid":"0000-0003-1939-1825","position":1,"is_corresponding":false},{"id":492366,"name":"Pan Su","orcid":"0000-0002-6728-5878","position":2,"is_corresponding":false},{"id":320070,"name":"Jay J. Pillai","orcid":"0000-0002-8306-7192","position":3,"is_corresponding":false},{"id":447295,"name":"Ye Qiao","orcid":"0000-0002-0499-9283","position":4,"is_corresponding":false},{"id":57482,"name":"Hanzhang Lu","orcid":"0000-0003-3871-1564","position":5,"is_corresponding":false},{"id":271396,"name":"Peter C.M. van Zijl","orcid":"0000-0002-9706-1066","position":6,"is_corresponding":false},{"id":282375,"name":"Linda Knutsson","orcid":"0000-0002-4263-113X","position":7,"is_corresponding":false},{"id":341294,"name":"Jun Hua","orcid":"0000-0001-5481-7380","position":8,"is_corresponding":false},{"id":506174,"name":"Di Cao","orcid":"0000-0002-2196-0639","position":0,"is_corresponding":true}],"reference_count":57,"raw_metadata":null,"created_at":"2026-07-19T00:33:28.480200Z","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":[]}