The five-factor model (FFM) is a widely used taxonomy of human personality; yet its neuro anatomical basis remains unclear. This is partly because past associations between gray-matter volume and FFM ...were driven by different surface-based morphometry (SBM) indices (i.e. cortical thickness, surface area, cortical folding or any combination of them). To overcome this limitation, we used Free-Surfer to study how variability in SBM measures was related to the FFM in n = 507 participants from the Human Connectome Project.Neuroticism was associated with thicker cortex and smaller area and folding in prefrontal-temporal regions. Extraversion was linked to thicker pre-cuneus and smaller superior temporal cortex area. Openness was linked to thinner cortex and greater area and folding in prefrontal-parietal regions. Agreeableness was correlated to thinner prefrontal cortex and smaller fusiform gyrus area. Conscientiousness was associated with thicker cortex and smaller area and folding in prefrontal regions. These findings demonstrate that anatomical variability in prefrontal cortices is linked to individual differences in the socio-cognitive dispositions described by the FFM. Cortical thickness and surface area/folding were inversely related each others as a function of different FFM traits (neuroticism, extraversion and consciousness vs openness), which may reflect brain maturational effects that predispose or protect against psychiatric disorders.
Primary Progressive Aphasia (PPA) is a neurodegenerative disease characterized by linguistic impairment. The two main clinical subtypes are semantic (svPPA) and non-fluent/agrammatic (nfvPPA) ...variants. Diagnosing and classifying PPA patients represents a complex challenge that requires the integration of multimodal information, including clinical, biological, and radiological features. Structural neuroimaging can play a crucial role in aiding the differential diagnosis of PPA and constructing diagnostic support systems.
In this study, we conducted a white matter texture analysis on T1-weighted images, including 56 patients with PPA (31 svPPA and 25 nfvPPA), and 53 age- and sex-matched controls. We trained a tree-based algorithm over combined clinical/radiomics measures and used Shapley Additive Explanations (SHAP) model to extract the greater impactful measures in distinguishing svPPA and nfvPPA patients from controls and each other.
Radiomics-integrated classification models demonstrated an accuracy of 95% in distinguishing svPPA patients from controls and of 93.7% in distinguishing svPPA from nfvPPA. An accuracy of 93.7% was observed in differentiating nfvPPA patients from controls. Moreover, Shapley values showed the strong involvement of the white matter near left entorhinal cortex in patients classification models.
Our study provides new evidence for the usefulness of radiomics features in classifying patients with svPPA and nfvPPA, demonstrating the effectiveness of an explainable machine learning approach in extracting the most impactful features for assessing PPA.
Differentiating clinically progressive supranuclear palsy-parkinsonism (PSP-P) from Parkinson's disease (PD) may be challenging, especially in the absence of vertical supranuclear gaze palsy (VSGP). ...The Magnetic Resonance Parkinsonism Index (MRPI) has been reported to accurately distinguish between PSP and PD, yet few data exist on the usefulness of this biomarker for the differentiation of PSP-P from PD.
Thirty-four patients with PSP-P, 46 with PSP-Richardson's syndrome (PSP-RS), 53 with PD, and 53 controls were enrolled. New consensus criteria for the clinical diagnosis of PSP were used as the reference standard. The MRPI, and a new index termed MRPI 2.0 including the measurement of the third ventricle width (MRPI multiplied by third ventricle width/frontal horns width ratio), were calculated on T1-weighted MR images.
The MRPI differentiated patients with PSP-P from those with PD with sensitivity and specificity of 73.5% and 98.1%, respectively, while the MRPI 2.0 showed higher sensitivity (100%) and similar specificity (94.3%) in differentiating between these two groups. Both biomarkers showed excellent performance in differentiating PSP-P patients with VSGP from those with PD, but the MRPI 2.0 was much more accurate (95.8%) than MRPI in differentiating PSP-P patients with slowness of vertical saccades from PD patients.
The MRPI 2.0 accurately differentiated PSP-P patients from those with PD. This new index was more powerful than MRPI in differentiating PSP patients in the early stage of the disease with slowness of vertical saccades from patients with PD, thus helping clinicians to consolidate the diagnosis based on clinical features, in vivo.
•Distinguishing PSP-P from PD is challenging in the early stages of the disease.•Few data exist on the usefulness of MRPI for diagnosing PSP-P patients.•MRPI 2.0 is a new version of MRPI which includes the 3rd ventricular width.•MRPI 2.0 accurately differentiated patients with PSP-P from those with PD.•MRPI 2.0 accurately diagnosed PSP-P in the absence of vertical ocular palsy.
Persistent postural-perceptual dizziness (PPPD) is a common functional vestibular disorder characterized by persistent symptoms of non-vertiginous dizziness and unsteadiness that are exacerbated by ...upright posture, self-motion, and exposure to complex or moving visual stimuli. Recent physiologic and neuroimaging data suggest that greater reliance on visual cues for postural control (as opposed to vestibular cues-a phenomenon termed visual dependence) and dysfunction in central visuo-vestibular networks may be important pathophysiologic mechanisms underlying PPPD. Dysfunctions are thought to involve insular regions that encode recognition of the visual effects of motion in the gravitational field.
We tested for altered activity in vestibular and visual cortices during self-motion simulation obtained
a visual virtual-reality rollercoaster stimulation using functional magnetic resonance imaging in 15 patients with PPPD and 15 healthy controls (HCs). We compared between groups differences in brain responses to simulated displacements in vertical vs horizontal directions and correlated the difference in directional responses with dizziness handicap in patients with PPPD.
HCs showed increased activity in the anterior bank of the central insular sulcus during vertical relative to horizontal motion, which was not seen in patients with PPPD. However, for the same comparison, dizziness handicap correlated positively with activity in the visual cortex (V1, V2, and V3) in patients with PPPD.
We provide novel insight into the pathophysiologic mechanisms underlying PPPD, including functional alterations in brain processes that affect balance control and reweighting of space-motion inputs to favor visual cues. For patients with PPPD, difficulties using visual data to discern the effects of gravity on self-motion may adversely affect balance control, particularly for individuals who simultaneously rely too heavily on visual stimuli. In addition, increased activity in the visual cortex, which correlated with severity of dizziness handicap, may be a neural correlate of visual dependence.
We investigated the disease progression rate in patients with progressive supranuclear palsy-Richardson syndrome (PSP-RS) and PSP-parkinsonism (PSP-P) in comparison with Parkinson disease (PD) ...patients, using MRPI (Magnetic Resonance Parkinsonism Index), and MRPI 2.0.
Fifteen PSP-RS patients (disease duration, y, mean ± SD: 2.5 ± 1.1), 16 PSP-P patients (disease duration, y, mean ± SD: 6.5 ± 3.2) and 19 PD patients (disease duration, y, mean ± SD: 3.2 ± 2.3) were enrolled. All patients underwent clinical assessment and MRI at baseline, 1-year, and 2-year follow-up. MRPI, MRPI 2.0 and clinical scores over 1 and 2-years were used to evaluate disease progression rate, and to calculate sample sizes required to power placebo-controlled trials.
All groups showed increased clinical motor scores over time whereas only PSP groups had increased MRPI and MRPI 2.0 values over T1 and T2 intervals. The percentage increase over 1 and 2-years of MRPI and MRPI 2.0 values was significantly higher in PSP groups than in PD group, and in PSP-RS than in PSP-P patients while no difference between patient groups was observed when clinical motor scores were considered. Sample size estimates showed that MRPI 2.0 performed better than MRPI and clinical scales. Treatment trials with MRPI 2.0 could be performed over 2-years both in PSP-RS and PSP-P with a sample size per treatment arm of 89 and 170 patients, respectively.
Our results demonstrate that MRPI 2.0 was more powerful than MRPI and clinical motor scales in evaluating PSP progression, and in providing the best sample size estimates for clinical trials.
•MRPI and MRPI 2.0 detected disease progression in PSP patients.•MRPI 2.0 was more powerful than MRPI and motor scales in detecting PSP progression.•MRPI 2.0 was the best measure for assessing sample size for clinical trials.
Sarcopenia is an age-related clinical syndrome characterized by the progressive loss of muscle mass and muscle strength. It appears to be closely linked to dementia, particularly Alzheimer's disease ...(AD); however, its prevalence among AD patients remains unclear. In this study, we assessed differences in sarcopenia prevalence between non-demented individuals and AD patients. Moreover, we assessed sex-specific differences in sarcopenia prevalence and explored the diagnostic value of the Muscle Quality Index (MQI) for diagnosing sarcopenia among AD patients.
Cross-sectional study including 145 patients with probable AD and 51 older adults with normal cognition. Sarcopenia was diagnosed according to the criteria of the European Working Group on Sarcopenia in Older People (EWGSOP1 and EWGSOP2) and of the Foundation for the National Institutes of Health (FNIH). The MQI was computed as the ratio of handgrip strength to skeletal muscle mass.
No significant difference in sarcopenia prevalence was observed between AD patients and controls. Prevalence ranged from 3.4 to 23.4% in AD patients and from 2 to 11.8% in controls, depending on diagnostic criteria. Prevalence was higher using EWGSOP1 and decreased using EWGSOP2 and FNIH. Prevalence was higher in males than in females with AD. The MQI was lower in AD patients than in controls (95%CI: - 0.23, - 0.05, p < 0.001), but displayed poor diagnostic accuracy in identifying sarcopenia cases.
AD patients and controls show comparable sarcopenia prevalence. Sarcopenia prevalence is higher in males than females among AD patients and higher when using EWGSOP1 compared to FNIH and EWGSOP2 criteria.
Radiomics is a challenging development area in imaging field that is greatly capturing interest of radiologists and neuroscientists. However, radiomics features show a strong non-biological ...variability determined by different facilities and imaging protocols, limiting the reproducibility and generalizability of analysis frameworks. Our study aimed to investigate the usefulness of harmonization to reduce site-effects on radiomics features over specific brain regions. We selected T1-weighted magnetic resonance imaging (MRI) by using the MRI dataset
Parkinson’s Progression Markers Initiative
(PPMI) from different sites with healthy controls (HC) and Parkinson’s disease (PD) patients. First, the investigation of radiomics measure discrepancies were assessed on healthy brain regions-of-interest (ROIs)
via
a classification pipeline based on LASSO feature selection and support vector machine (SVM) model. Then, a ComBat-based harmonization approach was applied to correct site-effects. Finally, a validation step on PD subjects evaluated diagnostic accuracy before and after harmonization of radiomics data. Results on healthy subjects demonstrated a dependence from site-effects that could be corrected with ComBat harmonization. LASSO regressor after harmonization was unable to select any feature to distinguish controls by site. Moreover, harmonized radiomics features achieved an area under the receiving operating characteristic curve (AUC) of 0.77 (compared to AUC of 0.71 for raw radiomics measures) in distinguish Parkinson’s patients from HC. We found a not-negligible site-effect studying radiomics of HC pre- and post-harmonization of features. Our validation study on PD patients demonstrated a significant influence of non-biological noise source in diagnostic performances. Finally, harmonization of multicenter radiomic data represent a necessary step to make analysis pipelines reliable and replicable for multisite neuroimaging studies.
Radiomics has been proposed as a useful approach to extrapolate novel morphological and textural information from brain Magnetic resonance images (MRI). Radiomics analysis has shown unique potential ...in the diagnostic work-up and in the follow-up of patients suffering from neurodegenerative diseases. However, the potentiality of this technique in distinguishing frontotemporal dementia (FTD) subtypes has so far not been investigated. In this study, we explored the usefulness of radiomic features in differentiating FTD subtypes, namely, the behavioral variant of FTD (bvFTD), the non-fluent and/or agrammatic (PNFA) and semantic (svPPA) variants of a primary progressive aphasia (PPA). Classification analyses were performed on 3 Tesla T1-weighted images obtained from the Frontotemporal Lobar Degeneration Neuroimaging Initiative. We included 49 patients with bvFTD, 25 patients with PNFA, 34 patients with svPPA, and 60 healthy controls. Texture analyses were conducted to define the first-order statistic and textural features in cortical and subcortical brain regions. Recursive feature elimination was used to select the radiomics signature for each pairwise comparison followed by a classification framework based on a support vector machine. Finally, 10-fold cross-validation was used to assess classification performances. The radiomics-based approach successfully identified the brain regions typically involved in each FTD subtype, achieving a mean accuracy of more than 80% in distinguishing between patient groups. Note mentioning is that radiomics features extracted in the left temporal regions allowed achieving an accuracy of 91 and 94% in distinguishing patients with svPPA from those with PNFA and bvFTD, respectively. Radiomics features show excellent classification performances in distinguishing FTD subtypes, supporting the clinical usefulness of this approach in the diagnostic work-up of FTD.
Primary Progressive Aphasia (PPA) is a neurological disease characterized by linguistic deficits. Semantic (svPPA) and non-fluent/agrammatic (nfvPPA) variants are the two main clinical subtypes. We ...applied a novel analytical framework, based on radiomic analysis, to investigate White Matter (WM) asymmetry and to examine whether asymmetry is associated with verbal fluency performance.
Analyses were performed on T1-weighted images including 56 patients with PPA (31 svPPA and 25 nfvPPA) and 53 age- and sex-matched controls. Asymmetry Index (AI) was computed for 86 radiomics features in 34 white matter regions. The relationships between AI, verbal fluency performance (semantic and phonemic) and Boston Naming Test score (BNT) were explored through Spearman correlation analysis.
Relative to controls, WM asymmetry in svPPA patients involved regions adjacent to middle temporal cortex as part of the inferior longitudinal (ILF), fronto-occipital (IFOF) and superior longitudinal fasciculi. Conversely, nfvPPA patients showed an asymmetry of WM in lateral occipital regions (ILF/IFOF). A higher lateralization involving IFOF, cingulum and forceps minor was found in nfvPPA compared to svPPA patients. In nfvPPA patients, semantic fluency was positively correlated to asymmetry in ILF/IFOF tracts. Performances at BNT were associated with AI values of the middle temporal (ILF/SLF) and parahippocampal (ILF/IFOF) gyri in svPPA patients.
Radiomics features depicted distinct pathways of asymmetry in svPPA and nfvPPA involving damage of principal fiber tracts associated with speech and language. Assessing asymmetry of radiomics in PPA allows achieving a deeper insight into the neuroanatomical damage and may represent a candidate severity marker for language impairments in PPA patients.
Introduction
The functional connectivity patterns in the brain are highly heritable; however, it is unclear how genetic factors influence the directionality of such “information flows.” Studying the ...“directionality” of the brain functional connectivity and assessing how heritability modulates it can improve our understanding of the human connectome.
Methods
Here, we investigated the heritability of “directed” functional connections using a state‐space formulation of Granger causality (GC), in conjunction with blind deconvolution methods accounting for local variability in the hemodynamic response function. Such GC implementation is ideal to explore the directionality of functional interactions across a large number of networks. Resting‐state functional magnetic resonance imaging data were drawn from the Human Connectome Project (total n = 898 participants). To add robustness to our findings, the dataset was randomly split into a “discovery” and a “replication” sample (each with n = 449 participants). The two cohorts were carefully matched in terms of demographic variables and other confounding factors (e.g., education). The effect of shared environment was also modeled.
Results
The parieto‐ and prefronto‐cerebellar, parieto‐prefrontal, and posterior‐cingulate to hippocampus connections showed the highest and most replicable heritability effects with little influence by shared environment. In contrast, shared environmental factors significantly affected the visuo‐parietal and sensory‐motor directed connectivity.
Conclusion
We suggest a robust role of heritability in influencing the directed connectivity of some cortico‐subcortical circuits implicated in cognition. Further studies, for example using task‐based fMRI and GC, are warranted to confirm the asymmetric effects of genetic factors on the functional connectivity within cognitive networks and their role in supporting executive functions and learning.
We investigated the heritability of ‘directed’ functional connections using a state‐space formulation of Granger causality on resting‐state functional magnetic resonance imaging data from the Human Connectome Project. The parieto‐cerebellar, parieto‐prefrontal, and posterior‐cingulate to hippocampus connections showed the highest and most replicable heritability effects with little influence by the shared environment. In contrast, shared environmental factors significantly affected the visuo‐parietal and sensory‐motor directed connectivity.
We suggest a robust role of heritability in influencing the function of some cortico‐subcortical circuits consistently implicated in cognition.
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