{"doi":"10.20944/preprints202203.0259.v1","title":"In Vivo Renal Lipid Quantification by Accelerated Magnetic Resonance Spectroscopic Imaging at 3 T: Feasibility and Reliability Study","abstract":"A reliable and practical renal-lipid quantification and imaging method is needed. Here, the feasibility of an accelerated MRSI method to map renal fat fractions (FF) at 3T and its repeatability were investigated. A 2D density-weighted concentric-ring-trajectory MRSI was used to accelerate acquiring 48×48 voxels (each of 0.25 ml spatial-resolution) without respiratory navigation implementations. The data was collected over 512 complex-FID timepoints with a 1250 Hz spectral bandwidth. The MRSI sequence was designed with a metabolite-cycling technique for lipid-water separation. The in vivo repeatability performance of the sequence was assessed by conducting a test-reposition-retest study within healthy subjects. The coefficient of variation (CV) in the estimated FF from the test-retest measurements showed a high degree of repeatability of the MRSI-FF (CV= 4.3 ±2.5%). Additionally, the matching level of spectral signature within the same anatomical region was also investigated, and their intrasubject repeatability was also high, with a small standard deviation (8.1 ±6.4%). The MRSI acquisition duration was ~3 minutes only. The proposed MRSI technique can be a reliable technique to quantify and map renal metabolites within a clinically acceptable scan time at 3T that supports the future application of this technique for the non-invasive characterization of heterogeneous renal diseases and tumors.","journal":"Preprints.org","year":2022,"id":298609,"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":5,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.957,"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":956162,"name":"Mahsa Servati","orcid":"0000-0002-1420-5926","position":1,"is_corresponding":false},{"id":956529,"name":"Nathan Ooms","orcid":null,"position":2,"is_corresponding":false},{"id":325925,"name":"Oğuz Akın","orcid":"0000-0002-2041-6199","position":3,"is_corresponding":false},{"id":956163,"name":"Alp Di̇nçer","orcid":"0000-0001-9158-8353","position":4,"is_corresponding":false},{"id":407454,"name":"M. Albert Thomas","orcid":"0000-0001-9037-2585","position":5,"is_corresponding":false},{"id":407456,"name":"Ulrike Dydak","orcid":"0000-0003-1852-7110","position":6,"is_corresponding":false},{"id":407457,"name":"Uzay E. Emir","orcid":"0000-0001-5376-0431","position":7,"is_corresponding":false},{"id":407451,"name":"Ahmad A. Alhulail","orcid":"0000-0002-6393-5415","position":0,"is_corresponding":true}],"reference_count":35,"raw_metadata":null,"created_at":"2026-07-19T00:31:36.269611Z","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":[]}