Gutierrez, José

Background and Objectives: Acute small subcortical infarcts (SSI) result in high rates of early neurological deterioration (END) despite best medical management. Those with SSI-related END have worse functional outcomes after stroke leading to increased morbidity. Presently, it is unknown in a robust manner the incidence or risk factors for END within this demographic. The aim of this study was to perform a systematic review and meta-analysis to understand the incidence and risk factors of SSI-related END. Methods: We searched PubMed, Cochrane Library, and Google Scholar between January 1, 2000, and June 1, 2022, including both retrospective cross-sectional and prospective observational studies. The primary outcome was development of END based on publishing authors’ definition. Abstracted data included age, sex, cohort size, diagnoses of hypertension, hyperlipidemia, diabetes mellitus, study definition of END and SSI, and presence of branch atheromatous disease (BAD) and lesion diameter. Results: We identified 31 studies enrolling 6376 patients. Most studies were conducted in East Asia (27/31, 87%) and had a least some concern for risk of bias. Funnel plot illustrated a high level of publication bias favoring high incidence studies. END was commonly defined as ≥ 2 overall NIHSS change or ≥ 1 motor change within 3 to 7 days from admission (average: 5 days). A pooled proportion of END was 22% (95%CI 0.19 - 0.25, I2 = 91.2%, 31 studies). Meta-regression identified that female sex [risk ratio (RR) 1.23, 95%CI 1.09-1.39, I2=30.8%, 31 studies], diabetes mellitus (RR 1.16 95%CI 1.01-1.33, I2=38.4%, 30 studies), and BAD (RR 1.99 95%CI 1.61-2.46, I2=50.7%, 17 studies) as risk factors for END. Discussion: Our data identified primarily within an East Asian cohort that risk factors for SSI-related END include diabetes mellitus and branch atheromatous disease with a pooled prevalence of END occurring in 1 in 4 patients. Future studies are needed to understand treatment and preventative strategies for this patient population.

Background: Perfusion weighted imaging on MRI (MRP) and computerized tomography perfusion (CTP) are increasingly required to manage large vessel disease. Computerized algorithms can quantify perfusion data, but the programs are expensive and not widely used outside acute stroke evaluation. We aimed to determine how well human observers can identify asymmetries in cerebral perfusion images compared with an automated computer algorithm. Methods: Ten clinicians experienced in treating carotid artery disease (4 vascular neurologists, 3 neuroradiologists, 1 vascular surgeon, 1 neurosurgeon, 1 interventional radiologist) were given 28 post-processed, color-coded, axial-slice MRP scans from patients in the Carotid Revascularization Endovascular versus Stenting Trial - Hemodynamics (CREST-H) study. All patients had >70%, unilateral, asymptomatic carotid artery stenosis and had varying degrees of time-to-peak (TTP) delay on the side of stenosis, ranging from 0 to 2 secs, quantified by a semi-automated system that computes quantitative perfusion maps, using deconvolution of tissue and arterial signals (Olea, Cambridge, MA). A minimum volume of 10cc was required for a given TTP delay. Clinicians were asked to determine asymmetry (y/n) and side of occlusion for each case. Number of correct responses that matched the computer output were tallied. Results: We averaged correct responses by the 10 clinicians for cases at each increment of TTP delay; (Figure). At TTP delays ≥1.5 seconds, accuracy was ≥80%. At 1.25 sec accuracy fell to 60%, and at ≤ 1 sec, accuracy was ≤50%. For TTP=0 (no asymmetry), accuracy was 71%. Conclusions: Visual impression of hemodynamic asymmetry among experienced clinicians was reasonably accurate for TTP delays ≥1.5 seconds, but declined with more subtle asymmetries. Depending on the clinical impact of TTP delays (for CREST-H: correlation with cognitive decline), experienced clinicians may perform as well as an automated algorithm.