Volumetric Magnetic Resonance Imaging Research Articles

Deep learning-based brain tumor segmentation on limited sequences of magnetic resonance imaging.

2054 Background: Deep learning algorithms trained to segment brain tumors from magnetic resonance imaging (MRI) perform well in ideal conditions supplied by curated datasets. An example is the MICCAI BraTS 2018 dataset, which provides a set of four MRI sequences (T1, T1 post-gadolinium contrast-enhanced, T2, FLAIR) on 285 samples, along with ground truth segmentations annotated by experts. In real-world settings, however, it is not uncommon for patients to undergo MRI with a limited number of image sequence acquisitions. We examined the effect of restricting the imaging sequence set when training a deep learning model for brain tumor segmentation. Our goal was to identify a limited subset that still achieved acceptably high performance. Methods: In our experiments, we used the convolutional neural network-based U-Net architecture. Instead of the standard BraTS task, we focused on sub-segmenting specific areas of brain tumors: the active, enhancing tumor (AT) and the tumor core (TC; AT plus the cystic/necrotic core). We trained the architecture on 285 samples of the BraTS 2018 dataset using one or both of two sequences: T1 contrast-enhanced (T1CE) and FLAIR. Using each training model, we predicted segmentation masks given a volumetric MR image of a brain tumor on 66 samples in the held-out validation dataset. We submitted the predicted segmentations to the Center for Biomedical Image Computing and Analytics (CBICA) imaging portal for evaluation, which reports prediction accuracy by returning dice scores on each prediction. Results: As shown in the Table, the U-Net model using T1CE alone yielded high performances, with median dice scores of 0.84461 and 0.88267, when segmenting AT and TC, respectively. On the other hand, using FLAIR alone generated lower performances on the same tasks of segmenting the AT (0.25996) and the TC regions (0.51153). Combining T1CE and FLAIR provided no additional performance improvement compared with T1CE used as a standalone sequence. Conclusions: We achieved high performances in two brain tumor sub-segmentation tasks using a limited number of MRI sequences in training a deep-learning algorithm. T1CE alone produced high performances on both TC and AT segmentations. Given the ubiquity of the T1CE sequence, the ability to achieve high performance tumor segmentations in the face of limited image sequence availability is critical when applying our algorithm in real-world clinical or research settings. [Table: see text]

Thalamic atrophy, duration of illness, and years of education are the best predictors of cognitive impairment in multiple sclerosis

Background Cognitive impairment (CI) is common in multiple sclerosis. We assessed the relationship between CI and demographic, motor disability, and volumetric brain atrophy in relapsing remitting multiple sclerosis (RRMS). Methods In all, 43 RRMS patients and 40 age- sex-, and education-matched normal volunteers were enrolled. Assessments included: demographic, Expanded Disability Status Scale (EDSS); Brief International Cognitive Assessment for Multiple Sclerosis (BICAMS); and brain volumetric assessment. Results The mean age of onset of RRMS patients was 25.72 y and the mean number of attacks was 3.30 ± 2.33/year. The total brain volume, cerebral, and cerebellar hemispheres, brainstem as well as thalamic and hippocampal gray matter were significantly reduced in RRMS patients compared with controls. CI was detected in 41.9% of patients. Patients with CI had fewer years of education (P = .001), a higher number of attacks (P = .002), worse EDSS scores (P = .030); reduced gray matter volume, particularly of the thalamus, and hippocampus compared with patients without CI. There were significant negative correlations between CI with duration of illness, number of attacks, time elapsed between onset and diagnosis, and EDSS. Thalamic volume showed strong positive correlations with CI (P < .0001). The best predictors of CI were thalamic atrophy, duration of illness, and years of education (P = .001, .010, and .035 respectively). Conclusion We confirmed the presence of gray matter atrophy of the brain in RRMS patients. Volumetric magnetic resonance imaging measures of thalamus, duration of illness, and years of education could be useful biomarkers of CI in RRMS.

Automated cervical tumor segmentation on MR images using multi-view feature attention network

Precise cervical cancer treatment highly relies on accurate segmentation of cervical tumors from magnetic resonance (MR) images. However, this task is challenged by the inhomogeneous intensity distributions in MR images and the large variations in tumor shapes and locations. The large slice thickness further results in limited inter-slice correlations and 3D contextual information can be utilized, which influences the segmentation performance greatly. To tackle the above challenges and make full use of the 3D contextual information, a multi-view feature attention-based segmentation network (MVFA-Net) is proposed in this study. Toward the weak correlations among adjacent MR slices, features from different views of the volumetric MR images are extracted and treated individually and then fused by a channel-wise attention model. A cervical MR data set collected from 160 cervical cancer patients was employed to evaluate the performance of the proposed MVFA-Net. In comparison experiments, the proposed MVFA-Net outperforms the other eight medical image segmentation networks 2.6%-11.1% and 0.39 mm-0.97 mm on Dice similarity coefficient (DSC) and Average surface distance (ASD), respectively. Extensive ablation studies demonstrate the effectiveness of the proposed multi-view attention block and MVFA-Net. Additionally, with the trained segmentation network, no more than 6 s will be taken to segment one unseen patient, which is highly efficient for clinical practice. The presented segmentation network might be useful for cervical cancer treatment routine to improve the segmentation accuracy, consistency, and efficiency. The code is publicly available at: https://github.com/xyndameinv/MVFA-Net.

11C-methionine PET aids localization of microprolactinomas in patients with intolerance or resistance to dopamine agonist therapy

PurposeTo assess the potential for 11C-methionine PET (Met-PET) coregistered with volumetric magnetic resonance imaging (Met-PET/MRCR) to inform clinical decision making in patients with poorly visualized or occult microprolactinomas and dopamine agonist intolerance or resistance.Patients and methodsThirteen patients with pituitary microprolactinomas, and who were intolerant (n = 11) or resistant (n = 2) to dopamine agonist therapy, were referred to our specialist pituitary centre for Met-PET/MRCR between 2016 and 2020. All patients had persistent hyperprolactinemia and were being considered for surgical intervention, but standard clinical MRI had shown either no visible adenoma or equivocal appearances.ResultsIn all 13 patients Met-PET/MRCR demonstrated a single focus of avid tracer uptake. This was localized either to the right or left side of the sella in 12 subjects. In one patient, who had previously undergone surgery for a left-sided adenoma, recurrent tumor was unexpectedly identified in the left cavernous sinus. Five patients underwent endoscopic transsphenoidal selective adenomectomy, with subsequent complete remission of hyperprolactinaemia and normalization of other pituitary function; three patients are awaiting surgery. In the patient with inoperable cavernous sinus disease PET-guided stereotactic radiosurgery (SRS) was performed with subsequent near-normalization of serum prolactin. Two patients elected for a further trial of medical therapy, while two declined surgery or radiotherapy and chose to remain off medical treatment.ConclusionsIn patients with dopamine agonist intolerance or resistance, and indeterminate pituitary MRI, molecular (functional) imaging with Met-PET/MRCR can allow precise localization of a microprolactinoma to facilitate selective surgical adenomectomy or SRS.

Psychometric deficits in autoimmune encephalitis: A retrospective study from the Australian Autoimmune Encephalitis Consortium.

Despite the rapid increase in research examining outcomes in autoimmune encephalitis (AE) patients, there are few cohort studies examining cognitive outcomes in this population. The current study aimed to characterise psychometric outcomes in this population, and explore variables that may predict psychometric outcomes. This retrospective observational study collected psychometric data from 59 patients across six secondary and tertiary referral centres in metropolitan hospitals in Victoria, Australia between January 2008 and July 2019. Frequency and pattern analysis were employed to define and characterize psychometric outcomes. Univariable logistic regression was performed to examine predictors of intact and pathological psychometric outcomes. Deficits in psychometric markers of executive dysfunction were the most common finding in this cohort, followed by deficits on tasks sensitive to memory. A total of 54.2% of patients were classified as having psychometric impairments across at least two cognitive domains. Twenty-nine patterns were observed, suggesting outcomes in AE are complex. None of the demographic data, clinical features or auxiliary examination variables were predictors of psychometric outcome. Cognitive outcomes in AE are complex. Further detailed and standardized cognitive testing, in combination with magnetic resonance imaging volumetrics and serum/cerebrospinal fluid biomarkers, is required to provide rigorous assessments of disease outcomes.

Pituitary Volume in Individuals with Social Anxiety Disorder.

There are no volumetric magnetic resonance imaging studies on the pituitary gland in individuals with social anxiety disorder. The present study aimed to investigate pituitary volume in individuals with social anxiety disorder compared to healthy controls due to the correlation between pituitary gland volume and stress response and the hypothalamic-pituitary-adrenal axis and hypothesized that pituitary gland volume would be different in these individuals. In this study, 21 individuals with social anxiety disorder based on fourth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) and 20 healthy controls were included. Both patient and control groups were scanned with a 1.5-Tesla General Electric (GE) Magnetic Resonance Imaging scanner. Pituitary volume was measured with the manual tracing method. The statistical analysis revealed that the mean pituitary gland volume of the individuals with social anxiety disorder was significantly smaller when compared to that of healthy controls, statistically, as presented inTable 1 [594.10±104.56 mm3 for individuals with social anxiety disorder and 818.01±215.25 mm3 for healthy controls] when it was done by using the analysis of covariance controlled for age (F = 12.979, df = 1, P < .001), sex (F = 11.448, df = 1, P < .001), and total brain volume (F = 10.772, df = 1, P < .001), demonstrating that smaller pituitary volume in social anxiety disorder, when compared to healthy subjects, was an important finding independent of age, sex, or total brain volume. We suggest that social anxiety disorder may be associated with smaller pituitary volume, supporting the notion that anxiety itself could reduce the pituitary volume.

Cerebellum and nucleus caudatus asymmetry in major depressive disorder

Background/Aim: The relationship between major depressive disorder (MDD) and specific brain regions was investigated using neuroimaging methods. Although the findings show structural hemispheric asymmetry, research has often focused on the specific brain region involved in MDD. This study aimed to investigate asymmetry in the brain regions of MDD patients for the first time with volBrain, which is a fully automated segmentation technique. Methods: Our study was designed as a case-control study. Structural asymmetry was evaluated using the current web-based fully automated segmentation algorithm, volBrain, that analyzes volumetric T1 axial magnetic resonance imaging data. Sixteen cases with MDD and 14 healthy controls were analyzed. For comparison of continuous data between binary groups, an independent T-test was used for data that follow a normal distribution and Mann–Whitney U (MWU) test was used for data that did not follow a normal distribution while categorical data were evaluated using Chi-square test (or Fisher’s exact test when needed). Results: There was no significant difference in terms of gender (χ2 [1, n = 30] = 0.117, P = 0.732), education level (2 [1, n = 30] = 0.002; P = 0.961] and marital status (P = 0.596, Fisher exact chi-square test). However, both groups were found to be similar in terms of age (P = 0.608, MWU test). Right/left nucleus caudatus volume ratios (P = 0.028, MWU test) and right/left cerebellum volume ratios were significantly smaller in the case group (P = 0.006, independent T-test). When the volumes of the right and left parts were compared, only the volume of the right globus pallidus was larger (statistically significant) in the case group (P = 0.008, independent T-test). Conclusion: In line with our hypothesis, our study supports the notion of cortico–striatal–pallidal–thalamic circuit abnormalities in current MDD research and found that some regions in this phase may contain structural asymmetry. In addition, this study contributed to the literature consisting of studies that have examined the relationship between cerebellum and MDD by adding that the cerebellum may show structural asymmetry. The results of our study suggest that research using volBrain may be beneficial to patients with MDD. Current web-based fully automatic segmentation algorithms can restrict both the rater-induced differences in manual segmentation applications and the differences that various segmentation algorithms can create. The challenge of multicenter research can be overcome by using web-based fully automated segmentation volumetry systems and data containing the same standardized magnetic resonance imaging (MRI) acquisition parameters because it is easy for clinicians around the world to access web-based fully automated segmentation volumetry systems. Research on fully automatic segmentation techniques might be the driving force behind fully understanding biological foundations of MDD in the future.

Regional brain development in fetuses with Dandy-Walker malformation: A volumetric fetal brain magnetic resonance imaging study.

Dandy-Walker malformation (DWM) is a common prenatally diagnosed cerebellar malformation, characterized by cystic dilatation of the fourth ventricle, upward rotation of the hypoplastic vermis, and posterior fossa enlargement with torcular elevation. DWM is associated with a broad spectrum of neurodevelopmental abnormalities such as cognitive, motor, and behavioral impairments, which cannot be explained solely by cerebellar malformations. Notably, the pathogenesis of these symptoms remains poorly understood. This study investigated whether fetal structural developmental abnormalities in DWM extended beyond the posterior fossa to the cerebrum even in fetuses without apparent cerebral anomalies. Post-acquisition volumetric fetal magnetic resonance imaging (MRI) analysis was performed in 12 fetuses with DWM and 14 control fetuses. Growth trajectories of the volumes of the cortical plate, subcortical parenchyma, cerebellar hemispheres, and vermis between 18 and 33 weeks of gestation were compared. The median (interquartile range) gestational ages at the time of MRI were 22.4 (19.4–24.0) and 23.9 (20.6–29.2) weeks in the DWM and control groups, respectively (p = 0.269). Eight of the 12 fetuses with DWM presented with associated cerebral anomalies, including hydrocephalus (n = 3), cerebral ventriculomegaly (n = 3), and complete (n = 2) and partial (n = 2) agenesis of the corpus callosum (ACC); 7 presented with extracerebral abnormalities. Chromosomal abnormalities were detected by microarray analysis in 4 of 11 fetuses with DWM, using amniocentesis. Volumetric analysis revealed that the cortical plate was significantly larger in fetuses with DWM than in controls (p = 0.040). Even without ACC, the subcortical parenchyma, whole cerebrum, cerebellar hemispheres, and whole brain were significantly larger in fetuses with DWM (n = 8) than in controls (p = 0.004, 0.025, 0.033, and 0.026, respectively). In conclusion, volumetric fetal MRI analysis demonstrated that the development of DWM extends throughout the brain during the fetal period, even without apparent cerebral anomalies.

Role of Volumetric Magnetic Resonance Imaging in Evaluation of Nonlesional Childhood Epilepsy

Role of Volumetric Magnetic Resonance Imaging in Evaluation of Nonlesional Childhood Epilepsy

Magnetic Resonance Imaging in Tauopathy Animal Models.

The microtubule-associated protein tau plays an important role in tauopathic diseases such as Alzheimer’s disease and primary tauopathies such as progressive supranuclear palsy and corticobasal degeneration. Tauopathy animal models, such as transgenic, knock-in mouse and rat models, recapitulating tauopathy have facilitated the understanding of disease mechanisms. Aberrant accumulation of hyperphosphorylated tau contributes to synaptic deficits, neuroinflammation, and neurodegeneration, leading to cognitive impairment in animal models. Recent advances in molecular imaging using positron emission tomography (PET) and magnetic resonance imaging (MRI) have provided valuable insights into the time course of disease pathophysiology in tauopathy animal models. High-field MRI has been applied for in vivo imaging in animal models of tauopathy, including diffusion tensor imaging for white matter integrity, arterial spin labeling for cerebral blood flow, resting-state functional MRI for functional connectivity, volumetric MRI for neurodegeneration, and MR spectroscopy. In addition, MR contrast agents for non-invasive imaging of tau have been developed recently. Many preclinical MRI indicators offer excellent translational value and provide a blueprint for clinical MRI in the brains of patients with tauopathies. In this review, we summarized the recent advances in using MRI to visualize the pathophysiology of tauopathy in small animals. We discussed the outstanding challenges in brain imaging using MRI in small animals and propose a future outlook for visualizing tau-related alterations in the brains of animal models.

High-fidelity fast volumetric brain MRI using synergistic wave-controlled aliasing in parallel imaging and a hybrid denoising generative adversarial network (HDnGAN).

The goal of this study is to leverage an advanced fast imaging technique, wave-controlled aliasing in parallel imaging (Wave-CAIPI), and a generative adversarial network (GAN) for denoising to achieve accelerated high-quality high-signal-to-noise-ratio (SNR) volumetric magnetic resonance imaging (MRI). Three-dimensional (3D) T2 -weighted fluid-attenuated inversion recovery (FLAIR) image data were acquired on 33 multiple sclerosis (MS) patients using a prototype Wave-CAIPI sequence (acceleration factor R=3×2, 2.75min) and a standard T2 -sampling perfection with application-optimized contrasts by using flip angle evolution (SPACE) FLAIR sequence (R=2, 7.25min). A hybrid denoising GAN entitled "HDnGAN" consisting of a 3D generator and a 2D discriminator was proposed to denoise highly accelerated Wave-CAIPI images. HDnGAN benefits from the improved image synthesis performance provided by the 3D generator and increased training samples from a limited number of patients for training the 2D discriminator. HDnGAN was trained and validated on data from 25 MS patients with the standard FLAIR images as the target and evaluated on data from eight MS patients not seen during training. HDnGAN was compared to other denoising methods including adaptive optimized nonlocal means (AONLM), block matching with 4D filtering (BM4D), modified U-Net (MU-Net), and 3D GAN in qualitative and quantitative analysis of output images using the mean squared error (MSE) and Visual Geometry Group (VGG) perceptual loss compared to standard FLAIR images, and a reader assessment by two neuroradiologists regarding sharpness, SNR, lesion conspicuity, and overall quality. Finally, the performance of these denoising methods was compared at higher noise levels using simulated data with added Rician noise. HDnGAN effectively denoised low-SNR Wave-CAIPI images with sharpness and rich textural details, which could be adjusted by controlling the contribution of the adversarial loss to the total loss when training the generator. Quantitatively, HDnGAN (λ=10-3 ) achieved low MSE and the lowest VGG perceptual loss. The reader study showed that HDnGAN (λ=10-3 ) significantly improved the SNR of Wave-CAIPI images (p<0.001), outperformed AONLM (p=0.015), BM4D (p<0.001), MU-Net (p<0.001), and 3D GAN (λ=10-3 ) (p<0.001) regarding image sharpness, and outperformed MU-Net (p<0.001) and 3D GAN (λ=10-3 ) (p=0.001) regarding lesion conspicuity. The overall quality score of HDnGAN (λ=10-3 ) (4.25±0.43) was significantly higher than those from Wave-CAIPI (3.69±0.46, p=0.003), BM4D (3.50±0.71, p=0.001), MU-Net (3.25±0.75, p<0.001), and 3D GAN (λ=10-3 ) (3.50±0.50, p<0.001), with no significant difference compared to standard FLAIR images (4.38±0.48, p=0.333). The advantages of HDnGAN over other methods were more obvious at higher noise levels. HDnGAN provides robust and feasible denoising while preserving rich textural detail in empirical volumetric MRI data. Our study using empirical patient data and systematic evaluation supports the use of HDnGAN in combination with modern fast imaging techniques such as Wave-CAIPI to achieve high-fidelity fast volumetric MRI and represents an important step to the clinical translation of GANs.

Exploratory imaging outcomes of a phase 1b/2a clinical trial of allopregnanolone as a regenerative therapeutic for Alzheimer's disease: Structural effects and functional connectivity outcomes.

IntroductionAllopregnanolone (ALLO), an endogenous neurosteroid, promoted neurogenesis and oligogenesis and restored cognitive function in animal models of Alzheimer's disease (AD). Based on these discovery research findings, we conducted a randomized‐controlled phase 1b/2a multiple ascending dose trial of ALLO in persons with early AD (NCT02221622) to assess safety, tolerability, and pharmacokinetics. Exploratory imaging outcomes to determine whether ALLO impacted hippocampal structure, white matter integrity, and functional connectivity are reported.MethodsTwenty‐four individuals participated in the trial (n = 6 placebo; n = 18 ALLO) and underwent brain magnetic resonance imaging (MRI) before and after 12 weeks of treatment. Hippocampal atrophy rate was determined from volumetric MRI, computed as rate of change, and qualitatively assessed between ALLO and placebo sex, apolipoprotein E (APOE) ε4 allele, and ALLO dose subgroups. White matter microstructural integrity was compared between placebo and ALLO using fractional and quantitative anisotropy (QA). Changes in local, inter‐regional, and network‐level functional connectivity were also compared between groups using resting‐state functional MRI.ResultsRate of decline in hippocampal volume was slowed, and in some cases reversed, in the ALLO group compared to placebo. Gain of hippocampal volume was evident in APOE ε4 carriers (range: 0.6% to 7.8% increased hippocampal volume). Multiple measures of white matter integrity indicated evidence of preserved or improved integrity. ALLO significantly increased fractional anisotropy (FA) in 690 of 690 and QA in 1416 of 1888 fiber tracts, located primarily in the corpus callosum, bilateral thalamic radiations, and bilateral corticospinal tracts. Consistent with structural changes, ALLO strengthened local, inter‐regional, and network level functional connectivity in AD‐vulnerable regions, including the precuneus and posterior cingulate, and network connections between the default mode network and limbic system.DiscussionIndicators of regeneration from previous preclinical studies and these exploratory MRI‐based outcomes from this phase 1b/2a clinical cohort support advancement to a phase 2 proof‐of‐concept efficacy clinical trial of ALLO as a regenerative therapeutic for mild AD (REGEN‐BRAIN study; NCT04838301).

Associations of Stages of Objective Memory Impairment with Cerebrospinal Fluid and Neuroimaging Biomarkers of Alzheimer's Disease.

To investigate cerebrospinal fluid (CSF) and neuroimaging correlates of Stages of Objective Memory Impairment (SOMI) based on Free and Cued Selective Reminding Test (FCSRT) performance, and to evaluate the effect of APOE ε4 status on this relationship. Data from 586 cognitively unimpaired individuals who had FCSRT, CSF, and volumetric magnetic resonance imaging (MRI) measures available was used. We compared CSF measures of β-amyloid (Aβ42/Aβ40 ratio), phosphorylated tau (p-Tau181), total tau (t-Tau), hippocampal volume, and PIB-PET mean cortical binding potential with partial volume correction (MCBP) among SOMI groups in the whole sample and in subsamples stratified by APOE ε4 status. Participants had a mean age of 67.4 (SD=9.1) years, had 16.1 (SD=2.6) years of education, 57.0% were female, and 33.8% were APOE ε4 positive. In the entire sample, there was no significant difference between SOMI stages in Aβ42/Aβ40 ratio, p-Tau181, t-Tau, or PIB-PET MCBP when adjusted for age, sex, and education. However, higher SOMI stages had smaller hippocampal volume (F=3.29, p=0.020). In the stratified sample based on APOE ε4 status, in APOE ε4 positive individuals, higher SOMI stages had higher p-Tau181 (F=2.94, p=0.034) higher t-Tau (F=3.41, p=0.019), and smaller hippocampal volume (F=5.78, p<0.001). There were no significant differences in CSF or imaging biomarkers between SOMI groups in the APOE ε4 negative subsample. Cognitively normal older individuals with higher SOMI stages have higher in-vivo tau and neurodegenerative pathology only in APOE ε4 carriers. These original results indicate the potential usefulness of the SOMI staging system in assessing of tau and neurodegenerative pathology.

Magnetic resonance imaging measures of brain volumes across the EXPEDITION trials in mild and moderate Alzheimer's disease dementia.

IntroductionSolanezumab is a monoclonal antibody that preferentially binds soluble amyloid beta and promotes its clearance from the brain. The aim of this post hoc analysis was to assess the effect of low‐dose solanezumab (400 mg) on global brain volume measures in patients with mild or moderate Alzheimer's disease (AD) dementia quantified using volumetric magnetic resonance imaging (vMRI) data from the EXPEDITION clinical trial program.MethodsPatients with mild or moderate AD (EXPEDITION and EXPEDITION2) and mild AD (EXPEDITION3), were treated with either placebo or solanezumab (400 mg) every 4 weeks (Q4W) for 76 weeks. vMRI scans were acquired at baseline and at 80 weeks from 427 MRI facilities using a standardized imaging protocol. Whole brain volume (WBV) and ventricle volume (VV) changes were estimated at 80 weeks using either boundary shift integral (EXPEDITION and EXPEDITION2) or tensor‐based morphometry (EXPEDITION3).ResultsThe pooled cohort used for this study consisted of participants with vMRI at baseline and week 80 across the three trials. Analyzed patient subgroups comprised full patient cohort (N = 2933), apolipoprotein E (APOE) ε4+ carriers (N = 1835), and patients with mild (N = 2497) or moderate AD dementia (N = 428). No significant effect (all P‐values ≥.05) of treatment was observed in the pooled sample, individual trials, or subgroups of patients with mild or moderate AD or APOE ε4 carriers, in either WBV or VV change.DiscussionAnalysis of patients with mild or moderate AD dementia from baseline to 80 weeks using vMRI measures of WBV and VV changes suggested that low‐dose solanezumab was not linked to changes in volumes at 80 weeks. Analysis of the pooled cohort did not demonstrate an effect on brain volumes with treatment. Evaluation of a higher dose of solanezumab in the preclinical stage of AD is currently being undertaken.

Presurgical diffusion metrics of the thalamus and thalamic nuclei in postoperative delirium: A prospective two-centre cohort study in older patients

BackgroundThe thalamus seems to be important in the development of postoperative delirium (POD) as previously revealed by volumetric and diffusion magnetic resonance imaging. In this observational cohort study, we aimed to further investigate the impact of the microstructural integrity of the thalamus and thalamic nuclei on the incidence of POD by applying diffusion kurtosis imaging (DKI). MethodsOlder patients without dementia (≥65 years) who were scheduled for major elective surgery received preoperative DKI at two study centres. The DKI metrics fractional anisotropy (FA), mean diffusivity (MD), mean kurtosis (MK) and free water (FW) were calculated for the thalamus and – as secondary outcome – for eight predefined thalamic nuclei and regions. Low FA and MK and, conversely, high MD and FW, indicate aspects of microstructural abnormality. To assess patients’ POD status, the Nursing Delirium Screening Scale (Nu-DESC), Richmond Agitation Sedation Scale (RASS), Confusion Assessment Method (CAM) and Confusion Assessment Method for the Intensive Care Unit score (CAM-ICU) and chart review were applied twice a day after surgery for the duration of seven days or until discharge. For each metric and each nucleus, logistic regression was performed to assess the risk of POD. ResultsThis analysis included the diffusion scans of 325 patients, of whom 53 (16.3 %) developed POD. Independently of age, sex and study centre, thalamic MD was statistically significantly associated with POD [OR 1.65 per SD increment (95 %CI 1.17 – 2.34) p = 0.004]. FA (p = 0.84), MK (p = 0.41) and FW (p = 0.06) were not significantly associated with POD in the examined sample. Exploration of thalamic nuclei also indicated that only the MD in certain areas of the thalamus was associated with POD. MD was increased in bilateral hemispheres, pulvinar nuclei, mediodorsal nuclei and the left anterior nucleus. ConclusionsMicrostructural abnormalities of the thalamus and thalamic nuclei, as reflected by increased MD, appear to predispose to POD. These findings affirm the thalamus as a region of interest in POD research.

In vivo hypothalamic regional volumetry across the frontotemporal dementia spectrum

BackgroundFrontotemporal dementia (FTD) is a spectrum of diseases characterised by language, behavioural and motor symptoms. Among the different subcortical regions implicated in the FTD symptomatology, the hypothalamus regulates various bodily functions, including eating behaviours which are commonly present across the FTD spectrum. The pattern of specific hypothalamic involvement across the clinical, pathological, and genetic forms of FTD has yet to be fully investigated, and its possible associations with abnormal eating behaviours have yet to be fully explored. MethodsUsing an automated segmentation tool for volumetric T1-weighted MR images, we measured hypothalamic regional volumes in a cohort of 439 patients with FTD (197 behavioural variant FTD [bvFTD]; 7 FTD with associated motor neurone disease [FTD-MND]; 99 semantic variant primary progressive aphasia [svPPA]; 117 non-fluent variant PPA [nfvPPA]; 19 PPA not otherwise specified [PPA-NOS]) and 118 age-matched controls. We compared volumes across the clinical, genetic (29 MAPT, 32 C9orf72, 23 GRN), and pathological diagnoses (61 tauopathy, 40 TDP-43opathy, 4 FUSopathy). We correlated the volumes with presence of abnormal eating behaviours assessed with the revised version of the Cambridge Behavioural Inventory (CBI-R). ResultsOn average, FTD patients showed 14% smaller hypothalamic volumes than controls. The groups with the smallest hypothalamic regions were FTD-MND (20%), MAPT (25%) and FUS (33%), with differences mainly localised in the anterior and posterior regions. The inferior tuberal region was only significantly smaller in tauopathies (MAPT and Pick’s disease) and in TDP-43 type C compared to controls and was the only regions that did not correlate with eating symptoms. PPA-NOS and nfvPPA were the groups with the least frequent eating behaviours and the least hypothalamic involvement. ConclusionsAbnormal hypothalamic volumes are present in all the FTD forms, but different hypothalamic regions might play a different role in the development of abnormal eating behavioural and metabolic symptoms. These findings might therefore help in the identification of different underlying pathological mechanisms, suggesting the potential use of hypothalamic imaging biomarkers and the research of potential therapeutic targets within the hypothalamic neuropeptides.

Cognitive Function Deficits Associated with Type 2 Diabetes and Retinopathy: Volumetric Brain MR Imaging Study

Cognitive Function Deficits Associated with Type 2 Diabetes and Retinopathy: Volumetric Brain MR Imaging Study

Volumetric MRI Evaluation of Pituitary Gland in North Indian Subjects with Non-diseased Pituitary: Setting the Standards for Normative Data

Introduction The pituitary gland, also called the master gland, was first described by a Belgian scientist Andreas Vesalius in 1543. Pituitary gland is the engine of normal human physiology and its size and volume changes normally during various physiological stages as well as in various pathological processes, so it becomes imperative to have a normal reference value for a particular population to differentiate the normal and pathological pituitary gland. It is a tiny endocrine gland and is found in sella turcica (meaning Turkish Saddle) of sphenoid. Our study was designed to obtain standardized reference values for the volumes of pituitary gland among North Indian population to analyze the potential diagnostic values of pituitary gland volumetric variation with respect to age and gender. The volume of the pituitary gland was measured using a thin section three dimensional (3D) magnetic resonance imaging (MRI) with a section thickness of 1 mm. Methods The study was conducted between 2018-21 on patients with non-diseased pituitary by performing T1-multiplanar sequence and calculating pituitary volume by using Di chiro &amp; Nelson formula. MRI was performed on a Siemens 3 Tesla MRI scanner unit. High resolution Multiplanar-T1 Weighted images were obtained with following parameters: Slice thickness: 1 mm, Acquisition plane: Sagittal &amp; Coronal TR 1180 MS, TE 4.4 MS, Flip angle: 15 degrees, Matrix size: 256 × 256, FOV: 24 × 24 cm. Volume = 0.52 × Depth in Sagittal Plane × Height in Sagittal Plane × Width in Coronal Plane Results There were 152 patients included in the study. The mean age of participants was 43.50 years. Age group of 20-30 years comprised the maximum number of patient’s .The overall mean pituitary volume was 277.96 mm3 and in males the mean pituitary was 267.74 mm3 while in females the mean volume was 288.74 mm3. The largest pituitary gland volumes were 401.94 mm3 and 369.86 mm3 in females and males respectively in 10–20-year group while 319.18 mm3 and 360.49 mm3 in females and males respectively in 20-30 years age group. Beyond 70 years and children age group less than 10 years showed the smallest pituitary. Mean pituitary depth was 9.40 mm. Mean pituitary width was 8.81 mm.

A study of the longitudinal changes in multiple cerebrospinal fluid and volumetric magnetic resonance imaging biomarkers on converter and non-converter Alzheimer's disease subjects with consideration for their amyloid beta status.

IntroductionThis study aims to determine whether newly introduced biomarkers Visinin‐like protein‐1 (VILIP‐1), chitinase‐3‐like protein 1 (YKL‐40), synaptosomal‐associated protein 25 (SNAP‐25), and neurogranin (NG) in cerebrospinal fluid are useful in evaluating the asymptomatic and early symptomatic stages of Alzheimer's disease (AD). It further aims to shed new insight into the differences between stable subjects and those who progress to AD by associating cerebrospinal fluid (CSF) biomarkers and specific magnetic resonance imaging (MRI) regions with disease progression, more deeply exploring how such biomarkers relate to AD pathology.MethodsWe examined baseline and longitudinal changes over a 7‐year span and the longitudinal interactions between CSF and MRI biomarkers for subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI). We stratified all CSF (140) and MRI (525) cohort participants into five diagnostic groups (including converters) further dichotomized by CSF amyloid beta (Aβ) status. Linear mixed models were used to compare within‐person rates of change across diagnostic groups and to evaluate the association of CSF biomarkers as predictors of magnetic resonance imaging (MRI) biomarkers. CSF biomarkers and disease‐prone MRI regions are assessed for CSF proteins levels and brain structural changes.ResultsVILIP‐1 and SNAP‐25 displayed within‐person increments in early symptomatic, amyloid‐positive groups. CSF amyloid‐positive (Aβ+) subjects showed elevated baseline levels of total tau (tTau), phospho‐tau181 (pTau), VILIP‐1, and NG. YKL‐40, SNAP‐25, and NG are positively intercorrelated. Aβ+ subjects showed negative MRI biomarker changes. YKL‐40, tTau, pTau, and VILIP‐1 are longitudinally associated with MRI biomarkers atrophy.DiscussionConverters (CNc, MCIc) highlight the evolution of biomarkers during the disease progression. Results show that underlying amyloid pathology is associated with accelerated cognitive impairment. CSF levels of Aβ42, pTau, tTau, VILIP‐1, and SNAP‐25 show utility to discriminate between mild cognitive impairment (MCI) converter and control subjects (CN). Higher levels of YKL‐40 in the Aβ+ group were longitudinally associated with declines in temporal pole and entorhinal thickness. Increased levels of tTau, pTau, and VILIP‐1 in the Aβ+ groups were longitudinally associated with declines in hippocampal volume. These CSF biomarkers should be used in assessing the characterization of the AD progression.

Effect of Professional Fighters' Weight Class on Regional Brain Volume, Cognition, and Other Neuropsychiatric Outcomes

To evaluate the relationship between professional fighter weight class and neuropsychiatric outcomes. Traumatic brain injury (TBI) is a common source of functional impairment among athletes, military personnel, and the general population. Professional fighters in both boxing and mixed martial arts (MMA) are at particular risk for repetitive TBI and may provide valuable insight into both the pathophysiology of TBI and its consequences. Currently, effects of fighter weight class on brain volumetrics (regional and total) and functional outcomes are unknown. n = 53 boxers and n = 103 MMA fighters participating in the Professional Fighters Brain Health Study (PRBHS) underwent volumetric magnetic resonance imaging (MRI) and neuropsychological testing. Fighters were divided into lightweight (=139.9 lb), middleweight (140.0-178.5 lb), and heavyweight (>178.5 lb). Compared with lightweight fighters, heavyweights displayed greater yearly reductions in regional brain volume (boxers: bilateral thalami; MMA: left thalamus, right putamen) and functional performance (boxers: processing speed, simple and choice reaction; MMA: Trails A and B tests). Lightweights suffered greater reductions in regional brain volume on a per-fight basis (boxers: left thalamus; MMA: right putamen). Heavyweight fighters bore greater yearly burden of regional brain volume and functional decrements, possibly related to differing fight dynamics and force of strikes in this division. Lightweights demonstrated greater volumetric decrements on a per-fight basis. Although more research is needed, greater per-fight decrements in lightweights may be related to practices of weight-cutting, which may increase vulnerability to neurodegeneration post-TBI. Observed decrements associated with weight class may result in progressive impairments in fighter performance, suggesting interventions mitigating the burden of TBI in professional fighters may both improve brain health and increase professional longevity.