{"doi":"10.1161/strokeaha.121.038101","title":"Estimating Perfusion Deficits in Acute Stroke Patients Without Perfusion Imaging","abstract":"BACKGROUND: Perfusion weighted imaging (PWI) is critical for determining whether stroke patients presenting in an extended time window are candidates for mechanical thrombectomy. However, PWI is not always available. Fluid-attenuated inversion recovery hyperintense vessels (FHVs) are seen in patients with a PWI lesion. We investigated whether a scale measuring the extent FHV could serve as a surrogate for PWI to determine eligibility for thrombectomy. METHODS: The National Institutes of Health (NIH) FHV score was developed to quantify the burden of FHV and applied to magnetic resonance imaging scans of stroke patients with fluid-attenuated inversion recovery and perfusion imaging. The NIH-FHV was combined with the diffusion weighted image volume to estimate the diffusion-perfusion mismatch ratio. Linear regression was used to compare PWI volumes and mismatch ratios with estimates from the NIH-FHV score. Receiver operating characteristic analysis was used to test the ability of the NIH-FHV score to identify a significant mismatch. RESULTS: =0.32; β-coefficient, 0.57). When combined with diffusion weighted image lesion volume, receiver operating characteristic analysis testing the ability to detect a mismatch ratio ≥1.8 using the NIH-FHV score resulted in an area under the curve of 0.94. CONCLUSIONS: The NIH-FHV score provides an estimate of the PWI lesion volume and, when combined with diffusion weighted imaging, may be helpful when trying to determine whether there is a clinically relevant diffusion-perfusion mismatch in situations where perfusion imaging is not available. Further studies are needed to validate this approach.","journal":"Stroke","year":2022,"id":262210,"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":14,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9657,"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":436216,"name":"Alexis N. Simpkins","orcid":"0000-0001-7529-4267","position":1,"is_corresponding":false},{"id":399867,"name":"Emi Hitomi","orcid":"0000-0002-0016-6372","position":2,"is_corresponding":false},{"id":524410,"name":"John K. Lynch","orcid":null,"position":3,"is_corresponding":false},{"id":523590,"name":"Amie W. Hsia","orcid":"0000-0002-0214-9736","position":4,"is_corresponding":false},{"id":523591,"name":"Zurab Nadareishvili","orcid":"0000-0002-5526-1342","position":5,"is_corresponding":false},{"id":399868,"name":"Marie Luby","orcid":"0000-0001-7698-5123","position":6,"is_corresponding":false},{"id":249925,"name":"Lawrence L. Latour","orcid":"0000-0001-6160-5263","position":7,"is_corresponding":false},{"id":399869,"name":"Richard Leigh","orcid":"0000-0002-8285-1815","position":8,"is_corresponding":false},{"id":917516,"name":"Dennys Reyes","orcid":"0000-0002-0715-0736","position":0,"is_corresponding":true}],"reference_count":29,"raw_metadata":null,"created_at":"2026-07-19T00:26:20.717229Z","pmid":"35866426","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":[]}