Erschienen in:
09.08.2019 | Original Article
Associations Between Diffusion Dynamics and Functional Outcome in Acute and Early Subacute Ischemic Stroke
verfasst von:
Chengxia Liu, Shun Zhang, Yihao Yao, Changliang Su, Zhenxiong Wang, Minghuan Wang, Wenzhen Zhu
Erschienen in:
Clinical Neuroradiology
|
Ausgabe 3/2020
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Abstract
Purpose
The current study aimed to investigate the associations between diffusion dynamics of ischemic lesions and clinical functional outcome of acute and early subacute stroke.
Material and Methods
A total of 80 patients with first ever infarcts in the territory of the middle cerebral artery underwent multi-b-values diffusion-weighted imaging and diffusion kurtosis imaging. Multiple diffusion parameters were generated in postprocessing using different diffusion models. Long-term functional outcome was evaluated with modified Rankin scale (mRS) at 6 months post-stroke. Good functional outcome was defined as mRS score ≤ 2 and poor functional outcome was defined as mRS score ≥ 3. Univariate analysis was used to compare the diffusion parameters and clinical features between patients with poor and good functional outcome. Significant parameters were further analyzed for correlations with functional outcome using partial correlation.
Results
In univariate analyses, standard-b-values apparent diffusion coefficient (ADCst) ratio and fractional anisotropy (FA) ratio of acute stroke, ADCst ratio and mean kurtosis (MK) ratio of early subacute stroke were statistically different between patients with poor outcome and good outcome (P < 0.05). When the potential confounding factor of lesion volume was controlled, only FA ratio of acute stroke, ADCst ratio and MK ratio of early subacute stroke remained correlated with the functional outcome (P < 0.05).
Conclusion
Diffusion dynamics are correlated with the clinical functional outcome of ischemic stroke. This correlation is independent of the effect of lesion volume and is specific to the time period between symptom onset and imaging. More effort is needed to further investigate the predictive value of diffusion-weighted imaging.