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Higher-Level Gait Disorder (HLGD) is a type of gait disorder estimated to affect up to 6% of the older population. By definition, its symptoms originate from the higher-level nervous system, yet its association with brain morphology remains unclear. This study hypothesizes that there are patterns in brain morphology linked to HLGD. For the first time in the literature, this work investigates whether deep learning, in the form of convolutional neural networks, can capture patterns in magnetic resonance images to identify individuals affected by HLGD. To handle this new classification task, we propose setting up an ensemble of models. This leverages the benefits of combining classifiers instead of determining which network is the most suitable, developing a new architecture, or customizing an existing one. We introduce a computationally cost-effective search algorithm to find the optimal ensemble by leveraging a cost function of both traditional performance scores and the diversity among the models. Using a unique dataset from a large population-based cohort (VESPR), the ensemble identified by our algorithm demonstrated superior performance compared to single networks, other ensemble fusion techniques, and the best linear radiological measure. This emphasizes the importance of implementing diversity into the cost function. Furthermore, the results indicate significant morphological differences in brain structure between HLGD-affected individuals and controls, motivating research about which areas the networks base their classifications on, to get a better understanding of the pathophysiology of HLGD.

Selective antegrade cerebral perfusion (SACP) is a protective procedure to ascertain adequate brain perfusion during aortic arch surgeries requiring moderate hypothermic circulatory arrest. SACP entails catheterization of arteries feeding the brain, which can be done bilaterally (bSACP) or unilaterally (uSACP), but there is no consensus on when to use each approach. bSACP may increase the risk of embolization, while uSACP risks hypoperfusion due to insufficient perfusion pressure in the contralateral hemisphere, since a single catheter must perfuse both hemispheres. We developed and tested the feasibility of a new method for predicting cerebral perfusion pressures (CPP) during SACP, which could potentially aid clinicians in preoperatively identifying which SACP approach to use. Feasibility of the method was evaluated in five patients eligible for aortic arch surgery (65 ± 7 years, 3 men). Patients were investigated preoperatively with computed tomography angiography (CTA) and 4D flow magnetic resonance imaging (MRI) to assess patient-specific arterial anatomy and blood flows. From the imaging, computational fluid dynamics (CFD) simulations estimated the patients' vascular resistances. Applying these resistances and intraoperative SACP pressure/flow settings to the model's boundary conditions allowed for predictions of contralateral CPP during SACP. Predicted pressures were compared to corresponding intraoperative pressure measurements. The method showed promise for predicting contralateral CPP during both uSACP (median error (range): 2.4 (−0.2–18.0) mmHg) and bSACP (0.8 (−3.3–5.4) mmHg). Predictions were most sensitive to collateral artery size. This study showed the feasibility of CPP predictions of SACP, and presents key features needed for accurate modelling.

Background and purpose: Disproportionately enlarged subarachnoid space hydrocephalus (DESH) is a radiological biomarker for idiopathic normal pressure hydrocephalus (iNPH). DESH is a subjective measure, based on visual assessments, which may limit its reliability. The aim of this study was to develop and validate a method for the objective quantification of DESH.

Materials and methods: By using a semiautomatic quantitative method, we calculated quantitative DESH (qDESH), defined as a ratio between CSF volumes at high convexities and Sylvian fissures. The analysis was based on three-dimensional T1-weighted images from 35 subjects with iNPH (mean age 74 yrs; 10 females) and 45 controls (mean age 72 yrs; 13 females). The interrater agreement for qDESH was evaluated by the intraclass correlation coefficient, and qDESH was compared with visual assessments performed by two neuroradiologists.

Results: All subjects with iNPH and 13% of the controls visually scored DESH positive. The median qDESH was 2.48 (5th to 95th percentile 0.88 to 5.42) for iNPH and 0.63 (5th to 95th percentile 0.37 to 1.73) for the controls. The area under the receiver operating characteristic curve for qDESH was 0.95 (95% confidence interval 0.90–1) in separating iNPH patients from controls. The interrater agreement for qDESH was 0.99 (95% CI 0.986–0.994, p < 0.001).

Conclusion: Unlike visual DESH, qDESH generates a continuous variable, enabling reproducible quantification of DESH severity. With this method we can objectively investigate the diagnostic accuracy and prognostic assessment of DESH in iNPH.

Variations in cerebral blood flow and blood volume interact with intracranial pressure and cerebrospinal fluid dynamics, all of which play a crucial role in brain homeostasis. A key physiological modulator is respiration, but its impact on cerebral blood flow and volume has not been thoroughly investigated. Here we used 4D flow MRI in a population-based sample of 65 participants (mean age = 75 ± 1) to quantify these effects. Two gating approaches were considered, one using respiratory-phase and the other using respiratory-time (i.e. raw time in the cycle). For both gating methods, the arterial inflow was significantly larger during exhalation compared to inhalation, whereas the venous outflow was significantly larger during inhalation compared to exhalation. The cerebral blood volume variation per respiratory cycle was 0.83 [0.62, 1.13] ml for respiratory-phase gating and 0.78 [0.59, 1.02] ml for respiratory-time gating. For comparison, the volume variation of the cardiac cycle was 1.01 [0.80, 1.30] ml. Taken together, our results clearly demonstrate respiratory influences on cerebral blood flow. The corresponding vascular volume variations appear to be of the same order of magnitude as those of the cardiac cycle, highlighting respiration as an important modulator of cerebral blood flow and blood volume.

Blood-brain barrier (BBB) disruption may contribute to cognitive decline, but questions remain whether this association is more pronounced for certain brain regions, such as the hippocampus, or represents a whole-brain mechanism. Further, whether human BBB leakage is triggered by excessive vascular pulsatility, as suggested by animal studies, remains unknown. In a prospective cohort (N = 50; 68-84 years), we used contrast-enhanced MRI to estimate the permeability-surface area product (PS) and fractional plasma volume ( formula presented ), and 4D flow MRI to assess cerebral arterial pulsatility. Cognition was assessed by the Montreal Cognitive Assessment (MoCA) score. We hypothesized that high PS would be associated with high arterial pulsatility, and that links to cognition would be specific to hippocampal PS. For 15 brain regions, PS ranged from 0.38 to 0.85 (·10-3 min-1) and formula presented from 0.79 to 1.78%. Cognition was related to PS (·10-3 min-1) in hippocampus (β = - 2.9; p = 0.006), basal ganglia (β = - 2.3; p = 0.04), white matter (β = - 2.6; p = 0.04), whole-brain (β = - 2.7; p = 0.04) and borderline-related for cortex (β = - 2.7; p = 0.076). Pulsatility was unrelated to PS for all regions (p > 0.19). Our findings suggest PS-cognition links mainly reflect a whole-brain phenomenon with only slightly more pronounced links for the hippocampus, and provide no evidence of excessive pulsatility as a trigger of BBB disruption.

White matter hyperintensities (WMH), perivascular spaces (PVS) and lacunes are common MRI features of small vessel disease (SVD). However, no shared underlying pathological mechanism has been identified. We investigated whether SVD burden, in terms of WMH, PVS and lacune status, was related to changes in the cerebral arterial wall by applying global cerebral pulse wave velocity (gcPWV) measurements, a newly described marker of cerebral vascular stiffness. In a population-based cohort of 190 individuals, 66–85 years old, SVD features were estimated from T1-weighted and FLAIR images while gcPWV was estimated from 4D flow MRI data. Additionally, the gcPWV’s stability to variations in field-of-view was analyzed. The gcPWV was 10.82 (3.94) m/s and displayed a significant correlation to WMH and white matter PVS volume (r = 0.29, p < 0.001; r = 0.21, p = 0.004 respectively from nonparametric tests) that persisted after adjusting for age, blood pressure variables, body mass index, ApoB/A1 ratio, smoking as well as cerebral pulsatility index, a previously suggested early marker of SVD. The gcPWV displayed satisfactory stability to field-of-view variations. Our results suggest that SVD is accompanied by changes in the cerebral arterial wall that can be captured by considering the velocity of the pulse wave transmission through the cerebral arterial network.

Background: Adequate cerebral perfusion is central during general anesthesia. However, perfusion is not readily measured bedside. Clinicians currently rely mainly on MAP as a surrogate even though the relationship between blood pressure and cerebral blood flow is not well understood. The aim of this study was to apply phase contrast MRI to characterize blood flow responses in healthy volunteers to commonly used pharmacological agents that increase or decrease arterial blood pressure.

Methods: Eighteen healthy volunteers aged 30-50 years were investigated with phase contrast MRI. Intraarterial blood pressure monitoring was used. First, intravenous noradrenaline was administered to a target MAP of 20% above baseline. After a wash-out period, intravenous labetalol was given to a target MAP of 15% below baseline. Cerebral blood flow was measured using phase contrast MRI and defined as the sum of flow in the internal carotid arteries and vertebral arteries. CO was defined as the flow in the ascending aorta.

Baseline median cerebral blood flow was 772 ml/min (interquartile range, 674 to 871), and CO was 5,874 ml/min (5,199 to 6,355). The median dose of noradrenaline was 0.17 µg · kg⁻¹ · h⁻¹ (0.14 to 0.22). During noradrenaline infusion, cerebral blood flow decreased to 705 ml/min (606 to 748; P = 0.001), and CO decreased to 4,995 ml/min (4,705 to 5,635; P = 0.01). A median dose of labetalol was 120 mg (118 to 150). After labetalol boluses, cerebral blood flow was unchanged at 769 ml/min (734 to 900; P = 0.68). CO increased to 6,413 ml/min (6,056 to 7,464; P = 0.03).

Conclusion: In healthy awake subjects, increasing MAP using intravenous noradrenaline decreased cerebral blood flow and CO. This data does not support inducing hypertension with noradrenaline to increase cerebral blood flow. Cerebral blood flow was unchanged when decreasing MAP using labetalol.

Background: Compromised cerebral blood flow can contribute to future ischemic events in patients with symptomatic carotid artery disease. However, there is limited knowledge of the effects on cerebral hemodynamics resulting from a reduced internal carotid artery (ICA) blood flow rate (BFR).

Purpose: Investigate how reduced ICA-BFR, relates to BFR in the cerebral arteries.

Study Type: Prospective.

Subjects: Thirty-eight patients, age 72 ± 6 years (11 female).

Field Strength/Sequence: 3-Tesla, four-dimensional phase-contrast magnetic resonance imaging (4D-PCMRI).

Assessment: Patients with ischemic stroke or transient ischemic attack were evaluated regarding the degree of stenosis. 4D-PCMRI was used to measure cerebral BFR in 38 patients with symptomatic carotid stenosis (≥50%). BFR in the cerebral arteries was assessed in two subgroups based on symptomatic ICA-BFR: reduced ICA-flow (<160 mL/minutes) and preserved ICA-flow (≥160 mL/minutes). BFR laterality was defined as a difference in the paired ipsilateral-contralateral arteries.

Statistical Tests: Patients were grouped based on ICA-BFR (reduced vs. preserved). Statistical tests (independent sample t-test/paired t-test) were used to compare groups and hemispheres. Significance was determined at P < 0.05.

Results: The degree of stenosis was not significantly different, 80% (95% confidence interval [CI] = 73%–87%) in the reduced ICA-flow vs. 72% (CI = 66%–76%) in the preserved ICA-flow; P = 0.09. In the reduced ICA-flow group, a significantly reduced BFR was found in the ipsilateral middle cerebral artery and anterior cerebral artery (A1), while significantly increased in the contralateral A1. Retrograde BFR was found in the posterior communicating artery and ophthalmic artery. Significant BFR laterality was present in all paired arteries in the reduced ICA-flow group, contrasting the preserved ICA-flow group (P = 0.14–0.93).

Data Conclusions: 4D-PCMRI revealed compromised cerebral BFR due to carotid stenosis, not possible to detect by solely analyzing the degree of stenosis. In patients with reduced ICA-flow, collaterals were not sufficient to maintain symmetrical BFR distribution to the two hemispheres.

Evidence Level: 2.

Technical Efficacy: Stage 3.

Background: Studies indicate that brain clearance via the glymphatic system is impaired in idiopathic normal pressure hydrocephalus (INPH). This has been suggested to result from reduced cerebrospinal fluid (CSF) turnover, which could be caused by a reduced CSF formation rate. The aim of this study was to determine the formation rate of CSF in a cohort of patients investigated for INPH and compare this to a historical control cohort.

Methods: CSF formation rate was estimated in 135 (75 ± 6 years old, 64/71 men/women) patients undergoing investigation for INPH. A semiautomatic CSF infusion investigation (via lumbar puncture) was performed. CSF formation rate was assessed by downregulating and steadily maintaining CSF pressure at a zero level. During the last 10 min, the required outflow to maintain zero pressure, i.e., CSF formation rate, was continuously measured. The values were compared to those of a historical reference cohort from a study by Ekstedt in 1978.

Results: Mean CSF formation rate was 0.45 ± 0.15 ml/min (N = 135), equivalent to 27 ± 9 ml/hour. There was no difference in the mean (p = 0.362) or variance (p = 0.498) of CSF formation rate between the subjects that were diagnosed as INPH (N = 86) and those who were not (N = 43). The CSF formation rate in INPH was statistically higher than in the reference cohort (0.46 ± 0.15 vs. 0.40 ± 0.08 ml/min, p = 0.005), but the small difference was probably not physiologically relevant. There was no correlation between CSF formation rate and baseline CSF pressure (r = 0.136, p = 0.115, N = 135) or age (-0.02, p = 0.803, N = 135).

Conclusions: The average CSF formation rate in INPH was not decreased compared to the healthy reference cohort, which does not support reduced CSF turnover. This emphasizes the need to further investigate the source and routes of the flow in the glymphatic system and the cause of the suggested impaired glymphatic clearance in INPH.