Abstract
Stroke-like episodes (SLEs) in patients with mitochondrial encephalomyopathy, lactic acidosis, and stroke-like episodes (MELAS) syndrome are often misdiagnosed as acute ischemic stroke (AIS). We aimed to determine unique clinical and neuroimaging features for SLEs and formulate diagnostic criteria. We retrospectively identified patients with MELAS admitted for SLEs between January 2012 and December 2021. Clinical features and imaging findings were compared with a cohort of patients who presented with AIS and similar lesion topography. A set of criteria was formulated and then tested by a blinded rater to evaluate diagnostic performance. Eleven MELAS patients with 17 SLE and 21 AISs were included. Patients with SLEs were younger (median 45 [37-60] vs 77 [68-82] years, p < 0.01) and had a lower body mass index (18 ± 2.6 vs 29 ± 4, p < 0.01), more commonly reported hearing loss (91% vs 5%, p < 0.01), and more commonly presented with headache and/or seizures (41% vs 0%, p < 0.01). The earliest neuroimaging test performed at presentation was uniformly a noncontrast CT. Two main patterns of lesion topography with a stereotypical spatiotemporal evolution were identified-an anterior pattern (7/21, 41%) starting at the temporal operculum and spreading to the peripheral frontal cortex and a posterior pattern (10/21, 59%) starting at the cuneus/precuneus and spreading to the lateral occipital and parietal cortex. Other distinguishing features for SLEs vs AIS were cerebellar atrophy (91% vs 19%, p < 0.01), previous cortical lesions with typical SLE distribution (46% vs 9%, p = 0.03), acute lesion tissue hyperemia and venous engorgement on CT angiography (CTA) (45% vs 0%, p < 0.01), and no large vessel occlusion on CTA (0% vs 100%, p < 0.01). Based on these clinicoradiologic features, a set of diagnostic criteria were constructed for possible SLE (sensitivity 100%, specificity 81%, AUC 0.905) and probable SLE (sensitivity 88%, specificity 95%, AUC 0.917). Clinicoradiologic criteria based on simple anamnesis and a CT scan at presentation can accurately diagnose SLE and lead to early administration of appropriate therapy. This study provides Class III evidence that an algorithm using clinical and imaging features can differentiate stroke-like episodes due to MELAS from acute ischemic strokes.
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