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Two different stroke mechanisms are involved in small vessel disease: branch atheromatous disease (BAD) and lipohyalinotic degeneration (LD). We compared mechanisms of stroke in lenticulostriate arteries (LSA) vs. anterior pontine arteries (APA) and verified factors associated with stroke mechanisms, including shape of middle cerebral artery (MCA) and basilar artery (BA). We retrospectively reviewed patients with acute ischemic stroke with penetrating artery territory confirmed by MRI. The mechanisms of stroke were categorized based on diffusion-weighted imaging; BAD was defined as lesion larger than 10 mm in LSA and lesions involving basal pontine in APA. Other lesions were classified as LD. The shapes of MCA and BA were classified as straight, with one angle, or with two angles (U, C or S shape, respectively) using anterior–posterior view. The study included 221 patients. LD was more common in LSA infarcts, but BAD was more common in APA infarcts (p < 0.001). Low initial National Institutes of Health Stroke Scale [Adjusted Odds ratio (aOR) = 0.78; p < 0.001], absence of hyperlipidemia [aOR = 0.31; p = 0.002], previous statin use [aOR = 4.35; p = 0.028] LSA infarcts [reference = APA territory; aOR = 11.07; p < 0.001], and S-shaped vessels (reference = straight shaped vessels; aOR = 3.51; p = 0.004) were independently associated with LD. Angulations in the mother vessels may be more associated with true small vessel disease more with LD than BAD. [ABSTRACT FROM AUTHOR]

Multimodal magnetic resonance imaging (MRI) has emerged as a promising tool for diagnosing ischemic stroke and for determining treatment strategies in the acute phase. The detection and quantification of the penumbra and the infarct core regions aid the assessment of the potential risks and benefits of thrombolysis by providing information on salvageable tissue or ischemic lesion age. In this study, we proposed a fully automated and real-time algorithm to compute parameter maps of perfusion-weighted images (PWIs) and to identify an infarct core from diffusion-weighted images (DWIs). DWI and PWI were obtained using a 1.5 Tesla MRI scanner for 15 patients with acute ischemic stroke. Parameter maps of PWI were computed using restricted gamma-variate curve fitting and Fourier-based deconvolution. The ischemic penumbra was identified using time-to-maximum (Tmax) > 6 s as the mutual optimal threshold, while the infarct core was segmented using an adaptive thresholding on DWI. When the penumbra on PWI was compared with that generated using commercial software Pearson's linear correlation coefficient between penumbra volumes was 0.601 (p = 0.030), and the Dice coefficient was 0.51 ± 0.15. The infarct core on DWI was compared with the manually segmented gold standard. Dice coefficient between the manually drawn and automated segmented infarct cores was 0.62 ± 0.18. The processing times for PWI and DWI were 222.9 ± 16.4 and 53.4 ± 4.8 s, respectively. In conclusion, we demonstrate a fully automated and real-time algorithm to segment the penumbra and the infarct core regions based on PWI and DWI. [ABSTRACT FROM AUTHOR]