MRI Assessment of Brain Frailty and Clinical Outcome in Patients With Acute Posterior Perforating Artery Infarction.

BACKGROUND: Global brain health has gained increasing attention recently. Imaging markers of brain frailty have been related to functional outcomes in previous studies on anterior circulation; however, little data are available on imaging markers and posterior circulation. PURPOSE: To investigate the impact of brain frailty on functional outcomes in patients with acute perforating artery infarction (PAI) of the posterior circulation. STUDY TYPE: Prospective. POPULATION: One hundred patients (60.78 ± 9.51 years, 72% men) with acute posterior circulation PAI (determined by diffusion-weighted magnetic resonance imaging (MRI)/time-of-flight MR angiography). FIELD STRENGTH/SEQUENCE: T1- and T2-weighted fast spin echo, T2-weighted fluid-attenuated inversion recovery, diffusion-weighted echo planar, gradient echo (susceptibility-weight imaging), and 3D time-of-flight MR angiography sequences at 3.0 T. ASSESSMENT: Periventricular and deep white matter hyperintensities (WMH), enlarged perivascular spaces (EPVS) in the basal ganglia and centrum semiovale area, lacunes, cerebral microbleeds (CMB), and total brain frailty score by calculating the above imaging characters were rated visually by three radiologists with 9, 10, and 11 years of experience and one neuroradiologist with 12. Infarction volume was assessed using baseline diffusion-weighted imaging (DWI) data obtained within 24 hours of symptom onset. A modified Rankin Scale (mRS) score >1 on day 90 defined an adverse functional outcome. Associations between the imaging markers of brain frailty and functional outcomes were assessed. STATISTICAL TESTS: Fisher's exact test, Mann-Whitney U test, and multivariable binary logistic regression. A P value <0.05 was considered statistically significant. RESULTS: Adverse prognoses (mRS > 1) were observed in 34 (34%) patients. Infarction volume, periventricular WMH, deep WMH, basal ganglia EPVS, CMB, and the brain frailty score were significantly associated with adverse functional outcomes. An increased brain frailty score was significantly associated with unfavorable mRS score on day 90 (odds ratio 1.773, 95% confidence interval 1.237-2.541). DATA CONCLUSION: Advanced MRI imaging markers of brain frailty, individually or combined as a total brain frailty score, were associated with worse functional outcomes after acute posterior circulation PAI. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 3.

Small vessel disease burden predicts functional outcomes in patients with acute ischemic stroke using machine learning.

AIMS: Our purpose is to assess the role of cerebral small vessel disease (SVD) in prediction models in patients with different subtypes of acute ischemic stroke (AIS). METHODS: We enrolled 398 small-vessel occlusion (SVO) and 175 large artery atherosclerosis (LAA) AIS patients. Functional outcomes were assessed using the modified Rankin Scale (mRS) at 90 days. MRI was performed to assess white matter hyperintensity (WMH), perivascular space (PVS), lacune, and cerebral microbleed (CMB). Logistic regression (LR) and machine learning (ML) were used to develop predictive models to assess the influences of SVD on the prognosis. RESULTS: In the feature evaluation of SVO-AIS for different outcomes, the modified total SVD score (Gain: 0.38, 0.28) has the maximum weight, and periventricular WMH (Gain: 0.07, 0.09) was more important than deep WMH (Gain: 0.01, 0.01) in prognosis. In SVO-AIS, SVD performed better than regular clinical data, which is the opposite of LAA-AIS. Among all models, eXtreme gradient boosting (XGBoost) method with optimal index (OI) has the best performance to predict excellent outcome in SVO-AIS. [0.91 (0.84-0.97)]. CONCLUSIONS: Our results revealed that different SVD markers had distinct prognostic weights in AIS patients, and SVD burden alone may accurately predict the SVO-AIS patients' prognosis.