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OBJECTIVES: To develop a multiparametric machine-learning (ML) framework using high-resolution 3 dimensional (3D) magnetic resonance (MR) fingerprinting (MRF) data for quantitative characterization of focal cortical dysplasia (FCD). MATERIALS: We included 119 subjects, 33 patients with focal epilepsy and histopathologically confirmed FCD, 60 age- and gender-matched healthy controls (HCs), and 26 disease controls (DCs). Subjects underwent whole-brain 3 Tesla MRF acquisition, the reconstruction of which generated T1 and T2 relaxometry maps. A 3D region of interest was manually created for each lesion, and z-score normalization using HC data was performed. We conducted 2D classification with ensemble models using MRF T1 and T2 mean and standard deviation from gray matter and white matter for FCD versus controls. Subtype classification additionally incorporated entropy and uniformity of MRF metrics, as well as morphometric features from the morphometric analysis program (MAP). We translated 2D results to individual probabilities using the percentage of slices above an adaptive threshold. These probabilities and clinical variables were input into a support vector machine for individual-level classification. Fivefold cross-validation was performed and performance metrics were reported using receiver-operating-characteristic-curve analyses. RESULTS: FCD versus HC classification yielded mean sensitivity, specificity, and accuracy of 0.945, 0.980, and 0.962, respectively; FCD versus DC classification achieved 0.918, 0.965, and 0.939. In comparison, visual review of the clinical magnetic resonance imaging (MRI) detected 48% (16/33) of the lesions by official radiology report. In the subgroup where both clinical MRI and MAP were negative, the MRF-ML models correctly distinguished FCD patients from HCs and DCs in 98.3% of cross-validation trials for the magnetic resonance imaging negative group and MAP negative group. Type II versus non-type-II classification exhibited mean sensitivity, specificity, and accuracy of 0.835, 0.823, and 0.83, respectively; type IIa versus IIb classification showed 0.85, 0.9, and 0.87. In comparison, the transmantle sign was present in 58% (7/12) of the IIb cases. INTERPRETATION: The MRF-ML framework presented in this study demonstrated strong efficacy in noninvasively classifying FCD from normal cortex and distinguishing FCD subtypes. ANN NEUROL 2024.
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INTRODUCTION: Cerebral amyloid angiopathy (CAA) is characterized by amyloid ß (Aß) deposition in brain vessels, leading to hemorrhagic phenomena and cognitive impairment. Magnetic resonance imaging (MRI)-based criteria allow a diagnosis of probable CAA in vivo, but such a diagnosis cannot predict the eventual development of CAA. METHODS: We conducted a retrospective cohort study of 464 patients with cognitive disorders whose data were included in a brain health biobank. De-identified parameters including sex, age, cognitive score, APOE status, and cerebrospinal fluid (CSF) levels of Aß 1-40, Aß 1-42, phosphorylated tau, and total tau were assessed in those with and without CAA. Odds ratios (ORs) and 95% confidence intervals (CIs) were determined. RESULTS: CAA was present in 53 of 464 (11.5%) patients. P-tau level was significantly higher in those with CAA (115 vs. 84.3 pg/mL p = 0.038). In univariate analyses, the risk of developing CAA was higher with increased age (OR, 1.036; 95% CI: 1.008, 1.064; p = 0.011) and decreased CSF level of Aß 1-40 (OR, 0.685; 95% CI: 0.534, 0.878; p = 0.003). In multivariate analyses, the risk of CAA remained higher with a decreased CSF level of Aß 1-40 (OR, 0.681; 95% CI: 0.531, 0.874; p = 0.003). CONCLUSION: These findings suggest that Aß 1-40 levels in the CSF might be a useful molecular biomarker of CAA in patients with dementia.
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Background: Cognitive dysfunction is a known symptom of multiple sclerosis (MS), with memory recognized as a frequently impacted domain. Here, we used high-resolution MRI at 7 tesla to build on cross-sectional work by evaluating the longitudinal relationship of diffusion tensor imaging (DTI) measures of the fornix to episodic memory performance. Methods: A sample of 80 people with multiple sclerosis (mean age 51.9 ± 8.1 years; 24% male) underwent baseline clinical evaluation, neuropsychological assessment, and MRI. Sixty-four participants had follow-up neuropsychological testing after 1-2 years. Linear regression was used to assess the relationship of baseline imaging measures to follow-up episodic memory performance, measured using the Selective Reminding Test and Brief Visuospatial Memory Test. A reduced prediction model included cognitive function at baseline, age, sex, and disease course. Results: Radial (ß = -0.222, p < 0.026; likelihood ratio test (LRT) p < 0.018), axial (ß = -0.270, p < 0.005; LRT p < 0.003), and mean (ß = -0.242, p < 0.0139; LRT p < 0.009) diffusivity of the fornix significantly added to the model, with follow-up analysis indicating that a longer prediction interval may increase accuracy. Conclusion: These results suggest that fornix DTI has predictive value specific to memory function in MS and warrants additional investigation in the drive to develop predictors of disease progression.
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In addition to Alzheimer's disease (AD), the hippocampus is now known to be affected in variants of frontotemporal degeneration (FTD). In semantic variant primary progressive aphasia (svPPA), characterized by language impairments, hippocampal atrophy is greater in the left hemisphere. Nonverbal impairments (e.g., visual object recognition) are prominent in the right temporal variant of FTD (rtvFTD), and hippocampal atrophy may be greater in the right hemisphere. In this study we examined the hypothesis that leftward hippocampal asymmetry (predicted in svPPA) would be associated with selective verbal memory impairments (with relative preservation of visual memory), while rightward asymmetry (predicted in rtvFTD) would be associated with the opposite pattern (greater visual memory impairment). In contrast, we predicted that controls and individuals in the amnestic mild cognitive impairment stage of AD (aMCI), both of whom were expected to show symmetrical hippocampal volumes, would show roughly equivalent scores in verbal and visual memory. Participants completed delayed recall tests with words and geometric shapes, and hippocampal volumes were assessed with MRI. The aMCI sample showed symmetrical hippocampal atrophy, and similar degree of verbal and visual memory impairment. The svPPA sample showed greater left hippocampal atrophy and verbal memory impairment, while rtvFTD showed greater right hippocampal atrophy and visual memory impairment. Greater asymmetry in hippocampal volumes was associated with larger differences between verbal and visual memory in the FTD samples. Unlike AD, asymmetry is a core feature of brain-memory relationships in temporal variants of FTD.