Hippocampal connectivity and memory decline in cognitively intact APOE ε4 carriers.

INTRODUCTION: Resting-state functional magnetic resonance imaging (fMRI) graph theory may help detect subtle functional connectivity changes affecting memory prior to impairment. METHODS: Cognitively normal apolipoprotein E (APOE) ε4 carriers/noncarriers underwent longitudinal cognitive assessment and one-time MRI. The relationship of left/right hippocampal connectivity and memory trajectory were compared between carriers/noncarriers. RESULTS: Steepness of verbal memory decline correlated with decreased connectivity in the left hippocampus, only among APOE ε4 carriers. Right hippocampal metrics were not correlated with memory and there were no significant correlations in the noncarriers. Verbal memory decline correlated with left hippocampal volume loss for both carriers and noncarriers, with no other significant volumetric findings. DISCUSSION: Findings support early hippocampal dysfunction in intact carriers, the AD disconnection hypothesis, and left hippocampal dysfunction earlier than the right. Combining lateralized graph theoretical metrics with a sensitive measure of memory trajectory allowed for detection of early-stage changes in APOE ε4 carriers before symptoms of mild cognitive impairment are present. HIGHLIGHTS: Graph theory connectivity detects preclinical hippocampal changes in APOE ε4 carriers. The AD disconnection hypothesis was supported in unimpaired APOE ε4 carriers. Hippocampal dysfunction starts asymmetrically on the left.

Longitudinal Assessment of Intravoxel Incoherent Motion Diffusion-Weighted MRI Metrics in Cognitive Decline.

BACKGROUND: Advanced diffusion-based MRI biomarkers may provide insight into microstructural and perfusion changes associated with neurodegeneration and cognitive decline. PURPOSE: To assess longitudinal microstructural and perfusion changes using apparent diffusion coefficient (ADC) and intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) parameters in cognitively impaired (CI) and healthy control (HC) groups. STUDY TYPE: Prospective/longitudinal. POPULATION: Twelve CI patients (75% female) and 13 HC subjects (69% female). FIELD STRENGTH/SEQUENCE: 3 T; Spin-Echo-IVIM-DWI. ASSESSMENT: Two MRI scans were performed with a 12-month interval. ADC and IVIM-DWI metrics (diffusion coefficient [D] and perfusion fraction [f]) were generated from monoexponential and biexponential fits, respectively. Additionally, voxel-based correlations were evaluated between change in Montreal Cognitive Assessment (ΔMoCA) and baseline imaging parameters. STATISTICAL TESTS: Analysis of covariance with sex and age as covariates was performed for main effects of group and time (false discovery rate [FDR] corrected) with post hoc comparisons using Bonferroni correction. Partial-η2 and Hedges' g were used for effect-size analysis. Spearman's correlations (FDR corrected) were used for the relationship between ΔMoCA score and imaging. P < 0.05 was considered statistically significant. RESULTS: Significant differences were found for the main effects of group (HC vs. CI) and time. For group effects, higher ADC, IVIM-D, and IVIM-f were observed in the CI group compared to HC (ADC: 1.23 ± 0.08. 10-3 vs. 1.09 ± 0.07. 10-3  mm2 /sec; IVIM-D: 0.82 ± 0.01. 10-3 vs. 0.73 ± 0.01. 10-3  mm2 /sec; and IVIM-f: 0.317 ± 0.008 vs. 0.253 ± 0.009). Significantly higher ADC, IVIM-D, and IVIM-f values were observed in the CI group after 12 months (ADC: 1.45 ± 0.05. 10-3 vs. 1.50 ± 0.07. 10-3  mm2 /sec; IVIM-D: 0.87 ± 0.01. 10-3 vs. 0.94 ± 0.02. 10-3  mm2 /sec; and IVIM-f: 0.303 ± 0.007 vs. 0.332 ± 0.008), but not in the HC group at large effect size. ADC, IVIM-D, and IVIM-f negatively correlated with ΔMoCA score (ρ = -0.49, -0.51, and -0.50, respectively). DATA CONCLUSION: These findings demonstrate that longitudinal differences between CI and HC cohorts can be measured using IVIM-based metrics. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY STAGE: 2.

Preliminary Assessment of Intravoxel Incoherent Motion Diffusion-Weighted MRI (IVIM-DWI) Metrics in Alzheimer's Disease.

BACKGROUND: Alzheimer's disease (AD) is a progressive neurodegenerative disease that affects aging populations. Current MRI techniques are often limited in their sensitivity to underlying neuropathological changes. PURPOSE: To characterize differences in voxel-based morphometry (VBM), apparent diffusion coefficient (ADC), and intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) metrics in aging populations. Additionally, to investigate the connection between cognitive assessments and neuroimaging metrics. STUDY TYPE: Prospective/cross-sectional. POPULATION: In all, 49 subjects, including 13 with AD dementia, 12 with mild cognitive impairment (MCI), and 24 healthy controls (HC). FIELD STRENGTH/SEQUENCE: 3T/magnetization-prepared rapid acquisition gradient echo (MP-RAGE) and IVIM-DWI ASSESSMENT: All participants completed a cognitive screening battery prior to MRI. IVIM-DWI maps (pure diffusion coefficient [D], pseudodiffusion coefficient [D*], and perfusion fraction [f]) were generated from a biexponential fit of diffusion MRI data. VBM was performed on the standard T1 -weighted MP-RAGE structural images. Group-wise templates were used to compare across groups. STATISTICAL TESTS: Analysis of covariance (ANCOVA) with gender and age as covariates (familywise error [FWE] corrected, post-hoc comparisons using Bonferroni correction) for group comparisons. Partial-η2 and Hedges' g were used for effect-size analysis. Spearman's correlations (false discovery rate [FDR]-corrected) for the relationship between cognitive scores and imaging. RESULTS: Clusters of significant group-wise differences were found mainly in the temporal lobe, hippocampus, and amygdala using all VBM and IVIM methods (P < 0.05 FWE). While VBM showed significant changes between MCI and AD groups and between HC and AD groups, no significant clusters were observed between HC and MCI using VBM. ADC and IVIM-D demonstrated significant changes, at P < 0.05 FWE, between HC and MCI, notably in the amygdala and hippocampus. Several voxel-based correlations were observed between neuroimaging metrics and cognitive tests within the cognitively impaired groups (P < 0.05 FDR). DATA CONCLUSION: These findings suggest that IVIM-DWI metrics may be earlier biomarkers for AD-related changes than VBM. The use of these techniques may provide novel insight into subvoxel neurodegenerative processes. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY STAGE: 2 J. MAGN. RESON. IMAGING 2020;52:1811-1826.

Age-Related Atrophy and Compensatory Neural Networks in Reading Comprehension.

OBJECTIVES: Despite changes to brain integrity with aging, some functions like basic language processes remain remarkably preserved. One theory for the maintenance of function in light of age-related brain atrophy is the engagement of compensatory brain networks. This study examined age-related changes in the neural networks recruited for simple language comprehension. METHODS: Sixty-five adults (native English-speaking, right-handed, and cognitively normal) aged 17-85 years underwent a functional magnetic resonance imaging (fMRI) reading paradigm and structural scanning. The fMRI data were analyzed using independent component analysis to derive brain networks associated with reading comprehension. RESULTS: Two typical frontotemporal language networks were identified, and these networks remained relatively stable across the wide age range. In contrast, three attention-related networks showed increased activation with increasing age. Furthermore, the increased recruitment of a dorsal attention network was negatively correlated to gray matter thickness in temporal regions, whereas an anterior frontoparietal network was positively correlated to gray matter thickness in insular regions. CONCLUSIONS: We found evidence that older adults can exert increased effort and recruit additional attentional resources to maintain their reading abilities in light of increased cortical atrophy.

Presurgical language fMRI: Mapping of six critical regions.

Language mapping is a key goal in neurosurgical planning. fMRI mapping typically proceeds with a focus on Broca's and Wernicke's areas, although multiple other language-critical areas are now well-known. We evaluated whether clinicians could use a novel approach, including clinician-driven individualized thresholding, to reliably identify six language regions, including Broca's Area, Wernicke's Area (inferior, superior), Exner's Area, Supplementary Speech Area, Angular Gyrus, and Basal Temporal Language Area. We studied 22 epilepsy and tumor patients who received Wada and fMRI (age 36.4[12.5]; Wada language left/right/mixed in 18/3/1). fMRI tasks (two × three tasks) were analyzed by two clinical neuropsychologists who flexibly thresholded and combined these to identify the six regions. The resulting maps were compared to fixed threshold maps. Clinicians generated maps that overlapped significantly, and were highly consistent, when at least one task came from the same set. Cases diverged when clinicians prioritized different language regions or addressed noise differently. Language laterality closely mirrored Wada data (85% accuracy). Activation consistent with all six language regions was consistently identified. In blind review, three external, independent clinicians rated the individualized fMRI language maps as superior to fixed threshold maps; identified the majority of regions significantly more frequently; and judged language laterality to mirror Wada lateralization more often. These data provide initial validation of a novel, clinician-based approach to localizing language cortex. They also demonstrate clinical fMRI is superior when analyzed by an experienced clinician and that when fMRI data is of low quality judgments of laterality are unreliable and should be withheld. Hum Brain Mapp 38:4239-4255, 2017. © 2017 Wiley Periodicals, Inc.

Studying ventricular abnormalities in mild cognitive impairment with hyperbolic Ricci flow and tensor-based morphometry.

Mild Cognitive Impairment (MCI) is a transitional stage between normal aging and dementia and people with MCI are at high risk of progression to dementia. MCI is attracting increasing attention, as it offers an opportunity to target the disease process during an early symptomatic stage. Structural magnetic resonance imaging (MRI) measures have been the mainstay of Alzheimer's disease (AD) imaging research, however, ventricular morphometry analysis remains challenging because of its complicated topological structure. Here we describe a novel ventricular morphometry system based on the hyperbolic Ricci flow method and tensor-based morphometry (TBM) statistics. Unlike prior ventricular surface parameterization methods, hyperbolic conformal parameterization is angle-preserving and does not have any singularities. Our system generates a one-to-one diffeomorphic mapping between ventricular surfaces with consistent boundary matching conditions. The TBM statistics encode a great deal of surface deformation information that could be inaccessible or overlooked by other methods. We applied our system to the baseline MRI scans of a set of MCI subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI: 71 MCI converters vs. 62 MCI stable). Although the combined ventricular area and volume features did not differ between the two groups, our fine-grained surface analysis revealed significant differences in the ventricular regions close to the temporal lobe and posterior cingulate, structures that are affected early in AD. Significant correlations were also detected between ventricular morphometry, neuropsychological measures, and a previously described imaging index based on fluorodeoxyglucose positron emission tomography (FDG-PET) scans. This novel ventricular morphometry method may offer a new and more sensitive approach to study preclinical and early symptomatic stage AD.

Sex-based memory advantages and cognitive aging: a challenge to the cognitive reserve construct?

Education and related proxies for cognitive reserve (CR) are confounded by associations with environmental factors that correlate with cerebrovascular disease possibly explaining discrepancies between studies examining their relationships to cognitive aging and dementia. In contrast, sex-related memory differences may be a better proxy. Since they arise developmentally, they are less likely to reflect environmental confounds. Women outperform men on verbal and men generally outperform women on visuospatial memory tasks. Furthermore, memory declines during the preclinical stage of AD, when it is clinically indistinguishable from normal aging. To determine whether CR mitigates age-related memory decline, we examined the effects of gender and APOE genotype on longitudinal memory performances. Memory decline was assessed in a cohort of healthy men and women enriched for APOE ɛ4 who completed two verbal [Rey Auditory Verbal Learning Test (AVLT), Buschke Selective Reminding Test (SRT)] and two visuospatial [Rey-Osterrieth Complex Figure Test (CFT), and Benton Visual Retention Test (VRT)] memory tests, as well as in a separate larger and older cohort [National Alzheimer's Coordinating Center (NACC)] who completed a verbal memory test (Logical Memory). Age-related memory decline was accelerated in APOE ɛ4 carriers on all verbal memory measures (AVLT, p=.03; SRT p<.001; logical memory p<.001) and on the VRT p=.006. Baseline sex associated differences were retained over time, but no sex differences in rate of decline were found for any measure in either cohort. Sex-based memory advantage does not mitigate age-related memory decline in either APOE ɛ4 carriers or non-carriers.

Genetic influence of apolipoprotein E4 genotype on hippocampal morphometry: An N = 725 surface-based Alzheimer's disease neuroimaging initiative study.

The apolipoprotein E (APOE) e4 allele is the most prevalent genetic risk factor for Alzheimer's disease (AD). Hippocampal volumes are generally smaller in AD patients carrying the e4 allele compared to e4 noncarriers. Here we examined the effect of APOE e4 on hippocampal morphometry in a large imaging database-the Alzheimer's Disease Neuroimaging Initiative (ADNI). We automatically segmented and constructed hippocampal surfaces from the baseline MR images of 725 subjects with known APOE genotype information including 167 with AD, 354 with mild cognitive impairment (MCI), and 204 normal controls. High-order correspondences between hippocampal surfaces were enforced across subjects with a novel inverse consistent surface fluid registration method. Multivariate statistics consisting of multivariate tensor-based morphometry (mTBM) and radial distance were computed for surface deformation analysis. Using Hotelling's T(2) test, we found significant morphological deformation in APOE e4 carriers relative to noncarriers in the entire cohort as well as in the nondemented (pooled MCI and control) subjects, affecting the left hippocampus more than the right, and this effect was more pronounced in e4 homozygotes than heterozygotes. Our findings are consistent with previous studies that showed e4 carriers exhibit accelerated hippocampal atrophy; we extend these findings to a novel measure of hippocampal morphometry. Hippocampal morphometry has significant potential as an imaging biomarker of early stage AD.

Pathologic and imaging correlates of cognitive deficits in multiple sclerosis: changing the paradigm of diagnosis and prognosis.

From 1868, when Charcot first described the clinical features and the pathologic correlates, up till the present day, multiple sclerosis (MS) has commonly been characterized by the symptoms caused by inflammatory plaques in the white matter of the brain and spinal cord. Early use of magnetic resonance imaging (MRI) to diagnose MS focused on detecting these white matter lesions. By the 1990s, researchers recognized that many patients with MS have cognitive deficits that can cause severe disability, and also determined the associated pathology; these findings shed more light on both the pathogenesis and progression. Since 2004, several lines of evidence have shown that the extent of white matter plaques identified on MRI does not correlate well with cognitive deficits. High-resolution MRI and advances in immunohistochemical techniques have enabled detection of cortical demyelination early in the course, correlating with cognitive deficits. Late in the course, pathologic changes in normal-looking white and gray matter correlate more closely with progressive cognitive deficits than with visual, sensory, and motor symptoms. This finding implies the need to redefine the disease and its progression. In this review, we discuss the histopathologic studies of cortical plaques in MS and early indications about their role in disease definition and progression, describe the role of high-resolution MRI in staging and determining progression of cognitive symptoms, and discuss how advances in these areas are forcing us to rethink diagnosis and determination of progression.

Altered resting-state functional connectivity and dynamic network properties in cognitive impairment: an independent component and dominant-coactivation pattern analyses study.

Introduction: Cognitive impairment (CI) due to Alzheimer's disease (AD) encompasses a decline in cognitive abilities and can significantly impact an individual's quality of life. Early detection and intervention are crucial in managing CI, both in the preclinical and prodromal stages of AD prior to dementia. Methods: In this preliminary study, we investigated differences in resting-state functional connectivity and dynamic network properties between 23 individual with CI due to AD based on clinical assessment and 15 healthy controls (HC) using Independent Component Analysis (ICA) and Dominant-Coactivation Pattern (d-CAP) analysis. The cognitive status of the two groups was also compared, and correlations between cognitive scores and d-CAP switching probability were examined. Results: Results showed comparable numbers of d-CAPs in the Default Mode Network (DMN), Executive Control Network (ECN), and Frontoparietal Network (FPN) between HC and CI groups. However, the Visual Network (VN) exhibited fewer d-CAPs in the CI group, suggesting altered dynamic properties of this network for the CI group. Additionally, ICA revealed significant connectivity differences for all networks. Spatial maps and effect size analyses indicated increased coactivation and more synchronized activity within the DMN in HC compared to CI. Furthermore, reduced switching probabilities were observed for the CI group in DMN, VN, and FPN networks, indicating less dynamic and flexible functional interactions. Discussion: The findings highlight altered connectivity patterns within the DMN, VN, ECN, and FPN, suggesting the involvement of multiple functional networks in CI. Understanding these brain processes may contribute to developing targeted diagnostic and therapeutic strategies for CI due to AD.

Adapting the PEERS® for Young Adults Program for Autistic Adults across the Lifespan.

The Program for the Education and Enrichment of Relational Skills (PEERS®) is an evidence-based intervention developed for autistic individuals to support social communication, peer interactions, independence, and interpersonal relationships. Despite a demonstrated effectiveness for young autistic individuals in the US and several other countries, PEERS has yet to be modified to support the needs of autistic adults across the lifespan. The present study describes how our team sought autistic voices to adapt PEERS for adults of any age. Specifically, we aimed to address the needs of middle-aged and older adults and adapt the curriculum to be more neurodiversity-affirming. Between two cohorts that completed the program consecutively, we evaluated the acceptability of the adapted PEERS program and made refinements based on feedback from autistic participants and their study partners. Results indicated that Cohort 2 reported higher satisfaction with the PEERS components and overall program than Cohort 1, suggesting effective refinement. We present a framework of adaptations that more specifically address the needs of middle-aged and older adults in a neurodiverse-affirming way compared to previous iterations. Our approach to implementing an adapted PEERS curriculum across the adult lifespan may serve as a model for improved clinical care and cultivate the acceptance of neurodiversity in the interpersonal domains of autistic adults' lives.

Quantifying intra-tumoral genetic heterogeneity of glioblastoma toward precision medicine using MRI and a data-inclusive machine learning algorithm.

BACKGROUND AND OBJECTIVE: Glioblastoma (GBM) is one of the most aggressive and lethal human cancers. Intra-tumoral genetic heterogeneity poses a significant challenge for treatment. Biopsy is invasive, which motivates the development of non-invasive, MRI-based machine learning (ML) models to quantify intra-tumoral genetic heterogeneity for each patient. This capability holds great promise for enabling better therapeutic selection to improve patient outcome. METHODS: We proposed a novel Weakly Supervised Ordinal Support Vector Machine (WSO-SVM) to predict regional genetic alteration status within each GBM tumor using MRI. WSO-SVM was applied to a unique dataset of 318 image-localized biopsies with spatially matched multiparametric MRI from 74 GBM patients. The model was trained to predict the regional genetic alteration of three GBM driver genes (EGFR, PDGFRA and PTEN) based on features extracted from the corresponding region of five MRI contrast images. For comparison, a variety of existing ML algorithms were also applied. Classification accuracy of each gene were compared between the different algorithms. The SHapley Additive exPlanations (SHAP) method was further applied to compute contribution scores of different contrast images. Finally, the trained WSO-SVM was used to generate prediction maps within the tumoral area of each patient to help visualize the intra-tumoral genetic heterogeneity. RESULTS: WSO-SVM achieved 0.80 accuracy, 0.79 sensitivity, and 0.81 specificity for classifying EGFR; 0.71 accuracy, 0.70 sensitivity, and 0.72 specificity for classifying PDGFRA; 0.80 accuracy, 0.78 sensitivity, and 0.83 specificity for classifying PTEN; these results significantly outperformed the existing ML algorithms. Using SHAP, we found that the relative contributions of the five contrast images differ between genes, which are consistent with findings in the literature. The prediction maps revealed extensive intra-tumoral region-to-region heterogeneity within each individual tumor in terms of the alteration status of the three genes. CONCLUSIONS: This study demonstrated the feasibility of using MRI and WSO-SVM to enable non-invasive prediction of intra-tumoral regional genetic alteration for each GBM patient, which can inform future adaptive therapies for individualized oncology.

Image-based models of T-cell distribution identify a clinically meaningful response to a dendritic cell vaccine in patients with glioblastoma.

BACKGROUND: Glioblastoma is an extraordinarily heterogeneous tumor, yet the current treatment paradigm is a "one size fits all" approach. Hundreds of glioblastoma clinical trials have been deemed failures because they did not extend median survival, but these cohorts are comprised of patients with diverse tumors. Current methods of assessing treatment efficacy fail to fully account for this heterogeneity. METHODS: Using an image-based modeling approach, we predicted T-cell abundance from serial MRIs of patients enrolled in the dendritic cell (DC) vaccine clinical trial. T-cell predictions were quantified in both the contrast-enhancing and non-enhancing regions of the imageable tumor, and changes over time were assessed. RESULTS: A subset of patients in a DC vaccine clinical trial, who had previously gone undetected, were identified as treatment responsive and benefited from prolonged survival. A mere two months after initial vaccine administration, responsive patients had a decrease in model-predicted T-cells within the contrast-enhancing region, with a simultaneous increase in the T2/FLAIR region. CONCLUSIONS: In a field that has yet to see breakthrough therapies, these results highlight the value of machine learning in enhancing clinical trial assessment, improving our ability to prospectively prognosticate patient outcomes, and advancing the pursuit towards individualized medicine.

Longitudinal modeling of age-related memory decline and the APOE epsilon4 effect.

BACKGROUND: The APOE epsilon4 allele is associated with the risk of late-onset Alzheimer's disease. The age at which memory decline diverges among persons who are homozygous for the APOE epsilon4 allele, those who are heterozygous for the allele, and noncarriers is unknown. METHODS: Using local advertisements, we recruited cognitively normal subjects between the ages of 21 and 97 years, who were grouped according to their APOE epsilon4 status. We then followed the subjects with longitudinal neuropsychological testing. Anyone in whom mild cognitive impairment or dementia developed during follow-up was excluded. We compared the rates of decline in predetermined cognitive measures between carriers and noncarriers of the APOE epsilon4 allele, using a mixed model for longitudinal change with age. RESULTS: We analyzed 815 subjects: 317 APOE epsilon4 carriers (79 who were homozygous for the APOE epsilon4 allele and 238 who were heterozygous) and 498 noncarriers. Carriers, as compared with noncarriers, were generally younger (mean age, 58.0 vs. 61.4 years; P<0.001) and were followed for a longer period (5.3 vs. 4.7 years, P=0.01), with an equivalent duration of formal education (15.4 years) and proportion of women (69%). Longitudinal decline in memory in carriers began before the age of 60 years and showed greater acceleration than in noncarriers (P=0.03), with a possible allele-dose effect (P=0.008). We observed similar although weaker effects on measures of visuospatial awareness and general mental status. CONCLUSIONS: Age-related memory decline in APOE epsilon4 carriers diverges from that of noncarriers before the age of 60 years, despite ongoing normal clinical status.

Sex Differences in Alzheimer's Disease Revealed by Free-Water Diffusion Tensor Imaging and Voxel-Based Morphometry.

BACKGROUND: Imaging biomarkers are increasingly used in Alzheimer's disease (AD), and the identification of sex differences using neuroimaging may provide insight into disease heterogeneity, progression, and therapeutic targets. OBJECTIVE: The purpose of this study was to investigate differences in grey matter (GM) volume and white matter (WM) microstructural disorganization between males and females with AD using voxel-based morphometry (VBM) and free-water-corrected diffusion tensor imaging (FW-DTI). METHODS: Data were downloaded from the OASIS-3 database, including 158 healthy control (HC; 86 females) and 46 mild AD subjects (24 females). VBM and FW-DTI metrics (fractional anisotropy (FA), axial and radial diffusivities (AxD and RD, respectively), and FW index) were compared using effect size for the main effects of group, sex, and their interaction. RESULTS: Significant group and sex differences were observed, with no significant interaction. Post-hoc comparisons showed that AD is associated with reduced GM volume, reduced FW-FA, and higher FW-RD/FW-index, consistent with neurodegeneration. Females in both groups exhibited higher GM volume than males, while FW-DTI metrics showed sex differences only in the AD group. Lower FW, lower FW-FA and higher FW-RD were observed in females relative to males in the AD group. CONCLUSION: The combination of VBM and DTI may reveal complementary sex-specific changes in GM and WM associated with AD and aging. Sex differences in GM volume were observed for both groups, while FW-DTI metrics only showed significant sex differences in the AD group, suggesting that WM tract disorganization may play a differential role in AD pathophysiology between females and males.

Cognitive and neural predictors of speech comprehension in noisy backgrounds in older adults.

Older adults often experience difficulties comprehending speech in noisy backgrounds, which hearing loss does not fully explain. It remains unknown how cognitive abilities, brain networks, and age-related hearing loss may uniquely contribute to speech in noise comprehension at the sentence level. In 31 older adults, using cognitive measures and resting-state fMRI, we investigated the cognitive and neural predictors of speech comprehension with energetic (broadband noise) and informational masking (multi-speakers) effects. Better hearing thresholds and greater working memory abilities were associated with better speech comprehension with energetic masking. Conversely, faster processing speed and stronger functional connectivity between frontoparietal and language networks were associated with better speech comprehension with informational masking. Our findings highlight the importance of the frontoparietal network in older adults' ability to comprehend speech in multi-speaker backgrounds, and that hearing loss and working memory in older adults contributes to speech comprehension abilities related to energetic, but not informational masking.

Evaluation of single bolus, dual-echo dynamic susceptibility contrast MRI protocols in brain tumor patients.

Relative cerebral blood volume (rCBV) obtained from dynamic susceptibility contrast (DSC) MRI is adversely impacted by contrast agent leakage in brain tumors. Using simulations, we previously demonstrated that multi-echo DSC-MRI protocols provide improvements in contrast agent dosing, pulse sequence flexibility, and rCBV accuracy. The purpose of this study is to assess the in-vivo performance of dual-echo acquisitions in patients with brain tumors (n = 59). To verify pulse sequence flexibility, four single-dose dual-echo acquisitions were tested with variations in contrast agent dose, flip angle, and repetition time, and the resulting dual-echo rCBV was compared to standard single-echo rCBV obtained with preload (double-dose). Dual-echo rCBV was comparable to standard double-dose single-echo protocols (mean (standard deviation) tumor rCBV 2.17 (1.28) vs. 2.06 (1.20), respectively). High rCBV similarity was observed (CCC = 0.96), which was maintained across both flip angle (CCC = 0.98) and repetition time (CCC = 0.96) permutations, demonstrating that dual-echo acquisitions provide flexibility in acquisition parameters. Furthermore, a single dual-echo acquisition was shown to enable quantification of both perfusion and permeability metrics. In conclusion, single-dose dual-echo acquisitions provide similar rCBV to standard double-dose single-echo acquisitions, suggesting contrast agent dose can be reduced while providing significant pulse sequence flexibility and complementary tumor perfusion and permeability metrics.

Uncertainty quantification in the radiogenomics modeling of EGFR amplification in glioblastoma.

Radiogenomics uses machine-learning (ML) to directly connect the morphologic and physiological appearance of tumors on clinical imaging with underlying genomic features. Despite extensive growth in the area of radiogenomics across many cancers, and its potential role in advancing clinical decision making, no published studies have directly addressed uncertainty in these model predictions. We developed a radiogenomics ML model to quantify uncertainty using transductive Gaussian Processes (GP) and a unique dataset of 95 image-localized biopsies with spatially matched MRI from 25 untreated Glioblastoma (GBM) patients. The model generated predictions for regional EGFR amplification status (a common and important target in GBM) to resolve the intratumoral genetic heterogeneity across each individual tumor-a key factor for future personalized therapeutic paradigms. The model used probability distributions for each sample prediction to quantify uncertainty, and used transductive learning to reduce the overall uncertainty. We compared predictive accuracy and uncertainty of the transductive learning GP model against a standard GP model using leave-one-patient-out cross validation. Additionally, we used a separate dataset containing 24 image-localized biopsies from 7 high-grade glioma patients to validate the model. Predictive uncertainty informed the likelihood of achieving an accurate sample prediction. When stratifying predictions based on uncertainty, we observed substantially higher performance in the group cohort (75% accuracy, n = 95) and amongst sample predictions with the lowest uncertainty (83% accuracy, n = 72) compared to predictions with higher uncertainty (48% accuracy, n = 23), due largely to data interpolation (rather than extrapolation). On the separate validation set, our model achieved 78% accuracy amongst the sample predictions with lowest uncertainty. We present a novel approach to quantify radiogenomics uncertainty to enhance model performance and clinical interpretability. This should help integrate more reliable radiogenomics models for improved medical decision-making.

Auditory attention following a left hemisphere stroke: comparisons of alerting, orienting, and executive control performance using an auditory Attention Network Test.

INTRODUCTION: Auditory attention is a critical foundation for successful language comprehension, yet is rarely studied in individuals with acquired language disorders. METHODS: We used an auditory version of the well-studied Attention Network Test to study alerting, orienting, and executive control in 28 persons with chronic stroke (PWS). We further sought to characterize the neurobiology of each auditory attention measure in our sample using exploratory lesion-symptom mapping analyses. RESULTS: PWS exhibited the expected executive control effect (i.e., decreased accuracy for incongruent compared to congruent trials), but their alerting and orienting attention were disrupted. PWS did not exhibit an alerting effect and they were actually distracted by the auditory spatial orienting cue compared to the control cue. Lesion-symptom mapping indicated that poorer alerting and orienting were associated with damage to the left retrolenticular part of the internal capsule (adjacent to the thalamus) and left posterior middle frontal gyrus (overlapping with the frontal eye fields), respectively. DISCUSSION: The behavioral findings correspond to our previous work investigating alerting and spatial orienting attention in persons with aphasia in the visual modality and suggest that auditory alerting and spatial orienting attention may be impaired in PWS due to stroke lesions damaging multi-modal attention resources.

Effects of prosody on the cognitive and neural resources supporting sentence comprehension: A behavioral and lesion-symptom mapping study.

Non-canonical sentence comprehension impairments are well-documented in aphasia. Studies of neurotypical controls indicate that prosody can aid comprehension by facilitating attention towards critical pitch inflections and phrase boundaries. However, no studies have examined how prosody may engage specific cognitive and neural resources during non-canonical sentence comprehension in persons with left hemisphere damage. Experiment 1 examines the relationship between comprehension of non-canonical sentences spoken with typical and atypical prosody and several cognitive measures in 25 persons with chronic left hemisphere stroke and 20 matched controls. Experiment 2 explores the neural resources critical for non-canonical sentence comprehension with each prosody type using region-of-interest-based multiple regressions. Lower orienting attention abilities and greater inferior frontal and parietal damage predicted lower comprehension, but only for sentences with typical prosody. Our results suggest that typical sentence prosody may engage attention resources to support non-canonical sentence comprehension, and this relationship may be disrupted following left hemisphere stroke.