{"doi":"10.1109/ius62464.2025.11201412","title":"Multiparametric imaging of metabolic dysfunction-associated steatotic liver disease using handheld point-of-care ultrasound","abstract":"Liver steatosis and inflammation are key features of metabolic dysfunction-associated steatotic liver disease (MASLD) progression. Noninvasive tools capable of distinguishing these phenotypes remain limited. This preclinical study evaluated the use of handheld point-of-care ultrasound (POCUS) imaging and a multiparametric framework for the assessment of MASLD. Both controls and mice with varying degrees of liver steatosis and inflammation were used (4 groups, n = 5 to 7 animals per group). Radiofrequency (RF) data from each animal was acquired using a POCUS system (L20 HD3, Clarius Mobile Health). A multiparametric analysis included the following: attenuation coefficient estimates, US speckle statistics, B-mode echogenicity, and H-mode frequency. After imaging, mice were euthanized and livers excised for quantification of liver steatosis and macrophage infiltration (inflammation). Correlation analysis of multiparametric US and histology results revealed a significant correlation (R<sup xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">2</sup> > 0.33, p < 0.05). Support vector machine classification using principal component analysis achieved 95.5% accuracy in MASLD staging. These preclinical results highlight the potential use of a multiparametric POCUS approach for early MASLD detection and staging.","journal":null,"year":2025,"id":578589,"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":0.9679,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"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":1074335,"name":"Leroy Arthur","orcid":null,"position":1,"is_corresponding":false},{"id":1469695,"name":"Joshua Hanson","orcid":null,"position":2,"is_corresponding":false},{"id":1488890,"name":"Xinlei Gu","orcid":null,"position":3,"is_corresponding":false},{"id":1488503,"name":"Xiaoxiao Wang","orcid":"0000-0002-5840-5348","position":4,"is_corresponding":false},{"id":630257,"name":"Xiaojing Li","orcid":"0000-0002-2609-0572","position":5,"is_corresponding":false},{"id":262698,"name":"Honggui Li","orcid":"0000-0002-6294-1581","position":6,"is_corresponding":false},{"id":1488504,"name":"Chaodong Wu","orcid":"0000-0002-5503-8853","position":7,"is_corresponding":false},{"id":1469327,"name":"Kenneth Hoyt","orcid":"0000-0001-9187-1263","position":8,"is_corresponding":false},{"id":1488889,"name":"Layan Al-Huneidi","orcid":null,"position":0,"is_corresponding":true}],"reference_count":18,"raw_metadata":null,"created_at":"2026-07-19T02:58:24.957414Z","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":[]}