Computed tomography hypoperfusion-hypodensity mismatch vs. automated perfusion mismatch to identify stroke patients eligible for thrombolysis

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

  • Peter B Sporns - , University Hospital Basel (Author)
  • André Kemmling - , University Hospital Münster (Author)
  • Lennart Meyer - , University of Münster (Author)
  • Christos Krogias - , Ruhr University Bochum (Author)
  • Volker Puetz - , Department of Neurology, Dresden Neurovascular Center, University Hospital Carl Gustav Carus Dresden (Author)
  • Kolja M Thierfelder - , Rostock University Medical Centre (Author)
  • Marco Duering - , University of Basel (Author)
  • Carsten Lukas - , Ruhr University Bochum (Author)
  • Daniel Kaiser - , Institute and Polyclinic of Diagnostic and Interventional Neuroradiology, University Hospital Carl Gustav Carus Dresden (Author)
  • Sönke Langner - , Rostock University Medical Centre (Author)
  • Alex Brehm - , University Hospital Basel (Author)
  • Lukas T Rotkopf - , German Cancer Research Center (DKFZ) (Author)
  • Wolfgang G Kunz - , University Hospital Olomouc (Author)
  • Carolin Beuker - , University of Münster (Author)
  • Walter Heindel - , University Hospital Münster (Author)
  • Jens Fiehler - , University Hospital Hamburg Eppendorf (Author)
  • Peter Schramm - , Universitätsklinikum Schleswig-Holstein - Campus Lübeck (Author)
  • Heinz Wiendl - , University of Münster (Author)
  • Heike Minnerup - , University of Münster (Author)
  • Marios Nikos Psychogios - , University Hospital Basel (Author)
  • Jens Minnerup - , University of Münster (Author)

Abstract

BACKGROUND AND PURPOSE: Automated perfusion imaging can detect stroke patients with unknown time of symptom onset who are eligible for thrombolysis. However, the availability of this technique is limited. We, therefore, established the novel concept of computed tomography (CT) hypoperfusion-hypodensity mismatch, i.e., an ischemic core lesion visible on cerebral perfusion CT without visible hypodensity in the corresponding native cerebral CT. We compared both methods regarding their accuracy in identifying patients suitable for thrombolysis.

METHODS: In a retrospective analysis of the MissPerfeCT observational cohort study, patients were classified as suitable or not for thrombolysis based on established time window and imaging criteria. We calculated predictive values for hypoperfusion-hypodensity mismatch and automated perfusion imaging to compare accuracy in the identification of patients suitable for thrombolysis.

RESULTS: Of 247 patients, 219 (88.7%) were eligible for thrombolysis and 28 (11.3%) were not eligible for thrombolysis. Of 197 patients who were within 4.5 h of symptom onset, 190 (96.4%) were identified by hypoperfusion-hypodensity mismatch and 88 (44.7%) by automated perfusion mismatch (p < 0.001). Of 22 patients who were beyond 4.5 h of symptom onset but were eligible for thrombolysis, 5 patients (22.7%) were identified by hypoperfusion-hypodensity mismatch. Predictive values for the hypoperfusion-hypodensity mismatch vs. automated perfusion mismatch were as follows: sensitivity, 89.0% vs. 50.2%; specificity, 71.4% vs. 100.0%; positive predictive value, 96.1% vs. 100.0%; and negative predictive value, 45.5% vs. 20.4%.

CONCLUSION: The novel method of hypoperfusion-hypodensity mismatch can identify patients suitable for thrombolysis with higher sensitivity and lower specificity than established techniques. Using this simple method might therefore increase the proportion of patients treated with thrombolysis without the use of special automated software.The MissPerfeCT study is a retrospective observational multicenter cohort study and is registered with clinicaltrials.gov (NCT04277728).

Details

Original languageEnglish
Article number1320620
Number of pages7
JournalFrontiers in neurology
Volume14
Publication statusPublished - 29 Dec 2023
Peer-reviewedYes

External IDs

ORCID /0000-0001-5258-0025/work/150330307
PubMed 38225983
PubMedCentral PMC10788186
Scopus 85182159604

Keywords

Library keywords