FreeSurfer Research Articles

In vivo imaging of LC‐NE Integrity: Mechanism for racial/ethnic disparity in preclinical AD

AbstractBackgroundDespite studies suggesting that blacks may be at greater risk of developing AD, there have been few studies investigating health disparities, and blacks have been underrepresented in many prominent AD biomarker studies and clinical trials. The current ATN biomarker classification system may not fully account for health disparities and can’t explain the increased prevalence among blacks for both AD and AD vascular risks of diabetes and hypertension when compared to whites. Research on cognitive aging has traditionally focused on how decline in various cortical and hippocampal (Hip) regions influences cognition. However, tau pathology emerges decades before amyloid pathology, appearing first in the brainstem (BS); particularly in the locus coeruleus (LC), the source of brain’s norepinephrine (NE). Our decade‐long studies in humans using a norepinephrine transporter (NET)‐selective radiotracer ([11C]MRB) have demonstrated a special vulnerability of LC to aging and stress.MethodCo‐registration of PET (dynamic [11C]MRB), MRI and the FreeSurfer (FS) atlas images of each individual was used to generate regional time‐activity curves using Firevoxel. Binding potential (BPND) values were determined using MRTM2 with occipital as the reference region. Annual percent change (APC) of BPND was calculated based on linear regression (APC = 100 × (em – 1), m: slope) and effects of age, gender and ethnicity on tracer binding were evaluated.ResultFor all HC (N=31), with both genders and all races included, age‐sensitive decline of NET availability was observed; e.g., 0.3‐0.5%/yr for Hip, BS and olfactory. However, our data reveals that the decline rate of NET is much faster among blacks starting in the mid‐30s, particularly in black males; e.g., 2‐3%/yr vs. 0.14‐0.23%/yr in thalamus and brainstem for black males vs. white males (p<0.00001).ConclusionIn addition to our previously determined age effect on MRB‐NET binding, this report further reveals the role of ethnicity effects on NET availability. Our study showed that a faster decline of LC‐NE function occurs in blacks, possibly caused by cumulative stress to socioeconomic disadvantage and racial discrimination, and may be responsible for the different disease expression among blacks. Thus, NET availability imaging represents a novel biomarker approach to racial‐dependent strategies for diagnosis and assessment of therapeutic interventions.

Neural networks in the predictive diagnosis of cognitive impairment in type 1 and type 2 diabetes mellitus

Cognitive dysfunction, including mild cognitive impairment and dementia, is increasingly recognized as a serious complication of diabetes mellitus (DM) that affects patient well-being and disease management. Magnetic resonance imaging (MRI)-studies have shown varying degrees of cortical atrophy, cerebral infarcts, and deep white matter lesions. To explain the relationship between DM and cognitive decline, several hypotheses have been proposed, based on the variability of glycemia leading to morphometric changes in the brain. The ability to predict cognitive decline even before its clinical development will allow the early prevention of this pathology, as well as to predict the course of the existing pathology and to adjust medication regimens. To create a computer neural network model for predicting the development of cognitive impairment in DM on the basis of brain neuroimaging techniques. The study was performed in accordance with the standards of good clinical practice; the protocol was approved by the Ethics Committee. The study included 85 patients with type 1 diabetes and 95 patients with type 2 diabetes, who were divided into a group of patients with normal cognitive function and a group with cognitive impairment. The patient groups were comparable in age and duration of disease. Cognitive impairment was screened using the Montreal Cognitive Assessment Scale. Data for glycemic variability were obtained using continuous glucose monitoring (iPro2, Libre). A standard MRI scan of the brain was performed axially, sagittally, and coronally on a Signa Creator E, GE Healthcare, 1.5 Tesla, China. For MRI data processing we used Free Surfer program (USA) for analysis and visualization of structural and functional neuroimaging data from cross-sectional or longitudinal studies, and for segmentation we used Recon-all batch program directly. All statistical analyses and data processing were performed using Statistica Statsofi software (version 10) on Windows 7/XP Pro operating systems. The IBM WATSON cognitive system was used to build a neural network model. As a result of the study, cognitive impairment in DM type 1was predominantly of mild degree 36.9% (n=24) and moderate degree 30.76% (n=20), and in DM type 2 mild degree 37% (n=30), moderate degree 49.4% (n=40) and severe degree 13.6% (n=11). Cognitive functions in DM type 1 were impaired in memory and attention, whereas in DM type 2 they were also impaired in tasks of visual-constructive skills, fluency, and abstraction (p0.001). The analysis revealed differences in glycemic variability indices in patients with type 1 and type 2 DM and cognitive impairment. Standard MRI of the brain recorded the presence of white and gray matter changes (gliosis and leukoareosis). General and regional cerebral atrophy is characteristic of type 1 and type 2 DM, which is associated with dysglycemia. When building neural network models for type 1 diabetes, the parameters of decreased volumes of the brain regions determine the development of cognitive impairment by 93.5%, whereas additionally, the coefficients of glycemic variability by 98.5%. The same peculiarity was revealed in type 2 DM 95.3% and 97.9%, respectively. In DM type 1 and type 2 with cognitive impairment, elevated coefficients of glycemic variability are more frequently recorded. This publication describes laboratory and instrumental parameters as potential diagnostic options for effective management of DM and prevention of cognitive impairment. Neural network models using glycemic variability coefficients and MR morphometry allow for predictive diagnosis of cognitive disorders in both types of diabetes.

A volumetric magnetic resonance imaging study in migraine

BackgroundAlthough migraine phenotype has been widely described, the explanation of migraine pathophysiology still has a gap that might be partly bridged by neuroimaging investigations. The aim of the study is to assess volumetric brain changes in migraineurs compared with controls, and in episodic migraine in comparison to chronic type. Structural brain changes in migraineurs (with and without aura) were assessed by an automated segmentation method (Free Surfer). T1-weighted MRIs of 25 migraineurs (14 diagnosed as episodic type and 11 diagnosed as chronic migraine) and 25 headache-free controls were evaluated and processed.ResultsMigraine patients had significant reduction of the volume of total brain, grey matter, brain stem, cerebellum, basal ganglia, thalamus, hippocampus and amygdala in comparison to control subjects. Patients with chronic migraine had significant reduction in volume of total brain, grey matter, cerebellum and frontal lobe thickness in comparison to those with episodic migraine.ConclusionMigraineurs showed volumetric brain changes mainly in areas related to central processing of pain and in areas specific for migraine (such as brain stem) when compared to healthy controls. Chronic migraineurs showed significant reduction in grey matter, in areas involved in processing of pain, cognition and multisensory integration versus patients with episodic migraine, which adds insight into the pathophysiology of migraine as a progressive disorder that may have long-term impacts on the brain as regards structure and function.

Differences Between MR Brain Region Segmentation Methods: Impact on Single-Subject Analysis.

For the segmentation of magnetic resonance brain images into anatomical regions, numerous fully automated methods have been proposed and compared to reference segmentations obtained manually. However, systematic differences might exist between the resulting segmentations, depending on the segmentation method and underlying brain atlas. This potentially results in sensitivity differences to disease and can further complicate the comparison of individual patients to normative data. In this study, we aim to answer two research questions: 1) to what extent are methods interchangeable, as long as the same method is being used for computing normative volume distributions and patient-specific volumes? and 2) can different methods be used for computing normative volume distributions and assessing patient-specific volumes? To answer these questions, we compared volumes of six brain regions calculated by five state-of-the-art segmentation methods: Erasmus MC (EMC), FreeSurfer (FS), geodesic information flows (GIF), multi-atlas label propagation with expectation–maximization (MALP-EM), and model-based brain segmentation (MBS). We applied the methods on 988 non-demented (ND) subjects and computed the correlation (PCC-v) and absolute agreement (ICC-v) on the volumes. For most regions, the PCC-v was good (), indicating that volume differences between methods in ND subjects are mainly due to systematic differences. The ICC-v was generally lower, especially for the smaller regions, indicating that it is essential that the same method is used to generate normative and patient data. To evaluate the impact on single-subject analysis, we also applied the methods to 42 patients with Alzheimer’s disease (AD). In the case where the normative distributions and the patient-specific volumes were calculated by the same method, the patient’s distance to the normative distribution was assessed with the z-score. We determined the diagnostic value of this z-score, which showed to be consistent across methods. The absolute agreement on the AD patients’ z-scores was high for regions of thalamus and putamen. This is encouraging as it indicates that the studied methods are interchangeable for these regions. For regions such as the hippocampus, amygdala, caudate nucleus and accumbens, and globus pallidus, not all method combinations showed a high ICC-z. Whether two methods are indeed interchangeable should be confirmed for the specific application and dataset of interest.

Norms for Automatic Estimation of Hippocampal Atrophy and a Step Forward for Applicability to the Italian Population.

IntroductionHippocampal volume is one of the main biomarkers of Alzheimer’s Dementia (AD). Over the years, advanced tools that performed automatic segmentation of Magnetic Resonance Imaging (MRI) T13D scans have been developed, such as FreeSurfer (FS) and ACM-Adaboost (AA). Hippocampal volume is considered abnormal when it is below the 5th percentile of the normative population. The aim of this study was to set norms, established from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) population, for hippocampal volume measured with FS v.6.0 and AA tools in the neuGRID platform (www.neugrid2.eu) and demonstrate their applicability for the Italian population.MethodsNorms were set from a large group of 545 healthy controls belonging to ADNI. For each pipeline, subjects with segmentation errors were discarded, resulting in 532 valid segmentations for FS and 421 for AA (age range 56–90 years). The comparability of ADNI and the Italian Brain Normative Archive (IBNA), representative of the Italian general population, was assessed testing clinical variables, neuropsychological scores and normalized hippocampal volumes. Finally, percentiles were validated using the Italian Alzheimer’s disease Repository Without Borders (ARWiBo) as external independent data set to evaluate FS and AA generalizability.ResultsHippocampal percentiles were checked with the chi-square goodness of fit test. P-values were not significant, showing that FS and AA algorithm distributions fitted the data well. Clinical, neuropsychological and volumetric features were similar in ADNI and IBNA (p > 0.01). Hippocampal volumes measured with both FS and AA were associated with age (p < 0.001). The 5th percentile thresholds, indicating left/right hippocampal atrophy were respectively: (i) below 3,223/3,456 mm3 at 56 years and 2,506/2,415 mm3 at 90 years for FS; (ii) below 4,583/4,873 mm3 at 56 years and 3,831/3,870 mm3 at 90 years for AA. The average volumes computed on 100 cognitively intact healthy controls (CN) selected from ARWiBo were close to the 50th percentiles, while those for 100 AD patients were close to the abnormal percentiles.DiscussionNorms generated from ADNI through the automatic FS and AA segmentation tools may be used as normative references for Italian patients with suspected AD.

Evaluation of Early Cerebral Atrophy in Mild Cognitive Impairment with Positive Amyloid PET using MRIVolumetric Measurement

Objective: To identify early cerebral atrophy by using magnetic resonance imaging (MRI) volumetric measurement to distinguish mild cognitive impairment (MCI) from normal aging. Materials and Methods: A retrospective study in 29 Alzheimer’s disease (AD) patients (mean 75.6±7.3 years), 11 MCI patients (mean 68.8±3.9 years), and 27 healthy control (HC) subjects (mean 69.3±4.7 years) was performed with analysis of neurological and neuropsychiatric test, and underwent 3T MRI with high-resolution 3D-T1W. Quantitative volumetric analysis of brain including surface area, cortical gray matter volume, cortical thickness, and hippocampal subfields was performed by using FreeSurfer software. Results: The diminishment of cortical gray matter volume and cortical thickness were involved in most of brain regions, predominantly in temporal lobe with statistical significance in AD compared with MCI and HC. Comparison between amyloid positron emission tomography (PET) positive MCI subjects and HC has statistically significant difference in most regions of hippocampal subfield. The highest accuracy of 90.01% with sensitivity of 50% and specificity of 100% were found at subiculum. A comparison between amyloid PET positive MCI subjects and amyloid PET negative MCI subjects revealed significant differences at right molecular layer, right/average GC-ML-DG, right CA2/3, right CA4, and average CA4 with good accuracy, sensitivity, and specificity. Conclusion: The present study confirmed improved sensitivity of MRI volumetric measurement with hippocampal subfield analysis to identify early stage of AD in MCI patients, at least compared with positive amyloid PET MCI. Study with higher number of subjects using this method to discriminate MCI and normal aging control would provide benefits as the screening tool in older population. Keywords: Hippocampal subfield; Volumetric analysis; Alzheimer’s disease; Mild cognitive impairment

Hippocampal and Hippocampal-Subfield Volumes From Early-Onset Major Depression and Bipolar Disorder to Cognitive Decline.

Background: The hippocampus and its subfields (HippSub) are reported to be diminished in patients with Alzheimer's disease (AD), bipolar disorder (BD), and major depressive disorder (MDD). We examined these groups vs healthy controls (HC) to reveal HippSub alterations between diseases.Methods: We segmented 3T-MRI T2-weighted hippocampal images of 67 HC, 58 BD, and MDD patients from the AFFDIS study and 137 patients from the DELCODE study assessing cognitive decline, including subjective cognitive decline (SCD), amnestic mild cognitive impairment (aMCI), and AD, via Free Surfer 6.0 to compare volumes across groups.Results: Groups differed significantly in several HippSub volumes, particularly between patients with AD and mood disorders. In comparison to HC, significant lower volumes appear in aMCI and AD groups in specific subfields. Smaller volumes in the left presubiculum are detected in aMCI and AD patients, differing from the BD group. A significant linear regression is seen between left hippocampus volume and duration since the first depressive episode.Conclusions: HippSub volume alterations were observed in AD, but not in early-onset MDD and BD, reinforcing the notion of different neural mechanisms in hippocampal degeneration. Moreover, duration since the first depressive episode was a relevant factor explaining the lower left hippocampal volumes present in groups.

PET imaging of net availability in humans using [11C]MRB: Age, gender and ethnicity effects

AbstractBackgroundUnderstanding the underlying pathological mechanisms of AD is urgently needed to enable the development of effective treatments. Tau pathology emerges decades before amyloid pathology, appearing first in the brainstem (BS); particularly in the locus coeruleus (LC), the source of brain’s norepinephrine (NE). Our preliminary data using [11C]MRB have documented an age‐related decline in NE transporters (NET) starting in middle age, suggesting in vivo NET availability is a sensitive biomarker for aging and preclinical stages of AD. This report investigated the age, gender and ethnicity effects on NET availabilityMethodCoregistration of PET (dynamic [11C]MRB), MRI and the FreeSurfer (FS) atlas images of each individual to generate regional time‐activity curves (TAC) using Firevoxel. Binding potential (BPND) were determined using MRTM2 (t2* 20 min and k2’ 0.021 min‐1 with occipital as the reference region). Annual percent change (APC) of BPND was calculated based on linear regression (APC = 100 × (em – 1), m: slope) and effects of age, gender and ethnicity on tracer binding were evaluated.ResultFor all HC (N=31), with both genders and all races included, the NET availability decline can be observed; e.g., ‐0.4%/yr for BS &amp; ROfac. However, in gender‐separated group analysis [(19M, age 36.2±9.9) vs. (12F, age 36.6±9.0)], there was a significant gender effect for APC (P &lt;0.01) with decline rates faster for M (e.g., ‐0.8%/yr for LTH), starting from mid 30 (p&lt;0.001). Interestingly, out of 16 ROIs, while AA (N=14, age 34±7) had consistently higher regional BPND than white subjects (N=12, age 35±8)(P&lt;0.000), the decline rate was much higher for AA (P&lt;0.00001); e.g., ‐3%/yr in LTH for AA‐M.ConclusionIn addition to our previously determined age effect on MRB‐NET binding, this report further reveals, for the first time, the role of gender and ethnicity effects on NET availability, in the context of the aging brain. A bigger sample size is warranted to investigate these effects on the NET availability.

Morphometric characteristics of the brain in patients with type 1 diabetes mellitus on diff erent modes of basic bolus insulin therapy

Objective— to study the morphometric characteristics of the brain in patients with type 1 diabetes mellitus (DM) receiving insulin therapy in diff erent modes, taking into account the variability of glycemia.Material and methods.120 patients with type 1 diabetes, living in Tomsk and the Tomsk Region, were examined. All patients were divided into 2 groups: group 1 — patients receiving insulin in the base-bolus regimen of multiple insulin injections (MII), group 2 — using pump insulin therapy by continuous subcutaneous infusion of insulin using a wearable dispenser (CSII). Patients took this therapy for at least 6 months before inclusion in the study. All patients underwent a general clinical examination, testing of cognitive functions using the Montreal scale (MoCA test), continuous monitoring of blood glycemia (CMG) using iPro™ 2 Professional Continuous Glucose Monitoring (Medtronic, USA), FreeStyle Libre (Abbot, USA) in for 14 days, standard magnetic resonance imaging (MRI) on a 1.5 Tesla apparatus in axial, sagittal and coronal projections using T2, TE, T1, and using programs that suppress the signal of free water. We processed the results of MRI using Free Surfer (USA) and recon-all segmentation algorithm. Statistical analysis was performed using the R-system software package.Results.It was found that in both groups with type 1 diabetes there was a decrease in cognitive functions. It has been shown that CSII is associated with the best completion of the MoCA test. In addition, it has been reported that more frequent episodes of diabetic ketoacidosis and increased glycated hemoglobin (HbA1c) are the main causes of cognitive impairment in this group of patients. Changes in the morphometric parameters of the brain are interconnected with glycemic variability.Conclusion.In patients with type 1 diabetes, cognitive impairment associated with acute and chronic hyperglycemia was verifi ed. Morphometric features of brain changes are more dependent on glycemic variability. CSII helps improve cognitive function.

Post Radiation Cortical Thickness Variations In Brain "Association Areas"

Higher order cognitive functions (attention and memory) performed by “association cortex” decline more compared to basic somatosensory defects performed by motor cortex to fractionated RT. Authors sought to evaluate the regional vulnerability subserving the higher order cognition to fractionated RT using Quantitative MRI. This retrospective single center study encompassed a cohort of 25 brain tumor patients treated using fractionated partial brain irradiation & underwent standard high-resolution volumetric MR protocol (T1-weighted; T2 FLAIR) pre-RT and one-year post-RT start (9-15 months). Semi-automated free surfer software was used to segment anatomic regions of the cerebral cortex for each patient. Mean Cortical thickness was measured for each region pre-RT and at one year. MRI voxels falling within 5mm of Gross tumor volume were excluded. Two higher-order cortical regions of interest (ROIs) were tested for association between radiation dose and cortical thinning: entorhinal (memory) and inferior parietal (attention/memory). For comparison, two primary cortex ROIs were also tested: pericalcarine (vision) and paracentral lobule (somatosensory/motor). Radiation dose data were projected onto the pre-RT cortical surface using FreeSurfer, and mean radiation dose was also calculated for each cortical region. The relationship of mean radiation dose and mean cortical thickness change was assessed by univariate linear regression for all instances of right or left entorhinal cortex & primary cortex areas in the patient cohort. All “association cortex” regions of interest (entorhinal or inferior parietal) that received greater than 40 Gy mean dose were tested for significant cortical thickness change via Student’s t-test. Cortical thinning was significantly associated with mean radiation dose for the entorhinal cortex (p = 0.01) and inferior parietal cortex (p = 0.02), both association cortex ROIs. Primary cortex ROIs showed no significant cortical thinning regardless of whether they received a high (>40 Gy) or low (<20 Gy) radiation dose. In the whole-cortex analysis, regions showed significant radiation dose-dependent atrophy, including areas responsible for memory, attention, and executive function (p≤0.002). Areas of cerebral cortex most vulnerable to radiation-related atrophy includes those performing higher-order cognition in brain "association areas ” thus leading to deficits in domains of memory, executive function, and attention.

Lógica interna del surf

Objetivo: En este artículo analizaremos la lógica interna del surf teniendo como marco de referencia la Praxiología Motriz. Nuestro propósito es investigar los modos en que se relaciona el participante con el medio, los demás, los materiales y el tiempo, principalmente en el surf que es practicado de manera libre y no competitiva, pero también tomando algunas referencias de su vertiente deportiva. Método: Se utilizó una metodología cualitativa y de carácter interpretativo, basada fundamentalmente en la realización de observaciones participantes y entrevistas en playas de la ciudad de Mar del Plata (Argentina). Resultados y discusión: Tomando como punto de partida el concepto lógica interna, fueron indagadas las maneras en que el surfista se relaciona con el espacio, los demás, los materiales y el tiempo. Todos estos aspectos se encuentran claramente diferenciados, pero a la vez es necesario relacionarlos entre sí para que la práctica pueda ser estudiada de manera sistémica. Consideraciones finales: El estudio de la lógica interna nos permite una comprensión más completa del surf, evitando reducirlo solamente a su dimensión de técnica corporal. Esta investigación se proyecta como una herramienta de potencial interés para el docente a cargo de la enseñanza, brindando elementos para construir metodologías reflexivas.

Longer Duration of Hypertension and MRI Microvascular Brain Alterations Are Associated with Lower Hippocampal Volumes in Older Individuals with Hypertension.

Background:Hippocampal atrophy is associated with cognitive decline. Determining the clinical features associated with hippocampal volume (HV)/atrophy may help in tailoring preventive strategies.Objective:This study was aimed to investigate the association between HV (at visit 2) and vascular status (both at visit 1 and visit 2) in a cohort of individuals aged 60+ with hypertension and without overt cognitive impairment at visit 1 (visit 1 and visit 2 were separated by approximately 8 years).Methods:Hippocampal volume was estimated in brain MRIs as HV both clinically with the Scheltens’ Medial Temporal Atrophy score, and automatically with the Free Surfer Software application. A detailed medical history, somatometric measurements, cognitive tests, leukoaraiosis severity (Fazekas score), vascular parameters including pulse wave velocity, central blood pressure, and carotid artery plaques, as well as several biochemical parameters were also measured.Results:113 hypertensive patients, 47% male, aged 75.1±5.6 years, participated in both visit 1 and visit 2 of the ADELAHYDE study. Age (β= –0.30) and hypertension duration (β= –0.20) at visit 1 were independently associated with smaller HV at visit 2 (p < 0.05 for all). In addition to these variables, low body mass index (β= 0.18), high MRI Fazekas score (β= –0.20), and low Gröber-Buschke total recall (β= 0.27) were associated with smaller HV at visit 2 (p < 0.05 for all).Conclusion:In a cohort of older individuals without cognitive impairment at baseline, we described several factors associated with lower HV, of which hypertension duration can potentially be modified.

An MRI Study of the Relationship Between Duration of Untreated Psychosis and Morphology of Cerebral Cortex in First-episode Schizophrenia

We analyzed the brain structure of schizophrenia patients from multiple perspectives to explore the relationship between the duration of untreated psychosis (DUP) and clinical outcomes. For 85 patients and 86 controls, clinical symptoms and cognitive function were evaluated, magnetic resonance imaging (MRI) and free surfer analysis were used to extract the cortical indicator, such as brain cortex thickness, surface area, volume, and so on. The patients were divided into four subgroups according to the boundary of March, June and two year due to the distribution and median of DUP. Finally multi-group comparison and correlation analysis for above indicators were analysed. DUP was associated with the surface area of the left insula, parsorbitalis, right hippocampus, superior frontal gyrus, frontal pole, and temporal pole; DUP mainly influenced the cortical thickness of left posterior cingulate gyrus, postcentral gyrus, right lateral occipital cortex, parsopercularis, medial orbitofrontal cortex, and the bilateral precentral gyrus. For cortical volume, DUP significantly affected left postcentral gyrus, right precuneus, lateral occipital cortex, parsopercularis, lingual gyrus, superior temporal gyrus, bilateral cuneus, pericalcarine cortex, precentral gyrus,superior parietal lobule, and insula.The first three months after onset is a critical period for the deterioration of cortical morphology and clinical function. DUP in first-episode schizophrenia is associated with cortical morphological changes of temporal lobe, precentral, orbitofrontal cortex and the majority of medial regions of occipital lobe, it is very important to conduct early intervention for patients.

Biomarker Localization, Analysis, Visualization, Extraction, and Registration (BLAzER) Methodology for Research and Clinical Brain PET Applications.

Tools for efficient evaluation of amyloid- and tau-PET images are needed in both clinical and research settings. This study was designed to validate a semi-automated image analysis methodology, called Biomarker Localization, Analysis, Visualization, Extraction, and Registration (BLAzER). We tested BLAzER using two different segmentation platforms, FreeSurfer (FS) and Neuroreader (NR), for regional brain PET quantification in participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. 127 amyloid-PET and 55 tau-PET studies with volumetric MRIs were obtained from ADNI. The BLAzER methodology utilizes segmentation of MR images by FS or NR, then visualizes and quantifies regional brain PET data using FDA-cleared software (MIM), enabling quality control to ensure optimal registration and to detect segmentation errors. BLAzER analysis required ∼5 min plus segmentation time. BLAzER using FS segmentation showed strong agreement with ADNI for global amyloid-PET standardized uptake value ratios (SUVRs) (r = 0.9922, p < 0.001) and regional tau-PET SUVRs across all Braak staging regions (r > 0.97, p < 0.001) with high inter-operator reproducibility (ICC > 0.97) and nearly identical dichotomization as amyloid-positive or -negative (2 discrepant cases out of 127). Comparing FS versus NR segmentation with BLAzER, global SUVRs were strongly correlated for amyloid-PET (r = 0.9841, p < 0.001), but were systematically higher (4% on average) with NR, likely due to more inclusion of white matter with NR-defined regions. BLAzER provides an efficient methodology for regional brain PET quantification. FDA-cleared components and visualization of registration reduce barriers between research and clinical applications.

Cortical thickness following electroconvulsive therapy in patients with depression: a longitudinal MRI study.

Several studies have found an increase in hippocampal volume following electroconvulsive therapy (ECT), but the effect on cortical thickness has been less investigated. We aimed to examine the effects of ECT on cortical thickness and their associations with clinical outcome. Using 3 Tesla MRI scanner, we obtained T1-weighted brain images of 18 severely depressed patients at three time points: before, right after and 6months after a series of ECT. The thickness of 68 cortical regions was extracted using Free Surfer, and Linear Mixed Model was used to analyze the longitudinal changes. We found significant increases in cortical thickness of 26 regions right after a series of ECT, mainly within the frontal, temporal and insular cortex. The thickness returned to the baseline values at 6-month follow-up. We detected no significant decreases in cortical thickness. The increase in the thickness of the right lateral orbitofrontal cortex was associated with a greater antidepressant effect, r=0.75, P=0.0005. None of the corticalregions showed any associations with cognitive side effects. The increases in cortical thickness induced by ECT are transient. Further multimodal MRI studies should examine the neural correlates of these increases and their relationship with the antidepressant effect.

Evaluation of the intra- and inter-method agreement of brain MRI segmentation software packages: A comparison between SPM12 and FreeSurfer v6.0

PurposeThe lack of inter-method agreement can produce inconsistent results in neuroimaging studies. We evaluated the intra-method repeatability and the inter-method reproducibility of two widely-used automatic segmentation methods for brain MRI: the FreeSurfer (FS) and the Statistical Parametric Mapping (SPM) software packages. MethodsWe segmented the gray matter (GM), the white matter (WM) and subcortical structures in test-retest MRI data of healthy volunteers from Kirby-21 and OASIS datasets. We used Pearson’s correlation (r), Bland-Altman plot and Dice index to study intra-method repeatability and inter-method reproducibility. In order to test whether different processing methods affect the results of a neuroimaging-based group study, we carried out a statistical comparison between male and female volume measures. ResultsA high correlation was found between test-retest volume measures for both SPM (r in the 0.98–0.99 range) and FS (r in the 0.95–0.99 range). A non-null bias between test-retest FS volumes was detected for GM and WM in the OASIS dataset. The inter-method reproducibility analysis measured volume correlation values in the 0.72–0.98 range and the overlap between the segmented structures assessed by the Dice index was in the 0.76–0.83 range. SPM systematically provided significantly greater GM volumes and lower WM and subcortical volumes with respect to FS. In the male vs. female brain volume comparisons, inconsistencies arose for the OASIS dataset, where the gender-related differences appear subtler with respect to the Kirby dataset. ConclusionsThe inter-method reproducibility should be evaluated before interpreting the results of neuroimaging studies.

Application of local gyrification index in the early diagnosis of Alzheimer disease

Objective To evaluate the role of local gyrification index (LGI) in the early diagnosis of Alzheimer disease(AD). Methods Thirty-five amnestic-type mild cognitive impairment patients (aMCI group), 34 mild AD patients (mild AD group) and 33 healthy volunteers (normal control group) were studied. All patients underwent high resolution MRI examination and mini-mental state examination (MMSE). Using surface-based morphometry, the FreeSurfer was employed to access LGI of vertex over every participant′s whole cortical surface, then we calculated the mean LGI (mLGI) of each subject′s left and right hemisphere separately. Taking age, gender and educational year as covariance, analysis of covariance was used to compare the difference of mLGI of left and right brain among 3 groups, then Bonferroni was done between every two groups. Analysis of covariance was applied to compare the difference of LGI of every participant among 3 groups, and Monte Carlo method was employed to perform multiple comparison corrections. The correlations between the MMSE scores and LGIs of the three groups were analyzed. Results Compared with normal control group(left 3.03±0.12,right 3.02±0.13), the mLGI of hemispheres in mild AD group(left 2.94±0.11,right 2.93±0.10) decreased respectively(P 0.05). The difference of mLGI of hemispheres between aMCI group and mild AD group also had no statistical significance(P>0.05). The aMCI group showed decrease of LGI in some brain regions located at the right temporal lobe, bilateral frontal and parietal lobe compared with the normal control group. While compared with aMCI group, decreased LGIs was presented in some brain regions located at bilateral temporal, occipital, frontal lobe and the right parietal lobe of mild AD group. There was a positive correlation between MMSE scores and LGIs of some brain regions in the bilateral temporal, occipital lobe, the left frontal lobe and the right parietal lobe in the three groups. Conclusion LGI is conductive in the early diagnosis of AD and can serve as an imaging marker for monitoring disease progresses. Key words: Alzheimer disease; Mild cognitive impairment; Magnetic resonance imaging; Local gyrification index

Accuracy and bias of automatic hippocampal segmentation in children and adolescents.

The hippocampus (Hc) is of great importance in various psychiatric diseases in adults, children and adolescents. Automated Hc segmentation has been widely used in adults, implying sufficient overlap with manual segmentation. However, estimation biases related to the Hc volume have been pointed out. This may particularly apply to children who show age-related Hc volume changes, thus, questioning the accuracy of automated Hc segmentation in this age group. The aim of this study was to compare manual segmentation with automated segmentation using the widely adopted FreeSurfer (FS) and MAGeT-Brain software. In 70 children and adolescents (5-16years, mean age 10.6years), T1-weighted images were acquired on one of two identical 3T scanners. Automated segmentation was performed using the FS subcortical segmentation, the FS hippocampal subfields segmentation and the MAGeT-Brain software. In comparison with manual segmentation, volume differences, Dice similarity coefficient (DSC), Bland-Altman plot, intraclass correlation coefficient (ICC) and left-right consistency of automated segmentation were calculated. The average percentage of volume differences (PVD) with manual segmentation was 56.8% for FS standard segmentation, 32.2% for FS subfield segmentation and - 15.6% for MAGeT-Brain. The FS Hc subfields segmentation (left/right DSC = 0.86/0.87) and MAGeT-Brain (both hemispheres DSC = 0.91) resulted in a higher volume overlap with manual segmentation compared with the FS subcortical segmentation (DSC = 0.79/0.78). In children aged 5-10.5years, MAGeT-Brain yielded the highest overlap (DSC = 0.92/0.93). Contrary volume estimation biases were detected in FS and MAGeT-Brain: FS showed larger volume overestimation in smaller Hc volumes, while MAGeT-Brain showed more pronounced volume underestimation in larger Hc volumes. While automated Hc segmentation using FS hippocampal subfields or MAGeT-Brain resulted in adequate volume overlap with manual segmentation, estimation biases compromised the reliability of automated procedures in children and adolescents.

Optimizing Fractional Intensity Threshold for FSLBrain Extraction Tool (BET) and Comparing with FreeSurfer on 3D T1W MR Images

Objective: To find out the optimal Brain Extraction Tool (BET) parameter (fractional intensity threshold) for measuring the brain volume compared with the standard manual method in our institute and to compare with those of automated FreeSurfer software Methods: This retrospective study was performed in 10 healthy adult subjects with data of 3D-T1W on 3T MR machine. The manual gold standard brain volume measurements were done by two independent readers. The automated segmentations using BET with varied parameters and FreeSurfer software were also performed. Then, the two automated methods were compared with the manual tracing to make the optimal parameter by seeking for the highest intraclass correlation coefficient (ICC) using SPSS software. Results: The fractional intensity threshold for whole brain volume measurement of 0.1- 0.6 showed high ICC with the manual gold standard (ranging from 0.639 to 0.748). The best value was 0.1, showing highest ICC of 0.748 (p < 0.006) with confidence interval of 95% equal to (0.242; 0.932). There were no optimal parameters for right and left hippocampus volume measurement by BET due to very low ICC between BET and the reader (ICC ranging from 0.017 to 0.139 and from 0.012 to 0.110, for the right and left hippocampus volume, respectively). The ICC values of the automated FreeSurfer method with the manual tracing were also very low (0.063, 0.068, and 0.063 for right, left and bilateral hippocampi respectively). Conclusion: The optimal BET parameter (fractional intensity threshold) for automated brain volume measurement in our institute is 0.1 similar to the suggested value by prior study with high agreement (ICC=0.748) to the manual method.

Brainstem enlargement in preschool children with autism: Results from an intermethod agreement study of segmentation algorithms.

The intermethod agreement between automated algorithms for brainstem segmentation is investigated, focusing on the potential involvement of this structure in Autism Spectrum Disorders (ASD). Inconsistencies highlighted in previous studies on brainstem in the population with ASD may in part be a result of poor agreement in the extraction of structural features between different methods. A sample of 76 children with ASD and 76 age-, gender-, and intelligence-matched controls was considered. Volumetric analyses were performed using common tools for brain structures segmentation, namely FSL-FIRST, FreeSurfer (FS), and Advanced Normalization Tools (ANTs). For shape analysis SPHARM-MAT was employed. Intermethod agreement was quantified in terms of Pearson correlations between pairs of volumes obtained by the different methods. The degree of overlap between segmented masks was quantified in terms of the Dice index. Both Pearson correlations and Dice indices, showed poor agreement between FSL-FIRST and the other methods (ANTs and FS), which by contrast, yielded Pearson correlations greater than 0.93 and average Dice indices greater than 0.76 when compared with each other. As with volume, shape analyses exhibited discrepancies between segmentation methods, with particular differences noted between FSL-FIRST and the others (ANT and FS), with under- and over-segmentation in specific brainstem regions. These data suggest that research on brain structure alterations should cross-validate findings across multiple methods. We consistently detected an enlargement of brainstem volume in the whole sample and in the male cohort across multiple segmentation methods, a feature particularly driven by the subgroup of children with idiopathic intellectual disability associated with ASD.