Sensitivity of unconstrained quantitative magnetization transfer MRI to Amyloid burden in preclinical Alzheimer's disease.

Introduction: Magnetization transfer MRI is sensitive to semi-solid macromolecules, including amyloid beta, and has been used to discriminate Alzheimer's disease (AD) patients from controls. Here, we utilize an unconstrained 2-pool quantitative MT (qMT) approach that quantifies the longitudinal relaxation rates of free water and semi-solids separately, and investigate its sensitivity to amyloid accumulation in preclinical subjects. Methods: We recruited 15 cognitively normal subjects, of which nine were amyloid positive by [ 18 F]Florbetaben PET. A 12 min qMT scan was used to estimate the unconstrained 2-pool qMT parameters. Group comparisons and correlations were analyzed at the lobar level. Results: The exchange rate and semi-solid pool's were sensitive to the amyloid concentration. The former finding is consistent with previous reports in clinical AD, but the latter is novel as its value is typically constrained. Discussion: qMT MRI may be a promising surrogate marker of amyloid beta without the need for contrast agents or radiotracers.

Brain Fluid Clearance After Traumatic Brain Injury Measured Using Dynamic Positron Emission Tomography.

Brain fluid clearance by pathways including the recently described paravascular glymphatic system is a critical homeostatic mechanism by which metabolic products, toxins, and other wastes are removed from the brain. Brain fluid clearance may be especially important after traumatic brain injury (TBI), when blood, neuronal debris, inflammatory cells, and other substances can be released and/or deposited. Using a non-invasive dynamic positron emission tomography (PET) method that models the rate at which an intravenously injected radiolabeled molecule (in this case 11C-flumazenil) is cleared from ventricular cerebrospinal fluid (CSF), we estimated the overall efficiency of brain fluid clearance in humans who had experienced complicated-mild or moderate TBI 3-6 months before neuroimaging (n = 7) as compared to healthy controls (n = 9). While there was no significant difference in ventricular clearance between TBI subjects and controls, there was a significant group difference in dependence of ventricular clearance upon tracer delivery/blood flow to the ventricles. Specifically, in controls, ventricular clearance was highly, linearly dependent upon blood flow to the ventricle, but this relation was disrupted in TBI subjects. When accounting for blood flow and group-specific alterations in blood flow, ventricular clearance was slightly (non-significantly) increased in TBI subjects as compared to controls. Current results contrast with past studies showing reduced glymphatic function after TBI and are consistent with possible differential effects of TBI on glymphatic versus non-glymphatic clearance mechanisms. Further study using multi-modal methods capable of assessing and disentangling blood flow and different aspects of fluid clearance is needed to clarify clearance alterations after TBI.

[1-11C]-Butanol Positron Emission Tomography reveals an impaired brain to nasal turbinates pathway in aging amyloid positive subjects.

BACKGROUND: Reduced clearance of cerebrospinal fluid (CSF) has been suggested as a pathological feature of Alzheimer's disease (AD). With extensive documentation in non-human mammals and contradictory human neuroimaging data it remains unknown whether the nasal mucosa is a CSF drainage site in humans. Here, we used dynamic PET with [1-11C]-Butanol, a highly permeable radiotracer with no appreciable brain binding, to test the hypothesis that tracer drainage from the nasal pathway reflects CSF drainage from brain. As a test of the hypothesis, we examined whether brain and nasal fluid drainage times were correlated and affected by brain amyloid. METHODS: 24 cognitively normal subjects (≥ 65 years) were dynamically PET imaged for 60 min. using [1-11C]-Butanol. Imaging with either [11C]-PiB or [18F]-FBB identified 8 amyloid PET positive (Aß+) and 16 Aß- subjects. MRI-determined regions of interest (ROI) included: the carotid artery, the lateral orbitofrontal (LOF) brain, the cribriform plate, and an All-turbinate region comprised of the superior, middle, and inferior turbinates. The bilateral temporalis muscle and jugular veins served as control regions. Regional time-activity were used to model tracer influx, egress, and AUC. RESULTS: LOF and All-turbinate 60 min AUC were positively associated, thus suggesting a connection between the brain and the nose. Further, the Aß+ subgroup demonstrated impaired tracer kinetics, marked by reduced tracer influx and slower egress. CONCLUSION: The data show that tracer kinetics for brain and nasal turbinates are related to each other and both reflect the amyloid status of the brain. As such, these data add to evidence that the nasal pathway is a potential CSF drainage site in humans. These data warrant further investigation of brain and nasal contributions to protein clearance in neurodegenerative disease.

The neutrophil to lymphocyte ratio associates with markers of Alzheimer's disease pathology in cognitively unimpaired elderly people.

Background: An elevated neutrophil-lymphocyte ratio (NLR) in blood has been associated with Alzheimer's disease (AD). However, an elevated NLR has also been implicated in many other conditions that are risk factors for AD, prompting investigation into whether the NLR is directly linked with AD pathology or a result of underlying comorbidities. Herein, we explored the relationship between the NLR and AD biomarkers in the cerebrospinal fluid (CSF) of cognitively unimpaired (CU) subjects. Adjusting for sociodemographics, APOE4, and common comorbidities, we investigated these associations in two cohorts: the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the M.J. de Leon CSF repository at NYU. Specifically, we examined associations between the NLR and cross-sectional measures of amyloid-ß42 (Aß42), total tau (t-tau), and phosphorylated tau181 (p-tau), as well as the trajectories of these CSF measures obtained longitudinally. Results: A total of 111 ADNI and 190 NYU participants classified as CU with available NLR, CSF, and covariate data were included. Compared to NYU, ADNI participants were older (73.79 vs. 61.53, p < 0.001), had a higher proportion of males (49.5% vs. 36.8%, p = 0.042), higher BMIs (27.94 vs. 25.79, p < 0.001), higher prevalence of hypertensive history (47.7% vs. 16.3%, p < 0.001), and a greater percentage of Aß-positivity (34.2% vs. 20.0%, p = 0.009). In the ADNI cohort, we found cross-sectional associations between the NLR and CSF Aß42 (ß=-12.193, p = 0.021), but not t-tau or p-tau. In the NYU cohort, we found cross-sectional associations between the NLR and CSF t-tau (ß = 26.812, p = 0.019) and p-tau (ß = 3.441, p = 0.015), but not Aß42. In the NYU cohort alone, subjects classified as Aß+ (n = 38) displayed a stronger association between the NLR and t-tau (ß = 100.476, p = 0.037) compared to Aß- subjects or the non-stratified cohort. In both cohorts, the same associations observed in the cross-sectional analyses were observed after incorporating longitudinal CSF data. Conclusions: We report associations between the NLR and Aß42 in the older ADNI cohort, and between the NLR and t-tau and p-tau181 in the younger NYU cohort. Associations persisted after adjusting for comorbidities, suggesting a direct link between the NLR and AD. However, changes in associations between the NLR and specific AD biomarkers may occur as part of immunosenescence.

Quantitative Characterization of Respiratory Patterns on Dynamic Higher Temporal Resolution MRI to Stratify Postacute Covid-19 Patients by Cardiopulmonary Symptom Burden.

BACKGROUND: Postacute Covid-19 patients commonly present with respiratory symptoms; however, a noninvasive imaging method for quantitative characterization of respiratory patterns is lacking. PURPOSE: To evaluate if quantitative characterization of respiratory pattern on free-breathing higher temporal resolution MRI stratifies patients by cardiopulmonary symptom burden. STUDY TYPE: Prospective analysis of retrospectively acquired data. SUBJECTS: A total of 37 postacute Covid-19 patients (25 male; median [interquartile range (IQR)] age: 58 [42-64] years; median [IQR] days from acute infection: 335 [186-449]). FIELD STRENGTH/SEQUENCE: 0.55 T/two-dimensional coronal true fast imaging with steady-state free precession (trueFISP) at higher temporal resolution. ASSESSMENT: Patients were stratified into three groups based on presence of no (N = 11), 1 (N = 14), or ≥2 (N = 14) cardiopulmonary symptoms, assessed using a standardized symptom inventory within 1 month of MRI. An automated lung postprocessing workflow segmented each lung in each trueFISP image (temporal resolution 0.2 seconds) and respiratory curves were generated. Quantitative parameters were derived including tidal lung area, rates of inspiration and expiration, lung area coefficient of variability (CV), and respiratory incoherence (departure from sinusoidal pattern) were. Pulmonary function tests were recorded if within 1 month of MRI. Qualitative assessment of respiratory pattern and lung opacity was performed by three independent readers with 6, 9, and 23 years of experience. STATISTICAL TESTS: Analysis of variance to assess differences in demographic, clinical, and quantitative MRI parameters among groups; univariable analysis and multinomial logistic regression modeling to determine features predictive of patient symptom status; Akaike information criterion to compare the quality of regression models; Cohen and Fleiss kappa (κ) to quantify inter-reader reliability. Two-sided 5% significance level was used. RESULTS: Tidal area and lung area CV were significantly higher in patients with two or more symptoms than in those with one or no symptoms (area: 15.4 cm2 vs. 12.9 cm2 vs. 12.8 cm2 ; CV: 0.072, 0.067, and 0.058). Respiratory incoherence was significantly higher in patients with two or more symptoms than in those with one or no symptoms (0.05 vs. 0.043 vs. 0.033). There were no significant differences in patient age (P = 0.19), sex (P = 0.88), lung opacity severity (P = 0.48), or pulmonary function tests (P = 0.35-0.97) among groups. Qualitative reader assessment did not distinguish between groups and showed slight inter-reader agreement (κ = 0.05-0.11). DATA CONCLUSION: Quantitative respiratory pattern measures derived from dynamic higher-temporal resolution MRI have potential to stratify patients by symptom burden in a postacute Covid-19 cohort. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 3.

The ISMRM Open Science Initiative for Perfusion Imaging (OSIPI): Results from the OSIPI-Dynamic Contrast-Enhanced challenge.

PURPOSE: K trans $$ {K}^{\mathrm{trans}} $$ has often been proposed as a quantitative imaging biomarker for diagnosis, prognosis, and treatment response assessment for various tumors. None of the many software tools for K trans $$ {K}^{\mathrm{trans}} $$ quantification are standardized. The ISMRM Open Science Initiative for Perfusion Imaging-Dynamic Contrast-Enhanced (OSIPI-DCE) challenge was designed to benchmark methods to better help the efforts to standardize K trans $$ {K}^{\mathrm{trans}} $$ measurement. METHODS: A framework was created to evaluate K trans $$ {K}^{\mathrm{trans}} $$ values produced by DCE-MRI analysis pipelines to enable benchmarking. The perfusion MRI community was invited to apply their pipelines for K trans $$ {K}^{\mathrm{trans}} $$ quantification in glioblastoma from clinical and synthetic patients. Submissions were required to include the entrants' K trans $$ {K}^{\mathrm{trans}} $$ values, the applied software, and a standard operating procedure. These were evaluated using the proposed OSIP I gold $$ \mathrm{OSIP}{\mathrm{I}}_{\mathrm{gold}} $$ score defined with accuracy, repeatability, and reproducibility components. RESULTS: Across the 10 received submissions, the OSIP I gold $$ \mathrm{OSIP}{\mathrm{I}}_{\mathrm{gold}} $$ score ranged from 28% to 78% with a 59% median. The accuracy, repeatability, and reproducibility scores ranged from 0.54 to 0.92, 0.64 to 0.86, and 0.65 to 1.00, respectively (0-1 = lowest-highest). Manual arterial input function selection markedly affected the reproducibility and showed greater variability in K trans $$ {K}^{\mathrm{trans}} $$ analysis than automated methods. Furthermore, provision of a detailed standard operating procedure was critical for higher reproducibility. CONCLUSIONS: This study reports results from the OSIPI-DCE challenge and highlights the high inter-software variability within K trans $$ {K}^{\mathrm{trans}} $$ estimation, providing a framework for ongoing benchmarking against the scores presented. Through this challenge, the participating teams were ranked based on the performance of their software tools in the particular setting of this challenge. In a real-world clinical setting, many of these tools may perform differently with different benchmarking methodology.

A multiphysics model to predict periventricular white matter hyperintensity growth during healthy brain aging.

Periventricular white matter hyperintensities (WMH) are a common finding in medical images of the aging brain and are associated with white matter damage resulting from cerebral small vessel disease, white matter inflammation, and a degeneration of the lateral ventricular wall. Despite extensive work, the etiology of periventricular WMHs remains unclear. We pose that there is a strong coupling between age-related ventricular expansion and the degeneration of the ventricular wall which leads to a dysregulated fluid exchange across this brain-fluid barrier. Here, we present a multiphysics model that couples cerebral atrophy-driven ventricular wall loading with periventricular WMH formation and progression. We use patient data to create eight 2D finite element models and demonstrate the predictive capabilities of our damage model. Our simulations show that we accurately capture the spatiotemporal features of periventricular WMH growth. For one, we observe that damage appears first in both the anterior and posterior horns and then spreads into deeper white matter tissue. For the other, we note that it takes up to 12 years before periventricular WMHs first appear and derive an average annualized periventricular WMH damage growth rate of 15.2 ± 12.7 mm2/year across our models. A sensitivity analysis demonstrated that our model parameters provide sufficient sensitivity to rationalize subject-specific differences with respect to onset time and damage growth. Moreover, we show that the septum pellucidum, a membrane that separates the left and right lateral ventricles, delays the onset of periventricular WMHs at first, but leads to a higher WMH load in the long-term.

Mechanical loading of the ventricular wall as a spatial indicator for periventricular white matter degeneration.

Progressive white matter degeneration in periventricular and deep white matter regions appears as white matter hyperintensities (WMH) on MRI scans. To date, periventricular WMHs are often associated with vascular dysfunction. Here, we demonstrate that ventricular inflation resulting from cerebral atrophy and hemodynamic pulsation with every heartbeat leads to a mechanical loading state of periventricular tissues that significantly affects the ventricular wall. Specifically, we present a physics-based modeling approach that provides a rationale for ependymal cell involvement in periventricular WMH formation. Building on eight previously created 2D finite element brain models, we introduce novel mechanomarkers for ependymal cell loading and geometric measures that characterize lateral ventricular shape. We show that our novel mechanomarkers, such as maximum ependymal cell deformations and maximum curvature of the ventricular wall, spatially overlap with periventricular WMH locations and are sensitive predictors for WMH formation. We also explore the role of the septum pellucidum in mitigating mechanical loading of the ventricular wall by constraining the radial expansion of the lateral ventricles during loading. Our models consistently show that ependymal cells are stretched thin only in the horns of the ventricles irrespective of ventricular shape. We therefore pose that periventricular WMH etiology is strongly linked to the deterioration of the over-stretched ventricular wall resulting in CSF leakage into periventricular white matter. Subsequent secondary damage mechanisms, including vascular degeneration, exacerbate lesion formation and lead to progressive growth into deep white matter regions.

Quadratic relationship between systolic blood pressure and white matter lesions in individuals with hypertension.

BACKGROUND: There is a well documented relationship between cardiovascular risk factors and the development of brain injury, which can lead to cognitive dysfunction. Hypertension (HTN) is a condition increasing the risk of silent and symptomatic ischemic brain lesions. Although benefits of hypertension treatment are indisputable, the target blood pressure value where the possibility of tissue damage is most reduced remains under debate. METHOD: Our group performed a cross-sectional ( n  = 376) and longitudinal ( n  = 188) study of individuals without dementia or stroke (60% women n  = 228, age 68.5 ±â€Š7.4 years; men n  = 148, age 70.7 ±â€Š6.9 years). Participants were split into hypertensive ( n  = 169) and normotensive ( n  = 207) groups. MR images were obtained on a 3T system. Linear modeling was performed in hypertensive and normotensive cohorts to investigate the relationship between systolic (SBP) and diastolic (DBP) blood pressure, white matter lesion (WML), and brain volumes. RESULTS: Participants in the hypertensive cohort showed a quadratic relationship between SBP and WML, with the lowest amounts of WML being measured in participants with readings at approximately 124 mmHg. Additionally, the hypertensive cohort also exhibited a quadratic relationship between DBP and mean hippocampal volume; participants with readings at approximately 77 mmHg showing the largest volumes. Longitudinally, all groups experienced WML growth, despite different BP trajectories, further suggesting that WML expansion may occur despite or because of BP reduction in individuals with compromised vascular system. CONCLUSION: Overall, our study suggests that in the hypertensive group there is a valley of mid-range blood pressures displaying less pathology in the brain.

Cortical myelin profile variations in healthy aging brain: A T1w/T2w ratio study.

Demyelination is observed in both healthy aging and age-related neurodegenerative disorders. While the significance of myelin within the cortex is well acknowledged, studies focused on intracortical demyelination and depth-specific structural alterations in normal aging are lacking. Using the recently available Human Connectome Project Aging dataset, we investigated intracortical myelin in a normal aging population using the T1w/T2w ratio. To capture the fine changes across cortical depths, we employed a surface-based approach by constructing cortical profiles traveling perpendicularly through the cortical ribbon and sampling T1w/T2w values. The curvatures of T1w/T2w cortical profiles may be influenced by differences in local myeloarchitecture and other tissue properties, which are known to vary across cortical regions. To quantify the shape of these profiles, we parametrized the level of curvature using a nonlinearity index (NLI) that measures the deviation of the profile from a straight line. We showed that NLI exhibited a steep decline in aging that was independent of local cortical thinning. Further examination of the profiles revealed that lower T1w/T2w near the gray-white matter boundary and superficial cortical depths were major contributors to the apparent NLI variations with age. These findings suggest that demyelination and changes in other T1w/T2w related tissue properties in normal aging may be depth-specific and highlight the potential of NLI as a unique marker of microstructural alterations within the cerebral cortex.

Generalizable deep learning model for early Alzheimer's disease detection from structural MRIs.

Early diagnosis of Alzheimer's disease plays a pivotal role in patient care and clinical trials. In this study, we have developed a new approach based on 3D deep convolutional neural networks to accurately differentiate mild Alzheimer's disease dementia from mild cognitive impairment and cognitively normal individuals using structural MRIs. For comparison, we have built a reference model based on the volumes and thickness of previously reported brain regions that are known to be implicated in disease progression. We validate both models on an internal held-out cohort from The Alzheimer's Disease Neuroimaging Initiative (ADNI) and on an external independent cohort from The National Alzheimer's Coordinating Center (NACC). The deep-learning model is accurate, achieved an area-under-the-curve (AUC) of 85.12 when distinguishing between cognitive normal subjects and subjects with either MCI or mild Alzheimer's dementia. In the more challenging task of detecting MCI, it achieves an AUC of 62.45. It is also significantly faster than the volume/thickness model in which the volumes and thickness need to be extracted beforehand. The model can also be used to forecast progression: subjects with mild cognitive impairment misclassified as having mild Alzheimer's disease dementia by the model were faster to progress to dementia over time. An analysis of the features learned by the proposed model shows that it relies on a wide range of regions associated with Alzheimer's disease. These findings suggest that deep neural networks can automatically learn to identify imaging biomarkers that are predictive of Alzheimer's disease, and leverage them to achieve accurate early detection of the disease.

Higher body mass index is associated with worse hippocampal vasoreactivity to carbon dioxide.

Background and objectives: Obesity is a risk factor for cognitive decline. Probable mechanisms involve inflammation and cerebrovascular dysfunction, leading to diminished cerebral blood flow (CBF) and cerebrovascular reactivity (CVR). The hippocampus, crucially involved in memory processing and thus relevant to many types of dementia, poses a challenge in studies of perfusion and CVR, due to its location, small size, and complex shape. We examined the relationships between body mass index (BMI) and hippocampal resting CBF and CVR to carbon dioxide (CVRCO2) in a group of cognitively normal middle-aged and older adults. Methods: Our study was a retrospective analysis of prospectively collected data. Subjects were enrolled for studies assessing the role of hippocampal hemodynamics as a biomarker for AD among cognitively healthy elderly individuals (age > 50). Participants without cognitive impairment, stroke, and active substance abuse were recruited between January 2008 and November 2017 at the NYU Grossman School of Medicine, former Center for Brain Health. All subjects underwent medical, psychiatric, and neurological assessments, blood tests, and MRI examinations. To estimate CVR, we increased their carbon dioxide levels using a rebreathing protocol. Relationships between BMI and brain measures were tested using linear regression. Results: Our group (n = 331) consisted of 60.4% women (age 68.8 ± 7.5 years; education 16.8 ± 2.2 years) and 39.6% men (age 70.4 ± 6.4 years; education 16.9 ± 2.4 years). Approximately 22% of them (n = 73) were obese. BMI was inversely associated with CVRCO2 (ß = -0.12, unstandardized B = -0.06, 95% CI -0.11, -0.004). A similar relationship was observed after excluding subjects with diabetes and insulin resistance (ß = -0.15, unstandardized B = -0.08, 95% CI -0.16, -0.000). In the entire group, BMI was more strongly related to hippocampal CVRCO2 in women (ß = -0.20, unstandardized B = -0.08, 95% CI -0.13, -0.02). Discussion: These findings lend support to the notion that obesity is a risk factor for hippocampal hemodynamic impairment and suggest targeting obesity as an important prevention strategy. Prospective studies assessing the effects of weight loss on brain hemodynamic measures and inflammation are warranted.

Reduced white matter venous density on MRI is associated with neurodegeneration and cognitive impairment in the elderly.

High-resolution susceptibility weighted imaging (SWI) provides unique contrast to small venous vasculature. The conspicuity of these mesoscopic veins, such as deep medullary veins in white matter, is subject to change from SWI venography when venous oxygenation in these veins is altered due to oxygenated blood susceptibility changes. The changes of visualization in small veins shows potential to depict regional changes of oxygen utilization and/or vascular density changes in the aging brain. The goal of this study was to use WM venous density to quantify small vein visibility in WM and investigate its relationship with neurodegenerative features, white matter hyperintensities (WMHs), and cognitive/functional status in elderly subjects (N = 137). WM venous density was significantly associated with neurodegeneration characterized by brain atrophy (ß = 0.046± 0.01, p < 0.001), but no significant association was found between WM venous density and WMHs lesion load (p = 0.3963). Further analysis of clinical features revealed a negative trend of WM venous density with the sum-of-boxes of Clinical Dementia Rating and a significant association with category fluency (1-min animal naming). These results suggest that WM venous density on SWI can be used as a sensitive marker to characterize cerebral oxygen metabolism and different stages of cognitive and functional status in neurodegenerative diseases.

Positron Emission Tomography reveals age-associated hypothalamic microglial activation in women.

In rodents, hypothalamic inflammation plays a critical role in aging and age-related diseases. Hypothalamic inflammation has not previously been assessed in vivo in humans. We used Positron Emission Tomography (PET) with a radiotracer sensitive to the translocator protein (TSPO) expressed by activated microglia, to assess correlations between age and regional brain TSPO in a group of healthy subjects (n = 43, 19 female, aged 23-78), focusing on hypothalamus. We found robust age-correlated TSPO expression in thalamus but not hypothalamus in the combined group of women and men. This pattern differs from what has been described in rodents. Prominent age-correlated TSPO expression in thalamus in humans, but in hypothalamus in rodents, could reflect evolutionary changes in size and function of thalamus versus hypothalamus, and may be relevant to the appropriateness of using rodents to model human aging. When examining TSPO PET results in women and men separately, we found that only women showed age-correlated hypothalamic TSPO expression. We suggest this novel result is relevant to understanding a stark sex difference in human aging: that only women undergo loss of fertility-menopause-at mid-life. Our finding of age-correlated hypothalamic inflammation in women could have implications for understanding and perhaps altering reproductive aging in women.

Deep Learning Achieves Neuroradiologist-Level Performance in Detecting Hydrocephalus Requiring Treatment.

In large clinical centers a small subset of patients present with hydrocephalus that requires surgical treatment. We aimed to develop a screening tool to detect such cases from the head MRI with performance comparable to neuroradiologists. We leveraged 496 clinical MRI exams collected retrospectively at a single clinical site from patients referred for any reason. This diagnostic dataset was enriched to have 259 hydrocephalus cases. A 3D convolutional neural network was trained on 16 manually segmented exams (ten hydrocephalus) and subsequently used to automatically segment the remaining 480 exams and extract volumetric anatomical features. A linear classifier of these features was trained on 240 exams to detect cases of hydrocephalus that required treatment with surgical intervention. Performance was compared to four neuroradiologists on the remaining 240 exams. Performance was also evaluated on a separate screening dataset of 451 exams collected from a routine clinical population to predict the consensus reading from four neuroradiologists using images alone. The pipeline was also tested on an external dataset of 31 exams from a 2nd clinical site. The most discriminant features were the Magnetic Resonance Hydrocephalic Index (MRHI), ventricle volume, and the ratio between ventricle and brain volume. At matching sensitivity, the specificity of the machine and the neuroradiologists did not show significant differences for detection of hydrocephalus on either dataset (proportions test, p > 0.05). ROC performance compared favorably with the state-of-the-art (AUC 0.90-0.96), and replicated in the external validation. Hydrocephalus cases requiring treatment can be detected automatically from MRI in a heterogeneous patient population based on quantitative characterization of brain anatomy with performance comparable to that of neuroradiologists.

Radiomics-Based Image Phenotyping of Kidney Apparent Diffusion Coefficient Maps: Preliminary Feasibility & Efficacy.

Given the central role of interstitial fibrosis in disease progression in chronic kidney disease (CKD), a role for diffusion-weighted MRI has been pursued. We evaluated the feasibility and preliminary efficacy of using radiomic features to phenotype apparent diffusion coefficient (ADC) maps and hence to the clinical classification(s) of the participants. The study involved 40 individuals (10 healthy and 30 with CKD (eGFR < 60 mL/min/1.73 m2)). Machine learning methods, such as hierarchical clustering and logistic regression, were used. Clustering resulted in the identification of two clusters, one including all individuals with CKD (n = 17), while the second one included all the healthy volunteers (n = 10) and the remaining individuals with CKD (n = 13), resulting in 100% specificity. Logistic regression identified five radiomic features to classify participants as with CKD vs. healthy volunteers, with a sensitivity and specificity of 93% and 70%, respectively, and an AUC of 0.95. Similarly, four radiomic features were able to classify participants as rapid vs. non-rapid CKD progressors among the 30 individuals with CKD, with a sensitivity and specificity of 71% and 43%, respectively, and an AUC of 0.75. These promising preliminary data should support future studies with larger numbers of participants with varied disease severity and etiologies to improve performance.

Decreased CSF clearance and increased brain amyloid in Alzheimer's disease.

BACKGROUND: In sporadic Alzheimer's disease (AD), brain amyloid-beta (Aß) deposition is believed to be a consequence of impaired Aß clearance, but this relationship is not well established in living humans. CSF clearance, a major feature of brain glymphatic clearance (BGC), has been shown to be abnormal in AD murine models. MRI phase contrast and intrathecally delivered contrast studies have reported reduced CSF flow in AD. Using PET and tau tracer 18F-THK5117, we previously reported that the ventricular CSF clearance of the PET tracer was reduced in AD and associated with elevated brain Aß levels. METHODS: In the present study, we use two PET tracers, 18F-THK5351 and 11C-PiB to estimate CSF clearance calculated from early dynamic PET frames in 9 normal controls and 15 AD participants. RESULTS: we observed that the ventricular CSF clearance measures were correlated (r = 0.66, p < 0.01), with reductions in AD of 18 and 27%, respectively. We also replicated a significant relationship between ventricular CSF clearance (18F-THK5351) and brain Aß load (r = - 0.64, n = 24, p < 0.01). With a larger sample size, we extended our observations to show that reduced CSF clearance is associated with reductions in cortical thickness and cognitive performance. CONCLUSIONS: Overall, the findings support the hypothesis that failed CSF clearance is a feature of AD that is related to Aß deposition and to the pathology of AD. Longitudinal studies are needed to determine whether failed CSF clearance is a predictor of progressive amyloidosis or its consequence.

Repeatability, robustness, and reproducibility of texture features on 3 Tesla liver MRI.

OBJECTIVE: Texture features are proposed for classification and prognostication, with lacking information about variability. We assessed 3 T liver MRI feature variability. METHODS: Five volunteers underwent standard 3 T MRI, and repeated with identical and altered parameters. Two readers placed regions of interest using 3DSlicer. Repeatability (between standard and repeat scan), robustness (between standard and parameter changed scan), and reproducibility (two reader variation) were computed using coefficient of variation (CV). RESULTS: 67%, 49%, and 61% of features had good-to-excellent (CV ≤ 10%) repeatability on ADC, T1, and T2, respectively, least frequently for first order (19-35%). 22%, 19%, and 21% of features had good-to-excellent robustness on ADC, T1, and T2, respectively. 52%, 35%, and 25% of feature measurements had good-to-excellent inter-reader reproducibility on ADC, T1, and T2, respectively, with highest good-to-excellent reproducibility for first order features on ADC/T1. CONCLUSION: We demonstrated large variations in texture features on 3 T liver MRI. Further study should evaluate methods to reduce variability.