Conglomerated beads shape of lacunar infarcts on diffusion-weighted MRI: what does it suggest?
prospective_cohort · Level II
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- Record sourced from PubMed, PMID 22517100.
- Also identified by DOI 10.1212/WNL.0b013e318253d62f.
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Abstract
We aimed to analyze lesion patterns of lacunae-sized infarctions in the perforating arterial territory in terms of shape and to determine whether the particular pattern of conglomerated beads shape affected early neurologic deterioration. We consecutively included acute ischemic stroke patients with confirmed lacunae-sized acute ischemic infarcts in the penetrating arterial territories on diffusion-weighted MRI. Based on diffusion-weighted MRI, the shape of ischemic infarcts was divided into oval or conglomerated beads shape. Demographics, risk factors, NIH Stroke Scale (NIHSS) score at admission and discharge, and stroke mechanisms were analyzed. Early neurologic deterioration was defined as any increase of NIHSS score at the time of discharge. Among 105 patients included, the conglomerated beads shape of infarcts was observed in 34 (32.4%) patients and the oval shape in 71 (67.6%) patients. The baseline characteristics were not different between the 2 groups. However, the maximal diameter of the lesion was significantly larger in the conglomerated beads shape group (12.8 ± 3.3 mm vs 10.8 ± 3.8 mm, p = 0.009). Early neurologic deterioration was also more commonly observed in the conglomerated beads shape group than in the oval shape group (20.6% vs 4.2%, p = 0.012). Multiple logistic regression analysis showed that the conglomerated beads shape was significantly associated with early neurologic deterioration (odds ratio 6.83, 95% confidence interval 1.53-30.55, p = 0.012). In 32.4% of all the lacunae-sized infarcts in the perforating artery territory, the conglomerated beads shape was observed. This shape was significantly associated with early neurologic deterioration.
Medical subject headings
- Diffusion Magnetic Resonance Imaging
- Image Processing, Computer-Assisted
- Stroke, Lacunar