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Abstract BACKGROUND Increased body mass index (BMI) may be protective against cerebral ischemia in certain clinical contexts. OBJECTIVE To investigate whether increased BMI was associated with delayed cerebral ischemia (DCI) and subsequent infarction after aneurysmal subarachnoid hemorrhage (aSAH). METHODS We retrospectively reviewed the clinical course of patients presenting to our institution for management of aSAH. Patient were segregated according to BMI< or ≥29.4, a value determined by Classification and Regression Tree analysis. Predictors of DCI and delayed infarction were identified using stepwise multivariate logistic regression analysis. RESULTS There were 161 patients included for analysis. Average BMI within our patient cohort was 28.9, with 67 patients presenting with a BMI of ≥29.4 on admission. DCI occurred in 50 patients (31.1%) and was complicated by delayed infarction in 15 patients (9.3%). On stepwise multivariate analysis, BMI ≥ 29.4 was independently associated with reduced likelihood of DCI (odds ratio [OR] 0.42, 95% confidence interval [CI] 0.18-0.92) and delayed infarction (OR 0.13, 95% CI 0.02-0.61; P = .008). Increasing maximum flow velocity on transcranial Doppler ultrasound was independently associated with increased odds of both DCI (Unit OR 1.19, 95% CI 1.09-1.30; P < .001) and delayed infarction (Unit OR 1.31, 95% CI 1.13-1.56; P < .001), while intracerebral hemorrhage was independently associated with increased odds of delayed infarction (OR 6.99, 95% CI 1.82-30.25; P = .005). CONCLUSION We report an association between elevated BMI and reduced incidence of DCI and delayed infarction, suggesting a protective effect of increasing BMI on the risk of ischemic complications after aSAH.

BackgroundCarotid plaque imaging with MRI is becoming more commonplace, but practical challenges exist in performing plaque imaging with surface coils.PurposeTo compare the diagnostic performance of a carotid plaque MRI protocol using a standard neurovascular coil (Neurovascular Coil Protocol) to a higher‐resolution carotid plaque MRI using carotid surface coils (Surface Coil Protocol) in characterizing carotid plaque.Study TypeProspective study comparing two MR techniques in plaque characterization.PopulationThirty‐eight consecutive carotid artery disease patients.Field Strength/SequencePatients underwent 3T MRI using 1) a Neurovascular Coil Protocol including the following sequences: 3D‐FSE T1 pre/postcontrast and precontrast 3D IR‐FSPGR, and 2) a Surface Coil Protocol using standard multicontrast MRI sequences.AssessmentPlaque characteristics analyzed by two independent neuroradiologists included intraplaque hemorrhage (IPH), lipid‐rich necrotic‐core (LRNC), and thin/ruptured fibrous cap (TRFC).Statistical TestsDiagnostic performance of the Neurovascular Coil Protocol was compared to the Surface Coil Protocol reference standard using receiver‐operating curves.ResultsFor IPH, sensitivity, specificity, and area under the curve (AUC) of the Neurovascular Coil Protocol were 91.1% (95% confidence interval [CI] = 78.8–97.5%), 87.0% (95% CI = 66.4–97.2%), and 0.92, respectively. For LRNC without IPH sensitivity, specificity, and AUC were 73.3% (95% CI = 44.9–92.2%), 85.7% (95% CI = 67.3–96.0%), and 0.84, respectively. For TRFC, sensitivity, specificity, and AUC were 35.3% (95% CI = 14.2–61.7%), 97.6% (95% CI = 87.4–99.9%), and 0.66 respectively. Interobserver agreement for IPH, LRNC, and TRFC using the Neurovascular Coil Protocol were k = 0.87 (95% CI = 0.75–0.99), k = 0.54 (95% CI = 0.29–0.80), and k = 0.41 (95% CI = 0.08–0.74), respectively.Data ConclusionOur Neurovascular Coil Protocol has high sensitivity, specificity, and accuracy in identifying IPH and LRNC but is limited in assessment of TRFC.Level of Evidence: 1Technical Efficacy: Stage 2J. Magn. Reson. Imaging 2018;47:1264–1272.

Background and Purpose— Superficial siderosis (SS) is characterized by hemosiderin deposition in the superficial layers of the central nervous system and can be seen during postmortem examination or with iron-sensitive magnetic resonance imaging techniques. The distribution of SS may predict the probable underlying cause. This study aimed to report the prevalence and natural history of SS in a population-based study. Methods— Brain magnetic resonance imaging scans from the MCSA (Mayo Clinic Study of Aging), a population-based study of residents 50 to 89 years of age in Olmsted County, Minnesota, were reviewed. Participants with imaging consistent with SS were identified from 2011 through 2016. An inverse probability weighting approach was used to convert our observed frequencies to population prevalence of SS. Additional data abstracted included amyloid positron emission tomography, Apolipoprotein E genotype, coexisting cerebral microbleeds, and extent of SS. Results— A total of 1412 participants had eligible magnetic resonance imaging scans. Two participants had infratentorial SS, restricted to the posterior fossa. Thirteen participants had cortical SS involving the cerebral convexities (7 focal and 6 disseminated). Only 3 of the participants with cortical SS (23%) also had cerebral microbleeds. The population prevalence of SS was 0.21% (95% confidence interval, 0–0.45) in those 50 to 69 years old and 1.43% (confidence interval, 0.53–2.34) in those over 69 years old. Apolipoprotein E ε2 allele was more common in those with SS (57.1% versus 15.0%; P <0.001). Compared with participants without SS, those with SS were also more likely to have a positive amyloid positron emission tomographic scan (76.9% versus 29.8%; P <0.001). Conclusions— SS may be encountered in the general elderly population. The association with increased amyloid burden and Apolipoprotein E ε2 genotype supports cerebral amyloid angiopathy as the most common mechanism. Longitudinal follow-up is needed to evaluate the risk of subsequent hemorrhage in cases of incidentally discovered SS.

OBJECTIVEIt has been suggested that increased body mass index (BMI) may confer a protective effect on patients who suffer from aneurysmal subarachnoid hemorrhage (aSAH). Whether the modality of aneurysm occlusion influences the effect of BMI on patient outcomes is not well understood. The authors aimed to compare the effect of BMI on outcomes for patients with aSAH treated with surgical clipping versus endovascular coiling.METHODSThe authors retrospectively reviewed the outcomes for patients admitted to their institution for the management of aSAH treated with either clipping or coiling. BMI at the time of admission was recorded and used to assign patients to a group according to low or high BMI. Cutoff values for BMI were determined by classification and regression tree analysis. Predictors of poor functional outcome (defined as modified Rankin Scale score > 2 measured ≥ 90 days after the ictus) and posttreatment cerebral hypodensities detected during admission were then determined separately for patients treated with clipping or coiling using stepwise multivariate logistic regression analysis.RESULTSOf the 469 patients admitted to the authors’ institution with aSAH who met the study’s inclusion criteria, 144 were treated with clipping and 325 were treated with coiling. In the clipping group, the frequency of poor functional outcome was higher in patients with BMI ≥ 32.3 kg/m2 (47.6% vs 19.0%; p = 0.007). In contrast, in the coiling group, patients with BMI ≥ 32.3 kg/m2 had a lower frequency of poor functional outcome at ≥ 90 days (5.8% vs 30.9%; p < 0.001). On multivariate analysis, high BMI was independently associated with an increased (OR 3.92, 95% CI 1.20–13.41; p = 0.024) and decreased (OR 0.13, 95% CI 0.03–0.40; p < 0.001) likelihood of poor functional outcome for patients treated with clipping and coiling, respectively. For patients in the surgical group, BMI ≥ 28.4 kg/m2 was independently associated with incidence of cerebral hypodensities during admission (OR 2.44, 95% CI 1.16–5.25; p = 0.018) on multivariate analysis. For patients treated with coiling, BMI ≥ 33.2 kg/m2 was independently associated with reduced odds of hypodensities (OR 0.45, 95% CI 0.21–0.89; p = 0.021).CONCLUSIONSThe results of this study suggest that BMI may differentially affect functional outcomes after aSAH, depending on treatment modality. These findings may aid in treatment selection for patients with aSAH.