Resting-state functional connectivity magnetic resonance imaging and outcome after acute stroke

Josep Puig, Gerard Blasco, Angel Alberich-Bayarri, Gottfried Schlaug, Gustavo Deco, Carles Biarnes, Marian Navas-Martí, Mireia Rivero, Jordi Gich, Jaume Figueras, Cristina Torres, Pepus Daunis-I-Estadella, Celia L. Oramas-Requejo, Joaquín Serena, Cathy M. Stinear, Amy Kuceyeski, Carles Soriano-Mas, Götz Thomalla, Marco Essig, Chase R. FigleyBijoy Menon, Andrew Demchuk, Kambiz Nael, Max Wintermark, David S. Liebeskind, Salvador Pedraza

Research output: Contribution to journalArticlepeer-review

34 Scopus citations


Background and Purpose: Physiological effects of stroke are best assessed over entire brain networks rather than just focally at the site of structural damage. Resting-state functional magnetic resonance imaging can map functional-anatomic networks by analyzing spontaneously correlated low-frequency activity fluctuations across the brain, but its potential usefulness in predicting functional outcome after acute stroke remains unknown. We assessed the ability of resting-state functional magnetic resonance imaging to predict functional outcome after acute stroke. Methods: We scanned 37 consecutive reperfused stroke patients (age, 69±14 years; 14 females; 3-day National Institutes of Health Stroke Scale score, 6±5) on day 3 after symptom onset. After imaging preprocessing, we used a whole-brain mask to calculate the correlation coefficient matrices for every paired region using the Harvard-Oxford probabilistic atlas. To evaluate functional outcome, we applied the modified Rankin Scale at 90 days. We used region of interest analyses to explore the functional connectivity between regions and graph-computation analysis to detect differences in functional connectivity between patients with good functional outcome (modified Rankin Scale score ≤2) and those with poor outcome (modified Rankin Scale score >2). Results: Patients with good outcome had greater functional connectivity than patients with poor outcome. Although 3-day National Institutes of Health Stroke Scale score was the most accurate independent predictor of 90-day modified Rankin Scale (84.2%), adding functional connectivity increased accuracy to 94.7%. Preserved bilateral interhemispheric connectivity between the anterior inferior temporal gyrus and superior frontal gyrus and decreased connectivity between the caudate and anterior inferior temporal gyrus in the left hemisphere had the greatest impact in favoring good prognosis. Conclusions: hese data suggest that information about functional connectivity from resting-state functional magnetic resonance imaging may help predict 90-day stroke outcome.

Original languageEnglish (US)
Pages (from-to)2353-2360
Number of pages8
Issue number10
StatePublished - 2018
Externally publishedYes


  • Brain
  • Magnetic resonance imaging
  • Patients
  • Reperfusion
  • Stroke

ASJC Scopus subject areas

  • Clinical Neurology
  • Cardiology and Cardiovascular Medicine
  • Advanced and Specialized Nursing


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