A Review of Translational Magnetic Resonance Imaging in Human and Rodent Experimental Models of Small Vessel Disease

Nanomaterial technologies for precision diagnosis and treatment of brain hemorrhage

Brain hemorrhage events present complex clinical challenges due to their rapid progression and the intricate interplay of oxidative stress, inflammation, and neuronal damage. Traditional diagnostic and therapeutic approaches often struggle to meet the demands for timely and effective intervention. This review explores the cutting-edge role of nanomaterials in transforming cerebral hemorrhage management, focusing on both diagnostic and therapeutic advancements. Nanomaterial-enabled imaging techniques, such as optical imaging, magnetic resonance imaging, and magnetic particle imaging, significantly enhance the accuracy of hemorrhage detection by providing real-time, high-resolution assessments of blood-brain barrier (BBB) integrity, cerebral perfusion, and hemorrhage progression, which is critical for guiding intervention strategies. On the therapeutic front, nanomaterial-based systems enable the precise delivery of drugs and bioactive molecules, fostering neural repair and functional recovery while minimizing systemic side effects. Furthermore, multifunctional nanomaterials not only address the primary injury but also offer precise control over secondary injuries, such as edema and oxidative stress. Their ability to enhance neuroprotection, prevent re-bleeding, and stimulate brain tissue regeneration provides a holistic approach and marks a significant advancement in brain hemorrhage therapy. As the field continues to advance, nanotechnology is set to fundamentally reshape the clinical management and long-term outcomes of brain hemorrhages, presenting a paradigm shift towards personalized and highly effective neurological care.

Cerebral small vessel disease: The impact of glymphopathy and sleep disorders

The glymphatic system, a vital brain perivascular network for waste clearance, hinges on the functionality of the aquaporin 4 (AQP4) water channel. Alarmingly, AQP4 single nucleotide polymorphisms (SNPs) are linked to impaired glymphatic clearance, or glymphopathy, which contributes to sleep disturbances and various age-related neurodegenerative diseases. Despite the critical role of glymphopathy and sleep disturbances in cerebral small vessel disease (CSVD) - a silent precursor to age-related neurodegenerative disorders - their interplay remains underexplored. CSVD is a major cause of stroke and dementia, yet its pathogenesis is not fully understood. Emerging evidence implicates glymphopathy and sleep disorders as pivotal factors in age-related CSVD, exacerbating the condition by hindering waste removal and compromising blood-brain barrier (BBB) integrity. Advanced imaging techniques promise to enhance diagnosis and monitoring, while lifestyle modifications and personalised medicine present promising treatment avenues. This narrative review underscores the need for a multidisciplinary approach to understanding glymphopathy and sleep disorders in CSVD. By exploring their roles, emphasising the necessity for longitudinal studies, and discussing potential therapeutic interventions, this paper aims to pave the way for new research and therapeutic directions in CSVD management.

Cerebrovascular Function in Sporadic and Genetic Cerebral Small Vessel Disease

OBJECTIVE

Cerebral small vessel diseases (SVDs) are associated with cerebrovascular dysfunction, such as increased blood-brain barrier leakage (permeability surface area product), vascular pulsatility, and decreased cerebrovascular reactivity (CVR). No studies assessed all 3 functions concurrently. We assessed 3 key vascular functions in sporadic and genetic SVD to determine associations with SVD severity, subtype, and interrelations.

METHODS

In this prospective, cross-sectional, multicenter INVESTIGATE-SVDs study, we acquired brain magnetic resonance imaging in patients with sporadic SVD/cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL), including structural, quantitative microstructural, permeability surface area product, blood plasma volume fraction, vascular pulsatility, and CVR (in response to CO2) scans. We determined vascular function and white matter hyperintensity (WMH) associations, using covariate-adjusted linear regression; normal-appearing white matter and WMH differences, interrelationships between vascular functions, using linear mixed models; and major sources of variance using principal component analyses.

RESULTS

We recruited 77 patients (45 sporadic/32 CADASIL) at 3 sites. In adjusted analyses, patients with worse WMH had lower CVR (B = -1.78, 95% CI -3.30, -0.27) and blood plasma volume fraction (B = -0.594, 95% CI -0.987, -0.202). CVR was worse in WMH than normal-appearing white matter (eg, CVR: B = -0.048, 95% CI -0.079, -0.017). Adjusting for WMH severity, SVD subtype had minimal influence on vascular function (eg, CVR in CADASIL vs sporadic: B = 0.0169, 95% CI -0.0247, 0.0584). Different vascular function mechanisms were not generally interrelated (eg, permeability surface area product~CVR: B = -0.85, 95% CI -4.72, 3.02). Principal component analyses identified WMH volume/quantitative microstructural metrics explained most variance in CADASIL and arterial pulsatility in sporadic SVD, but similar main variance sources.

INTERPRETATION

Vascular function was worse with higher WMH, and in WMH than normal-appearing white matter. Sporadic SVD-CADASIL differences largely reflect disease severity. Limited vascular function interrelations may suggest disease stage-specific differences. ANN NEUROL 2025;97:483-498.

Dynamic retinal vessel analysis: flickering a light into the brain

Introduction

Growing aging populations pose new challenges to public health as the number of people living with dementia grows in tandem. To alleviate the burden of dementia, prodromal signs of cognitive impairment must be recognized and risk factors reduced. In this context, non-invasive techniques may be used to identify early changes and monitor disease progression. Dynamic retinal vessel analysis (DVA) provides an opportunity to measure retinal vasoreactivity in a way that may be comparable to cerebral vasoreactivity, thus providing a window to the brain.

Methods

We conducted a literature search on PubMed and Scopus to identify studies utilizing DVA to describe retinal vasoreactivity in central nervous system diseases and compare it with brain function and structure. We included original papers with full text in English.

Results

We identified 11 studies, of which most employed a cross-sectional design (91%). Studies on cerebrovascular diseases reported that retinal vasoreactivity decreased in patient populations compared with that of healthy controls. Studies on cognitive impairment and dementia yielded mixed results, at least in part due to high population heterogeneity. There is also evidence for the association between DVA and brain and cognition parameters such as cerebral blood flow velocity, cerebral microvascular diffusivity, and cognitive function score.

Discussion

The reviewed papers on DVA and brain function, despite the mixed results, have demonstrated the relationship between retinal vasoreactivity and cerebrovascular function and cognition. Heterogeneity in study populations, procedures, and analyses make comparisons difficult. Studies with larger sample size, clear description of the population and methods, and standardized DVA analysis are needed to elucidate the eye-brain connection and to enhance the translational and clinical applications of DVA.

Deep learning applied to the segmentation of rodent brain MRI data outperforms noisy ground truth on full-fledged brain atlases

Translational magnetic resonance imaging of the rodent brain provides invaluable information for preclinical drug development. However, the automated segmentation of such images for quantitative analyses is limited compared to human brain imaging mainly due to the inferior anatomical contrast and the resulting less advanced registration and atlasing tools. Here, we investigated the potential of deep learning models for the segmentation of magnetic resonance images of rat brains into an entire set of multiple regions of interest (rather than individual loci), focusing on the development of a robust method that accommodates changes in the input based on differences in animal strain (genotype) and size. Manually generated labels are expensive, so we tested the ability of neural networks to learn brain structures from noisy but inexpensive registration-based labels, allowing very large datasets to be leveraged for training. We compared three distinct model architectures (U-Net, Attention-U-Net and DeepLab) by training them on a dataset of >10,000 magnetic resonance images of rat brains and found that each model was able to segment the entire brain into predefined sets of 29 and 58 regions, respectively, with the Attention U-Net achieving the best performance. The models canceled out unstructured label noise in the imperfect training data to provide smoother and more symmetric segmentations than registration-based labeling, and were more robust when presented with input variations, thus outperforming the noisy ground truth. Our pipeline also includes uncertainty estimation and an explainability mechanism, hence providing features essential for anomaly detection and quality assurance. In summary, our study shows that deep learning models do achieve accurate brain segmentation in high-throughput quantitative preclinical imaging without the need for expensive expert-generated labels.

A multi-disciplinary commentary on preclinical research to investigate vascular contributions to dementia

Although dementia research has been dominated by Alzheimer's disease (AD), most dementia in older people is now recognised to be due to mixed pathologies, usually combining vascular and AD brain pathology. Vascular cognitive impairment (VCI), which encompasses vascular dementia (VaD) is the second most common type of dementia. Models of VCI have been delayed by limited understanding of the underlying aetiology and pathogenesis. This review by a multidisciplinary, diverse (in terms of sex, geography and career stage), cross-institute team provides a perspective on limitations to current VCI models and recommendations for improving translation and reproducibility. We discuss reproducibility, clinical features of VCI and corresponding assessments in models, human pathology, bioinformatics approaches, and data sharing. We offer recommendations for future research, particularly focusing on small vessel disease as a main underpinning disorder.

Glymphatic pathway in sporadic cerebral small vessel diseases: From bench to bedside

Cerebral small vessel diseases (CSVD) consist of a group of diseases with high heterogeneity induced by pathologies of intracranial small blood vessels. Endothelium dysfunction, bloodbrain barrier leakage and the inflammatory response are traditionally considered to participate in the pathogenesis of CSVD. However, these features cannot fully explain the complex syndrome and related neuroimaging characteristics. In recent years, the glymphatic pathway has been discovered to play a pivotal role in clearing perivascular fluid and metabolic solutes, which has provided novel insights into neurological disorders. Researchers have also explored the potential role of perivascular clearance dysfunction in CSVD. In this review, we presented a brief overview of CSVD and the glymphatic pathway. In addition, we elucidated CSVD pathogenesis from the perspective of glymphatic failure, including basic animal models and clinical neuroimaging markers. Finally, we proposed forthcoming clinical applications targeting the glymphatic pathway, hoping to provide novel ideas on promising therapies and preventions of CSVD.

Empowering drug development: Leveraging insights from imaging technologies to enable the advancement of digital health technologies

The US Food and Drug Administration (FDA) has publicly recognized the importance of improving drug development efficiency, deeming translational biomarkers a top priority. The use of imaging biomarkers has been associated with increased rates of drug approvals. An appropriate level of validation provides a pragmatic way to choose and implement these biomarkers. Standardizing imaging modality selection, data acquisition protocols, and image analysis (in ways that are agnostic to equipment and algorithms) have been key to imaging biomarker deployment. The best known examples come from studies done via precompetitive collaboration efforts, which enable input from multiple stakeholders and data sharing. Digital health technologies (DHTs) provide an opportunity to measure meaningful aspects of patient health, including patient function, for extended periods of time outside of the hospital walls, with objective, sensor-based measures. We identified the areas where learnings from the imaging biomarker field can accelerate the adoption and widespread use of DHTs to develop novel treatments. As with imaging, technical validation parameters and performance acceptance thresholds need to be established. Approaches amenable to multiple hardware options and data processing algorithms can be enabled by sharing DHT data and by cross-validating algorithms. Data standardization and creation of shared databases will be vital. Pre-competitive consortia (public-private partnerships and professional societies that bring together all stakeholders, including patient organizations, industry, academic experts, and regulators) will advance the regulatory maturity of DHTs in clinical trials.

Characterization of perivascular space pathology in a rat model of cerebral small vessel disease by in vivo magnetic resonance imaging

One of the most common causes of dementia is cerebral small vessel disease (SVD), which is associated with enlarged perivascular spaces (PVS). Clinically, PVS are visible as hyperintensities on T2-weighted (T2w) magnetic resonance images (MRI). While rodent SVD models exhibit arteriolosclerosis, PVS have not been robustly documented by MRI casting doubts on their clinical relevance. Here we established that the severity of SVD in spontaneously hypertensive stroke prone (SHRSP) rats correlated to 'moderate' SVD in human post-mortem tissue. We then developed two approaches for detecting PVS in SHRSP rats: 1) T2w imaging and 2) T1-weighted imaging with administration of gadoteric acid into cerebrospinal fluid. We applied the two protocols to six Wistar-Kyoto (WKY) control rats and thirteen SHRSP rats at ∼12 month of age. The primary endpoint was the number of hyperintense lesions. We found more hyperintensities on T2w MRI in the SHRSP compared to WKY rats (p-value = 0.023). CSF enhancement with gadoteric acid increased the visibility of PVS-like lesions in SHRSP rats. In some of the SHRSP rats, the MRI hyperintensities corresponded to enlarged PVS on histopathology. The finding of PVS-like hyperintensities on T2w MRI support the SHRSP rat's clinical relevance for studying the underlying pathophysiology of SVD.

Loss of the heterogeneous expression of flippase ATP11B leads to cerebral small vessel disease in a normotensive rat model

Cerebral small vessel disease (SVD) is the leading cause of vascular dementia, causes a quarter of strokes, and worsens stroke outcomes. The disease is characterised by patchy cerebral small vessel and white matter pathology, but the underlying mechanisms are poorly understood. This microvascular and tissue damage has been classically considered secondary to extrinsic factors, such as hypertension, but this fails to explain the patchy nature of the disease, the link to endothelial cell (EC) dysfunction even when hypertension is absent, and the increasing evidence of high heritability to SVD-related brain damage. We have previously shown the link between deletion of the phospholipase flippase Atp11b and EC dysfunction in an inbred hypertensive rat model with SVD-like pathology and a single nucleotide polymorphism (SNP) in ATP11B associated with human sporadic SVD. Here, we generated a novel normotensive transgenic rat model, where Atp11b is deleted, and show pathological, imaging and behavioural changes typical of those in human SVD, but that occur without hypertension. Atp11bKO rat brain and retinal small vessels show ECs with molecular and morphological changes of dysfunction, with myelin disruption in a patchy pattern around some but not all brain small vessels, similar to the human brain. We show that ATP11B/ATP11B is heterogeneously expressed in ECs in normal rat and human brain even in the same transverse section of the same blood vessel, suggesting variable effects of the loss of ATP11B on each vessel and an explanation for the patchy nature of the disease. This work highlights a link between inherent EC dysfunction and vulnerability to SVD white matter damage with a marked heterogeneity of ECs in vivo which modulates this response, occurring even in the absence of hypertension. These findings refocus our strategies for therapeutics away from antihypertensive (and vascular risk factor) control alone and towards ECs in the effort to provide alternative targets to prevent a major cause of stroke and dementia.

Cerebral Vascular Dysfunctions Detected in Human Small Vessel Disease and Implications for Preclinical Studies

Cerebral small vessel disease (SVD) is highly prevalent and a common cause of ischemic and hemorrhagic stroke and dementia, yet the pathophysiology is poorly understood. Its clinical expression is highly varied, and prognostic implications are frequently overlooked in clinics; thus, treatment is currently confined to vascular risk factor management. Traditionally, SVD is considered the small vessel equivalent of large artery stroke (occlusion, rupture), but data emerging from human neuroimaging and genetic studies refute this, instead showing microvessel endothelial dysfunction impacting on cell-cell interactions and leading to brain damage. These dysfunctions reflect defects that appear to be inherited and secondary to environmental exposures, including vascular risk factors. Interrogation in preclinical models shows consistent and converging molecular and cellular interactions across the endothelial-glial-neural unit that increasingly explain the human macroscopic observations and identify common patterns of pathology despite different triggers. Importantly, these insights may offer new targets for therapeutic intervention focused on restoring endothelial-glial physiology.

Characterizing the Neuroimaging and Histopathological Correlates of Cerebral Small Vessel Disease in Spontaneously Hypertensive Stroke-Prone Rats

Introduction: Spontaneously hypertensive stroke-prone rats (SHRSP) are used to model clinically relevant aspects of human cerebral small vessel disease (CSVD). To decipher and understand the underlying disease dynamics, assessment of the temporal progression of CSVD histopathological and neuroimaging correlates is essential. Materials and Methods: Eighty age-matched male SHRSP and control Wistar Kyoto rats (WKY) were randomly divided into four groups that were aged until 7, 16, 24 and 32 weeks. Sensorimotor testing was performed weekly. Brain MRI was acquired at each study time point followed by histological analyses of the brain. Results: Compared to WKY controls, the SHRSP showed significantly higher prevalence of small subcortical hyperintensities on T2w imaging that progressed in size and frequency with aging. Volumetric analysis revealed smaller intracranial and white matter volumes on brain MRI in SHRSP compared to age-matched WKY. Diffusion tensor imaging (DTI) showed significantly higher mean diffusivity in the corpus callosum and external capsule in WKY compared to SHRSP. The SHRSP displayed signs of motor restlessness compared to WKY represented by hyperactivity in sensorimotor testing at the beginning of the experiment which decreased with age. Distinct pathological hallmarks of CSVD, such as enlarged perivascular spaces, microbleeds/red blood cell extravasation, hemosiderin deposits, and lipohyalinosis/vascular wall thickening progressively accumulated with age in SHRSP. Conclusions: Four stages of CSVD severity in SHRSP are described at the study time points. In addition, we find that quantitative analyses of brain MRI enable identification of in vivo markers of CSVD that can serve as endpoints for interventional testing in therapeutic studies.

Extracerebral microvascular dysfunction is related to brain MRI markers of cerebral small vessel disease: The Maastricht Study

BACKGROUND

Cerebral small vessel disease (cSVD) is a late consequence of cerebral microvascular dysfunction (MVD). MVD is hard to measure in the brain due to its limited accessibility. Extracerebral MVD (eMVD) measures can give insights in the etiology of cerebral MVD, as MVD may be a systemic process. We aim to investigate whether a compound score consisting of several eMVD measures is associated with structural cSVD MRI markers.

METHODS

Cross-sectional data of the population-based Maastricht Study was used (n = 1872, mean age 59 ± 8 years, 49% women). Measures of eMVD included flicker light-induced retinal arteriolar and venular dilation response (retina), albuminuria and glomerular filtration rate (kidney), heat-induced skin hyperemia (skin), and plasma biomarkers of endothelial dysfunction (sICAM-1, sVCAM-1, sE-selectin, and von Willebrand factor). These measures were standardized into z scores and summarized into a compound score. Linear and logistic regression analyses were used to investigate the associations between the compound score and white matter hyperintensity (WMH) volume, and the presence of lacunes and microbleeds, as measured by brain MRI.

RESULTS

The eMVD compound score was associated with WMH volume independent of age, sex, and cardiovascular risk factors (St β 0.057 [95% CI 0.010-0.081], p value 0.01), but not with the presence of lacunes (OR 1.011 [95% CI 0.803-1.273], p value 0.92) or microbleeds (OR 1.055 [95% CI 0.896-1.242], p value 0.52).

CONCLUSION

A compound score of eMVD is associated with WMH volume. Further research is needed to expand the knowledge about the role of systemic MVD in the pathophysiology of cSVD.

Air Pollution Particulate Matter Amplifies White Matter Vascular Pathology and Demyelination Caused by Hypoperfusion

Cerebrovascular pathologies are commonly associated with dementia. Because air pollution increases arterial disease in humans and rodent models, we hypothesized that air pollution would also contribute to brain vascular dysfunction. We examined the effects of exposing mice to nanoparticulate matter (nPM; aerodynamic diameter ≤200 nm) from urban traffic and interactions with cerebral hypoperfusion. C57BL/6 mice were exposed to filtered air or nPM with and without bilateral carotid artery stenosis (BCAS) and analyzed by multiparametric MRI and histochemistry. Exposure to nPM alone did not alter regional cerebral blood flow (CBF) or blood brain barrier (BBB) integrity. However, nPM worsened the white matter hypoperfusion (decreased CBF on DSC-MRI) and exacerbated the BBB permeability (extravascular IgG deposits) resulting from BCAS. White matter MRI diffusion metrics were abnormal in mice subjected to cerebral hypoperfusion and worsened by combined nPM+BCAS. Axonal density was reduced equally in the BCAS cohorts regardless of nPM status, whereas nPM exposure caused demyelination in the white matter with or without cerebral hypoperfusion. In summary, air pollution nPM exacerbates cerebrovascular pathology and demyelination in the setting of cerebral hypoperfusion, suggesting that air pollution exposure can augment underlying cerebrovascular contributions to cognitive loss and dementia in susceptible elderly populations.

Microvessel stenosis, enlarged perivascular spaces, and fibrinogen deposition are associated with ischemic periventricular white matter hyperintensities

Periventricular white matter hyperintensities (pvWMH) are neuroimaging abnormalities surrounding the lateral ventricles that are apparent on magnetic resonance imaging (MRI). They are associated with age, neurodegenerative disease, and cerebrovascular risk factors. While pvWMH ultimately represent a loss of white matter structural integrity, the pathological causes are heterogeneous in nature, and currently, cannot be distinguished using neuroimaging alone. pvWMH could occur because of a combination of small vessel disease (SVD), ependymal loss, blood–brain barrier dysfunction, and microgliosis. In this study we aimed to characterize microvascular stenosis, fibrinogen extravasation, and microgliosis within pvWMH with and without imaging evidence of periventricular infarction. Using postmortem neuroimaging of human brains (n = 20), we identified pvWMH with and without periventricular infarcts (PVI). We performed histological analysis of microvessel stenosis, perivascular spaces, microgliosis, and immunohistochemistry against fibrinogen as a measure of serum protein extravasation. Herein, we report distinctions between pvWMH with and without periventricular infarcts based on associations with microvessel stenosis, enlarged perivascular spaces, and fibrinogen IHC. Microvessel stenosis was significantly associated with PVI and with cellular deposition of fibrinogen in the white matter. The presence of fibrinogen was associated with PVI and increased number of microglia. These findings suggest that neuroimaging‐based detection of infarction within pvWMH may help distinguish more severe lesions, associated with underlying microvascular disease and BBB dysfunction, from milder pvWMH that are a highly frequent finding on MRI.

Cerebral small vessel disease: A glymphopathy?

Small vessel disease (SVD) is a common instigator of dementia in the aging population. The hallmarks of SVD are enlargement of the perivascular spaces and white matter hyperintensities. The latter represents local fluid accumulation in white matter that either subsides or develops into lacunar infarcts. We here propose that failure of brain fluid transport-via the glymphatic system-plays a key role in initiation and progression of SVD. Our major case for this concept is that perivascular spaces are utilized as waterways for influx of cerebrospinal fluid. Stagnation of glymphatic transport may drive loss of brain fluid homeostasis leading to transient white matter edema, perivascular dilation, and ultimately demyelination. This review will discuss how glymphatic rodent studies of hypertension and diabetes have provided new insight into the pathogenesis of SVD.

A Comparison of CVR Magnitude and Delay Assessed at 1.5 and 3T in Patients With Cerebral Small Vessel Disease

BACKGROUND

Cerebrovascular reactivity (CVR) measures blood flow change in response to a vasoactive stimulus. Impairment is associated with several neurological conditions and can be measured using blood oxygen level-dependent (BOLD) magnetic resonance imaging (MRI). Field strength affects the BOLD signal, but the effect on CVR is unquantified in patient populations.

METHODS

We recruited patients with minor ischemic stroke and assessed CVR magnitude and delay time at 3 and 1.5 Tesla using BOLD MRI during a hypercapnic challenge. We assessed subcortical gray (GM) and white matter (WM) differences using Wilcoxon signed rank tests and scatterplots. Additionally, we explored associations with demographic factors, WM hyperintensity burden, and small vessel disease score.

RESULTS

Eighteen of twenty patients provided usable data. At 3T vs. 1.5T: mean CVR magnitude showed less variance (WM 3T: 0.062 ± 0.018%/mmHg, range 0.035, 0.093; 1.5T: 0.057 ± 0.024%/mmHg, range 0.016, 0.094) but was not systematically higher (Wilcoxon signal rank tests, WM: r = -0.33, confidence interval (CI): -0.013, 0.003, p = 0.167); delay showed similar variance (WM 3T: 40 ± 12 s, range: 12, 56; 1.5T: 31 ± 13 s, range 6, 50) and was shorter in GM (r = 0.33, CI: -2, 9, p = 0.164) and longer in WM (r = -0.59, CI: -16, -2, p = 0.010). Patients with higher disease severity tended to have lower CVR at 1.5 and 3T.

CONCLUSION

Mean CVR magnitude at 3T was similar to 1.5T but showed less variance. GM/WM delay differences may be affected by low signal-to-noise ratio among other factors. Although 3T may reduce variance in CVR magnitude, CVR is readily assessable at 1.5T and reveals comparable associations and trends with disease severity.

Non-Invasive Evaluation of Cerebral Microvasculature Using Pre-Clinical MRI: Principles, Advantages and Limitations

Alterations to the cerebral microcirculation have been recognized to play a crucial role in the development of neurodegenerative disorders. However, the exact role of the microvascular alterations in the pathophysiological mechanisms often remains poorly understood. The early detection of changes in microcirculation and cerebral blood flow (CBF) can be used to get a better understanding of underlying disease mechanisms. This could be an important step towards the development of new treatment approaches. Animal models allow for the study of the disease mechanism at several stages of development, before the onset of clinical symptoms, and the verification with invasive imaging techniques. Specifically, pre-clinical magnetic resonance imaging (MRI) is an important tool for the development and validation of MRI sequences under clinically relevant conditions. This article reviews MRI strategies providing indirect non-invasive measurements of microvascular changes in the rodent brain that can be used for early detection and characterization of neurodegenerative disorders. The perfusion MRI techniques: Dynamic Contrast Enhanced (DCE), Dynamic Susceptibility Contrast Enhanced (DSC) and Arterial Spin Labeling (ASL), will be discussed, followed by less established imaging strategies used to analyze the cerebral microcirculation: Intravoxel Incoherent Motion (IVIM), Vascular Space Occupancy (VASO), Steady-State Susceptibility Contrast (SSC), Vessel size imaging, SAGE-based DSC, Phase Contrast Flow (PC) Quantitative Susceptibility Mapping (QSM) and quantitative Blood-Oxygenation-Level-Dependent (qBOLD). We will emphasize the advantages and limitations of each strategy, in particular on applications for high-field MRI in the rodent's brain.

Cerebrovascular Reactivity Measurement Using Magnetic Resonance Imaging: A Systematic Review

Cerebrovascular reactivity (CVR) magnetic resonance imaging (MRI) probes cerebral haemodynamic changes in response to a vasodilatory stimulus. CVR closely relates to the health of the vasculature and is therefore a key parameter for studying cerebrovascular diseases such as stroke, small vessel disease and dementias. MRI allows in vivo measurement of CVR but several different methods have been presented in the literature, differing in pulse sequence, hardware requirements, stimulus and image processing technique. We systematically reviewed publications measuring CVR using MRI up to June 2020, identifying 235 relevant papers. We summarised the acquisition methods, experimental parameters, hardware and CVR quantification approaches used, clinical populations investigated, and corresponding summary CVR measures. CVR was investigated in many pathologies such as steno-occlusive diseases, dementia and small vessel disease and is generally lower in patients than in healthy controls. Blood oxygen level dependent (BOLD) acquisitions with fixed inspired CO₂ gas or end-tidal CO₂ forcing stimulus are the most commonly used methods. General linear modelling of the MRI signal with end-tidal CO₂ as the regressor is the most frequently used method to compute CVR. Our survey of CVR measurement approaches and applications will help researchers to identify good practice and provide objective information to inform the development of future consensus recommendations.