Pulsatile hemodynamics are associated with brain small perivascular spaces (SPVS). It is unknown whether the stiffness of intermediary arteries connecting the aorta and brain modifies this ...association. Participants from the Northern Manhattan Study were assessed for SPVS (defined as ≤3 mm T1 voids) and white matter hyperintensity volume (WMH) using MRI. Middle (MCA) and anterior cerebral arterial (ACA) diameters (measured on time-of-flight MRA) and CCA strain (assessed by ultrasound) were used as surrogates of stiffness. Brachial and aortic pulse pressure (PP) and aortic augmentation index (Aix, assessed by applanation tonometry) were used as markers of pulsatility. We tested whether stiffness in intermediary arteries modifies the association between extracranial pulsatility with SPVS and WMH. We found that among 941 participants (mean age 71 ± 9 years, 60% women, 66% Hispanic), the right MCA/ACA diameter was associated with right anterior SPVS (B = 0.177, P = 0.002). Brachial PP was associated with right anterior SPVS (B = 0.003, P = 0.02), and the effect size was bigger with right MCA/ACA diameter in the upper tertile (P = 0.001 for the interaction). The association between right CCA strain and ipsilateral SPVS was modified by MCA/ACA diameter, with the largest effect size in those with ipsilateral MCA/ACA diameter in the upper tertile (P = 0.001 for the interaction). Similar dose-effects and statistical interactions were replicated using aortic AIx or aortic PP. We found no evidence of effect modification between pulsatile measures and WMH by stiffness measures. In summary, pulsatile hemodynamics relate to brain SPVS, and the association is the strongest among individuals with dilated brain arteries.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Abstract
BACKGROUND:
It has been well documented that, along with tonsillar herniation, Chiari Malformation Type I (CMI) is associated with smaller posterior cranial fossa (PCF) and altered ...cerebrospinal fluid (CSF) flow and tissue motion in the craniocervical junction.
OBJECTIVE:
This study assesses the relationship between PCF volumetry and CSF and tissue dynamics toward a combined imaging-based morphological-physiological characterization of CMI. Multivariate analysis is used to identify the subset of parameters that best discriminates CMI from a healthy cohort.
METHODS:
Eleven length and volumetric measures of PCF, including crowdedness and 4th ventricle volume, 4 measures of CSF and cord motion in the craniocervical junction, and 5 global intracranial measures, including intracranial compliance and pressure, were measured by magnetic resonance imaging (MRI) in 36 symptomatic CMI subjects (28 female, 37 ± 11 years) and 37 control subjects (24 female, 36 ± 12 years). The CMI group was further divided based on symptomatology into “typical” and “atypical” subgroups.
RESULTS:
Ten of the 20 morphologic and physiologic measures were significantly different between the CMI and the control cohorts. These parameters also had less variability and stronger significance in the typical CMI compared with the atypical. The measures with the most significance were clival and supraocciput lengths, PCF crowdedness, normalized PCF volume, 4th ventricle volume, maximal cord displacement (P < .001), and MR measure of intracranial pressure (P = .007). Multivariate testing identified cord displacement, PCF crowdedness, and normalized PCF as the strongest discriminator subset between CMI and controls. MR measure of intracranial pressure was higher in the typical CMI cohort compared with the atypical.
CONCLUSION:
The identified 10 complementing morphological and physiological measures provide a more complete and symptomatology-relevant characterization of CMI than tonsillar herniation alone.
Neurofluids is a term introduced to define all fluids in the brain and spine such as blood, cerebrospinal fluid, and interstitial fluid. Neuroscientists in the past millennium have steadily ...identified the several different fluid environments in the brain and spine that interact in a synchronized harmonious manner to assure a healthy microenvironment required for optimal neuroglial function. Neuroanatomists and biochemists have provided an incredible wealth of evidence revealing the anatomy of perivascular spaces, meninges and glia and their role in drainage of neuronal waste products. Human studies have been limited due to the restricted availability of noninvasive imaging modalities that can provide a high spatiotemporal depiction of the brain neurofluids. Therefore, animal studies have been key in advancing our knowledge of the temporal and spatial dynamics of fluids, for example, by injecting tracers with different molecular weights. Such studies have sparked interest to identify possible disruptions to neurofluids dynamics in human diseases such as small vessel disease, cerebral amyloid angiopathy, and dementia. However, key differences between rodent and human physiology should be considered when extrapolating these findings to understand the human brain. An increasing armamentarium of noninvasive MRI techniques is being built to identify markers of altered drainage pathways. During the three‐day workshop organized by the International Society of Magnetic Resonance in Medicine that was held in Rome in September 2022, several of these concepts were discussed by a distinguished international faculty to lay the basis of what is known and where we still lack evidence. We envision that in the next decade, MRI will allow imaging of the physiology of neurofluid dynamics and drainage pathways in the human brain to identify true pathological processes underlying disease and to discover new avenues for early diagnoses and treatments including drug delivery.
Evidence level: 1
Technical Efficacy: Stage 3
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Summary
Poor sleep quality is a known risk factor for Alzheimer’s disease. This longitudinal imaging study aimed to determine the acceleration in the rates of tissue loss in cognitively critical ...brain regions due to poor sleep in healthy elderly individuals. Cognitively‐normal healthy individuals, aged ≥60 years, reported Pittsburgh Sleep Quality Index (PSQI) and underwent baseline and 2‐year follow‐up magnetic resonance imaging brain scans. The links between self‐reported sleep quality, rates of tissue loss in cognitively‐critical brain regions, and white matter hyperintensity load were assessed. A total of 48 subjects were classified into normal (n = 23; PSQI score <5) and poor sleepers (n = 25; PSQI score ≥5). The two groups were not significantly different in terms of age, gender, years of education, ethnicity, handedness, body mass index, and cognitive performance. Compared to normal sleepers, poor sleepers exhibited much faster rates of volume loss, over threefold in the right hippocampus and fivefold in the right posterior cingulate over 2 years. In contrast, there were no significant differences in the rates of volume loss in the cerebral and cerebellar grey and white matter between the two groups. Rates of volume loss in the right posterior cingulate were negatively associated with global PSQI scores. Poor sleep significantly accelerates volume loss in the right hippocampus and the right posterior cingulate cortex. These findings demonstrate that self‐reported sleep quality explains inter‐individual differences in the rates of volume loss in cognitively‐critical brain regions in healthy older adults and provide a strong impetus to offer sleep interventions to cognitively normal older adults who are poor sleepers.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Purpose
To add the hydrostatic component of the cerebrospinal fluid (CSF) pressure to magnetic resonance imaging (MRI)‐derived intracranial pressure (ICP) measurements in the upright posture for ...derivation of pressure value in a central cranial location often used in invasive ICP measurements.
Materials and Methods
Additional analyses were performed using data previously collected from 10 healthy subjects scanned in supine and sitting positions with a 0.5T vertical gap MRI scanner (GE Medical). Pulsatile blood and CSF flows to and from the brain were quantified using cine phase‐contrast. Intracranial compliance and pressure were calculated using a previously described method. The vertical distance between the location of the CSF flow measurement and a central cranial location was measured manually in the mid‐sagittal T1‐weighted image obtained in the upright posture. The hydrostatic pressure gradient of a CSF column with similar height was then added to the MR‐ICP value.
Results
After adjustment for the hydrostatic component, the mean ICP value was reduced by 7.6 mmHg. Mean ICP referenced to the central cranial level was −3.4 ± 1.7 mmHg compared to the unadjusted value of +4.3 ± 1.8 mmHg.
Conclusion
In the upright posture, the hydrostatic pressure component needs to be added to the MRI‐derived ICP values for compatibility with invasive ICP at a central cranial location. J. Magn. Reson. Imaging 2015;42:1158–1163.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Background
Sleep quality decreases in normal aging and is manifested in neurodegenerative diseases including Alzheimer’s disease (AD). Hippocampus is a critical structure for brain health and plays a ...major role in memory. Although recent studies have demonstrated that reduced hippocampal volume is associated with poor sleep quality, the relationship between sleep quality and volumes of hippocampal subfields (HSs) remains unknown. The objective of this study is to investigate associations between self‐reported sleep quality measures and HS volumes in cognitively normal elderly individuals.
Method
Sixty‐seven cognitively normal elderly individuals aged 60 to 83 years with self‐reported Pittsburgh Sleep Quality Index (PSQI) were classified into two groups: 30 normal sleepers with PSQI < 5 and 37 poor sleepers with PSQI ≥5. The two groups were equivalent in terms of age, gender, ethnicity, education, handedness and cognitive performance. HSs were segmented in very high resolution T2‐weighted MRI sequence (with an in‐plane resolution of 0.4×0.4 mm2 and 2 mm slice thickness) using the automatic segmentation of hippocampal subfields (ASHS) tool. The HS Volumes were normalized with respect to intracranial volumes. We compared HS volumes between subjects with normal and poor sleep quality. Furthermore, we evaluated associations between the HS volumes and different sleep quality measures, and between the HS volumes and performance of different cognitive tests.
Result
Compared to normal sleepers, poor sleepers exhibited lower normalized volumes in the left cornu ammonis field 1 (CA1) (p=0.020), dentate gyrus (DG) (p=0.008) and subiculum (p=0.018). Global PSQI was significantly and negatively associated with the normalized volumes of the left CA1 (r=‐0.266), left DG (r=‐0.295) and left subiculum (r=‐0.276). Sleep duration was significantly associated with normalized volumes of the bilateral CA1 (left: r=0.428, right: r=0.438), DG (left: r=0.381, right: r=0.367), left CA2 (r=0.231) and subiculum (r=0.219). Verbal memory scores were associated with the normalized volumes of left CA1 (r=0.382).
Conclusion
We found association between poor sleep quality and volume decreases in multiple HSs. Improving overall sleep quality, especially sleep duration, could prevent or slow volume loss of the HSs, which are associated with cognitive decline and onset of mild cognitive impairment (MCI) and AD.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Background
Poor sleep quality is a known risk factor for the development of Alzheimer’s disease (AD). However, minimal data is available on the rate of brain tissue volume loss related to ...self‐reported poor sleep. Our previous cross‐sectional study in cognitively normal elderly adults age 60 and over, demonstrated that poor sleepers exhibited significantly smaller volumes, approximately 7%, in the bilateral hippocampi, superior parietal lobules and left amygdala and smaller cortical thicknesses, over 3%, in the right superior frontal, medial orbitofrontal cortices and frontal pole, compared to normal sleepers (Alperin et al, 2019). Current study is a follow‐up longitudinal investigation comparing rates of tissue loss in these brain regions of interest (ROIs) between elderly good and poor sleepers with normal cognition.
Method
Forty‐eight cognitively normal elderly individuals age 60 to 92 years were classified into two groups: 23 normal sleepers with self‐reported Pittsburgh Sleep Quality Index (PSQI) < 5 and 25 poor sleepers with PSQI ≥ 5. The two groups were equivalent in terms of age, gender, years of education and white matter hyperintensity (WMH) load. The volumes and thickness of the ROIs were measured at baseline and at follow‐up scans to assess rates of tissue loss using FreeSurfer software. Rates of tissue loss over 2 years were compared between two groups.
Result
No significant association was found between sleep quality, WMH load and rates of thickness loss. Compared to normal sleepers, poor sleepers exhibited 2.8 times higher rates of volume loss in the hippocampus, and 3.3 times higher rate in the posterior cingulate. Global PSQI at baseline was significantly and negatively associated with rates of volume loss in the right hippocampus (rs=‐0.33) and right posterior cingulate cortex (rs=‐0.47). Scores in verbal memory was negatively associated with rates of volume loss in the right hippocampus (r≥0.388).
Conclusion
Poor sleep quality is associated with significantly accelerated volume loss in the hippocampus and the posterior cingulate cortex in cognitively normal elderly individuals. Intervention for improving sleep quality should be highly considered in cognitively normal elderly adults to delay onset of cognitive impairment and onset of AD.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Purpose
To quantify the acute effect of the head‐down tilt (HDT) posture on intracranial hemodynamics and hydrodynamics.
Materials and Methods
We evaluated the intracranial physiological parameters, ...blood flow‐related parameters, and brain morphology in the HDT (–6° and –12°) and the horizontal supine (HS) positions. Seven and 15 healthy subjects were scanned for each position using 3.0 T magnetic resonance imaging system. The peak‐to‐peak intracranial volume change, the peak‐to‐peak cerebrospinal fluid (CSF) pressure gradient (PGp‐p), and the intracranial compliance index were calculated from the blood and CSF flow determined using a cine phase‐contrast technique. The brain volumetry was conducted using SPM12. The measurements were compared using the Wilcoxon signed‐rank test or a paired t‐test.
Results
No measurements changed in the –6° HDT. The PGp‐p and venous outflow of the internal jugular veins (IJVs) in the –12° HDT were significantly increased compared to the HS (P < 0.001 and P = 0.025, respectively). The cross‐sectional areas of the IJVs were significantly larger (P < 0.001), and the maximum, minimum, and mean blood flow velocity of the IJVs were significantly decreased (P = 0.003, < 0.001, and = 0.001, respectively) in the –12° HDT. The mean blood flow velocities of the internal carotid arteries were decreased (P = 0.023). Neither position affected the brain volume.
Conclusion
Pressure gradient and venous outflow were increased in accordance with the elevation of the intracranial pressure as an acute effect of the HDT. However, the CSF was not constantly shifted from the spinal canal to the cranium.
Level of Evidence: 2
Technical Efficacy: Stage 1
J. Magn. Reson. Imaging 2018;47:565–571.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Cervical blood and cerebrospinal fluid (CSF) flow rates can be quantified with Phase-contrast (PC) MRI, which is routinely used for clinical studies. Previous MRI studies showed that venous and CSF ...flow alterations are linked to various pathological conditions. Since it is well known that, besides the heart beating, the thoracic pump influences the blood and CSF dynamics, we studied the effect of different respiration modes on blood and CSF flow rates using a real-time (RT)-PC prototype.
Thirty healthy volunteers were examined with a 3 T scanner. A RT-PC sequence was acquired at the first cervical level to quantify the flow rates of internal carotid arteries, internal jugular veins (IJVs) and CSF. Each RT-PC acquisition was repeated three times, while the subjects were asked to breathe in three different ways for 60 s each: freely (F), with a constant rate (PN) and with deep and constant respiration rate (PD). The average flow rates were computed, they were removed from the respective signals and integrated in the inspiratory and expiratory phases (differential volumes). Finally, the power spectral density was computed for each detrended flow rate. High- and very-high frequency peaks were identified on the spectra while their frequencies were compared to the respiratory and cardiac frequencies estimated using a thoracic belt and a pulse oximeter. The area under the spectra was computed in four 0.5 Hz-wide ranges, centered on the high-frequency peak, on very-high frequency peak and its 2nd and 3rd harmonics, and then they were normalized by the flow rate variance. The effect of breathing patterns on average flow rates, on systolic and diastolic peaks, and on the normalized power was tested. Finally, the differential volumes of inspiration were compared to those of expiration.
The frequencies of the high- and very-high spectral peaks corresponded to the respiratory and cardiac frequencies. The average flow rate progressively decreased from F to PN to PD breathing, and the cardiac modulations were less predominant especially for the IJVs. The respiratory modulation increased with PD breathing. The average volumes displaced in the inspiratory phases were not significantly different from those of the expiratory one.
The spectral analyses demonstrated higher respiratory modulations in PD compared to free breathing, even prevailing the cardiac modulation in the IJVs, showing an increment of the thoracic pump affecting the flow rate shape.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Objective
The study was undertaken to determine whether normobaric hypoxia causes elevated brain volume and intracranial pressure in individuals with symptoms consistent with acute mountain sickness ...(AMS).
Methods
Thirteen males age = (26 (sd 6)) years were exposed to normobaric hypoxia (12% O2) and normoxia (21% O2). After 2 and 10 hours, AMS symptoms were assessed alongside ventricular and venous vessel volumes, cerebral blood flow, regional brain volumes, and intracranial pressure, using high‐resolution magnetic resonance imaging.
Results
In normoxia, neither lateral ventricular volume (R2 = 0.07, p = 0.40) nor predominance of unilateral transverse venous sinus drainage (R2 = 0.07, p = 0.45) was related to AMS symptoms. Furthermore, despite an increase in cerebral blood flow after 2 hours of hypoxia (hypoxia vs normoxia: Δ148ml/min−1, 95% confidence interval CI = 58 to 238), by 10 hours, when AMS symptoms had developed, cerebral blood flow was normal (Δ−51ml/min−1, 95% CI = −141 to 39). Conversely, at 10 hours brain volume was increased (Δ59ml, 95% CI = 8 to 110), predominantly due to an increase in gray matter volume (Δ73ml, 95% CI = 25 to 120). Therefore, cerebral spinal fluid volume was decreased (Δ−40ml, 95% CI = −67 to −14). The intracranial pressure response to hypoxia varied between individuals, and as hypothesized, the most AMS‐symptomatic participants had the largest increases in intracranial pressure (AMS present, Δ7mmHg, 95% CI = −2.5 to 17.3; AMS not present, Δ−1mmHg, 95% CI = −3.3 to 0.5). Consequently, there was a significant relationship between the change in intracranial pressure and AMS symptom severity (R2 = 0.71, p = 0.002).
Interpretation
The data provide the strongest evidence to date to support the hypothesis that the “random” nature of AMS symptomology is explained by a variable intracranial pressure response to hypoxia. ANN NEUROL 2014;75:890–898
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
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