Time dependence in diffusion MRI predicts tissue outcome in ischemic stroke patients

Research output: Contribution to journalArticle


Purpose: Reperfusion therapy enables effective treatment of ischemic stroke presenting within 4–6 hours. However, tissue progression from ischemia to infarction is variable, and some patients benefit from treatment up until 24 hours. Improved imaging techniques are needed to identify these patients. Here, it was hypothesized that time dependence in diffusion MRI may predict tissue outcome in ischemic stroke. Methods: Diffusion MRI data were acquired with multiple diffusion times in five non-reperfused patients at 2, 9, and 100 days after stroke onset. Maps of “rate of kurtosis change” (k), mean kurtosis, ADC, and fractional anisotropy were derived. The ADC maps defined lesions, normal-appearing tissue, and the lesion tissue that would either be infarcted or remain viable by day 100. Diffusion parameters were compared (1) between lesions and normal-appearing tissue, and (2) between lesion tissue that would be infarcted or remain viable. Results: Positive values of k were observed within stroke lesions on day 2 (P =.001) and on day 9 (P =.023), indicating diffusional exchange. On day 100, high ADC values indicated infarction of 50 ± 20% of the lesion volumes. Tissue infarction was predicted by high k values both on day 2 (P =.026) and on day 9 (P =.046), by low mean kurtosis values on day 2 (P =.043), and by low fractional anisotropy values on day 9 (P =.029), but not by low ADC values. Conclusions: Diffusion time dependence predicted tissue outcome in ischemic stroke more accurately than the ADC, and may be useful for predicting reperfusion benefit.


External organisations
  • Skåne University Hospital
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Radiology, Nuclear Medicine and Medical Imaging


  • diffusion-weighted imaging, human, ischemic stroke, reperfusion
Original languageEnglish
JournalMagnetic Resonance in Medicine
Publication statusE-pub ahead of print - 2021
Publication categoryResearch