{"doi":"10.1161/str.32.suppl_1.348-a","title":"Sensitivity and Specificity of Quantitative Cerebral Blood Flow vs. Time from Symptom Onset as a Predictor of Cerebral Infarction","abstract":"<jats:p>\n            <jats:bold>P50</jats:bold>\n          </jats:p>\n          <jats:p>\n            <jats:bold>Background and Purpose:</jats:bold>\n            To compare the sensitivity  and specificity of quantitative cerebral blood flow (qCBF) vs. time  from symptom onset to the measurement of qCBF (Time) as a predictor of  cerebral infarction in patients (pts.) with acute ischemic stroke.\n            <jats:bold>Methods:</jats:bold>\n            51 pts. with acute ischemic stroke who were  assessed with XeCT, CTA and CT within 24 hours of symptom onset were  studied. The MCA territory was divided into anterior and posterior  divisions (two divisions/pt. for a total of 102 divisions). The average  qCBF for each of these divisions was calculated and initial and  follow-up CT scans were read for new infarction in both divisions. 24  divisions with evidence of prior infarction on the initial CT were  excluded from the analysis. This left a total of 78 divisions available  for analysis. Logistic regression was used to generate receiver  operating curves (ROC) for both qCBF and Time. The area under each ROC  curve is reported.\n            <jats:bold>Results:</jats:bold>\n            Twenty-one of the 78 (26.9%)  divisions without initial infarction on CT had evidence of new  infarction on the follow-up CT. The area under the qCBF curve was 0.81  compared with an area of 0.49 under the Time curve (p=0.00025).  Excluding patients receiving thrombolytic therapy, (n=11), the area  under the qCBF curve was 0.799 and the area under the Time curve was  0.590 (p=0.00004). The area under the ROC curve for qCBF was  significantly greater than Time in those patients studied &lt; 180  minutes (qCBF=0.92, Time=0.51; p=0.02) and &gt; 180 min. (qCBF=0.76,  Time=0.50; p=0.01)\n            <jats:bold>Conclusion:</jats:bold>\n            Quantitative cerebral blood  flow measured by XeCT is a better predictor of new infarction on  follow-up CT than Time in pts. with acute ischemic stroke. This holds  true for time &lt; 180 minutes and &gt; 180 minutes.\n          </jats:p>","journal":"Stroke","year":2001,"id":630540,"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":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1633538,"name":"Steven Goldstein","orcid":null,"position":1,"is_corresponding":false},{"id":58043,"name":"Howard Yonas","orcid":null,"position":2,"is_corresponding":false},{"id":1633539,"name":"Amin B Kassam","orcid":null,"position":3,"is_corresponding":false},{"id":1633540,"name":"James Gebel","orcid":null,"position":4,"is_corresponding":false},{"id":1633542,"name":"Lawrence R Wechsler","orcid":null,"position":5,"is_corresponding":false},{"id":1633544,"name":"Charles A Jungreis","orcid":null,"position":6,"is_corresponding":false},{"id":1633546,"name":"Melanie Fukui","orcid":null,"position":7,"is_corresponding":false},{"id":1633537,"name":"Megan M Kilpatrick","orcid":null,"position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Sensitivity and Specificity of Quantitative Cerebral Blood Flow vs. Time from Symptom Onset as a Predictor of Cerebral Infarction","abstract":"<jats:p>\n            <jats:bold>P50</jats:bold>\n          </jats:p>\n          <jats:p>\n            <jats:bold>Background and Purpose:</jats:bold>\n            To compare the sensitivity  and specificity of quantitative cerebral blood flow (qCBF) vs. time  from symptom onset to the measurement of qCBF (Time) as a predictor of  cerebral infarction in patients (pts.) with acute ischemic stroke.\n            <jats:bold>Methods:</jats:bold>\n            51 pts. with acute ischemic stroke who were  assessed with XeCT, CTA and CT within 24 hours of symptom onset were  studied. The MCA territory was divided into anterior and posterior  divisions (two divisions/pt. for a total of 102 divisions). The average  qCBF for each of these divisions was calculated and initial and  follow-up CT scans were read for new infarction in both divisions. 24  divisions with evidence of prior infarction on the initial CT were  excluded from the analysis. This left a total of 78 divisions available  for analysis. Logistic regression was used to generate receiver  operating curves (ROC) for both qCBF and Time. The area under each ROC  curve is reported.\n            <jats:bold>Results:</jats:bold>\n            Twenty-one of the 78 (26.9%)  divisions without initial infarction on CT had evidence of new  infarction on the follow-up CT. The area under the qCBF curve was 0.81  compared with an area of 0.49 under the Time curve (p=0.00025).  Excluding patients receiving thrombolytic therapy, (n=11), the area  under the qCBF curve was 0.799 and the area under the Time curve was  0.590 (p=0.00004). The area under the ROC curve for qCBF was  significantly greater than Time in those patients studied &lt; 180  minutes (qCBF=0.92, Time=0.51; p=0.02) and &gt; 180 min. (qCBF=0.76,  Time=0.50; p=0.01)\n            <jats:bold>Conclusion:</jats:bold>\n            Quantitative cerebral blood  flow measured by XeCT is a better predictor of new infarction on  follow-up CT than Time in pts. with acute ischemic stroke. This holds  true for time &lt; 180 minutes and &gt; 180 minutes.\n          </jats:p>","is_dataset_classified":null,"base_score":0.0,"endowment":0.0,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":null,"pmcid":null,"openalex_id":null,"authors":[],"funders":[],"total_grants":0,"fwci":null,"citation_percentile":null,"influential_citations":0,"citation_trend":[],"oa_status":"bronze","license":null,"oa_locations":[{"url":"https://www.ahajournals.org/doi/pdf/10.1161/str.32.suppl_1.348-a","host_type":"publisher"}],"fields_of_study":[],"mesh_terms":[],"keywords":[],"sdg_mappings":[],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-05T21:36:11.601933Z","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":[]}