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Both inflow and the partial volume effect (PVE) are sources of error when measuring the arterial input function (AIF) in dynamic contrast-enhanced (DCE) MRI. This is relevant, as errors in the AIF can propagate into pharmacokinetic parameter estimations from the DCE data. A method was introduced for flow correction by estimating and compensating the number of the perceived pulse of spins during inflow. We hypothesized that the PVE has an impact on concentration-time curves similar to inflow. Therefore, we aimed to study the efficiency of this method to compensate for both effects simultaneously. We first simulated an AIF with different levels of inflow and PVE contamination. The peak, full width at half-maximum (FWHM), and area under curve (AUC) of the reconstructed AIFs were compared with the true (simulated) AIF. In clinical data, the PVE was included in AIFs artificially by averaging the signal in voxels surrounding a manually selected point in an artery. Subsequently, the artificial partial volume AIFs were corrected and compared with the AIF from the selected point. Additionally, corrected AIFs from the internal carotid artery (ICA), the middle cerebral artery (MCA), and the venous output function (VOF) estimated from the superior sagittal sinus (SSS) were compared. As such, we aimed to investigate the effectiveness of the correction method with different levels of inflow and PVE in clinical data. The simulation data demonstrated that the corrected AIFs had only marginal bias in peak value, FWHM, and AUC. Also, the algorithm yielded highly correlated reconstructed curves over increasingly larger neighbourhoods surrounding selected arterial points in clinical data. Furthermore, AIFs measured from the ICA and MCA produced similar peak height and FWHM, whereas a significantly larger peak and lower FWHM was found compared with the VOF. Our findings indicate that the proposed method has high potential to compensate for PVE and inflow simultaneously. The corrected AIFs could thereby provide a stable input source for DCE analysis.
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INTRODUCTION: Cerebral blood flow (CBF) is reduced in cognitively impaired (CI) Alzheimer's disease (AD) patients. We checked the sensitivity of time-encoded arterial spin labeling (te-ASL) in measuring CBF alterations in individuals with positive AD biomarkers and associations with relevant biomarkers in cognitively unimpaired (CU) individuals. METHODS: We compared te-ASL with single-postlabel delay (PLD) ASL in measuring CBF in 59 adults across the AD continuum, classified as CU amyloid beta (Aß) negative (-), CU Aß positive (+), and CI Aß+. We sought associations of CBF with biomarkers of AD, cerebrovascular disease, synaptic dysfunction, neurodegeneration, and cognition in CU participants. RESULTS: te-ASL was more sensitive at detecting CBF reduction in the CU Aß+ and CI Aß+ groups. In CU participants, lower CBF was associated with altered biomarkers of Aß, tau, synaptic dysfunction, and neurodegeneration. DISCUSSION: CBF reduction occurs early in the AD continuum. te-ASL is more sensitive than single-PLD ASL at detecting CBF changes in AD. HIGHLIGHTS: Lower CBF can be detected in CU subjects in the early AD continuum. te-ASL is more sensitive than single-PLD ASL at detecting CBF alterations in AD. CBF is linked to biomarkers of AD, synaptic dysfunction, and neurodegeneration.
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GE-BOLD contrast stands out as the predominant technique in functional MRI experiments for its high sensitivity and straightforward implementation. GE-BOLD exhibits rather similar sensitivity to vessels independent of their size at submillimeter resolution studies like those examining cortical columns and laminae. However, the presence of nonspecific macrovascular contributions poses a challenge to accurately isolate neuronal activity. SE-BOLD increases specificity towards small vessels, thereby enhancing its specificity to neuronal activity, due to the effective suppression of extravascular contributions caused by macrovessels with its refocusing pulse. However, even SE-BOLD measurements may not completely remove these macrovascular contributions. By simulating hemodynamic signals across cortical depth, we gain insights into vascular contributions to the laminar BOLD signal. In this study, we employed four realistic 3D vascular models to simulate oxygen saturation states in various vascular compartments, aiming to characterize both intravascular and extravascular contributions to GE and SE signals, and corresponding BOLD signal changes, across cortical depth at 7T. Simulations suggest that SE-BOLD cannot completely reduce the macrovascular contribution near the pial surface. Simulations also show that both the specificity and signal amplitude of BOLD signals at 7T depend on the spatial arrangement of large vessels throughout cortical depth and on the pial surface.
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The blood-brain barrier (BBB) is a barrier protecting the brain and a milieu of continuous exchanges between blood and brain. There is emerging evidence that the BBB plays a major role in epileptogenesis and drug-resistant epilepsy, through several mechanisms, such as water homeostasis dysregulation, overexpression of drug transporters, and inflammation. Studies have shown abnormal water homeostasis in epileptic tissue and altered aquaporin-4 water channel expression in animal epilepsy models. This review focuses on abnormal water exchange in epilepsy and describes recent non-invasive MRI methods of quantifying water exchange. PLAIN LANGUAGE SUMMARY: Abnormal exchange between blood and brain contribute to seizures and epilepsy. The authors describe why correct water balance is necessary for healthy brain functioning and how it is impacted in epilepsy. This review also presents recent MRI methods to measure water exchange in human brain. These measures would improve our understanding of factors leading to seizures.
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Barrera Hematoencefálica , Epilepsia , Neuroimagen , Barrera Hematoencefálica/metabolismo , Humanos , Epilepsia/metabolismo , Epilepsia/diagnóstico por imagen , Epilepsia/fisiopatología , Animales , Agua/metabolismo , Imagen por Resonancia Magnética , Encéfalo/metabolismo , Encéfalo/diagnóstico por imagen , Encéfalo/fisiopatologíaRESUMEN
Recent advances in functional magnetic resonance imaging (fMRI) at ultra-high field (≥7 tesla), novel hardware, and data analysis methods have enabled detailed research on neurovascular function, such as cortical layer-specific activity, in both human and nonhuman species. A widely used fMRI technique relies on the blood oxygen level-dependent (BOLD) signal. BOLD fMRI offers insights into brain function by measuring local changes in cerebral blood volume, cerebral blood flow, and oxygen metabolism induced by increased neuronal activity. Despite its potential, interpreting BOLD fMRI data is challenging as it is only an indirect measurement of neuronal activity. Computational modeling can help interpret BOLD data by simulating the BOLD signal formation. Current developments have focused on realistic 3D vascular models based on rodent data to understand the spatial and temporal BOLD characteristics. While such rodent-based vascular models highlight the impact of the angioarchitecture on the BOLD signal amplitude, anatomical differences between the rodent and human vasculature necessitate the development of human-specific models. Therefore, a computational framework integrating human cortical vasculature, hemodynamic changes, and biophysical properties is essential. Here, we present a novel computational approach: a three-dimensional VAscular MOdel based on Statistics (3D VAMOS), enabling the investigation of the hemodynamic fingerprint of the BOLD signal within a model encompassing a fully synthetic human 3D cortical vasculature and hemodynamics. Our algorithm generates microvascular and macrovascular architectures based on morphological and topological features from the literature on human cortical vasculature. By simulating specific oxygen saturation states and biophysical interactions, our framework characterizes the intravascular and extravascular signal contributions across cortical depth and voxel-wise levels for gradient-echo and spin-echo readouts. Thereby, the 3D VAMOS computational framework demonstrates that using human characteristics significantly affects the BOLD fingerprint, making it an essential step in understanding the fundamental underpinnings of layer-specific fMRI experiments.
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The brain's network of perivascular channels for clearance of excess fluids and waste plays a critical role in the pathogenesis of several neurodegenerative diseases including cerebral amyloid angiopathy (CAA). CAA is the main cause of hemorrhagic stroke in the elderly, the most common vascular comorbidity in Alzheimer's disease and also implicated in adverse events related to anti-amyloid immunotherapy. Remarkably, the mechanisms governing perivascular clearance of soluble amyloid ß-a key culprit in CAA-from the brain to draining lymphatics and systemic circulation remains poorly understood. This knowledge gap is critically important to bridge for understanding the pathophysiology of CAA and accelerate development of targeted therapeutics. The authors of this review recently converged their diverse expertise in the field of perivascular physiology to specifically address this problem within the framework of a Leducq Foundation Transatlantic Network of Excellence on Brain Clearance. This review discusses the overarching goal of the consortium and explores the evidence supporting or refuting the role of impaired perivascular clearance in the pathophysiology of CAA with a focus on translating observations from rodents to humans. We also discuss the anatomical features of perivascular channels as well as the biophysical characteristics of fluid and solute transport.
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Péptidos beta-Amiloides , Encéfalo , Angiopatía Amiloide Cerebral , Humanos , Encéfalo/metabolismo , Encéfalo/patología , Angiopatía Amiloide Cerebral/metabolismo , Angiopatía Amiloide Cerebral/patología , Animales , Péptidos beta-Amiloides/metabolismo , Sistema Glinfático/metabolismo , Sistema Glinfático/patología , Enfermedad de Alzheimer/metabolismo , Enfermedad de Alzheimer/patologíaRESUMEN
BACKGROUND: Neurofilament light chain (NFL) is a biomarker for neuroaxonal damage and glial fibrillary acidic protein (GFAP) for reactive astrocytosis. Both processes occur in cerebral amyloid angiopathy (CAA), but studies investigating the potential of NFL and GFAP as markers for CAA are lacking. We aimed to investigate NFL and GFAP as biomarkers for neuroaxonal damage and astrocytosis in CAA. METHODS: For this cross-sectional study serum and cerebrospinal fluid (CSF) samples were collected between 2010 and 2020 from controls, (pre)symptomatic Dutch-type hereditary (D-CAA) mutation-carriers and participants with sporadic CAA (sCAA) from two prospective CAA studies at two University hospitals in the Netherlands. NFL and GFAP levels were measured with Simoa-assays. The association between NFL and GFAP levels and age, cognitive performance (MoCA), CAA-related MRI markers (CAA-CSVD-burden) and Aß40 and Aß42 levels in CSF were assessed with linear regression adjusted for confounders. The control group was divided in age < 55 and ≥55 years to match the specific groups. RESULTS: We included 187 participants: 28 presymptomatic D-CAA mutation-carriers (mean age 40 years), 29 symptomatic D-CAA participants (mean age 58 years), 59 sCAA participants (mean age 72 years), 33 controls < 55 years (mean age 42 years) and 38 controls ≥ 55 years (mean age 65 years). In presymptomatic D-CAA, only GFAP in CSF (7.7*103pg/mL vs. 4.4*103pg/mL in controls; P<.001) was increased compared to controls. In symptomatic D-CAA, both serum (NFL:26.2pg/mL vs. 12.5pg/mL; P=0.008, GFAP:130.8pg/mL vs. 123.4pg/mL; P=0.027) and CSF (NFL:16.8*102pg/mL vs. 7.8*102pg/mL; P=0.01 and GFAP:11.4*103pg/mL vs. 7.5*103pg/mL; P<.001) levels were higher than in controls and serum levels (NFL:26.2pg/mL vs. 6.7pg/mL; P=0.05 and GFAP:130.8pg/mL vs. 66.0pg/mL; P=0.004) were higher than in pre-symptomatic D-CAA. In sCAA, only NFL levels were increased compared to controls in both serum (25.6pg/mL vs. 12.5pg/mL; P=0.005) and CSF (20.0*102pg/mL vs 7.8*102pg/mL; P=0.008). All levels correlated with age. Serum NFL correlated with MoCA (P=0.008) and CAA-CSVD score (P<.001). NFL and GFAP in CSF correlated with Aß42 levels (P=0.01/0.02). CONCLUSIONS: GFAP level in CSF is an early biomarker for CAA and is increased years before symptom onset. NFL and GFAP levels in serum and CSF are biomarkers for advanced CAA.
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Biomarcadores , Angiopatía Amiloide Cerebral , Proteína Ácida Fibrilar de la Glía , Proteínas de Neurofilamentos , Humanos , Proteínas de Neurofilamentos/líquido cefalorraquídeo , Proteínas de Neurofilamentos/sangre , Proteína Ácida Fibrilar de la Glía/líquido cefalorraquídeo , Proteína Ácida Fibrilar de la Glía/sangre , Femenino , Masculino , Persona de Mediana Edad , Estudios Transversales , Biomarcadores/líquido cefalorraquídeo , Biomarcadores/sangre , Anciano , Angiopatía Amiloide Cerebral/líquido cefalorraquídeo , Angiopatía Amiloide Cerebral/sangre , Angiopatía Amiloide Cerebral/genética , Péptidos beta-Amiloides/líquido cefalorraquídeo , Péptidos beta-Amiloides/sangre , Adulto , Estudios Prospectivos , Imagen por Resonancia MagnéticaRESUMEN
Over the last decade, it has become evident that cerebrospinal fluid (CSF) plays a pivotal role in brain solute clearance through perivascular pathways and interactions between the brain and meningeal lymphatic vessels. Whereas most of this fundamental knowledge was gained from rodent models, human brain clearance imaging has provided important insights into the human system and highlighted the existence of important interspecies differences. Current gold standard techniques for human brain clearance imaging involve the injection of gadolinium-based contrast agents and monitoring their distribution and clearance over a period from a few hours up to 2 days. With both intrathecal and intravenous injections being used, which each have their own specific routes of distribution and thus clearance of contrast agent, a clear understanding of the kinetics associated with both approaches, and especially the differences between them, is needed to properly interpret the results. Because it is known that intrathecally injected contrast agent reaches the blood, albeit in small concentrations, and that similarly some of the intravenously injected agent can be detected in CSF, both pathways are connected and will, in theory, reach the same compartments. However, because of clear differences in relative enhancement patterns, both injection approaches will result in varying sensitivities for assessment of different subparts of the brain clearance system. In this opinion review article, the "EU Joint Programme - Neurodegenerative Disease Research (JPND)" consortium on human brain clearance imaging provides an overview of contrast agent pharmacokinetics in vivo following intrathecal and intravenous injections and what typical concentrations and concentration-time curves should be expected. This can be the basis for optimizing and interpreting contrast-enhanced MRI for brain clearance imaging. Furthermore, this can shed light on how molecules may exchange between blood, brain, and CSF.
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Encéfalo , Medios de Contraste , Imagen por Resonancia Magnética , Humanos , Medios de Contraste/farmacocinética , Encéfalo/diagnóstico por imagen , Encéfalo/metabolismo , Tasa de Depuración Metabólica , Animales , Líquido Cefalorraquídeo/metabolismo , Líquido Cefalorraquídeo/diagnóstico por imagenRESUMEN
Arterial spin labeling (ASL) and dynamic susceptibility contrast (DSC) magnetic resonance imaging (MRI) have shown potential for differentiating tumor progression from pseudoprogression. For pseudocontinuous ASL with a single postlabeling delay, the presence of delayed arterial transit times (ATTs) could affect the evaluation of ASL-MRI perfusion data. In this study, the influence of ATT artifacts on the perfusion assessment and differentiation between tumor progression and pseudoprogression were studied. This study comprised 66 adult patients (mean age 60 ± 13 years; 40 males) with a histologically confirmed glioblastoma who received postoperative radio (chemo)therapy. ASL-MRI and DSC-MRI scans were acquired at 3 months postradiotherapy as part of the standard clinical routine. These scans were visually scored regarding (i) the severity of ATT artifacts (%) on the ASL-MRI scans only, scored by two neuroradiologists; (ii) perfusion of the enhancing tumor lesion; and (iii) radiological evaluation of tumor progression versus pseudoprogression by one neuroradiologist. The final outcome was based on combined clinical and radiological follow-up until 9 months postradiotherapy. ATT artifacts were identified in all patients based on the mean scores of two raters. A significant difference between the radiological evaluation of ASL-MRI and DSC-MRI was observed only for ASL images with moderate ATT severity (30%-65%). The perfusion assessment showed ASL-MRI tending more towards hyperperfusion than DSC-MRI in the case of moderate ATT artifacts. In addition, there was a significant difference between the prediction of tumor progression with ASL-MRI and the final outcome in the case of severe ATT artifacts (McNemar test, p = 0.041). Despite using ASL imaging parameters close to the recommended settings, ATT artifacts frequently occur in patients with treated brain tumors. Those artifacts could hinder the radiological evaluation of ASL-MRI data and the detection of true disease progression, potentially affecting treatment decisions for patients with glioblastoma.
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Neoplasias Encefálicas , Progresión de la Enfermedad , Glioblastoma , Marcadores de Spin , Humanos , Glioblastoma/diagnóstico por imagen , Glioblastoma/patología , Persona de Mediana Edad , Masculino , Femenino , Neoplasias Encefálicas/diagnóstico por imagen , Neoplasias Encefálicas/patología , Imagen por Resonancia Magnética , Anciano , Artefactos , Adulto , Factores de Tiempo , Diagnóstico Diferencial , Angiografía por Resonancia Magnética , Arterias/diagnóstico por imagen , Arterias/patologíaRESUMEN
Accurate assessment of cerebral perfusion is vital for understanding the hemodynamic processes involved in various neurological disorders and guiding clinical decision-making. This guidelines article provides a comprehensive overview of quantitative perfusion imaging of the brain using multi-timepoint arterial spin labeling (ASL), along with recommendations for its acquisition and quantification. A major benefit of acquiring ASL data with multiple label durations and/or post-labeling delays (PLDs) is being able to account for the effect of variable arterial transit time (ATT) on quantitative perfusion values and additionally visualize the spatial pattern of ATT itself, providing valuable clinical insights. Although multi-timepoint data can be acquired in the same scan time as single-PLD data with comparable perfusion measurement precision, its acquisition and postprocessing presents challenges beyond single-PLD ASL, impeding widespread adoption. Building upon the 2015 ASL consensus article, this work highlights the protocol distinctions specific to multi-timepoint ASL and provides robust recommendations for acquiring high-quality data. Additionally, we propose an extended quantification model based on the 2015 consensus model and discuss relevant postprocessing options to enhance the analysis of multi-timepoint ASL data. Furthermore, we review the potential clinical applications where multi-timepoint ASL is expected to offer significant benefits. This article is part of a series published by the International Society for Magnetic Resonance in Medicine (ISMRM) Perfusion Study Group, aiming to guide and inspire the advancement and utilization of ASL beyond the scope of the 2015 consensus article.
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Encéfalo , Circulación Cerebrovascular , Marcadores de Spin , Humanos , Encéfalo/diagnóstico por imagen , Encéfalo/irrigación sanguínea , Circulación Cerebrovascular/fisiología , Procesamiento de Imagen Asistido por Computador/métodos , Angiografía por Resonancia Magnética/métodos , Imagen por Resonancia Magnética/métodos , Imagen de PerfusiónRESUMEN
BACKGROUND AND OBJECTIVES: Individual brain MRI markers only show at best a modest association with long-term occurrence of dementia. Therefore, it is challenging to accurately identify individuals at increased risk for dementia. We aimed to identify different brain MRI phenotypes by hierarchical clustering analysis based on combined neurovascular and neurodegenerative brain MRI markers and to determine the long-term dementia risk within the brain MRI phenotype subgroups. METHODS: Hierarchical clustering analysis based on 32 combined neurovascular and neurodegenerative brain MRI markers in community-dwelling individuals of the Age-Gene/Environment Susceptibility Reykjavik Study was applied to identify brain MRI phenotypes. A Cox proportional hazards regression model was used to determine the long-term risk for dementia per subgroup. RESULTS: We included 3,056 participants and identified 15 subgroups with distinct brain MRI phenotypes. The phenotypes ranged from limited burden, mostly irregular white matter hyperintensity (WMH) shape and cerebral atrophy, mostly irregularly WMHs and microbleeds, mostly cortical infarcts and atrophy, mostly irregularly shaped WMH and cerebral atrophy to multiburden subgroups. Each subgroup showed different long-term risks for dementia (min-max range hazard ratios [HRs] 1.01-6.18; mean time to follow-up 9.9 ± 2.6 years); especially the brain MRI phenotype with mainly WMHs and atrophy showed a large increased risk (HR 6.18, 95% CI 3.37-11.32). DISCUSSION: Distinct brain MRI phenotypes can be identified in community-dwelling older adults. Our results indicate that distinct brain MRI phenotypes are related to varying long-term risks of developing dementia. Brain MRI phenotypes may in the future assist in an improved understanding of the structural correlates of dementia predisposition.
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Demencia , Sustancia Blanca , Humanos , Anciano , Encéfalo/patología , Vida Independiente , Imagen por Resonancia Magnética , Demencia/epidemiología , Fenotipo , Atrofia/patología , Sustancia Blanca/patologíaRESUMEN
BACKGROUND: The temporal ordering of biomarkers for cerebral amyloid angiopathy (CAA) is important for their use in trials and for the understanding of the pathological cascade of CAA. We investigated the presence and abnormality of the most common biomarkers in the largest (pre)symptomatic Dutch-type hereditary CAA (D-CAA) cohort to date. METHODS: We included cross-sectional data from participants with (pre)symptomatic D-CAA and controls without CAA. We investigated CAA-related cerebral small vessel disease markers on 3T-MRI, cerebrovascular reactivity with functional 7T-MRI (fMRI) and amyloid-ß40 and amyloid-ß42 levels in cerebrospinal fluid. We calculated frequencies and plotted biomarker abnormality according to age to form scatterplots. RESULTS: We included 68 participants with D-CAA (59% presymptomatic, mean age, 50 [range, 26-75] years; 53% women), 53 controls (mean age, 51 years; 42% women) for cerebrospinal fluid analysis and 36 controls (mean age, 53 years; 100% women) for fMRI analysis. Decreased cerebrospinal fluid amyloid-ß40 and amyloid-ß42 levels were the earliest biomarkers present: all D-CAA participants had lower levels of amyloid-ß40 and amyloid-ß42 compared with controls (youngest participant 30 years). Markers of nonhemorrhagic injury (>20 enlarged perivascular spaces in the centrum semiovale and white matter hyperintensities Fazekas score, ≥2, present in 83% [n=54]) and markers of impaired cerebrovascular reactivity (abnormal BOLD amplitude, time to peak and time to baseline, present in 56% [n=38]) were present from the age of 30 years. Finally, markers of hemorrhagic injury were present in 64% (n=41) and only appeared after the age of 41 years (first microbleeds and macrobleeds followed by cortical superficial siderosis). CONCLUSIONS: Our results suggest that amyloid biomarkers in cerebrospinal fluid are the first to become abnormal in CAA, followed by MRI biomarkers for cerebrovascular reactivity and nonhemorrhagic injury and lastly hemorrhagic injury. This temporal ordering probably reflects the pathological stages of CAA and should be taken into account when future therapeutic trials targeting specific stages are designed.
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Angiopatía Amiloide Cerebral Familiar , Angiopatía Amiloide Cerebral , Humanos , Femenino , Persona de Mediana Edad , Adulto , Masculino , Angiopatía Amiloide Cerebral Familiar/diagnóstico por imagen , Estudios Transversales , Angiopatía Amiloide Cerebral/diagnóstico por imagen , Imagen por Resonancia Magnética/métodos , Hemorragia Cerebral , BiomarcadoresRESUMEN
INTRODUCTION: Cerebral perforating arteries provide blood supply to the deep regions of the brain. Recently, it became possible to measure blood flow velocity and pulsatility in these small arteries. It is unknown if vascular risk factors are related to these measures. METHODS: We measured perforating artery flow with 2D phase contrast 7 Tesla MRI at the level of the centrum semiovale (CSO) and the basal ganglia (BG) in seventy participants from the Heart Brain Connection study with carotid occlusive disease (COD), vascular cognitive impairment (VCI), or no actual cerebrovascular disease. Vascular risk factors included hypertension, diabetes, hyperlipidemia and smoking. RESULTS: No consistent relations were found between any of the vascular risk factors and either flow velocity or flow pulsatility, although there was a relation between lower diastolic blood pressure and higher pulse pressure and higher cerebral perforator pulsatility (p=0,045 and p=0,044, respectively) at the BG level. Results were similar in stratified analyses for patients with and without a history of cardiovascular disease, or only COD or VCI. CONCLUSION: We conclude that, cross-sectionally, cerebral perforating artery flow velocity and pulsatility are largely independent of the presence of common vascular risk factors in a population with a mixed vascular burden.
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Cerebral amyloid angiopathy (CAA) is a type of cerebrovascular disorder characterised by the accumulation of amyloid within the leptomeninges and small/medium-sized cerebral blood vessels. Typically, cerebral haemorrhages are one of the first clinical manifestations of CAA, posing a considerable challenge to the timely diagnosis of CAA as the bleedings only occur during the later disease stages. Fluid biomarkers may change prior to imaging biomarkers, and therefore, they could be the future of CAA diagnosis. Additionally, they can be used as primary outcome markers in prospective clinical trials. Among fluid biomarkers, blood-based biomarkers offer a distinct advantage over cerebrospinal fluid biomarkers as they do not require a procedure as invasive as a lumbar puncture. This article aimed to provide an overview of the present clinical data concerning fluid biomarkers associated with CAA and point out the direction of future studies. Among all the biomarkers discussed, amyloid ß, neurofilament light chain, matrix metalloproteinases, complement 3, uric acid, and lactadherin demonstrated the most promising evidence. However, the field of fluid biomarkers for CAA is an under-researched area, and in most cases, there are only one or two studies on each of the biomarkers mentioned in this review. Additionally, a small sample size is a common limitation of the discussed studies. Hence, it is hard to reach a solid conclusion on the clinical significance of each biomarker at different stages of the disease or in various subpopulations of CAA. In order to overcome this issue, larger longitudinal and multicentered studies are needed.
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Metabolite-weighted chemical exchange saturation transfer MRI can be used to indirectly image metabolites such as creatine and glutamate. This study aims to further explore the contrast of CEST at 2 ppm in the human brain at 7T and investigate the metabolite correlates of CEST at 2 ppm via correlations with magnetic resonance spectroscopy (MRS). Simulations were performed to establish the optimal acquisition parameters, such as total saturation time (tsat) and B1 root mean squared (B1rms) for CEST at 2 ppm in the human brain. Parameters were validated via in vitro phantom studies at 7T using concentrations, pH and temperature comparable to what is found in the human brain. Finally, 10 healthy volunteers were scanned at 7T for comparison with MRS. Our results show that the optimal parameters to acquire CEST at 2 ppm images are: B1rms = 2.14 µT & tsat = 1500 ms, respectively. Comparison with MRS showed no significant correlation between CEST at 2 ppm and total Creatine measured by MRS (R = 0.19; p-value = 0.273). However, a significant correlation was found between CEST at 2 ppm and Glu (R = 0.39; p-value = 0.033), indicating the broad Glutamate-weighted CEST as the main measurable contributor to CEST at 2 ppm. We identified and confirmed optimal CEST at 2 ppm sequence parameters and validated CEST at 2 ppm measurements in a controlled in vitro environment. Our findings suggest that glutamate is a substantial contributor to the CEST at 2 ppm contrast observed in the human brain, whereas the creatine contribution to CEST at 2 ppm in the brain did not show a measurable contribution.
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Encéfalo , Creatina , Humanos , Creatina/metabolismo , Encéfalo/diagnóstico por imagen , Encéfalo/metabolismo , Imagen por Resonancia Magnética/métodos , Espectroscopía de Resonancia Magnética/métodos , Ácido Glutámico/metabolismoRESUMEN
Arterial spin labeling (ASL) is a promising, non-invasive perfusion magnetic resonance imaging technique for quantifying cerebral blood flow (CBF). Unfortunately, ASL suffers from an inherently low signal-to-noise ratio (SNR) and spatial resolution, undermining its potential. Increasing spatial resolution without significantly sacrificing SNR or scan time represents a critical challenge towards routine clinical use. In this work, we propose a model-based super-resolution reconstruction (SRR) method with joint motion estimation that breaks the traditional SNR/resolution/scan-time trade-off. From a set of differently oriented 2D multi-slice pseudo-continuous ASL images with a low through-plane resolution, 3D-isotropic, high resolution, quantitative CBF maps are estimated using a Bayesian approach. Experiments on both synthetic whole brain phantom data, and on in vivo brain data, show that the proposed SRR Bayesian estimation framework outperforms state-of-the-art ASL quantification.
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Procesamiento de Imagen Asistido por Computador , Angiografía por Resonancia Magnética , Humanos , Procesamiento de Imagen Asistido por Computador/métodos , Marcadores de Spin , Teorema de Bayes , Angiografía por Resonancia Magnética/métodos , Encéfalo/irrigación sanguínea , Circulación Cerebrovascular/fisiología , Relación Señal-Ruido , Imagen por Resonancia Magnética/métodosRESUMEN
BACKGROUND: Magnetic Resonance acquisition is a time consuming process, making it susceptible to patient motion during scanning. Even motion in the order of a millimeter can introduce severe blurring and ghosting artifacts, potentially necessitating re-acquisition. Magnetic Resonance Imaging (MRI) can be accelerated by acquiring only a fraction of k-space, combined with advanced reconstruction techniques leveraging coil sensitivity profiles and prior knowledge. Artificial intelligence (AI)-based reconstruction techniques have recently been popularized, but generally assume an ideal setting without intra-scan motion. PURPOSE: To retrospectively detect and quantify the severity of motion artifacts in undersampled MRI data. This may prove valuable as a safety mechanism for AI-based approaches, provide useful information to the reconstruction method, or prompt for re-acquisition while the patient is still in the scanner. METHODS: We developed a deep learning approach that detects and quantifies motion artifacts in undersampled brain MRI. We demonstrate that synthetically motion-corrupted data can be leveraged to train the convolutional neural network (CNN)-based motion artifact estimator, generalizing well to real-world data. Additionally, we leverage the motion artifact estimator by using it as a selector for a motion-robust reconstruction model in case a considerable amount of motion was detected, and a high data consistency model otherwise. RESULTS: Training and validation were performed on 4387 and 1304 synthetically motion-corrupted images and their uncorrupted counterparts, respectively. Testing was performed on undersampled in vivo motion-corrupted data from 28 volunteers, where our model distinguished head motion from motion-free scans with 91% and 96% accuracy when trained on synthetic and on real data, respectively. It predicted a manually defined quality label ('Good', 'Medium' or 'Bad' quality) correctly in 76% and 85% of the time when trained on synthetic and real data, respectively. When used as a selector it selected the appropriate reconstruction network 93% of the time, achieving near optimal SSIM values. CONCLUSIONS: The proposed method quantified motion artifact severity in undersampled MRI data with high accuracy, enabling real-time motion artifact detection that can help improve the safety and quality of AI-based reconstructions.