Deformation-based Morphometry Research Articles

Neuroanatomical Signature of the Transition from Normal Cognition to MCI in Parkinson's Disease.

The progression of Parkinson's disease (PD) is often accompanied by cognitive decline. We had previously developed a brain age estimation program utilizing structural MRI data of 949 healthy individuals from publicly available sources. Structural MRI data of 244 PD patients who were cognitively normal at baseline was acquired from the Parkinson Progression Markers Initiative (PPMI). 192 of these showed stable normal cognitive function from baseline out to 5 years (PD-SNC), and the remaining 52 had unstable normal cognition and developed mild cognitive impairment within 5 years (PD-UNC). 105 healthy controls were also included in the analysis as a reference. First, we examined if there were any baseline differences in regional brain structure between PD-UNC and PD-SNC cohorts utilizing the three most widely used atrophy estimation pipelines, i.e., voxel-based morphometry (VBM), deformation-based morphometry and cortical thickness analyses. We then investigated if accelerated brain age estimation with our multivariate regressive machine learning algorithm was different across these groups (HC, PD-SNC, and PD-UNC). As per the VBM analysis, PD-UNC patients demonstrated a noticeable increase in GM volume in the posterior and anterior lobes of the cerebellum, sub-lobar, extra-nuclear, thalamus, and pulvinar regions when compared to PD-SNC at baseline. PD-UNC patients were observed to have significantly older brain age compared to both PD-SNC patients (p=0.009) and healthy controls (p<0.009). The increase in GM volume in the PD-UNC group could potentially indicate an inflammatory or neuronal hypertrophy response, which could serve as a biomarker for future cognitive decline among this population.

GR.3 Distinct longitudinal brain atrophy trajectories in parkinson’s disease clinical subtypes: insight towards precision medicine

Background: Parkinson’s disease (PD) varies widely across individuals in terms of clinical manifestations and course of progression. We aimed to compare patterns of brain atrophy between PD clinical subtypes using longitudinally acquired brain MRIs. Methods: We used T1-weighted MRIs from Parkinson’s Progression Markers Initiative (PPMI) on 134 PD individuals and 60 healthy controls with at least two MRIs. Patients were classified into three clinical subtypes at de novo stage using validated subtyping criteria based on major motor and non-motor classifiers (early cognitive impairment, RBD, dysautonomia): mild-motor predominant (n=74), intermediate (n=44), and diffuse-malignant (n=16). Deformation-based morphometry (DBM) maps were calculated and mixed effect models were used to examine the interaction between PD subtypes and rate of atrophy across brain regions over time, controlling for sex and age at baseline. Results: Individuals with ‘diffuse malignant’ PD showed a significantly higher rate of atrophy across multiple brain regions, including lateral nucleus of the forebrain, precuneus, paracentral lobule, inferior temporal gyrus, fusiform gyrus, and lateral hemisphere of the cerebellum (FDR corrected p&lt;0.05). Conclusions: We demonstrated an accelerated atrophy pattern within several brain regions in ‘diffuse malignant’ PD subtype. These findings suggest the presence of a more diffuse multidomain neurodegenerative process in a subgroup of people with PD, favoring the existence of diverse underlying pathophysiologies.

Irregular word reading as a marker of semantic decline in Alzheimer’s disease: implications for premorbid intellectual ability measurement

BackgroundIrregular word reading has been used to estimate premorbid intelligence in Alzheimer’s disease (AD) dementia. However, reading models highlight the core influence of semantic abilities on irregular word reading, which shows early decline in AD. The primary objective of this study is to ascertain whether irregular word reading serves as an indicator of cognitive and semantic decline in AD, potentially discouraging its use as a marker for premorbid intellectual abilities.MethodSix hundred eighty-one healthy controls (HC), 104 subjective cognitive decline, 290 early and 589 late mild cognitive impairment (EMCI, LMCI) and 348 AD participants from the Alzheimer’s Disease Neuroimaging Initiative were included. Irregular word reading was assessed with the American National Adult Reading Test (AmNART). Multiple linear regressions were conducted predicting AmNART score using diagnostic category, general cognitive impairment and semantic tests. A generalized logistic mixed-effects model predicted correct reading using extracted psycholinguistic characteristics of each AmNART words. Deformation-based morphometry was used to assess the relationship between AmNART scores and voxel-wise brain volumes, as well as with the volume of a region of interest placed in the left anterior temporal lobe (ATL), a region implicated in semantic memory.ResultsEMCI, LMCI and AD patients made significantly more errors in reading irregular words compared to HC, and AD patients made more errors than all other groups. Across the AD continuum, as well as within each diagnostic group, irregular word reading was significantly correlated to measures of general cognitive impairment / dementia severity. Neuropsychological tests of lexicosemantics were moderately correlated to irregular word reading whilst executive functioning and episodic memory were respectively weakly and not correlated. Age of acquisition, a primarily semantic variable, had a strong effect on irregular word reading accuracy whilst none of the phonological variables significantly contributed. Neuroimaging analyses pointed to bilateral hippocampal and left ATL volume loss as the main contributors to decreased irregular word reading performances.ConclusionsWhile the AmNART may be appropriate to measure premorbid intellectual abilities in cognitively unimpaired individuals, our results suggest that it captures current semantic decline in MCI and AD patients and may therefore underestimate premorbid intelligence. On the other hand, irregular word reading tests might be clinically useful to detect semantic impairments in individuals on the AD continuum.

Degeneration in Nucleus basalis of Meynert signals earliest stage of Alzheimer’s disease progression

Nucleus Basalis of Meynert (NbM), a crucial source of cholinergic projection to the entorhinal cortex (EC) and hippocampus (HC), has shown sensitivity to neurofibrillary degeneration in the early stages of Alzheimer’s Disease. Using deformation-based morphometry (DBM) on up-sampled MRI scans from 1447 Alzheimer’s Disease Neuroimaging Initiative participants, we aimed to quantify NbM degeneration along the disease trajectory. Results from cross-sectional analysis revealed significant differences of NbM volume between cognitively normal and early mild cognitive impairment cohorts, confirming recent studies suggesting that NbM degeneration happens before degeneration in the EC or HC. Longitudinal linear mixed-effect models were then used to compare trajectories of volume change after realigning all participants into a common timeline based on their cognitive decline. Results indicated the earliest deviations in NbM volumes from the cognitively healthy trajectory, challenging the prevailing idea that Alzheimer’s originates in the EC. Converging evidence from cross-sectional and longitudinal models suggest that the NbM may be a focal target of early AD progression, which is often obscured by normal age-related decline.

Epilepsy-related functional brain network alterations are already present at an early age in the GAERS rat model of genetic absence epilepsy.

Genetic Absence Epilepsy Rats from Strasbourg (GAERS) represent a model of genetic generalized epilepsy. The present longitudinal study in GAERS and age-matched non-epileptic controls (NEC) aimed to characterize the epileptic brain network using two functional measures, resting state-functional magnetic resonance imaging (rs-fMRI) and manganese-enhanced MRI (MEMRI) combined with morphometry, and to investigate potential brain network alterations, following long-term seizure activity. Repeated rs-fMRI measurements at 9.4 T between 3 and 8 months of age were combined with MEMRI at the final time point of the study. We used graph theory analysis to infer community structure and global and local network parameters from rs-fMRI data and compared them to brain region-wise manganese accumulation patterns and deformation-based morphometry (DBM). Functional connectivity (FC) was generally higher in GAERS when compared to NEC. Global network parameters and community structure were similar in NEC and GAERS, suggesting efficiently functioning networks in both strains. No progressive FC changes were observed in epileptic animals. Network-based statistics (NBS) revealed stronger FC within the cortical community, including regions of association and sensorimotor cortex, and with basal ganglia and limbic regions in GAERS, irrespective of age. Higher manganese accumulation in GAERS than in NEC was observed at 8 months of age, consistent with higher overall rs-FC, particularly in sensorimotor cortex and association cortex regions. Functional measures showed less similarity in subcortical regions. Whole brain volumes of 8 months-old GAERS were higher when compared to age-matched NEC, and DBM revealed increased volumes of several association and sensorimotor cortex regions and of the thalamus. rs-fMRI, MEMRI, and volumetric data collectively suggest the significance of cortical networks in GAERS, which correlates with an increased fronto-central connectivity in childhood absence epilepsy (CAE). Our findings also verify involvement of basal ganglia and limbic regions. Epilepsy-related network alterations are already present in juvenile animals. Consequently, this early condition seems to play a greater role in dynamic brain function than chronic absence seizures.

Paternal Prenatal and Lactation Exposure to a High-Calorie Diet Shapes Transgenerational Brain Macro- and Microstructure Defects, Impacting Anxiety-Like Behavior in Male Offspring Rats.

Prenatal exposure to high-energy diets (HED) increases the susceptibility to behavioral alterations in the male offspring. We addressed whether prenatal HED primes the transgenerational inheritance of structural brain changes impacting anxiety/depression-like behavior in the offspring. For this, we used female Wistar rats exposed to a HED [cafeteria (CAF) diet, n = 6] or chow [control (CON) n = 6] during development. Anxiety and depression-like behavior were evaluated in filial 1 (F1), filial 2 (F2), and filial 3 (F3) male offspring using the open field (OFT), elevated plus maze, novelty suppressed feeding (NSFT), tail suspension (TST), and forced swimming tests. Structural brain changes were identified by deformation-based morphometry (DBM) and diffusion tensor imaging using ex vivo MRI. We found that the F1, F2, and F3 offspring exposed to CAF diet displayed higher anxious scores including longer feeding latency during the NSFT, and in the closed arms, only F1 offspring showed longer stay on edges during the OFT versus control offspring. DBM analysis revealed that CAF offspring exhibited altered volume in the cerebellum, hypothalamus, amygdala, and hippocampus preserved up to the F3 generation of anxious individuals. Also, F3 CAF anxious exhibited greater fractional anisotropy and axial diffusivity (AD) in the amygdala, greater apparent diffusion coefficient in the corpus callosum, and greater AD in the hippocampus with respect to the control. Our results suggest that prenatal and lactation exposure to HED programs the transgenerational inheritance of structural brain changes related to anxiety-like behavior in the male offspring.

Quantitative brain morphometry identifies cerebellar, cortical, and subcortical gray and white matter atrophy in late-onset Tay-Sachs disease.

Cerebellar atrophy is a characteristic sign of late-onset Tay-Sachs disease (LOTS). Other structural neuroimaging abnormalities are inconsistently reported. Our study aimed to perform a detailed whole-brain analysis and quantitatively characterize morphometric changes in LOTS patients. Fourteen patients (8 M/6F) with LOTS from three centers were included in this retrospective study. For morphometric brain analyses, we used deformation-based morphometry, voxel-based morphometry, surface-based morphometry, and spatially unbiased cerebellar atlas template. The quantitative whole-brain morphometric analysis confirmed the finding of profound pontocerebellar atrophy with most affected cerebellar lobules V and VI in LOTS patients. Additionally, the atrophy of structures mainly involved in motor control, including bilateral ventral and lateral thalamic nuclei, primary motor and sensory cortex, supplementary motor area, and white matter regions containing corticospinal tract, was present. The atrophy of the right amygdala, hippocampus, and regions of occipital, parietal and temporal white matter was also observed in LOTS patients in contrast with controls (p < 0.05, FWE corrected). Patients with dysarthria and those initially presenting with ataxia had more severe cerebellar atrophy. Our results show predominant impairment of cerebellar regions responsible for speech and hand motor function in LOTS patients. Widespread morphological changes of motor cortical and subcortical regions and tracts in white matter indicate abnormalities in central motor circuits likely coresponsible for impaired speech and motor function.

Characterization of dynamic patterns of human fetal to neonatal brain asymmetry with deformation-based morphometry.

Despite established knowledge on the morphological and functional asymmetries in the human brain, the understanding of how brain asymmetry patterns change during late fetal to neonatal life remains incomplete. The goal of this study was to characterize the dynamic patterns of inter-hemispheric brain asymmetry over this critically important developmental stage using longitudinally acquired MRI scans. Super-resolution reconstructed T2-weighted MRI of 20 neurotypically developing participants were used, and for each participant fetal and neonatal MRI was acquired. To quantify brain morphological changes, deformation-based morphometry (DBM) on the longitudinal MRI scans was utilized. Two registration frameworks were evaluated and used in our study: (A) fetal to neonatal image registration and (B) registration through a mid-time template. Developmental changes of cerebral asymmetry were characterized as (A) the inter-hemispheric differences of the Jacobian determinant (JD) of fetal to neonatal morphometry change and the (B) time-dependent change of the JD capturing left-right differences at fetal or neonatal time points. Left-right and fetal-neonatal differences were statistically tested using multivariate linear models, corrected for participants' age and sex and using threshold-free cluster enhancement. Fetal to neonatal morphometry changes demonstrated asymmetry in the temporal pole, and left-right asymmetry differences between fetal and neonatal timepoints revealed temporal changes in the temporal pole, likely to go from right dominant in fetal to a bilateral morphology in neonatal timepoint. Furthermore, the analysis revealed right-dominant subcortical gray matter in neonates and three clusters of increased JD values in the left hemisphere from fetal to neonatal timepoints. While these findings provide evidence that morphological asymmetry gradually emerges during development, discrepancies between registration frameworks require careful considerations when using DBM for longitudinal data of early brain development.

Volumetric brain correlates of gait associated with cognitive decline in community-dwelling older adults.

To determine the extent to which the regional brain volumes associated with slow gait speed can inform subsequent cognitive decline in older adults from the Rush Memory and Aging Project. We utilized deformation-based morphometry (DBM) in a whole-brain exploratory approach to identify the regional brain volumes associated with gait speed assessed over a short distance during an in-home assessment. We created deformation scores to summarize the gait-associated regions and entered the scores into a series of longitudinal mixed effects models to determine the extent to which deformation predicted change in cognition over time, controlling for associations between gait and cognition. In 438 older adults (81 ± 7; 76% female), DBM revealed that slower gait speed was associated with smaller volumes across frontal white matter, temporal grey matter, and subcortical areas and larger volumes in the ventricles during the same testing cycle. When a subset was followed over multiple (5 ± 2) years, slower gait speed was also associated with annual declines in global cognition, executive functioning, and memory abilities. Several of the gait-related brain structures were associated with these declines in cognition; however, larger ventricles and smaller medial temporal lobe volumes proved most robust and attenuated the association between slow gait and cognitive decline. Regional brain volumes in the ventricles and temporal lobe associated with both slow gait speed and faster cognitive decline have potential to improve risk stratification for cognitive decline in older adults.

Cortical and subcortical morphometric changes and their relation to cognitive impairment in isolated REM sleep behavior disorder.

To date, very few studies have focused on structural changes and their association with cognitive performance in isolated REM sleep behaviour disorder (iRBD). Moreover, the results of these studies are inconclusive. This study aims to evaluate differences in the associations between brain morphology and cognitive tests in iRBD and healthy controls. Sixty-three patients with iRBD and thirty-six controls underwent MRI with a 3T scanner. The cognitive performance was assessed by a comprehensive neuropsychological battery. Based on performance, the iRBD group was divided into two subgroups with (iRBD-MCI) and without mild cognitive impairment (iRBD-NC). The high-resolution T1-weighted images were analysed using an automated atlas segmentation tool, voxel-based (VBM) and deformation-based (DBM) morphometry to identify between-group differences and correlations with cognitive performance. VBM, DBM and the comparison of ROI volumes yielded no significant differences between iRBD and controls. In the iRBD group, significant correlations in VBM were found between several cortical and subcortical structures primarily located in the temporal, parietal, occipital lobe, cerebellum, and basal ganglia and three cognitive tests assessing psychomotor speed and one memory test. Between-group analysis of cognition revealed a significant difference between iRBD-MCI and iRBD-NC in tests including a processing speed component. iRBD shows deficits in several cognitive tests that correlate with morphological changes, the most prominent of which is in psychomotor speed and visual attention as measured by the TMT-A and associated with the volume of striatum, insula, cerebellum, temporal lobe, pallidum and amygdala.

Deformation‐based morphometry analysis shows early degeneration in Nucleus basalis of Meynert in Alzheimer’s disease

AbstractBackgroundNucleus basalis of Meynert (NbM) is the main source of cholinergic projection to the cerebral cortex, including entorhinal cortex (EC). Both cholinergic cells of NbM and their receptive targets in EC show degeneration during early stages of Alzheimer’s disease (AD). While precise delineation of NbM region on T1w scans is difficult due to limited spatial resolution and contrast, we sought to quantify the degeneration of NbM along the disease trajectory and confirm recent studies suggesting that NbM degeneration happens before degeneration in the EC using deformation‐based morphometry (DBM).MethodData included MRI scans of 1473 subjects from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset. Resolution was increased to 0.5 mm isotropic voxel‐size before non‐linear registration to an ADNI‐based unbiased symmetric template. The resulting deformation fields were used to compute the Jacobian determinant map for each subject as a proxy for local volume. NbM and EC masks were mapped to our high‐resolution template and mean determinant values inside these masks were calculated for groups with different baseline diagnosis, and sex‐ and age‐corrected z‐scores were calculated. Two‐sample t‐tests were then used to compare the scores between different groups.ResultFigure 1 shows the mean DBM score of both NbM and EC regions for Normal Controls (CN), subjects with early‐ and late‐stage mild cognitive impairment (EMCI and LMCI) and subjects with probable AD dementia. Results corrected for multiple comparisons showed a significant difference between CN and both EMCI and LMCI for left and right NbM. A significant difference was also observed between EMCI and LMCI in left NbM (p‐value = 0.0024). Z‐scored EC volumes did not show a significant difference between CN and EMCI groups; However, results from EMCI and LMCI differ significantly in both hemispheres. We also observed the expected differences between each group with AD in both NbM and EC (P&lt;0.001).ConclusionOur results show that while macroscopic changes in EC emerge as MCI subjects advance toward the later stages, NbM degeneration starts sooner, as early as preliminary stages of MCI. This points to MRI‐based measurements of NbM as potential biomarkers for early detection of AD and as a marker of disease burden.

Deformation‐based morphometry analysis shows early degeneration in Nucleus basalis of Meynert in Subjective Cognitive Decline

AbstractBackgroundPeople with subjective cognitive decline (SCD+) are thought to be at greater risk of Alzheimer’s disease (AD). The Nucleus basalis of Meynert (NbM) has been shown to change early in AD (Fernández‐Cabello et al., 2020), and it is the main source of cholinergic projection to entorhinal cortex (EC) (Mesulam et al., 2013). We thus investigated if there was evidence of degeneration in the NbM, or EC in SCD+ participants compared to those without (SCD‐), and if there was a relationship between changes in these regions and SCD status using deformation‐based morphometry (DBM).MethodData included baseline visit MRI scans of 232 cognitively healthy older adults (148 SCD‐; 84 SCD+) from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset (using only ADNI2). SCD status was extracted based on the cognitive change index (CCI) of the subjects reported in ADNIMERGE data (CCI ≥16). MRI resolution was increased to 0.5 mm isotropic voxel‐size before non‐linear registration to an ADNI‐based unbiased symmetric template. The resulting deformation fields were used to compute the Jacobian determinant map for each subject as a proxy for local volume. NbM, and EC masks were mapped to our high‐resolution template and mean determinant values inside these masks were estimated, and sex‐ and age‐corrected z‐scores were calculated. Two‐sample t‐tests were then used to compare the SCD+:SCD‐ differences.ResultFigure 1 shows the mean z‐score values for NbM and EC regions for both SCD+ and SCD‐ groups. Results for left NbM showed a significant difference between two groups (p = .007), but not for the right NbM (p = .12). However, z‐scored EC volumes did not show any statistically significant difference between groups for either left (p = .58) or right region (p = .41).ConclusionOur results suggest that in SCD+ subjects, while the EC is still intact, neurodegeneration in the NbM appears to have already begun. Quantifying degeneration in the NbM may allow for early diagnosis of AD. Further research is needed to evaluate if such differences can be computed on an individual subject basis for use as a biomarker.

Brain gray matter reduction and premature brain aging after breast cancer chemotherapy: a longitudinal multicenter data pooling analysis.

Brain gray matter (GM) reductions have been reported after breast cancer chemotherapy, typically in small and/or cross-sectional cohorts, most commonly using voxel-based morphometry (VBM). There has been little examination of approaches such as deformation-based morphometry (DBM), machine-learning-based brain aging metrics, or the relationship of clinical and demographic risk factors to GM reduction. This international data pooling study begins to address these questions. Participants included breast cancer patients treated with (CT+, n = 183) and without (CT-, n = 155) chemotherapy and noncancer controls (NC, n = 145), scanned pre- and post-chemotherapy or comparable intervals. VBM and DBM examined GM volume. Estimated brain aging was compared to chronological aging. Correlation analyses examined associations between VBM, DBM, and brain age, and between neuroimaging outcomes, baseline age, and time since chemotherapy completion. CT+ showed longitudinal GM volume reductions, primarily in frontal regions, with a broader spatial extent on DBM than VBM. CT- showed smaller clusters of GM reduction using both methods. Predicted brain aging was significantly greater in CT+ than NC, and older baseline age correlated with greater brain aging. Time since chemotherapy negatively correlated with brain aging and annual GM loss. This large-scale data pooling analysis confirmed findings of frontal lobe GM reduction after breast cancer chemotherapy. Milder changes were evident in patients not receiving chemotherapy. CT+ also demonstrated premature brain aging relative to NC, particularly at older age, but showed evidence for at least partial GM recovery over time. When validated in future studies, such knowledge could assist in weighing the risks and benefits of treatment strategies.

Cocaine Destroys Gray Matter Brain Cells and Accelerates Brain Aging.

Introduction: Cocaine use disorder (CUD) is a substance use disorder characterized by a strong desire to obtain, consume, and misuse cocaine. Little is known about how cocaine affects the structure of the brain. In this study, we first investigated the anatomical brain changes in individuals with CUD compared to their matched healthy controls, and then explored whether these anatomical brain abnormalities contribute to considerably accelerated brain aging among this population. Methods: At the first stage, we used anatomical magnetic resonance imaging (MRI) data, voxel-based morphometry (VBM), and deformation-based morphometry techniques to uncover the morphological and macroscopic anatomical brain changes in 74 CUD patients compared to 62 age- and sex-matched healthy controls (HCs) obtained from the SUDMEX CONN dataset, the Mexican MRI dataset of patients with CUD. Then, we computed brain-predicted age difference (i.e., brain-PAD: the brain-predicted age minus the actual age) in CUD and HC groups using a robust brain age estimation framework. Using a multiple regression analysis, we also investigated the regional gray matter (GM) and white matter (WM) changes associated with the brain-PAD. Results: Using a whole-brain VBM analysis, we observed widespread gray matter atrophy in CUD patients located in the temporal lobe, frontal lobe, insula, middle frontal gyrus, superior frontal gyrus, rectal gyrus, and limbic lobe regions compared to the HCs. In contrast, we did not observe any swelling in the GM, changes in the WM, or local brain tissue atrophy or expansion between the CUD and HC groups. Furthermore, we found a significantly higher brain-PAD in CUD patients compared to matched HCs (mean difference = 2.62 years, Cohen's d = 0.54; t-test = 3.16, p = 0.002). The regression analysis showed significant negative changes in GM volume associated with brain-PAD in the CUD group, particularly in the limbic lobe, subcallosal gyrus, cingulate gyrus, and anterior cingulate regions. Discussion: The results of our investigation reveal that chronic cocaine use is linked to significant changes in gray matter, which hasten the process of structural brain aging in individuals who use the drug. These findings offer valuable insights into the impact of cocaine on the composition of the brain.

Alteration of the cortical morphology in classical trigeminal neuralgia: voxel-, deformation-, and surface-based analysis

ObjectiveThis study aimed to combine voxel-based morphometry, deformation-based morphometry, and surface-based morphometry to analyze gray matter volume and cortex shape in classical trigeminal neuralgia patients.MethodsThis study included 79 classical trigeminal neuralgia patients and age- and sex-matched 81 healthy controls. The aforementioned three methods were used to analyze brain structure in classical trigeminal neuralgia patients. Spearman correlation analysis was used to analyze the correlation of brain structure with the trigeminal nerve and clinical parameters.ResultsThe bilateral trigeminal nerve was atrophied, and the ipsilateral trigeminal nerve volume was smaller than the contralateral volume in the classical trigeminal neuralgia. The gray matter volume of Temporal_Pole_Sup_R and Precentral_R was found to be decreased using voxel-based morphometry. The gray matter volume of Temporal_Pole_Sup_R had a positive correlation with disease duration and a negative correlation with the cross-section area of the compression point and the quality-of-life score in trigeminal neuralgia. The gray matter volume of Precentral_R was negatively correlated with the ipsilateral volume of the trigeminal nerve cisternal segment, cross-section area of compression point, and visual analogue scale. The gray matter volume of Temporal_Pole_Sup_L was found to be increased using deformation-based morphometry and had a negative correlation with the self-rating anxiety scale. The gyrification of the middle temporal gyrus_L increased and the Postcentral_L thickness decreased, as detected using surface-based morphometry.ConclusionsThe gray matter volume and cortical morphology of pain-related brain regions were correlated with clinical and trigeminal nerve parameters. voxel-based morphometry, deformation-based morphometry, and surface-based morphometry complemented each other in analyzing the brain structures of patients with classical trigeminal neuralgia and provided a basis for studying the pathophysiology of classical trigeminal neuralgia.Graphical

Brain Macro-Structural Alterations in Aging Rats: A Longitudinal Lifetime Approach.

Aging is accompanied by macro-structural alterations in the brain that may relate to age-associated cognitive decline. Animal studies could allow us to study this relationship, but so far it remains unclear whether their structural aging patterns correspond to those in humans. Therefore, by applying magnetic resonance imaging (MRI) and deformation-based morphometry (DBM), we longitudinally screened the brains of male RccHan:WIST rats for structural changes across their average lifespan. By combining dedicated region of interest (ROI) and voxel-wise approaches, we observed an increase in their global brain volume that was superimposed by divergent local morphologic alterations, with the largest aging effects in early and middle life. We detected a modality-dependent vulnerability to shrinkage across the visual, auditory, and somato-sensory cortical areas, whereas the piriform cortex showed partial resistance. Furthermore, shrinkage emerged in the amygdala, subiculum, and flocculus as well as in frontal, parietal, and motor cortical areas. Strikingly, we noticed the preservation of ectorhinal, entorhinal, retrosplenial, and cingulate cortical regions, which all represent higher-order brain areas and extraordinarily grew with increasing age. We think that the findings of this study will further advance aging research and may contribute to the establishment of interventional approaches to preserve cognitive health in advanced age.

Prenatal Cafeteria Diet Primes Anxiety-like Behavior Associated to Defects in Volume and Diffusion in the Fimbria-fornix of Mice Offspring

Prenatal exposure to high-energy diets primes brain alterations that increase the risk of developing behavioral and cognitive failures. Alterations in the structure and connectivity of brain involved in learning and memory performance are found in adult obese murine models and in humans. However, the role of prenatal exposure to high-energy diets in the modulation of the brain’s structure and function during cognitive decline remains unknown. We used female C57BL6 mice (n = 10) exposed to a high-energy diets (Cafeteria diet (CAF)) or Chow diet for 9 weeks (before, during and after pregnancy) to characterize their effect on brain structural organization and learning and memory performance in the offspring at two-month-old (n = 17). Memory and learning performance were evaluated using the Y-maze test including forced and spontaneous alternation, novel object recognition (NORT), open field and Barnes maze tests. We found no alterations in the short- or long-time spatial memory performance in male offspring prenatally exposed to CAF diet when compared to the control, but they increased time spent in the edges resembling anxiety-like behavior. By using deformation-based morphometry and diffusion tensor imaging analysis we found that male offspring exposed to CAF diet showed increased volume in primary somatosensory cortex and a reduced volume of fimbria-fornix, which correlate with alterations in its white matter integrity. Biological modeling revealed that prenatal exposure to CAF diet predicts low volume in the fimbria-fornix, which was associated with anxiety in the offspring. The findings suggest that prenatal exposure to high-energy diets prime brain structural alterations related to anxiety in the offspring.

Deep Learning Registration with Scan‐temporal Consistency May Improve Detection of Alzheimer’s Disease Progression

AbstractBackgroundStructural changes in Alzheimer’s disease (AD) can be detected as atrophy in the medial temporal lobe (MTL), which is normally studied by applying volumetric or deformation‐based morphometry (DBM) to longitudinal scans. However, conventional DMB methods are computationally intensive and may not estimate the atrophy accurately due to the noise in the longitudinal images, e.g., head motion or MRI artifacts. We hypothesize that deep learning models can be trained to estimate atrophy from longitudinal MRI scans and are more sensitive to biological changes rather than artifactual.MethodTwo models were trained on longitudinal T1 MRI from 155 ADNI participants and tested on 326 participants. First, a deep learning‐based registration model Voxelmorph (Balakrishnan et al., 2019) was applied to generate a deformation field to calculate MTL atrophy rate for each pair of images. Hypothesizing that noise is independent of time while neurodegeneration is time dependent, we then extended Voxelmorph to incorporate a loss that encourages the model to correctly infer the input scan temporal order (STO). In addition, in order to preserve the deformable registration nature of Voxelmorph, it’s weights were held fixed during network training, and instead a U‐Net reconstruction network was introduced, to synthesize inputs to Voxelmorph. Models were compared with a DBM method ALOHA (Das et al., 2012).ResultVoxelmorph generated atrophy measurements comparable to ALOHA in terms of differentiating AD stages (Figure 2) and STO consistency (Table 2). Voxelmorph + STO model has increased STO consistency and can more significantly differentiate disease stages (in absolute terms), especially between the normal controls and preclinical AD.ConclusionDeep learning‐based registration method Voxelmorph achieves comparable performance in longitudinal analysis of subtle changes as in DBM method ALOHA. With the introduction of a scan temporal order loss and reconstruction network, the model achieves higher sensitivity to disease stage, potentially because it learns to discount longitudinal changes that are related to noise and artifact. This may lead to more sensitive biomarkers for disease monitoring in clinical trials of early AD.

Brain-clinical signatures for vagus nerve stimulation response.

Vagus nerve stimulation (VNS) is a valuable treatment for drug-resistant epilepsy (DRE) without the indication of surgical resection. The clinical heterogeneity of DRE has limited the optimal indication of choice and diagnosis prediction. The study aimed to explore the correlations of brain-clinical signatures with the clinical phenotype and VNS responsiveness. A total of 89 DRE patients, including VNS- (n= 44) and drug-treated (n= 45) patients, were retrospectively recruited. The brain-clinical signature consisted of demographic information and brain structural deformations, which were measured using deformation-based morphometry and presented as Jacobian determinant maps. The efficacy and presurgical differences between these two cohorts were compared. Then, the potential of predicting VNS response using brain-clinical signature was investigated according to the different prognosis evaluation approaches. The seizure reduction was higher in the VNS-treated group (42.50%) as compared to the drug-treated group (12.09%) (p= 0.11). Abnormal imaging representation, showing encephalomalacia (pcorrected = 0.03), was commonly observed in the VNS-treated group (p= 0.04). In the patients treated with VNS, the mild/subtle brain abnormalities indicated higher seizure frequency (p= 0.03) and worse VNS response (p= 0.04). The partial least square regression analysis showed a moderate prediction potential of brain-clinical signature for VNS response (p< 0.01). The increase in the pre-VNS seizure frequency and structural etiology could indicate a worse prognosis (higher McHugh classification). The brain-clinical signature illustrated its clinical potential in predicting the VNS response, which might allow clinicians to personalize treatment decisions for DRE patients.

Left Frontal White Matter Links to Rhythm Processing Relevant to Speech Production in Apraxia of Speech.

Recent mechanistic models argue for a key role of rhythm processing in both speech production and speech perception. Patients with the non-fluent variant (NFV) of primary progressive aphasia (PPA) with apraxia of speech (AOS) represent a specific study population in which this link can be examined. Previously, we observed impaired rhythm processing in NFV with AOS. We hypothesized that a shared neurocomputational mechanism structures auditory input (sound and speech) and output (speech production) in time, a "temporal scaffolding" mechanism. Since considerable white matter damage is observed in NFV, we test here whether white matter changes are related to impaired rhythm processing. Forty-seven participants performed a psychoacoustic test battery: 12 patients with NFV and AOS, 11 patients with the semantic variant of PPA, and 24 cognitively intact age- and education-matched controls. Deformation-based morphometry was used to test whether white matter volume correlated to rhythmic abilities. In 34 participants, we also obtained tract-based metrics of the left Aslant tract, which is typically damaged in patients with NFV. Nine out of 12 patients with NFV displayed impaired rhythmic processing. Left frontal white matter atrophy adjacent to the supplementary motor area (SMA) correlated with poorer rhythmic abilities. The structural integrity of the left Aslant tract also correlated with rhythmic abilities. A colocalized and perhaps shared white matter substrate adjacent to the SMA is associated with impaired rhythmic processing and motor speech impairment. Our results support the existence of a temporal scaffolding mechanism structuring perceptual input and speech output.