{"doi":"10.1002/nbm.70168","title":"Motion and Flow Robust Free‐Breathing Diffusion Kurtosis Imaging of the Kidney","abstract":"ABSTRACT The development of noninvasive MRI biomarkers as surrogates of histopathological features in kidney tissue requires detailed explorations of contrast. Therefore, we studied kidney diffusion kurtosis imaging (DKI) with a wide array of encodings, including flow compensation, variable directional sampling, and cardiac gating regimes. Twelve healthy volunteers underwent DKI at 5–10 diffusion weightings ( b ‐values) ranging from 0 to 1200 smm −2 with 12 or 30 directional samplings, bipolar or flow‐compensated diffusion gradient waveforms, and at systolic or diastolic cardiac phases. DKI biomarkers, mean diffusivity (MD) and kurtosis (MK), were interrogated using a directionally robust fitting algorithm compared to conventional fits. The combination of flow compensation and cardiac triggering at the diastolic phase in the kidneys reduced flow effects on DKI. In systole, flow‐compensated waveforms significantly reduced MD and MK for both cortex and medulla: cortex MD: 3.00 versus 2.55 μm 2 ms −1 , medulla MD: 2.80 versus 2.39 μm 2 ms −1 , cortex MK: 0.58 versus 0.45, and medulla MK: 0.60 versus 0.47 (all p < 0.05). Flow suppression alleviated requirements for processing the DKI at higher minimum b ‐values, as neither MD nor MK significantly differed at the diastolic phase for minimum b ‐values of 0 versus 200 smm −2 : cortex MD: 2.30 versus 2.28 μm 2 ms −1 , p = 0.278; medulla MD: 2.29 versus 2.28 μm 2 ms −1 , p = 0.437; cortex MK: 0.37 versus 0.36, p = 0.308; and medulla MK: 0.40 versus 0.40, p = 0.904. Flow‐compensated waveforms mitigate cardiac and respiratory motion‐related artifacts at higher diffusion encodings in addition to microcirculation effects. The robust fitting initially developed for brain DKI is highly applicable to the kidneys because it disentangles tissue‐specific directional diffusion information from artifacts.","journal":"NMR in Biomedicine","year":2025,"id":529266,"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":2,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9564,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1073425,"name":"Malika Kumbella","orcid":null,"position":1,"is_corresponding":false},{"id":230013,"name":"Mary Bruno","orcid":"0000-0003-1625-0293","position":2,"is_corresponding":false},{"id":291215,"name":"Jelle Veraart","orcid":"0000-0003-0781-0420","position":3,"is_corresponding":false},{"id":601063,"name":"Xiaochun Li","orcid":"0000-0003-1109-6119","position":4,"is_corresponding":false},{"id":640018,"name":"Judith D. Goldberg","orcid":"0000-0003-3758-6976","position":5,"is_corresponding":false},{"id":899986,"name":"Dibash Basukala","orcid":"0000-0002-5820-866X","position":6,"is_corresponding":false},{"id":230017,"name":"Hersh Chandarana","orcid":"0000-0002-6807-4589","position":7,"is_corresponding":false},{"id":693443,"name":"Eric E. Sigmund","orcid":"0000-0001-6783-3611","position":8,"is_corresponding":false},{"id":899985,"name":"Nima Gilani","orcid":"0000-0002-6129-7763","position":0,"is_corresponding":true}],"reference_count":75,"raw_metadata":null,"created_at":"2026-07-19T02:50:56.971987Z","pmid":"41199578","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":[]}