Fluid-attenuated Inversion Recovery MRI Research Articles

Robust AI-Driven Segmentation of Glioblastoma T1c and FLAIR MRI Series and the Low Variability of the MRIMath© Smart Manual Contouring Platform

Patients diagnosed with glioblastoma multiforme (GBM) continue to face a dire prognosis. Developing accurate and efficient contouring methods is crucial, as they can significantly advance both clinical practice and research. This study evaluates the AI models developed by MRIMath© for GBM T1c and fluid attenuation inversion recovery (FLAIR) images by comparing their contours to those of three neuro-radiologists using a smart manual contouring platform. The mean overall Sørensen–Dice Similarity Coefficient metric score (DSC) for the post-contrast T1 (T1c) AI was 95%, with a 95% confidence interval (CI) of 93% to 96%, closely aligning with the radiologists’ scores. For true positive T1c images, AI segmentation achieved a mean DSC of 81% compared to radiologists’ ranging from 80% to 86%. Sensitivity and specificity for T1c AI were 91.6% and 97.5%, respectively. The FLAIR AI exhibited a mean DSC of 90% with a 95% CI interval of 87% to 92%, comparable to the radiologists’ scores. It also achieved a mean DSC of 78% for true positive FLAIR slices versus radiologists’ scores of 75% to 83% and recorded a median sensitivity and specificity of 92.1% and 96.1%, respectively. The T1C and FLAIR AI models produced mean Hausdorff distances (<5 mm), volume measurements, kappa scores, and Bland–Altman differences that align closely with those measured by radiologists. Moreover, the inter-user variability between radiologists using the smart manual contouring platform was under 5% for T1c and under 10% for FLAIR images. These results underscore the MRIMath© platform’s low inter-user variability and the high accuracy of its T1c and FLAIR AI models.

Leveraging radiomics and machine learning to differentiate radiation necrosis from recurrence in patients with brain metastases.

Radiation necrosis (RN) can be difficult to radiographically discern from tumor progression after stereotactic radiosurgery (SRS). The objective of this study was to investigate the utility of radiomics and machine learning (ML) to differentiate RN from recurrence in patients with brain metastases treated with SRS. Patients with brain metastases treated with SRS who developed either RN or tumor reccurence were retrospectively identified. Image preprocessing and radiomic feature extraction were performed using ANTsPy and PyRadiomics, yielding 105 features from MRI T1-weighted post-contrast (T1c), T2, and fluid-attenuated inversion recovery (FLAIR) images. Univariate analysis assessed significance of individual features. Multivariable analysis employed various classifiers on features identified as most discriminative through feature selection. ML models were evaluated through cross-validation, selecting the best model based on area under the receiver operating characteristic (ROC) curve (AUC). Specificity, sensitivity, and F1 score were computed. Sixty-six lesions from 55 patients were identified. On univariate analysis, 27 features from the T1c sequence were statistically significant, while no features were significant from the T2 or FLAIR sequences. For clinical variables, only immunotherapy use after SRS was significant. Multivariable analysis of features from the T1c sequence yielded an AUC of 76.2% (standard deviation [SD] ± 12.7%), with specificity and sensitivity of 75.5% (± 13.4%) and 62.3% (± 19.6%) in differentiating radionecrosis from recurrence. Radiomics with ML may assist the diagnostic ability of distinguishing RN from tumor recurrence after SRS. Further work is needed to validate this in a larger multi-institutional cohort and prospectively evaluate it's utility in patient care.

SUPRAMAX-study: supramaximal resection versus maximal resection for glioblastoma patients: study protocol for an international multicentre prospective cohort study (ENCRAM 2201)

IntroductionA greater extent of resection of the contrast-enhancing (CE) tumour part has been associated with improved outcomes in glioblastoma. Recent results suggest that resection of the non-contrast-enhancing (NCE) part might...

Experimental Ischemic Stroke Induces Secondary Bihemispheric White Matter Degeneration and Long-Term Cognitive Impairment.

Clinical studies have identified widespread white matter degeneration in ischemic stroke patients. However, contemporary research in stroke has predominately focused on the infarct and periinfarct penumbra regions. The involvement of white matter degeneration after ischemic stroke and its contribution to post-stroke cognitive impairment and dementia (PSCID) has remained less explored in experimental models. In this study, we examined the progression of locomotor and cognitive function up to 4 months after inducing ischemic stroke by middle cerebral artery occlusion in young adult rats. Despite evident ongoing locomotor recovery, long-term cognitive and affective impairments persisted after ischemic stroke, as indicated by Morris water maze, elevated plus maze, and open field performance. At 4 months after stroke, multimodal MRI was conducted to assess white matter degeneration. T2-weighted MRI (T2WI) unveiled bilateral cerebroventricular enlargement after ischemic stroke. Fluid Attenuated Inversion Recovery MRI (FLAIR) revealed white matter hyperintensities in the corpus callosum and fornix across bilateral hemispheres. A positive association between the volume of white matter hyperintensities and total cerebroventricular volume was noted in stroke rats. Further evidence of bilateral white matter degeneration was indicated by the reduction of fractional anisotropy and quantitative anisotropy at bilateral corpus callosum in diffusion-weighted MRI (DWI) analysis. Additionally, microglia and astrocyte activation were identified in the bilateral corpus callosum after stroke. Our study suggests that experimental ischemic stroke induced by MCAO in young rat replicate long-term cognitive impairment and bihemispheric white matter degeneration observed in ischemic stroke patients. This model provides an invaluable tool for unraveling the mechanisms underlying post-stroke secondary white matter degeneration and its contribution to PSCID.

Patient-Specific Three-Dimensional-Printed and Bolus Material-Based Localization Grids for Magnetic Resonance Imaging-Guided Interventional Procedures

Abstract In view of the lack of commercially available localization grids for magnetic resonance imaging (MRI)-guided interventional procedures, two customizable and easily fabricable grids are proposed. The first one is a patient-specific three-dimensional-printed localization grid that incorporates MRI markers while the second one is a grid constructed with Superflex Transparent Bolus material. MRI scans were performed with the grids attached on an abdominal phantom. The patient-specific three-dimensional-printed grid is visible in T1-weighted, T2-weighted, proton density (PD) and fluid attenuated inversion recovery MR images, whereas the Superflex grid is visible only in T1-weighted and PD images. However, the Superflex grid offers the advantage of a simpler fabrication process and is more cost-effective. Both proposed localization grids can facilitate the determination of the optimal needle entry positions for MRI-guided interventional procedures, leading to reduced overall procedure time and improved efficiency.

Subtle white matter intensity changes on fluid-attenuated inversion recovery imaging in patients with ischaemic stroke.

Leukoaraiosis is a neuroimaging marker of small-vessel disease that is characterized by high signal intensity on fluid-attenuated inversion recovery MRI. There is increasing evidence from pathology and neuroimaging suggesting that the structural abnormalities that characterize leukoaraiosis are actually present within regions of normal-appearing white matter, and that the underlying pathophysiology of white matter damage related to small-vessel disease involves blood-brain barrier damage. In this study, we aim to verify whether leukoaraiosis is associated with elevated signal intensity on fluid-attenuated inversion recovery imaging, a marker of brain tissue free-water accumulation, in normal-appearing white matter. We performed a cross-sectional study of adult patients admitted to our hospital with a diagnosis of acute ischaemic stroke or transient ischaemic attack. Leukoaraiosis was segmented using a semi-automated method involving manual outlining and signal thresholding. White matter regions were segmented based on the probabilistic tissue maps from the International Consortium for Brain Mapping 152 atlas. Also, normal-appearing white matter was further segmented based on voxel distance from leukoaraiosis borders, resulting in five normal-appearing white matter strata at increasing voxel distances from leukoaraiosis. The relationship between mean normalized fluid-attenuated inversion recovery signal intensity on normal-appearing white matter and leukoaraiosis volume was studied in a multivariable statistical analysis using linear mixed modelling, having normal-appearing white matter strata as a clustering variable. One hundred consecutive patients meeting inclusion and exclusion criteria were selected for analysis (53% female, mean age 68 years). Mean normalized fluid-attenuated inversion recovery signal intensity on normal-appearing white matter was higher in the vicinity of leukoaraiosis and progressively lower at increasing distances from leukoaraiosis. In a multivariable analysis, the mean normalized fluid-attenuated inversion recovery signal intensity on normal-appearing white matter was positively associated with leukoaraiosis volume and age (B = 0.025 for each leukoaraiosis quartile increase; 95% confidence interval 0.019-0.030). This association was found similarly across normal-appearing white matter strata. Voxel maps of the mean normalized fluid-attenuated inversion recovery signal intensity on normal-appearing white matter showed an increase in signal intensity that was not adjacent to leukoaraiosis regions. Our results show that normal-appearing white matter exhibits subtle signal intensity changes on fluid-attenuated inversion recovery imaging that are related to leukoaraiosis burden. These results suggest that diffuse free-water accumulation is likely related to the aetiopathogenic processes underlying the development of white matter damage related to small-vessel disease.

Chronic Active Lesions and Larger Choroid Plexus Explain Cognition and Fatigue in Multiple Sclerosis.

Chronic inflammation may contribute to cognitive dysfunction and fatigue in patients with multiple sclerosis (MS). Paramagnetic rim lesions (PRLs) and choroid plexus (CP) enlargement have been proposed as markers of chronic inflammation in MS being associated with a more severe disease course. However, their relation with cognitive impairment and fatigue has not been fully explored yet. Here, we investigated the contribution of PRL number and volume and CP enlargement to cognitive impairment and fatigue in patients with MS. Brain 3T MRI, neurologic evaluation, and neuropsychological assessment, including the Brief Repeatable Battery of Neuropsychological Tests and Modified Fatigue Impact Scale, were obtained from 129 patients with MS and 73 age-matched and sex-matched healthy controls (HC). PRLs were identified on phase images of susceptibility-weighted imaging, whereas CP volume was quantified using a fully automatic method on brain three-dimensional T1-weighted and fluid-attenuated inversion recovery MRI sequences. Predictors of cognitive impairment and fatigue were identified using random forest. Thirty-six (27.9%) patients with MS were cognitively impaired, and 31/113 (27.4%) patients had fatigue. Fifty-nine (45.7%) patients with MS had ≥1 PRLs (median = 0, interquartile range = 0;2). Compared with HC, patients with MS showed significantly higher T2-hyperintense white matter lesion (WM) volume; lower normalized brain, thalamic, hippocampal, caudate, cortical, and WM volumes; and higher normalized CP volume (p from <0.001 to 0.040). The predictors of cognitive impairment (relative importance) (out-of-bag area under the curve [OOB-AUC] = 0.707) were normalized brain volume (100%), normalized caudate volume (89.1%), normalized CP volume (80.3%), normalized cortical volume (70.3%), number (67.3%) and volume (66.7%) of PRLs, and T2-hyperintense WM lesion volume (64.0%). Normalized CP volume was the only predictor of the presence of fatigue (OOB-AUC = 0.563). Chronic inflammation, with higher number and volume of PRLs and enlarged CP, may contribute to cognitive impairment in MS in addition to gray matter atrophy. The contribution of enlarged CP in explaining fatigue supports the relevance of immune-related processes in determining this manifestation independently of disease severity. PRLs and CP enlargement may contribute to the pathophysiology of cognitive impairment and fatigue in MS, and they may represent clinically relevant therapeutic targets to limit the impact of these clinical manifestations in MS.

In vivo PET of synaptic density as potential diagnostic marker for cognitive disorders: prospective comparison with current imaging markers for neuronal dysfunction and relation to symptomatology - study protocol

Background18F-FDG brain PET is clinically used for differential diagnosis in cognitive dysfunction of unclear etiology and for exclusion of a neurodegenerative cause in patients with cognitive impairment in late-life psychiatric disorders. 18F-FDG PET measures regional glucose metabolism, which represents a combination of neuronal/synaptic activity but also astrocytic activity and neuroinflammation. Recently, imaging of synaptic vesicle protein 2 A (SV2A) has become available and was shown to be a proxy of synaptic density. This prospective study will investigate the use of 18F-SynVesT-1 for imaging SV2A and its discriminative power for differential diagnosis in cognitive disorders in a head-to-head comparison to 18F-FDG PET. In addition, simultaneous PET/MR allows an evaluation of contributing factors and the additional value of advanced MRI imaging to FDG/SV2A PET imaging will be investigated. In this work, the study design and protocol are depicted.MethodsIn this prospective, multimodal imaging study, 110 patients with uncertain diagnosis of cognitive impairment who are referred for 18F-FDG PET brain imaging in their diagnostic work-up in a tertiary memory clinic will be recruited. In addition, 40 healthy volunteers (HV) between 18 and 85 years (M/F) will be included. All study participants will undergo simultaneous 18F-SynVesT-1 PET/MR and an extensive neuropsychological evaluation. Amyloid status will be measured by PET using 18FNAV4694, in HV above 50 years of age. Structural T1-weighted and T2-weighted fluid-attenuated inversion recovery MR images, triple-tagging arterial spin labeling (ASL) and resting-state functional MRI (rs-fMRI) will be obtained. The study has been registered on ClinicalTrials.gov (NCT05384353) and is approved by the local Research Ethics Committee.DiscussionThe main endpoint of the study will be the comparison of the diagnostic accuracy between 18F-SynVesT-1 and 18F-FDG PET in cognitive disorders with uncertain etiology and in exclusion of a neurodegenerative cause in patients with cognitive impairment in late-life psychiatric disorders. The strength of the relationship between cognition and imaging data will be assessed, as well as the potential incremental diagnostic value of including MR volumetry, ASL perfusion and rs-fMRI.

Small vessel cerebrovascular disease is associated with cognition in prospective Alzheimer’s clinical trial participants

BackgroundSecondary prevention clinical trials for Alzheimer’s disease (AD) target amyloid accumulation in asymptomatic, amyloid-positive individuals, but it is unclear to what extent other pathophysiological processes, such as small vessel cerebrovascular disease, account for participant performance on the primary cognitive outcomes in those trials. White matter hyperintensities are areas of increased signal on T2-weighted magnetic resonance imaging (MRI) that reflect small vessel cerebrovascular disease. They are associated with cognitive functioning in older adults and with clinical presentation and course of AD, particularly when distributed in posterior brain regions. The purpose of this study was to examine to what degree regional WMH volume is associated with performance on the primary cognitive outcome measure in the Anti-Amyloid Treatment in Asymptomatic Alzheimer’s Disease (A4) study, a secondary prevention trial.MethodsData from 1791 participants (59.5% women, mean age (SD) 71.6 (4.74)) in the A4 study and the Longitudinal Evaluation of Amyloid Risk and Neurodegeneration (LEARN) companion study at the screening visit were used to quantify WMH volumes on T2-weighted fluid-attenuated inversion recovery (FLAIR) MR images. Cognition was assessed with the preclinical Alzheimer cognitive composite (PACC). We tested the association of total and regional WMH volumes with PACC performance, adjusting for age, education, and amyloid positivity status, with general linear models. We also considered interactions between WMH and amyloid positivity status.ResultsIncreased frontal and parietal lobe WMH volume was associated with poorer performance on the PACC. While amyloid positivity was also associated with lower cognitive test scores, WMH volumes did not interact with amyloid positivity status.ConclusionThese results highlight the potential of small vessel cerebrovascular disease to drive AD-related cognitive profiles. Measures of small vessel cerebrovascular disease should be considered when evaluating outcome in trials, both as potential effect modifiers and as a possible target for intervention or prevention.

Abstract 89: Portable, Low-Field Magnetic Resonance Imaging: Determining Mismatch Following Acute Ischemic Stroke

Background and Aims: Treatment options for acute ischemic stroke (AIS) are uniquely dependent on the time of stroke onset. Intravenous thrombolysis must be administered within 4.5 hours of symptoms commencing, yet a subset of patients wake-up with symptoms and time of onset is unknown. Mismatch between fluid-attenuated inversion recovery (FLAIR) and diffusion-weighted imaging (DWI) MRI can be used to qualify wake-up strokes for thrombolysis. This has been shown to lead to improved functional outcomes in multicenter trials (WAKE-UP, MR-WITNESS). However, access to MRI is a barrier to differential diagnosis and subsequent treatment. Recent advances in portable, low-field MRI (LF-MRI) offer a solution to increase access to MRI technologies and circumvent the limitations of conventional systems. As such, in this pilot study, we sought to establish the utility of portable LF-MRI to identify DWI-FLAIR mismatch following AIS. Methods: Patients with a diagnosis of AIS presenting to Emergency Department or Intensive Care Unit of the Yale New Haven Hospital or Massachusetts General Hospital from January 2020 to June 2023 underwent DWI and FLAIR acquisition on a 0.064T MRI (Hyperfine Research Inc.) at &lt;4.5 hours ( n =7), 4.5-6 hours ( n =7), and 6-48 hours ( n =110) since last known well (LKW). Conventional high-field (HF) MR images were acquired within 72 hours of LF-MRI. HF-DWI images were co-registered to LF-FLAIR and the hyperintense DWI stroke lesion segmented and superimposed on the FLAIR. The segmentation was mirrored to the contralateral hemisphere of the LF-FLAIR to establish a FLAIR signal intensity ratio (SIR). Results: The FLAIR SIR on images &lt;4.5 hours since LKW was 0.98±0.08. The SIR for cases 4.5-6 hours was 1.34±0.33. Cases 6-48 hours produced a SIR of 1.56±0.36. The SIR at &lt;4.5 hours was significantly less than that observed &gt;6 hours since LKW ( p =0.03). Conclusion: This pilot study demonstrates that a 0.064T portable MRI is capable of distinguishing hyperacute stroke from later stroke onset using FLAIR SIR. Future research is needed in a larger cohort to determine if this imaging technology can be used to guide thrombolysis in the setting of wake-up stroke.

Abstract TP286: Spatial Transcriptome Profile of Stem Cell-Mediated Recovery in Stroke-Injured Rat Brains

Introduction: Intraparenchymal stem cell transplantation shows therapeutic promise for chronic ischemic stroke patients. Our previous phase 1/2a trial revealed a transient T2-FLAIR (fluid-attenuated inversion recovery) MRI signal in the premotor cortex following intraparenchymal stem cell transplantation, the size of which positively correlated with the extent of clinical recovery. We sought to elucidate the underlying molecular mechanisms in this FLAIR region that may facilitate post-stroke recovery using spatial transcriptomic profiling in stroke-injured rat brains. Methods: Adult male SD rats underwent 30 min transient middle cerebral artery occlusion followed at 1 month by transplantation of human ES-derived neural stem cells (NR1) or buffer into the ipsilesional striatum. Whisker paw test and various MRI sequences (T2, FLAIR, DWI) were performed at multiple time points. The Visium platform (10X Genomics) was used for unbiased spatial transcriptome analysis in two stem-cell and two vehicle-treated brains at the peak of FLAIR. Results: We successfully replicated transplant-induced FLAIR after chronic stroke in rats and found a positive correlation between FLAIR and improved neurological outcomes. Visium identified specific gene clusters for the stroke injury, transplant/needle-track, stem cell graft, and the cortical ‘FLAIR’ region. The latter consisted of a central core containing the gene signature of the needle track and blood, and a wider region around this core which encompassed the FLAIR lesion seen by MRI. This wider FLAIR region displayed a predominantly microglia/inflammation-associated signature and was best characterized by the upregulation of apoptosis-associated genes. Pathway analysis of the differentially-expressed genes in the FLAIR cluster revealed a significant representation of immune cell responses (e.g. phagocytosis, immune cell migration, cytokine signaling), as well as ER stress mechanisms. Conclusion: This pilot study provides initial evidence that altered immune responses in the stem cell transplant-induced FLAIR region may promote recovery after chronic stroke. Further research on the role of microglia/neuroinflammation is needed to understand the mechanisms of stem cell-mediated brain repair.

Spatial normalization for voxel-based lesion symptom mapping: impact of registration approaches.

Voxel-based lesion symptom mapping (VLSM) assesses the relation of lesion location at a voxel level with a specific clinical or functional outcome measure at a population level. Spatial normalization, that is, mapping the patient images into an atlas coordinate system, is an essential pre-processing step of VLSM. However, no consensus exists on the optimal registration approach to compute the transformation nor are downstream effects on VLSM statistics explored. In this work, we evaluate four registration approaches commonly used in VLSM pipelines: affine (AR), nonlinear (NLR), nonlinear with cost function masking (CFM), and enantiomorphic registration (ENR). The evaluation is based on a standard VLSM scenario: the analysis of statistical relations of brain voxels and regions in imaging data acquired early after stroke onset with follow-up modified Rankin Scale (mRS) values. Fluid-attenuated inversion recovery (FLAIR) MRI data from 122 acute ischemic stroke patients acquired between 2 and 3 days after stroke onset and corresponding lesion segmentations, and 30 days mRS values from a European multicenter stroke imaging study (I-KNOW) were available and used in this study. The relation of the voxel location with follow-up mRS was assessed by uni- as well as multi-variate statistical testing based on the lesion segmentations registered using the four different methods (AR, NLR, CFM, ENR; implementation based on the ANTs toolkit). The brain areas evaluated as important for follow-up mRS were largely consistent across the registration approaches. However, NLR, CFM, and ENR led to distortions in the patient images after the corresponding nonlinear transformations were applied. In addition, local structures (for instance the lateral ventricles) and adjacent brain areas remained insufficiently aligned with corresponding atlas structures even after nonlinear registration. For VLSM study designs and imaging data similar to the present work, an additional benefit of nonlinear registration variants for spatial normalization seems questionable. Related distortions in the normalized images lead to uncertainties in the VLSM analyses and may offset the theoretical benefits of nonlinear registration.

The effect of delay time after injecting gadobutrol on the diagnosis of endolymphatic hydrops

ObjectivesThe aim of this study was to reduce the time delay between gadolinium injection and 3D-FLAIR (three-dimensional fluid-attenuated inversion recovery) MRI by using a single dose of intravenous gadobutrol in Menière's disease patients. Methods17 patients diagnosed with definite unilateral Meniere's disease underwent 3D-FLAIR MRI scans at 2, 4, and 6 h post-intravenous administration of a single-dose of gadobutrol. The signal intensity ratio of bilateral inner ear, cochlear and vestibular hydrops was measured at 2 h, 4 h and 6 h, while the differences in signal intensity ratio and endolymphatic hydrops were evaluated at three time points. ResultsThe cochlea, vestibule, and semicircular canal exhibit clear structural features with distinct perilymph-endolymph boundaries at 2 h, 4 h, and 6 h. The signal intensity ratio of the affected ear was significantly higher than that of the unaffected ear at 2 h, 4 h, and 6 h. The signal intensity ratio at 4 h and 6 h in both the affected and unaffected ears was significantly higher than that at 2 h, but there was no significant difference between 4 h and 6 h. Cochlear hydrops and vestibular hydrops show no significant differences at these time points, demonstrating excellent consistency. ConclusionsWe have demonstrated that 3D-FLAIR images acquired 2 h after intravenous administration of a single-dose gadobutrol are of high quality and equally effective as those obtained at the conventional 4-h time point for diagnosing endolymphatic hydrops in Menière's disease. In clinical practice, the delay time can be safely shortened to 2 h.

Relationship between a novel virtual reality test of mild functional difficulties and cerebrovascular disease

AbstractBackgroundIt is well known that mild cognitive impairment (MCI) is associated with subtle functional decline. However, standardized and cost‐effective methods for the objective quantification of mild functional difficulties are lacking. Here we report preliminary validity data for a novel, non‐immersive virtual‐reality task (Virtual Kitchen Challenge [VKC]) against brain markers of cerebrovascular disease and in contrast to a conventional, self‐report measure of function.MethodTwenty (n = 14 healthy control, n = 6 MCI) community‐dwelling older adults aged 60+ completed neuropsychological testing, including the Functional Activities Questionnaire (FAQ), and the VKC, which requires completion of simulated breakfast and lunch tasks on a touch‐screen computer. White matter hyperintensity (WMH) volumes from Fluid Attenuation Inversion Recovery (FLAIR) MRI sequences were derived using the UBO detector, a cluster‐based WMH extraction pipeline based on k‐nearest neighbors (k‐NN) algorithm. WMH volumes were calculated in SPM’s DARTEL space, precluding the need to adjust for intracranial volume (ICV).ResultMCI participants reported significantly more functional difficulties than healthy controls (FAQ U = 76.50 p = .002) and obtained marginally slower completion times on the VKC (U = 60.00, p = .138). VKC completion time was moderately associated with age (r = .441, p = .059) but relations with sex, race, and IQ were weak and not significant (all rs&lt;.195). VKC completion time significantly and strongly correlated with all WMH measures, even after controlling for age, sex, race, and IQ (total WMH r = .649, p = .031; deep WMH r = .615, p = .044; periventricular WMH r = .623, p = .041). By contrast, FAQ was not associated with WMH (rs&lt;.2, p&gt;.05 for all) or VKC completion time (r&lt;.1, p&gt;05) after controlling for age, sex, race, and IQ.ConclusionOur naturalistic, performance‐based measure of function (VKC) was not associated with race, sex, or premorbid IQ, but was strongly associated with neuroimaging markers of cerebrovascular disease (WMH). By contrast, a conventional self‐report measure of everyday functioning (FAQ) was not associated with neuroimaging measures (WMH). These results offer preliminary support for the VKC as a valid measure of early, subtle functional difficulties associated with cerebrovascular pathology that is not vulnerable to bias associated with race, sex, or premorbid IQ.

Relationship between a novel virtual reality test of mild functional difficulties and cerebrovascular disease

AbstractBackgroundIt is well known that mild cognitive impairment (MCI) is associated with subtle functional decline. However, standardized and cost‐effective methods for the objective quantification of mild functional difficulties are lacking. Here we report preliminary validity data for a novel, non‐immersive virtual‐reality task (Virtual Kitchen Challenge [VKC]) against brain markers of cerebrovascular disease and in contrast to a conventional, self‐report measure of function.MethodTwenty (n = 14 healthy control, n = 6 MCI) community‐dwelling older adults aged 60+ completed neuropsychological testing, including the Functional Activities Questionnaire (FAQ), and the VKC, which requires completion of simulated breakfast and lunch tasks on a touch‐screen computer. White matter hyperintensity (WMH) volumes from Fluid Attenuation Inversion Recovery (FLAIR) MRI sequences were derived using the UBO detector, a cluster‐based WMH extraction pipeline based on k‐nearest neighbors (k‐NN) algorithm. WMH volumes were calculated in SPM’s DARTEL space, precluding the need to adjust for intracranial volume (ICV).ResultMCI participants reported significantly more functional difficulties than healthy controls (FAQ U = 76.50 p = .002) and obtained marginally slower completion times on the VKC (U = 60.00, p = .138). VKC completion time was moderately associated with age (r = .441, p = .059) but relations with sex, race, and IQ were weak and not significant (all rs&lt;.195). VKC completion time significantly and strongly correlated with all WMH measures, even after controlling for age, sex, race, and IQ (total WMH r = .649, p = .031; deep WMH r = .615, p = .044; periventricular WMH r = .623, p = .041). By contrast, FAQ was not associated with WMH (rs&lt;.2, p&gt;.05 for all) or VKC completion time (r&lt;.1, p&gt;05) after controlling for age, sex, race, and IQ.ConclusionOur naturalistic, performance‐based measure of function (VKC) was not associated with race, sex, or premorbid IQ, but was strongly associated with neuroimaging markers of cerebrovascular disease (WMH). By contrast, a conventional self‐report measure of everyday functioning (FAQ) was not associated with neuroimaging measures (WMH). These results offer preliminary support for the VKC as a valid measure of early, subtle functional difficulties associated with cerebrovascular pathology that is not vulnerable to bias associated with race, sex, or premorbid IQ.

Neuroimaging Characteristics of Hearing Loss in the Mayo Clinic Study of Aging.

To investigate the association between standard pure tone and speech audiometry with neuroimaging characteristics reflective of aging and dementia in older adults. Prospective population-based study. Single tertiary care referral center. Participants from the Mayo Clinic Study of aging 60 years old or older with normal cognition or mild cognitive impairment, baseline neuroimaging, and a behavioral audiogram associated with neuroimaging were eligible for study. Imaging modalities included structural MRI (sMRI) and fluid-attenuated inversion recovery MRI (FLAIR-MRI; N = 605), diffusion tensor imaging MRI (DTI-MRI; N = 444), and fluorodeoxyglucose-positron emission tomography (FDG-PET; N = 413). Multivariable logistic and linear regression models were used to evaluate associations with neuroimaging outcomes. Mean (SD) pure tone average (PTA) was 33 (15) dB HL and mean (SD) word recognition score (WRS) was 91% (14). There were no significant associations between audiometric performance and cortical thinning assessed by sMRI. Each 10-dB increase in PTA was associated with increased likelihood of abnormal white-matter hyperintensity (WMH) from FLAIR-MRI (odds ratio 1.26, P = .02). From DTI-MRI, participants with <100% WRSs had significantly lower fractional anisotropy in the genu of the corpus callosum (parameter estimate [PE] -0.012, P = .008) compared to those with perfect WRSs. From FDG-PET, each 10% decrease in WRSs was associated with decreased uptake in the anterior cingulate cortex (PE -0.013, P = .001). Poorer audiometric performance was not significantly associated with cortical thinning but was associated with white matter damage relevant to cerebrovascular disease (increased abnormal WMH, decreased corpus callosum diffusion). These neuroimaging results suggest a pathophysiologic link between hearing loss and cerebrovascular disease.

T1-weighted fast fluid-attenuated inversion-recovery sequence (T1-FFLAIR) enables the visualization and quantification of fetal brain myelination in utero.

To investigate the advantage of T1-weighted fast fluid-attenuated inversion-recovery MRI sequence without (T1-FFLAIR) and with compressed sensing technology (T1-FFLAIR-CS), which shows improved T1-weighted contrast, over standard used T1-weighted fast field echo (T1-FFE) sequence for the assessment of fetal myelination. This retrospective single-center study included 115 consecutive fetal brain MRI examinations (63 axial and 76 coronal, mean gestational age (GA) 28.56 ± 5.23weeks, range 19-39weeks). Two raters, blinded to GA, qualitatively assessed a fetal myelin total score (MTS) on each T1-weighted sequence at five brain regions (medulla oblongata, pons, mesencephalon, thalamus, central region). One rater performed region-of-interest quantitative analysis (n = 61) at the same five brain regions. Pearson correlation analysis was applied for correlation of MTS and of the signal intensity ratios (relative to muscle) with GA on each T1-weighted sequence. Fetal MRI-based results were compared with myelination patterns of postmortem fetal human brains (n = 46; GA 18 to 42), processed by histological and immunohistochemical analysis. MTS positively correlated with GA on all three sequences (all r between 0.802 and 0.908). The signal intensity ratios measured at the five brain regions correlated best with GA on T1-FFLAIR (r between 0.583 and 0.785). T1-FFLAIR demonstrated significantly better correlations with GA than T1-FFE for both qualitative and quantitative analysis (all p < 0.05). Furthermore, T1-FFLAIR enabled the best visualization of myelinated brain structures when compared to histology. T1-FFLAIR outperforms the standard T1-FFE sequence in the visualization of fetal brain myelination, as demonstrated by qualitative and quantitative methods. T1-weighted fast fluid-attenuated inversion-recovery sequence (T1-FFLAIR) provided best visualization and quantification of myelination in utero that, in addition to the relatively short acquisition time, makes feasible its routine application in fetal MRI for the assessment of brain myelination. • So far, the assessment of fetal myelination in utero was limited due to the insufficient contrast. • T1-weighted fast fluid-attenuated inversion-recovery sequence allows a qualitative and quantitative assessment of fetal brain myelination. • T1-weighted fast fluid-attenuated inversion-recovery sequence outperforms the standard used T1-weighted sequence for visualization and quantification of myelination in utero.

Harnessing cognitive trajectory clusterings to examine subclinical decline risk factors.

Cognitive decline in Alzheimer's disease and other dementias typically begins long before clinical impairment. Identifying people experiencing subclinical decline may facilitate earlier intervention. This study developed cognitive trajectory clusters using longitudinally based random slope and change point parameter estimates from a Preclinical Alzheimer's disease Cognitive Composite and examined how baseline and most recently available clinical/health-related characteristics, cognitive statuses and biomarkers for Alzheimer's disease and vascular disease varied across these cognitive clusters. Data were drawn from the Wisconsin Registry for Alzheimer's Prevention, a longitudinal cohort study of adults from late midlife, enriched for a parental history of Alzheimer's disease and without dementia at baseline. Participants who were cognitively unimpaired at the baseline visit with ≥3 cognitive visits were included in trajectory modelling (n = 1068). The following biomarker data were available for subsets: positron emission tomography amyloid (amyloid: n = 367; [11C]Pittsburgh compound B (PiB): global PiB distribution volume ratio); positron emission tomography tau (tau: n = 321; [18F]MK-6240: primary regions of interest meta-temporal composite); MRI neurodegeneration (neurodegeneration: n = 581; hippocampal volume and global brain atrophy); T2 fluid-attenuated inversion recovery MRI white matter ischaemic lesion volumes (vascular: white matter hyperintensities; n = 419); and plasma pTau217 (n = 165). Posterior median estimate person-level change points, slopes' pre- and post-change point and estimated outcome (intercepts) at change point for cognitive composite were extracted from Bayesian Bent-Line Regression modelling and used to characterize cognitive trajectory groups (K-means clustering). A common method was used to identify amyloid/tau/neurodegeneration/vascular biomarker thresholds. We compared demographics, last visit cognitive status, health-related factors and amyloid/tau/neurodegeneration/vascular biomarkers across the cognitive groups using ANOVA, Kruskal-Wallis, χ2, and Fisher's exact tests. Mean (standard deviation) baseline and last cognitive assessment ages were 58.4 (6.4) and 66.6 (6.6) years, respectively. Cluster analysis identified three cognitive trajectory groups representing steep, n = 77 (7.2%); intermediate, n = 446 (41.8%); and minimal, n = 545 (51.0%) cognitive decline. The steep decline group was older, had more females, APOE e4 carriers and mild cognitive impairment/dementia at last visit; it also showed worse self-reported general health-related and vascular risk factors and higher amyloid, tau, neurodegeneration and white matter hyperintensity positive proportions at last visit. Subtle cognitive decline was consistently evident in the steep decline group and was associated with generally worse health. In addition, cognitive trajectory groups differed on aetiology-informative biomarkers and risk factors, suggesting an intimate link between preclinical cognitive patterns and amyloid/tau/neurodegeneration/vascular biomarker differences in late middle-aged adults. The result explains some of the heterogeneity in cognitive performance within cognitively unimpaired late middle-aged adults.

Leukoaraiosis Is Not Associated With Recovery From Aphasia in the First Year After Stroke.

After a stroke, individuals with aphasia often recover to a certain extent over time. This recovery process may be dependent on the health of surviving brain regions. Leukoaraiosis (white matter hyperintensities on MRI reflecting cerebral small vessel disease) is one indication of compromised brain health and is associated with cognitive and motor impairment. Previous studies have suggested that leukoaraiosis may be a clinically relevant predictor of aphasia outcomes and recovery, although findings have been inconsistent. We investigated the relationship between leukoaraiosis and aphasia in the first year after stroke. We recruited 267 patients with acute left hemispheric stroke and coincident fluid attenuated inversion recovery MRI. Patients were evaluated for aphasia within 5 days of stroke, and 174 patients presented with aphasia acutely. Of these, 84 patients were evaluated at ∼3 months post-stroke or later to assess longer-term speech and language outcomes. Multivariable regression models were fit to the data to identify any relationships between leukoaraiosis and initial aphasia severity, extent of recovery, or longer-term aphasia severity. We found that leukoaraiosis was present to varying degrees in 90% of patients. However, leukoaraiosis did not predict initial aphasia severity, aphasia recovery, or longer-term aphasia severity. The lack of any relationship between leukoaraiosis severity and aphasia recovery may reflect the anatomical distribution of cerebral small vessel disease, which is largely medial to the white matter pathways that are critical for speech and language function.

Diagnostic Accuracy of MR Spectroscopic Imaging and 18F-FET PET for Identifying Glioma: A Biopsy-Controlled Hybrid PET/MRI Study.

Contrast-enhanced MRI is the method of choice for brain tumor diagnostics, despite its low specificity for tumor tissue. This study compared the contribution of MR spectroscopic imaging (MRSI) and amino acid PET to improve the detection of tumor tissue. Methods: In 30 untreated patients with suspected glioma, O-(2-[18F]fluoroethyl)-l-tyrosine (18F-FET) PET; 3-T MRSI with a short echo time; and fluid-attenuated inversion recovery, T2-weighted, and contrast-enhanced T1-weighted MRI were performed for stereotactic biopsy planning. Serial samples were taken along the needle trajectory, and their masks were projected to the preoperative imaging data. Each sample was individually evaluated neuropathologically. 18F-FET uptake and the MRSI signals choline (Cho), N-acetyl-aspartate (NAA), creatine, myoinositol, and derived ratios were evaluated for each sample and classified using logistic regression. The diagnostic accuracy was evaluated by receiver operating characteristic analysis. Results: On the basis of the neuropathologic evaluation of tissue from 88 stereotactic biopsies, supplemented with 18F-FET PET and MRSI metrics from 20 areas on the healthy-appearing contralateral hemisphere to balance the glioma/nonglioma groups, 18F-FET PET identified glioma with the highest accuracy (area under the receiver operating characteristic curve, 0.89; 95% CI, 0.81-0.93; threshold, 1.4 × background uptake). Among the MR spectroscopic metabolites, Cho/NAA normalized to normal brain tissue showed the highest diagnostic accuracy (area under the receiver operating characteristic curve, 0.81; 95% CI, 0.71-0.88; threshold, 2.2). The combination of 18F-FET PET and normalized Cho/NAA did not improve the diagnostic performance. Conclusion: MRI-based delineation of gliomas should preferably be supplemented by 18F-FET PET.