Achieving imaging and computational reproducibility on multiparametric MRI radiomics features in brain tumor diagnosis: phantom and clinical validation.

OBJECTIVES: The Image Biomarker Standardization Initiative has helped improve the computational reproducibility of MRI radiomics features. Nonetheless, the MRI sequences and features with high imaging reproducibility are yet to be established. To determine reproducible multiparametric MRI radiomics features across test-retest, multi-scanner, and computational reproducibility comparisons, and to evaluate their clinical value in brain tumor diagnosis. METHODS: To assess reproducibility, T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), and diffusion-weighted imaging (DWI) were acquired from three 3-T MRI scanners using standardized phantom, and radiomics features were extracted using two computational algorithms. Reproducible radiomics features were selected when the concordance correlation coefficient value above 0.9 across multiple sessions, scanners, and computational algorithms. Random forest classifiers were trained with reproducible features (n = 117) and validated in a clinical cohort (n = 50) to evaluate whether features with high reproducibility improved the differentiation of glioblastoma from primary central nervous system lymphomas (PCNSLs). RESULTS: Radiomics features from T2WI demonstrated higher repeatability (65-94%) than those from DWI (38-48%) or T1WI (2-92%). Across test-retest, multi-scanner, and computational comparisons, T2WI provided 41 reproducible features, DWI provided six, and T1WI provided two. The performance of the classification model with reproducible features was higher than that using non-reproducible features in both training set (AUC, 0.916 vs. 0.877) and validation set (AUC, 0.957 vs. 0.869). CONCLUSION: Radiomics features with high reproducibility across multiple sessions, scanners, and computational algorithms were identified, and they showed higher diagnostic performance than non-reproducible radiomics features in the differentiation of glioblastoma from PCNSL. CLINICAL RELEVANCE STATEMENT: By identifying the radiomics features showing higher multi-machine reproducibility, our results also demonstrated higher radiomics diagnostic performance in the differentiation of glioblastoma from PCNSL, paving the way for further research designs and clinical application in neuro-oncology. KEY POINTS: • Highly reproducible radiomics features across multiple sessions, scanners, and computational algorithms were identified using phantom and applied to clinical diagnosis. • Radiomics features from T2-weighted imaging were more reproducible than those from T1-weighted and diffusion-weighted imaging. • Radiomics features with good reproducibility had better diagnostic performance for brain tumors than features with poor reproducibility.

The cerebellum could serve as a potential imaging biomarker of dementia conversion in patients with amyloid-negative amnestic mild cognitive impairment.

BACKGROUND AND PURPOSE: As part of network-specific neurodegeneration, changes in cerebellar gray matter (GM) volume and impaired cerebello-cerebral functional networks have been reported in Alzheimer disease (AD). Compared with healthy controls, a volume loss in the cerebellum has been observed in patients with continuum of AD. However, little is known about the anatomical or functional changes in patients with clinical AD but no brain amyloidosis. We aimed to identify the relationship between cerebellar volume and dementia conversion of amyloid-negative mild cognitive impairment (MCI). METHODS: This study was a retrospective cohort study of patients over the age 50 years with amyloid-negative amnestic MCI who visited the memory clinic of Asan Medical Center with no less than a 36-month follow-up period. All subjects underwent detailed neuropsychological tests, 3 T brain magnetic resonance imaging scans including three-dimensional T1 imaging, and fluorine-18[F18 ]-florbetaben amyloid positron emission tomography scans. A spatially unbiased atlas template of the cerebellum and brainstem was used for analyzing cerebellar GM volume. RESULTS: During the 36 months of follow-up, 39 of 107 (36.4%) patients converted to dementia from amnestic MCI. The converter group had more severe impairments in all visual memory tasks. In terms of volumetric analysis, reduced crus I/II volume adjusted with total intracranial volume, and age was observed in the converter group. CONCLUSIONS: Significant cerebellar GM atrophy involving the bilateral crus I/II may be a novel imaging biomarker for predicting dementia progression in amyloid-negative amnestic MCI patients.

Early Impairment in the Ventral Visual Pathway Can Predict Conversion to Dementia in Patients With Amyloid-negative Amnestic Mild Cognitive Impairment.

BACKGROUND: Around 15% to 20% of patients with clinically probable Alzheimer disease have been found to have no significant Alzheimer pathology on amyloid positron emission tomography. A previous study showed that conversion to dementia from amyloid-negative mild cognitive impairment (MCI) was observed in up to 11% of patients, drawing attention to this condition. OBJECT: We gathered the detailed neuropsychological and neuroimaging data of this population to elucidate factors for conversion to dementia from amyloid-negative amnestic MCI. METHODS: This study was a single-institutional, retrospective cohort study of amyloid-negative MCI patients over age 50 with at least 36 months of follow-up. All subjects underwent detailed neuropsychological testing, 3 tesla brain magnetic resonance imaging), and fluorine-18(18F)-florbetaben amyloid positron emission tomography scans. RESULTS: During the follow-up period, 39 of 107 (36.4%) patients converted to dementia from amnestic MCI. The converter group had more severe impairment in all visual memory tasks. The volumetric analysis revealed that the converter group had significantly reduced total hippocampal volume on the right side, gray matter volume in the right lateral temporal, lingual gyri, and occipital pole. CONCLUSION: Our study showed that reduced gray matter volume related to visual memory processing may predict clinical progression in this amyloid-negative MCI population.

Effects of strategic white matter hyperintensities of cholinergic pathways on basal forebrain volume in patients with amyloid-negative neurocognitive disorders.

BACKGROUND: The cholinergic neurotransmitter system is crucial to cognitive function, with the basal forebrain (BF) being particularly susceptible to Alzheimer's disease (AD) pathology. However, the interaction of white matter hyperintensities (WMH) in cholinergic pathways and BF atrophy without amyloid pathology remains poorly understood. METHODS: We enrolled patients who underwent neuropsychological tests, magnetic resonance imaging, and 18F-florbetaben positron emission tomography due to cognitive impairment at the teaching university hospital from 2015 to 2022. Among these, we selected patients with negative amyloid scans and additionally excluded those with Parkinson's dementia that may be accompanied by BF atrophy. The WMH burden of cholinergic pathways was quantified by the Cholinergic Pathways Hyperintensities Scale (CHIPS) score, and categorized into tertile groups because the CHIPS score did not meet normal distribution. Segmentation of the BF on volumetric T1-weighted MRI was performed using FreeSurfer, then was normalized for total intracranial volume. Multivariable regression analysis was performed to investigate the association between BF volumes and CHIPS scores. RESULTS: A total of 187 patients were enrolled. The median CHIPS score was 12 [IQR 5.0; 24.0]. The BF volume of the highest CHIPS tertile group (mean ± SD, 3.51 ± 0.49, CHIPSt3) was significantly decreased than those of the lower CHIPS tertile groups (3.75 ± 0.53, CHIPSt2; 3.83 ± 0.53, CHIPSt1; P = 0.02). In the univariable regression analysis, factors showing significant associations with the BF volume were the CHIPSt3 group, age, female, education, diabetes mellitus, smoking, previous stroke history, periventricular WMH, and cerebral microbleeds. In multivariable regression analysis, the CHIPSt3 group (standardized beta [ßstd] = -0.25, P = 0.01), female (ßstd = 0.20, P = 0.04), and diabetes mellitus (ßstd = -0.22, P < 0.01) showed a significant association with the BF volume. Sensitivity analyses showed a negative correlation between CHIPS score and normalized BF volume, regardless of WMH severity. CONCLUSIONS: We identified a significant correlation between strategic WMH burden in the cholinergic pathway and BF atrophy independently of amyloid positivity and WMH severity. These results suggest a mechanism of cholinergic neuronal loss through the dying-back phenomenon and provide a rationale that strategic WMH assessment may help identify target groups that may benefit from acetylcholinesterase inhibitor treatment.

Association Between Taurine Level in the Hippocampus and Major Depressive Disorder in Young Women: A Proton Magnetic Resonance Spectroscopy Study at 7T.

BACKGROUND: Major depressive disorder (MDD) is characterized by depressed mood or loss of interest or pleasure. Generally, women are twice as likely as men to have depression. Taurine, a type of amino acid, plays critical roles in neuronal generation, differentiation, arborization, and formation of synaptic connections. Importantly, it enhances proliferation and synaptogenesis in the hippocampus. When injected into animals, taurine has an antidepressant effect. However, there is no in vivo evidence to show an association between taurine concentration in the human brain and the development of MDD. METHODS: Forty-one unmedicated young women with MDD (ages 18-29) and 43 healthy control participants matched for gender and age were recruited in South Korea. Taurine concentration was measured in the hippocampus, anterior cingulate cortex, and occipital cortex of the MDD and healthy control groups using proton magnetic resonance spectroscopy at 7T. Analysis of covariance was used to examine differences in taurine concentration, adjusting for age as a covariate. RESULTS: Taurine concentration in the hippocampus was lower (F1,75 = 5.729, p = .019, Δη2 = 0.073) for the MDD group (mean [SEM] = 0.91 [0.06] mM) than for the healthy control group (1.13 [0.06] mM). There was no significant difference in taurine concentration in the anterior cingulate cortex or occipital cortex between the two groups. CONCLUSIONS: This study demonstrates that a lower level of taurine concentration in the hippocampus may be a novel characteristic of MDD.

Relationship between disproportionately enlarged subarachnoid-space hydrocephalus and white matter tract integrity in normal pressure hydrocephalus.

Normal pressure hydrocephalus (NPH) patients had altered white matter tract integrities on diffusion tensor imaging (DTI). Previous studies suggested disproportionately enlarged subarachnoid space hydrocephalus (DESH) as a prognostic sign of NPH. We examined DTI indices in NPH subgroups by DESH severity and clinical symptoms. This retrospective case-control study included 33 NPH patients and 33 age-, sex-, and education-matched controls. The NPH grading scales (0-12) were used to rate neurological symptoms. Patients with NPH were categorized into two subgroups, high-DESH and low-DESH groups, by the average value of the DESH scale. DTI indices, including fractional anisotropy, were compared across 14 regions of interest (ROIs). The high-DESH group had increased axial diffusivity in the lateral side of corona radiata (1.43 ± 0.25 vs. 1.72 ± 0.25, p = 0.04), and showed decreased fractional anisotropy and increased mean, and radial diffusivity in the anterior and lateral sides of corona radiata and the periventricular white matter surrounding the anterior horn of lateral ventricle. In patients with a high NPH grading scale, fractional anisotropy in the white matter surrounding the anterior horn of the lateral ventricle was significantly reduced (0.36 ± 0.08 vs. 0.26 ± 0.06, p = 0.03). These data show that DESH may be a biomarker for DTI-detected microstructural alterations and clinical symptom severity.

Role of White Matter Abnormalities in the Relationship Between Microbleed Burden and Cognitive Impairment in Cerebral Amyloid Angiopathy.

BACKGROUND: Cerebral amyloid angiopathy (CAA) often presents as cognitive impairment, but the mechanism of cognitive decline is unclear. Recent studies showed that number of microbleeds were associated with cognitive decline. OBJECTIVE: We aimed to investigate how microbleeds contribute to cognitive impairment in association with white matter tract abnormalities or cortical thickness in CAA. METHODS: This retrospective comparative study involved patients with probable CAA according to the Boston criteria (Aß+ CAA) and patients with Alzheimer's disease (Aß+ AD), all of whom showed severe amyloid deposition on amyloid PET. Using mediation analysis, we investigated how FA or cortical thickness mediates the correlation between the number of lobar microbleeds and cognition. RESULTS: We analyzed 30 patients with Aß+ CAA (age 72.2±7.6, female 53.3%) and 30 patients with Aß+ AD (age 71.5±7.6, female 53.3%). The two groups showed similar degrees of cortical amyloid deposition in AD-related regions. The Aß+ CAA group had significantly lower FA values in the clusters of the posterior area than did the Aß+ AD group(family-wise error-corrected p < 0.05). The correlation between the number of lobar microbleeds and visuospatial function was indirectly mediated by white matter tract abnormality of right posterior thalamic radiation (PTR) and tapetum, while lobar microbleeds and language function was indirectly mediated by the abnormality of left PTR and sagittal stratum. Cortical thickness did not mediate the association between lobar microbleeds and cognition. CONCLUSION: This result supports the hypothesis that microbleeds burden leads to white matter tract damage and subsequent cognitive decline in CAA.

Utility of 7 Tesla Magnetic Resonance Imaging in Patients With Epilepsy: A Systematic Review and Meta-Analysis.

Objective: 7 Tesla magnetic resonance imaging (MRI) enables high resolution imaging and potentially improves the detection of morphologic abnormalities in patients with epilepsy. However, its added value compared with conventional 1.5T and 3.0T MRI is unclear. We reviewed the evidence for the use of 7 Tesla MRI in patients with epilepsy and compared the detection rate of focal lesions with clinical MRI. Methods: Clinical retrospective case studies were identified using the indexed text terms "epilepsy" AND "magnetic resonance imaging" OR "MR imaging" AND "7T" OR "7 Tesla" OR "7T" in Medline (2002-September 1, 2020) and Embase (1999-September 1, 2020). The study setting, MRI protocols, qualitative, and quantitative assessment were systematically reviewed. The detection rate of morphologic abnormalities on MRI was reported in each study in which surgery was used as the reference standard. Meta-analyses were performed using a univariate random-effects model in diagnostic performance studies with patients that underwent both 7T MRI and conventional MRI. Results: Twenty-five articles were included (467 patients and 167 healthy controls) consisting of 10 case studies, 10 case-control studies, 4 case series, and 1 cohort study. All studies included focal epilepsy; 12 studies (12/25, 48%) specified the disease etiology and 4 studies reported focal but non-lesional (MRI-negative on 1.5/3.0T) epilepsy. 7T MRI showed superior detection and delineation of morphologic abnormalities in all studies. In nine comparative studies, 7T MRI had a superior detection rate of 65% compared with the 22% detection rate of 1.5T or 3.0T. Significance: 7T MRI is useful for delineating morphologic abnormalities with a higher detection rate compared with conventional clinical MRI. Most studies were conducted using a case series or case study; therefore, a cohort study design with clinical outcomes is necessary. Classification of Evidence: Class IV Criteria for Rating Diagnostic Accuracy Studies.

Extrahippocampal Radiomics Analysis Can Potentially Identify Laterality in Patients With MRI-Negative Temporal Lobe Epilepsy.

Objective: The objective of the study was to investigate whether radiomics features of extrahippocampal regions differ between patients with epilepsy and healthy controls, and whether any differences can identify patients with magnetic resonance imaging (MRI)-negative temporal lobe epilepsy (TLE). Methods: Data from 36 patients with hippocampal sclerosis (HS) and 50 healthy controls were used to construct a radiomics model. A total of 1,618 radiomics features from the affected hippocampal and extrahippocampal regions were compared with features from healthy controls and the unaffected side of patients. Using a stepwise selection method with a univariate t-test and elastic net penalization, significant predictors for identifying TLE were separately selected for the hippocampus (H+) and extrahippocampal region (H-). Each model was independently validated with an internal set of MRI-negative adult TLE patients (n = 22) and pediatric validation cohort with MRI-negative TLE (n = 20) from another tertiary center; diagnostic performance was calculated using area under the curve (AUC) of the receiver-operating-characteristic curve analysis. Results: Forty-eight significant H+ radiomic features and 99 significant H- radiomic features were selected from the affected side of patients and used to create a hippocampus model and an extrahippocampal model, respectively. Texture features were the most frequently selected feature. Training set showed slightly higher accuracy between hippocampal (AUC = 0.99) and extrahippocampal model (AUC = 0.97). In the internal validation and external validation sets, the extrahippocampal model (AUC = 0.80 and 0.92, respectively) showed higher diagnostic performance for identifying the affected side of patients than the hippocampus model (AUC = 0.67 and 0.69). Significance: Radiomics revealed extrahippocampal abnormality in the affected side of patients with TLE and could potentially help to identify MRI-negative TLE. Classification of Evidence: Class IV Criteria for Rating Diagnostic Accuracy Studies.

Clinical Features and Brain MRI Findings in Korean Patients with AGel Amyloidosis.

PURPOSE: AGel amyloidosis is systemic amyloidosis caused by pathogenic variants in the GSN gene. In this study, we sought to characterize the clinical and brain magnetic resonance image (MRI) features of Korean patients with AGel amyloidosis. MATERIALS AND METHODS: We examined 13 patients with AGel amyloidosis from three unrelated families. Brain MRIs were performed in eight patients and eight age- and sex-matched healthy controls. Therein, we analyzed gray and white matter content using voxel-based morphometry (VBM), tract-based spatial statistics (TBSS), and FreeSurfer. RESULTS: The median age at examination was 73 (interquartile range: 64-76) years. The median age at onset of cutis laxa was 20 (interquartile range: 15-30) years. All patients over that age of 60 years had dysarthria, cutis laxa, dysphagia, and facial palsy. Two patients in their 30s had only mild cutis laxa. The median age at dysarthria onset was 66 (interquartile range: 63.5-70) years. Ophthalmoparesis was observed in three patients. No patient presented with muscle weakness of the limbs. Axial fluid-attenuated inversion recovery images of the brain showed no significant differences between the patient and control groups. Also, analysis of VBM, TBSS, and FreeSurfer revealed no significant differences in cortical thickness between patients and healthy controls at the corrected significance level. CONCLUSION: Our study outlines the clinical manifestations of prominent bulbar palsy and early-onset cutis laxa in 13 Korean patients with AGel amyloidosis and confirms that AGel amyloidosis mainly affects the peripheral nervous system rather than the central nervous system.

Altered Effective Connectivity within the Fronto-Limbic Circuitry in Response to Negative Emotional Task in Female Patients with Major Depressive Disorder.

Background: Major depressive disorder (MDD) is a mood disorder associated with disruptions in emotional control. Previous studies have investigated abnormal regional activity and connectivity within the fronto-limbic circuit. However, condition-specific connectivity changes and their association with the pathophysiology of MDD remain unexplored. This study investigated effective connectivity in the fronto-limbic circuit induced by negative emotional processing from patients with MDD. Methods: Thirty-four unmedicated female patients with MDD and 28 healthy participants underwent event-related functional magnetic resonance imaging at 7T while viewing emotionally negative and neutral images. Brain regions whose dynamics are driven by experimental conditions were identified by using statistical parametric mapping. Effective connectivity among regions of interest was then estimated by using dynamic causal modeling. Results: Patients with MDD had lower activation of the orbitofrontal cortex (OFC) and higher activation of the parahippocampal gyrus (PHG) than healthy controls (HC). In association with these regional changes, we found that patients with MDD did not have significant modulatory connections from the primary visual cortex (V1) to OFC, whereas those connections of HC were significantly positively modulated during negative emotional processing. Regarding the PHG activity, patients with MDD had greater modulatory connection from the V1, but reduced negative modulatory connection from the OFC, compared with healthy participants. Conclusions: These results imply that disrupted effective connectivity among regions of the OFC, PHG, and V1 may be closely associated with the impaired regulation of negative emotional processing in the female patients with MDD.

FDG-PET patterns associated with ideomotor apraxia and imitation apraxia in patients with corticobasal syndrome.

INTRODUCTION: Apraxia is a core clinical feature of corticobasal syndrome (CBS). Among the subtypes of apraxia, ideomotor and imitation apraxia are frequently found in CBS. However, little is known about the brain networks that are characteristic of each apraxia subtype or their clinical implication. In this study, we used 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) to explore the specific patterns of glucose hypometabolism that are characteristic of apraxia subtypes by focusing on ideomotor and imitation apraxia. METHODS: We compared the areas of glucose hypometabolism in the brains of 52 patients with CBS and 13 healthy controls, both as a whole and according to apraxia subtypes. In addition, we investigated the relationship between the apraxia subtypes and the clinical phenotype of CBS. RESULTS: In patients with CBS, common hypometabolism was observed in the frontal gyrus, precentral gyrus and caudate regardless of apraxia subtypes. In particular, ideomotor apraxia was associated with hypometabolism in the angular gyrus, while imitation apraxia was associated with hypometabolism in the posterior part including the postcentral gyrus, precuneus, and posterior cingulate gyrus. Patients who showed both ideomotor and imitation apraxia were more likely to show the typical features of CBS and progressive supranuclear palsy compared with patients showing only one type of apraxia. CONCLUSION: Group comparison analysis using FDG-PET revealed distinct pathways of ideomotor and imitation apraxia in CBS. These findings add to our understanding of the brain networks underlying apraxia in association with the clinical features of CBS.

Deep-learned time-signal intensity pattern analysis using an autoencoder captures magnetic resonance perfusion heterogeneity for brain tumor differentiation.

Current image processing methods for dynamic susceptibility contrast (DSC) magnetic resonance imaging (MRI) do not capture complex dynamic information of time-signal intensity curves. We investigated whether an autoencoder-based pattern analysis of DSC MRI captured representative temporal features that improves tissue characterization and tumor diagnosis in a multicenter setting. The autoencoder was applied to the time-signal intensity curves to obtain representative temporal patterns, which were subsequently learned by a convolutional neural network. This network was trained with 216 preoperative DSC MRI acquisitions and validated using external data (n = 43) collected with different DSC acquisition protocols. The autoencoder applied to time-signal intensity curves and clustering obtained nine representative clusters of temporal patterns, which accurately identified tumor and non-tumoral tissues. The dominant clusters of temporal patterns distinguished primary central nervous system lymphoma (PCNSL) from glioblastoma (AUC 0.89) and metastasis from glioblastoma (AUC 0.95). The autoencoder captured DSC time-signal intensity patterns that improved identification of tumoral tissues and differentiation of tumor type and was generalizable across centers.

Elucidating the Risk Factors for Progression from Amyloid-Negative Amnestic Mild Cognitive Impairment to Dementia.

BACKGROUND: Amyloid PET allows for the assessment of amyloid ß status in the brain, distinguishing true Alzheimer's disease from Alzheimer's disease-mimicking conditions. Around 15-20% of patients with clinically probable Alzheimer's disease have been found to have no significant Alzheimer's pathology on amyloid PET. However, a limited number of studies had been conducted on this subpopulation in terms of clinical progression. OBJECTIVE: We investigated the risk factors that could affect the progression to dementia in patients with amyloid-negative amnestic mild cognitive impairment (MCI). METHODS: This study was a single-institutional, retrospective cohort study of patients over the age of 50 with amyloid-negative amnestic MCI who visited the memory clinic of Asan Medical Center with a follow-up period of more than 36 months. All participants underwent brain magnetic resonance imaging (MRI), detailed neuropsychological testing, and fluorine-18[F18]-florbetaben amyloid PET. RESULTS: During the follow-up period, 39 of 107 patients progressed to dementia from amnestic MCI. In comparison with the stationary group, the progressed group had a more severe impairment in verbal and visual episodic memory function and hippocampal atrophy, which showed an Alzheimer's diseaselike pattern despite the lack of evidence for significant Alzheimer's disease pathology. Voxel-based morphometric MRI analysis revealed that the progressed group had a reduced gray matter volume in the bilateral cerebellar cortices, right temporal cortex, and bilateral insular cortices. CONCLUSION: Considering the lack of evidence of amyloid pathology, clinical progression of these subpopulation may be caused by other neuropathologies such as TDP-43, abnormal tau or alpha synuclein that lead to neurodegeneration independent of amyloid-driven pathway. Further prospective studies incorporating biomarkers of Alzheimer's disease-mimicking dementia are warranted.