Disease Progression Patterns of Brain Morphology in Schizophrenia: More Progressed Stages in Treatment Resistance

BACKGROUND AND HYPOTHESIS

Given the heterogeneity and possible disease progression in schizophrenia, identifying the neurobiological subtypes and progression patterns in each patient may lead to novel biomarkers. Here, we adopted data-driven machine-learning techniques to identify the progression patterns of brain morphological changes in schizophrenia and investigate the association with treatment resistance.

STUDY DESIGN

In this cross-sectional multicenter study, we included 177 patients with schizophrenia, characterized by treatment response or resistance, with 3D T1-weighted magnetic resonance imaging. Cortical thickness and subcortical volumes calculated by FreeSurfer were converted into z scores using 73 healthy controls data. The Subtype and Stage Inference (SuStaIn) algorithm was used for unsupervised machine-learning analysis.

STUDY RESULTS

SuStaIn identified 3 different subtypes: (1) subcortical volume reduction (SC) type (73 patients), in which volume reduction of subcortical structures occurs first and moderate cortical thinning follows, (2) globus pallidus hypertrophy and cortical thinning (GP-CX) type (42 patients), in which globus pallidus hypertrophy initially occurs followed by progressive cortical thinning, and (3) cortical thinning (pure CX) type (39 patients), in which thinning of the insular and lateral temporal lobe cortices primarily happens. The remaining 23 patients were assigned to baseline stage of progression (no change). SuStaIn also found 84 stages of progression, and treatment-resistant schizophrenia showed significantly more progressed stages than treatment-responsive cases (P = .001). The GP-CX type presented earlier stages than the pure CX type (P = .009).

CONCLUSIONS

The brain morphological progressions in schizophrenia can be classified into 3 subtypes, and treatment resistance was associated with more progressed stages, which may suggest a novel biomarker.

Glymphatic System Activity and Brain Morphology in Patients With Psychogenic Non-epileptic Seizures

BACKGROUND

To clarify the neural correlates underlying psychogenic non-epileptic seizures (PNES), we compared glymphatic system activity between patients with PNES and healthy participants using diffusion tensor imaging (DTI)-analysis along the perivascular space (ALPS) method.

METHODS

The DTI scans were acquired from 16 patients with PNES and 25 healthy participants. We computed the DTI-ALPS index as an index of glymphatic system function and estimated the disease-related changes in the DTI-ALPS index and brain structures in PNES patients.

RESULTS

There were no significant differences in the DTI-ALPS index between patients with PNES and healthy participants. On the other hand, patients with PNES had decreased fractional anisotropy values in the bilateral posterior cingula, a higher mean diffusivity value around the left insula, and a lower gray matter volume in the bilateral amygdalae compared with healthy participants.

CONCLUSIONS

Patients with PNES exhibited an impairment of white matter integrity and a reduction of gray matter volume, but no glymphatic-system changes. These findings will play a significant role in our comprehension of this complex illness.

Identification of different MRI atrophy progression trajectories in epilepsy by subtype and stage inference

Artificial intelligence (AI)-based tools are widely employed, but their use for diagnosis and prognosis of neurological disorders is still evolving. Here we analyse a cross-sectional multicentre structural MRI dataset of 696 people with epilepsy and 118 control subjects. We use an innovative machine-learning algorithm, Subtype and Stage Inference, to develop a novel data-driven disease taxonomy, whereby epilepsy subtypes correspond to distinct patterns of spatiotemporal progression of brain atrophy.In a discovery cohort of 814 individuals, we identify two subtypes common to focal and idiopathic generalized epilepsies, characterized by progression of grey matter atrophy driven by the cortex or the basal ganglia. A third subtype, only detected in focal epilepsies, was characterized by hippocampal atrophy. We corroborate external validity via an independent cohort of 254 people and confirm that the basal ganglia subtype is associated with the most severe epilepsy.Our findings suggest fundamental processes underlying the progression of epilepsy-related brain atrophy. We deliver a novel MRI- and AI-guided epilepsy taxonomy, which could be used for individualized prognostics and targeted therapeutics.

White Matter Structural Connectivity and Its Impact on Psychogenic Non-Epileptic Seizures: An Evidence-Based Review

Psychiatric non-epileptic seizure (PNES), also known as a form of functional neurological disorders (FND), is a common but still underrecognized disorder presenting seizure-like symptoms and no electrophysiological abnormality. Despite the significant burden of this disorder, the neurobiological mechanisms are not clearly understood, which hinders the development of better diagnosis and treatment. In the recent neuroimaging research on PNES, brain network analysis has become a relevant topic beyond conventional methodologies. The human brain is a highly intricate system of interconnected regions that collaborate to facilitate a wide range of cognitive and behavioral functions. White matter tracts, which are comprised of bundles of axonal fibers, are the primary means by which information is transmitted between different brain regions. As such, comprehending the organization and structure of the brain's white matter network is critical for gaining insight into its functional architecture. This review article aims to provide an overview of the brain mechanisms underlying PNES, with a special focus on analyzing brain networks.

[Epilepsy in the Elderly Population: Clinical Practice and Recent Updates]

Optimal medical care and welfare is an urgent issue among the elderly population in a rapidly aging society. Epilepsy is a common chronic neurological disorder that affects all ages with peaks observed in children and in elderly individuals. Considering rapid population aging, the prevalence of epilepsy in the elderly population is expected to increase in the future. Clinicians should be aware of the clinical features of epilepsy in elderly patients because these differ from those observed in young patients from several perspectives. In this article, we review the clinical practice and recent updates in epilepsy in the elderly population. Epilepsy in elderly patients requires careful attention to subtle seizure symptoms and electroencephalography findings, and this disorder is associated with a wide range of differential diagnosis. Treatment is primarily pharmacological, and seizures may often be well controlled. Etiologies include dementia and cerebrovascular disease; however, a few patients may present with epilepsy secondary to an unknown cause. Psychosocial issues such as driver's license and stigma are also important.

Age and Sex-Related Effects on Single-Subject Gray Matter Networks in Healthy Participants

Recent developments in image analysis have enabled an individual’s brain network to be evaluated and brain age to be predicted from gray matter images. Our study aimed to investigate the effects of age and sex on single-subject gray matter networks using a large sample of healthy participants. We recruited 812 healthy individuals (59.3 ± 14.0 years, 407 females, and 405 males) who underwent three-dimensional T1-weighted magnetic resonance imaging. Similarity-based gray matter networks were constructed, and the following network properties were calculated: normalized clustering, normalized path length, and small-world coefficients. The predicted brain age was computed using a support-vector regression model. We evaluated the network alterations related to age and sex. Additionally, we examined the correlations between the network properties and predicted brain age and compared them with the correlations between the network properties and chronological age. The brain network retained efficient small-world properties regardless of age; however, reduced small-world properties were observed with advancing age. Although women exhibited higher network properties than men and similar age-related network declines as men in the subjects aged < 70 years, faster age-related network declines were observed in women, leading to no differences in sex among the participants aged ≥ 70 years. Brain age correlated well with network properties compared to chronological age in participants aged ≥ 70 years. Although the brain network retained small-world properties, it moved towards randomized networks with aging. Faster age-related network disruptions in women were observed than in men among the elderly. Our findings provide new insights into network alterations underlying aging.

Neuropsychiatric aspects of long COVID: A comprehensive review

Although some patients have persistent symptoms or develop new symptoms following coronavirus disease 2019 (COVID-19) infection, neuropsychiatric aspects of long COVID are not well known. This review summarizes and provides an update on the neuropsychiatric dimensions of long COVID. Its neuropsychiatric manifestations commonly include fatigue, cognitive impairment, sleep disorders, depression, anxiety, and post-traumatic stress disorder. There are no specific tests for long COVID, but some characteristic findings such as hypometabolism on positron emission tomography have been reported. The possible mechanisms of long COVID include inflammation, ischemic effects, direct viral invasion, and social and environmental changes. Some patient characteristics and the severity and complications of acute COVID-19 infection may be associated with an increased risk of neuropsychiatric symptoms. Long COVID may resolve spontaneously or persist, depending on the type of neuropsychiatric symptoms. Although established treatments are lacking, various psychological and pharmacological treatments have been attempted. Vaccination against COVID-19 infection plays a key role in the prevention of long coronavirus disease. With differences among the SARS-CoV-2 variants, including the omicron variant, the aspects of long COVID are likely to change in the future. Further studies clarifying the aspects of long COVID to develop effective treatments are warranted.

Contribution of the μ-opioid receptor system to affective disorders in temporal lobe epilepsy: A bidirectional relationship?

OBJECTIVE

Affective disorders are frequent comorbidities of temporal lobe epilepsy (TLE). The endogenous opioid system has been implicated in both epilepsy and affective disorders, and may play a significant role in their bidirectional relationship. In this cross-sectional study, we investigated the association between μ-opioid receptor binding and affective disorders in patients with TLE.

METHODS

Nine patients with TLE and depression/anxiety underwent ¹¹ C-carfentanil positron emission tomography (CFN PET) and neuropsychiatric assessment, including the Hospital Anxiety and Depression Scale and the Positive and Negative Affect Schedule. The normalized CFN PET scans were compared with those of 26 age-matched healthy controls. Correlation analyses with affective symptoms were performed by region of interest-based analysis focusing on the limbic circuit and orbitofrontal cortex.

RESULTS

We observed widely reduced CFN binding potential (BP) in bilateral frontal lobes and striata in patients with TLE compared to healthy controls. In the TLE group, more severe anxiety and negative affect were associated with decreased CFN BP in the posterior cingulate gyrus.

SIGNIFICANCE

In patients with TLE, interictally reduced binding in the opioid system was associated with higher levels of anxiety and negative affect. We speculate that seizure-related agonist-driven desensitization and downregulation of opioid receptors could be a potential underlying pathomechanism.

Neuroimaging-Based Brain Age Estimation: A Promising Personalized Biomarker in Neuropsychiatry

It is now possible to estimate an individual's brain age via brain scans and machine-learning models. This validated technique has opened up new avenues for addressing clinical questions in neurology, and, in this review, we summarize the many clinical applications of brain-age estimation in neuropsychiatry and general populations. We first provide an introduction to typical neuroimaging modalities, feature extraction methods, and machine-learning models that have been used to develop a brain-age estimation framework. We then focus on the significant findings of the brain-age estimation technique in the field of neuropsychiatry as well as the usefulness of the technique for addressing clinical questions in neuropsychiatry. These applications may contribute to more timely and targeted neuropsychiatric therapies. Last, we discuss the practical problems and challenges described in the literature and suggest some future research directions.

Free water derived by multi-shell diffusion MRI reflects tau/neuroinflammatory pathology in Alzheimer's disease

INTRODUCTION

Free-water (FW) imaging, a new analysis method for diffusion magnetic resonance imaging (MRI), can indicate neuroinflammation and degeneration. We evaluated FW in Alzheimer's disease (AD) using tau/inflammatory and amyloid positron emission tomography (PET).

METHODS

Seventy-one participants underwent multi-shell diffusion MRI, ¹⁸F-THK5351 PET, ¹¹C-Pittsburgh compound B PET, and neuropsychological assessments. They were categorized into two groups: healthy controls (HCs) (n = 40) and AD-spectrum group (AD-S) (n = 31) using the Centiloid scale with amyloid PET and cognitive function. We analyzed group comparisons in FW and PET, correlations between FW and PET, and correlation analysis with neuropsychological scores.

RESULTS

In AD-S group, there was a significant positive correlation between FW and ¹⁸F-THK5351 in the temporal lobes. In addition, there were negative correlations between FW and cognitive function in the temporal lobe and cingulate gyrus, and negative correlations between ¹⁸F-THK5351 and cognitive function in the same regions.

DISCUSSION

FW imaging could be a biomarker for tau in AD alongside clinical correlations.

Upper cerebellar glucose hypermetabolism in patients with temporal lobe epilepsy and interictal psychosis

OBJECTIVE

Psychosis is an important comorbidity in epilepsy, but its pathophysiology is still unknown. The imaging modality ¹⁸ F-fluorodeoxyglucose-positron emission tomography (¹⁸ F-FDG PET) is widely used to measure brain glucose metabolism, and we speculated that ¹⁸ F-FDG PET may detect characteristic alteration patterns in individuals with temporal lobe epilepsy (TLE) and psychosis.

METHODS

We enrolled 13 patients with TLE and interictal psychosis (TLE-P) and 21 patients with TLE without psychosis (TLE-N). All underwent interictal ¹⁸ F-FDG-PET scanning. Statistical Parametric Mapping (SPM)12 software was used for the normalization process, and we performed a voxel-wise comparison of the TLE-P and TLE-N groups.

RESULTS

Cerebral hypometabolic areas were observed in the ipsilateral temporal pole to hippocampus in both patient groups. In the TLE-P group, the voxel-wise comparison revealed significantly increased ¹⁸ F-FDG signals in the upper cerebellum, superior cerebellar peduncle, and midbrain. There were no significant between-group metabolic differences around the focus or other cerebral areas.

SIGNIFICANCE

Our results demonstrated significant hypermetabolism around the upper cerebellum in patients with TLE and interictal psychosis compared to patients with TLE without psychosis. These findings may reflect the involvement of the cerebellum in the underlying neurobiology of interictal psychosis and could contribute to a better understanding of this disorder.

Impact of COVID-19 pandemic on epilepsy care in Japan: A national-level multicenter retrospective cohort study

OBJECTIVE

The impact of the coronavirus disease 2019 (COVID-19) pandemic on epilepsy care across Japan was investigated by conducting a multicenter retrospective cohort study.

METHODS

This study included monthly data on the frequency of (1) visits by outpatients with epilepsy, (2) outpatient electroencephalography (EEG) studies, (3) telemedicine for epilepsy, (4) admissions for epilepsy, (5) EEG monitoring, and (6) epilepsy surgery in epilepsy centers and clinics across Japan between January 2019 and December 2020. We defined the primary outcome as epilepsy-center-specific monthly data divided by the 12-month average in 2019 for each facility. We determined whether the COVID-19 pandemic-related factors (such as year [2019 or 2020], COVID-19 cases in each prefecture in the previous month, and the state of emergency) were independently associated with these outcomes.

RESULTS

In 2020, the frequency of outpatient EEG studies (-10.7%, p<0.001) and cases with telemedicine (+2,608%, p=0.031) were affected. The number of COVID-19 cases was an independent associated factor for epilepsy admission (-3.75*10-3 % per case, p<0.001) and EEG monitoring (-3.81*10-3 % per case, p = 0.004). Further, the state of emergency was an independent factor associated with outpatient with epilepsy (-11.9%, p<0.001), outpatient EEG (-32.3%, p<0.001), telemedicine for epilepsy (+12,915%, p<0.001), epilepsy admissions (-35.3%; p<0.001), EEG monitoring (-24.7%: p<0.001), and epilepsy surgery (-50.3%, p<0.001).

SIGNIFICANCE

We demonstrated the significant impact that the COVID-19 pandemic had on epilepsy care. These results support those of previous studies and clarify the effect size of each pandemic-related factor on epilepsy care.

Effect of Anti-seizure Medications on Functional Anatomy of Language: A Perspective From Language Functional Magnetic Resonance Imaging

Background

In epilepsy, cognitive difficulties are common, partly a consequence of anti-seizure medications (ASM), and cognitive side-effects are often considered to be more disabling than seizures and significantly affect quality of life. Functional MRI during verbal fluency tasks demonstrated impaired frontal activation patterns and failed default mode network deactivation in people taking ASM with unfavourable cognitive profiles. The cognitive effect of ASMs given at different dosages in monotherapy, or in different combinations, remains to be determined.

Methods

Here, we compared the effects of different drug loads on verbal fluency functional MRI (fMRI) in people (i) taking dual therapy of ASMs either considered to be associated with moderate (levetiracetam, lamotrigine, lacosamide, carbamazepine/oxcarbazepine, eslicarbazepine, valproic acid; n = 119, 56 females) or severe (topiramate, zonisamide) side-effects; n = 119, 56 females), (ii) taking moderate ASMs in either mono-, dual- or triple-therapy (60 subjects in each group), or (iii) taking different dosages of ASMs with moderate side-effect profiles (n = 180). “Drug load” was defined as a composite value of numbers and dosages of medications, normalised to account for the highest and lowest dose of each specific prescribed medication.

Results

In people taking “moderate” ASMs (n = 119), we observed higher verbal-fluency related to left inferior frontal gyrus and right inferior parietal fMRI activations than in people taking “severe” ASMs (n = 119). Irrespective of the specific ASM, people on monotherapy (n = 60), showed greater frontal activations than people taking two (n = 60), or three ASMs (n = 60). People on two ASMs showed less default mode (precuneus) deactivation than those on monotherapy. In people treated with “moderate” ASMs (n = 180), increased drug load correlated with reduced activation of language-related regions and the right piriform cortex.

Conclusion

Our study delineates the effects of polytherapy and high doses of ASMs when given in monotherapy on the functional anatomy of language. Irrespective of the cognitive profile of individual ASMs, each additional ASM results in additional alterations of cognitive activation patterns. Selection of ASMs with moderate cognitive side effects, and low doses of ASMs when given in polytherapy, could reduce the cognitive effect.

Neurobiological mechanisms of psychosis in epilepsy: Findings from neuroimaging studies

Despite the high prevalence and clinical importance of comorbid psychosis in epilepsy, its neurobiological mechanisms remain understudied. This narrative mini-review aims to provide an overview of recent updates in in vivo neuroimaging studies on psychosis in epilepsy, including structural and diffusion magnetic resonance imaging (MRI) and functional and molecular imaging, and to discuss future directions in this field. While the conventional morphological analysis of structural MRI has provided relatively inconsistent results, advanced methods, including brain network analysis, hippocampal subregion volumetry, and machine learning models, have recently provided novel findings. Diffusion MRI, for example, has revealed a reduction in white matter integrity mainly in the frontal and temporal lobes, as well as a disruption of brain white matter networks. Functional neuroimaging, such as perfusion single-photon emission computed tomography (SPECT) or fluorodeoxyglucose positron emission tomography (FDG-PET), often identifies hyperactivity in various brain regions. The current limitations of these more recent studies may include small and sometimes heterogeneous samples, insufficient control groups, the effects of psychoactive drugs, and the lack of longitudinal analysis. Further investigations are required to establish novel treatments and identify clinical diagnostic or disease-monitoring biomarkers in psychosis in epilepsy.

Barriers to telemedicine among physicians in epilepsy care during the COVID-19 pandemic: A national-level cross-sectional survey in Japan

OBJECTIVE

This study aimed to investigate the factors affecting the unwillingness of physicians involved in epilepsy care to continue telemedicine during the coronavirus disease 2019 (COVID-19) pandemic in Japan.

METHOD

This was a national-level cross-sectional survey initiated by Japan Young Epilepsy Section (YES-Japan) which is a national chapter of The Young Epilepsy Section of the International League Against Epilepsy (ILAE-YES). We asked physicians who conducted telemedicine in patients with epilepsy (PWE) during the COVID-19 pandemic at four clinics and 21 hospitals specializing in epilepsy care in Japan from March 1 to April 30, 2021. The following data were collected: (1) participant profile, (2) characteristics of PWE treated by telemedicine, and (3) contents and environmental factors of telemedicine. Statistically significant variables (p < 0.05) in the univariate analysis were analyzed in a multivariate binary logistic regression model to detect the independently associated factors with the unwillingness to continue telemedicine.

RESULT

Among the 115 respondents (response rate: 64%), 89 were included in the final analysis. Of them, 60 (67.4%) were willing to continue telemedicine, and 29 (32.6%) were unwilling. In the univariate binary logistic regression analysis, age (Odds ratio [OR] = 1.84, 95% confidence interval [CI] 1.10-3.09, p = 0.02), psychiatrist (OR = 5.88, 95% CI 2.15-16.08, p = 0.001), hospital (OR = 0.10, 95% CI 0.01-0.94, p = 0.04), the number of COVID-19 risk factors in the participant (OR = 2.88, 95% CI 1.46-5.69, p = 0.002), the number of COVID-19 risk factors in the cohabitants (OR = 2.52, 95% CI 1.05-6.01, p = 0.04), COVID-19 epidemic area (OR = 4.37, 95% CI 1.18-16.20, p = 0.03), consultation time during telemedicine (OR = 2.51, 95% CI 1.32-4.76, p = 0.005), workload due to telemedicine (OR = 4.17, 95% CI 2.11-8.24, p < 0.001) were statistically significant. In the multivariate binary logistic regression analysis, workload due to telemedicine (OR = 4.93, 95% CI 1.96-12.35) was independently associated with the unwillingness to continue telemedicine.

CONCLUSION

This national-level cross-sectional survey found that workload due to telemedicine among physicians involved in epilepsy care was independently associated with the unwillingness to continue telemedicine.

Risk factors for psychological distress in electroencephalography technicians during the COVID-19 pandemic: A national-level cross-sectional survey in Japan

OBJECTIVE

To identify the risk factors for psychological distress in electroencephalography (EEG) technicians during the coronavirus disease 2019 (COVID-19) pandemic.

METHOD

In this national-level cross-sectional survey initiated by Japan Young Epilepsy Section (YES-Japan), which is a national chapter of The Young Epilepsy Section of the International League Against Epilepsy (ILAE-YES), a questionnaire was administered to 173 technicians engaged in EEG at four clinics specializing in epilepsy care and 20 hospitals accredited as (quasi-) epilepsy centers or epilepsy training facilities in Japan from March 1 to April 30, 2021. We collected data on participants' profiles, information about work, and psychological distress outcome measurements, such as the K-6 and Tokyo Metropolitan Distress Scale for Pandemic (TMDP). Linear regression analysis was used to identify the risk factors for psychological distress. Factors that were significantly associated with psychological distress in the univariate analysis were subjected to multivariate analysis.

RESULTS

Among the 142 respondents (response rate: 82%), 128 were included in the final analysis. As many as 35.2% of EEG technicians have been under psychological distress. In multivariate linear regression analysis for K-6, female sex, examination for patients (suspected) with COVID-19, and change in salary or bonus were independent associated factors for psychological distress. Contrastingly, in multivariate linear regression analysis for TMDP, female sex, presence of cohabitants who had to be separated from the respondent due to this pandemic, and change in salary or bonus were independent associated factors for psychological distress.

CONCLUSION

We successfully identified the risk factors associated with psychological distress in EEG technicians during the COVID-19 pandemic. Our results may help in understanding the psychological stress in EEG technicians during the COVID-19 pandemic and improving the work environment, which is necessary to maintain the mental health of EEG technicians.

Optimal Surgical Extent for Memory and Seizure Outcome in Temporal Lobe Epilepsy

OBJECTIVE

Postoperative memory decline is an important consequence of anterior temporal lobe resection (ATLR) for temporal lobe epilepsy (TLE), and the extent of resection may be a modifiable factor. This study aimed to define optimal resection margins for cognitive outcome while maintaining a high rate of postoperative seizure freedom.

METHODS

This cohort study evaluated the resection extent on postoperative structural MRI using automated voxel-based methods and manual measurements in 142 consecutive patients with unilateral drug refractory TLE (74 left, 68 right TLE) who underwent standard ATLR.

RESULTS

Voxel-wise analyses revealed that postsurgical verbal memory decline correlated with resections of the posterior hippocampus and inferior temporal gyrus, whereas larger resections of the fusiform gyrus were associated with worsening of visual memory in left TLE. Limiting the posterior extent of left hippocampal resection to 55% reduced the odds of significant postoperative verbal memory decline by a factor of 8.1 (95% CI 1.5-44.4, p = 0.02). Seizure freedom was not related to posterior resection extent, but to the piriform cortex removal after left ATLR. In right TLE, variability of the posterior extent of resection was not associated with verbal and visual memory decline or seizures after surgery.

INTERPRETATION

The extent of surgical resection is an independent and modifiable risk factor for cognitive decline and seizures after left ATLR. Adapting the posterior extent of left ATLR might optimize postoperative outcome, with reduced risk of memory impairment while maintaining comparable seizure-freedom rates. The current, more lenient, approach might be appropriate for right ATLR. ANN NEUROL 2021.

Histopathological validation and clinical correlates of hippocampal subfield volumetry based on T2-weighted MRI in temporal lobe epilepsy with hippocampal sclerosis

The objectives of this study were 1) to histologically validate the hippocampal subfield volumetry based on T2-weighted MRI, and 2) to explore its clinical impact on postsurgical memory function and seizure outcome in temporal lobe epilepsy (TLE) with hippocampal sclerosis (HS). We analyzed the cases of 24 patients with medial TLE (12 left, 12 right) and HS who were preoperatively examined with T2-weighted high-resolution MRI. The volume of each hippocampal subfield was calculated with an automatic segmentation of hippocampal subfields (ASHS) program. Hippocampal sclerosis patterns were determined pathologically, and the cross-sectional area and neuronal cell density of the CA1 and CA4 subfields were calculated using tissue specimens. Pre- and postoperative memory evaluations based on the Wechsler Memory Scale-Revised (WMS-R) were performed. We compared the presurgical MRI-based volumes with the pathological measurements in each subfield and then compared them with the change in the patients' neurocognitive function. As a result, there was a significant relationship between the presurgical MRI-based volume of CA4/dentate gyrus (DG) and the cross-sectional area of CA4 calculated with tissue specimens (Spearman's rs = 0.482, p = 0.023), and a similar trend-level correlation was observed in CA1 (rs = 0.455, p = 0.058). Some of MRI-based or pathology-based parameters in the subfields preliminarily showed relationships with the postsurgical memory changes. In conclusion, automated subfield volumetry for patients with hippocampal sclerosis moderately reflects their subfield atrophy and might be useful to predict the postsurgical change of memory function in these patients.

Accurate lateralization and classification of MRI-negative 18F-FDG-PET-positive temporal lobe epilepsy using double inversion recovery and machine-learning

OBJECTIVE

The main objective of this study was to determine the ability of double inversion recovery (DIR) data coupled with machine-learning algorithms to distinguish normal individuals from epileptic subjects and to identify the laterality of the focus side in MRI-negative, PET-positive temporal lobe epilepsy (TLE) patients.

MATERIALS AND METHODS

We used whole-brain DIR data as the input features with which to train a linear support-vector machine model in 63 participants who underwent high-resolution structural MRI and DIR scans. The subjects included 20 left TLE patients, 19 right TLE patients, and 24 healthy controls (HCs).

RESULTS

Using the DIR data, we achieved a robust accuracy of 87.30% for discriminating among the left TLE, right TLE, and HC groups as well as 84.61%, 97.72%, and 93.02% prediction accuracies for distinguishing left TLE from right TLE, HC from right TLE, and HC from left TLE, respectively.

INTERPRETATION

Our experimental results suggest that DIR data coupled with machine-learning algorithms provide a promising approach to identifying MRI-negative TLE patients, especially when fluorodeoxyglucose-PET is not available.

Making the Invisible Visible: Advanced Neuroimaging Techniques in Focal Epilepsy

It has been a clinically important, long-standing challenge to accurately localize epileptogenic focus in drug-resistant focal epilepsy because more intensive intervention to the detected focus, including resection neurosurgery, can provide significant seizure reduction. In addition to neurophysiological examinations, neuroimaging plays a crucial role in the detection of focus by providing morphological and neuroanatomical information. On the other hand, epileptogenic lesions in the brain may sometimes show only subtle or even invisible abnormalities on conventional MRI sequences, and thus, efforts have been made for better visualization and improved detection of the focus lesions. Recent advance in neuroimaging has been attracting attention because of the potentials to better visualize the epileptogenic lesions as well as provide novel information about the pathophysiology of epilepsy. While the progress of newer neuroimaging techniques, including the non-Gaussian diffusion model and arterial spin labeling, could non-invasively detect decreased neurite parameters or hypoperfusion within the focus lesions, advances in analytic technology may also provide usefulness for both focus detection and understanding of epilepsy. There has been an increasing number of clinical and experimental applications of machine learning and network analysis in the field of epilepsy. This review article will shed light on recent advances in neuroimaging for focal epilepsy, including both technical progress of images and newer analytical methodologies and discuss about the potential usefulness in clinical practice.

Clinical Application of Machine Learning Models for Brain Imaging in Epilepsy: A Review

Epilepsy is a common neurological disorder characterized by recurrent and disabling seizures. An increasing number of clinical and experimental applications of machine learning (ML) methods for epilepsy and other neurological and psychiatric disorders are available. ML methods have the potential to provide a reliable and optimal performance for clinical diagnoses, prediction, and personalized medicine by using mathematical algorithms and computational approaches. There are now several applications of ML for epilepsy, including neuroimaging analyses. For precise and reliable clinical applications in epilepsy and neuroimaging, the diverse ML methodologies should be examined and validated. We review the clinical applications of ML models for brain imaging in epilepsy obtained from a PubMed database search in February 2021. We first present an overview of typical neuroimaging modalities and ML models used in the epilepsy studies and then focus on the existing applications of ML models for brain imaging in epilepsy based on the following clinical aspects: (i) distinguishing individuals with epilepsy from healthy controls, (ii) lateralization of the temporal lobe epilepsy focus, (iii) the identification of epileptogenic foci, (iv) the prediction of clinical outcomes, and (v) brain-age prediction. We address the practical problems and challenges described in the literature and suggest some future research directions.

Gray matter structural networks related to 18F-THK5351 retention in cognitively normal older adults and Alzheimer's disease patients

Objective

This study aimed to examine the alterations in gray matter networks related to tau retention in Alzheimer's disease (AD) patients and cognitively normal (CN) older individuals.

Methods

Eighteen amyloid-positive AD patients and 30 age- and sex-matched amyloid-negative CN controls were enrolled. All underwent 3D T1-weighted MRI, amyloid positron-emission tomography imaging (PET) with ¹¹C-Pittsburgh Compound B (PiB), and tau PET with ¹⁸F-THK5351. The structural networks extracted from the T1-weighted MRI data based on cortical similarities within single subjects were analyzed. Based on graph theoretical approach, global and local network properties across the whole brain were computed. Group comparisons of global and local network properties were evaluated between the groups. Then, we correlated the global and local network measures with total cerebral ¹⁸F-THK5351 retention.

Results

AD patients moved toward more randomized global network compared to controls and regional differences were observed in the default mode network (DMN) area. No significant correlations existed between global network properties and tau retention. On a local level, AD and controls showed opposite relationships between network properties and tau retention mainly in the DMN areas; CN controls showed positive correlations, whereas AD showed negative correlations.

Conclusion

We found opposite relationships between local network properties and tau retention between amyloid-positive AD patients and amyloid-negative controls. Our findings suggest that the presence of amyloid and induced exacerbated tau retention alter the relationship of local network properties and tau retention.

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Correlation of structural network properties and tau retention.

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Positive correlations between local network properties and tau retention in healthy elderly.

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Negative correlations between local network properties and tau retention in AD.

Quantitative analysis of double inversion recovery and FLAIR signals in temporal lobe epilepsy

This study aimed to quantitatively compare the signals from double inversion recovery (DIR) and fluid-attenuated inversion recovery (FLAIR) in temporal lobe epilepsy (TLE) with a focus on anterior temporal lobe white matter abnormal signal (ATLAS) lesions. We recruited 59 patients with TLE (32 left, 27 right) and 24 healthy controls (HCs). All patients underwent 3T-MRI scans including 3D DIR and FLAIR images, and the images were normalized and compared among the three groups by the software program SPM 12. We also explored the association of the ATLAS with disease duration, seizure types, and the existence of hippocampal sclerosis (HS). As a result, compared to the HCs, there were significantly increased DIR signals in the ipsilateral anterior temporal white matter of both the left and right TLE patients. There was no significant signal difference in FLAIR images between the HCs and patients except for a trend-level increase in left TLE. There was also no significant association between the ATLAS and disease duration, seizure type, or HS. These results quantitatively confirmed the significant signal increases of DIR in the ipsilateral anterior temporal lobe in both left and right TLE, whereas FLAIR revealed no significant between-group differences. These findings may indicate greater usefulness of DIR compared to FLAIR for detecting ATLAS lesions.

Association between neurite metrics and tau/inflammatory pathology in Alzheimer's disease

INTRODUCTION

The molecular mechanism of neurodegeneration, including tau and neurite complexity, is an important topic in Alzheimer's disease (AD) research.

METHODS

We recruited 27 amyloid-positive individuals identified through 11C-Pittsburgh compound B (PiB) positron emission tomography (PET) and 31 amyloid-negative individuals with normal cognition. All participants underwent 11C-PiB and 18F-THK5351 PET and magnetic resonance imaging (MRI) with neurite orientation dispersion and density imaging (NODDI) protocol. The neurite density index (NDI), orientation dispersion index (ODI), and PET images were analyzed to calculate voxel-wise correlations among the imaging modalities and correlations with cognitions.

RESULTS

In the amyloid-positive participants, there were significant negative correlations between 18F-THK5351 and NDI and between 18F-THK5351 and ODI. The bilateral mesial and lateral temporal lobes were mainly involved. Regarding cognition, 18F-THK5351 showed more marked associations with all cognitive domains than the other modalities.

DISCUSSION

Tau and neuroinflammation in AD may reduce the neurite density and orientation dispersion, particularly in the mesial and lateral temporal lobes.

FLAIR-Wise Machine-Learning Classification and Lateralization of MRI-Negative 18F-FDG PET-Positive Temporal Lobe Epilepsy

Objective: In this study, we investigated the ability of fluid-attenuated inversion recovery (FLAIR) data coupled with machine-leaning algorithms to differentiate normal and epileptic brains and identify the laterality of focus side in temporal lobe epilepsy (TLE) patients with visually negative MRI.

Materials and Methods: The MRI data were acquired on a 3-T MR system (Philips Medical Systems). After pre-proceeding stage, the FLAIR signal intensities were extracted from specific regions of interest, such as the amygdala, cerebral white matter, inferior temporal gyrus, middle temporal gyrus, parahippocampal gyrus, superior temporal gyrus, and temporal pole, and fed into a classification framework followed by a support vector machine as classifier. The proposed lateralization framework was assessed in a group of MRI-negative unilateral TLE patients (N = 42; 23 left TLE and 19 right TLE) and 34 healthy controls (HCs) based on a leave-one-out cross-validation strategy.

Results: Using the FLAIR data, we obtained a 75% accuracy for discriminating the three groups, as well as 87.71, 83.01, and 76.19% accuracies for HC/right TLE, HC/left TLE, and left TLE/right TLE tasks, respectively.

Interpretation: The experimental results show that FLAIR data can potentially be considered an informative biomarker for improving the pre-surgical diagnostic confidence in patients with MRI-negative TLE.

Disrupted White Matter Integrity and Structural Brain Networks in Temporal Lobe Epilepsy With and Without Interictal Psychosis

Background: Despite the importance of psychosis as a comorbidity of temporal lobe epilepsy (TLE), the underlying neural mechanisms are still unclear. We aimed to investigate abnormalities specific to psychosis in TLE, using diffusion MRI parameters and graph-theoretical network analysis.

Material and Methods: We recruited 49 patients with TLE (20 with and 29 without interictal schizophrenia-like psychosis) and 42 age-/gender-matched healthy controls. We performed 3-tesla MRI scans including 3D T1-weighted imaging and diffusion tensor imaging in all participants. Among the three groups, fractional anisotropy (FA), mean diffusivity (MD), and global network metrics were compared by analyses of covariance. Regional connectivity strength was compared by network-based statistics.

Results: Compared to controls, TLE patients showed significant temporal and extra-temporal changes in FA, and MD, which were more severe and widespread in patients with than without psychosis. We observed distinct differences between TLE patients with and without psychosis in the anterior thalamic radiation (ATR), inferior fronto-occipital fasciculus (IFOF), and inferior longitudinal fasciculus (ILF). Similarly, for network metrics, global, and local efficiency and increased path length were significantly reduced in TLE patients compared to controls, but with more severe changes in TLE with psychosis than without psychosis. Network-based statistics detected significant differences between TLE with and without psychosis mainly involving the left limbic and prefrontal areas.

Conclusion: TLE patients with interictal schizophrenia-like psychosis showed more widespread and severe white matter impairment, involving the ATR, IFOF and ILF, as well as disrupted network connectivity, particularly in the left limbic and prefrontal cortex, than patients without psychosis.

T1-weighted MRI-driven Brain Age Estimation in Alzheimer's Disease and Parkinson's Disease

Neuroimaging-driven brain age estimation has introduced a robust (reliable and heritable) biomarker for detecting and monitoring neurodegenerative diseases. Here, we computed and compared brain age in Alzheimer's disease (AD) and Parkinson's disease (PD) patients using an advanced machine learning procedure involving T1-weighted MRI scans and gray matter (GM) and white matter (WM) models. Brain age estimation frameworks were built using 839 healthy individuals and then the brain estimated age difference (Brain-EAD: chronological age subtracted from brain estimated age) was assessed in a large sample of PD patients (n = 160) and AD patients (n = 129), respectively. The mean Brain-EADs for GM were +9.29 ± 6.43 years for AD patients versus +1.50 ± 6.03 years for PD patients. For WM, the mean Brain-EADs were +8.85 ± 6.62 years for AD patients versus +2.47 ± 5.85 years for PD patients. In addition, PD patients showed a significantly higher WM Brain-EAD than GM Brain-EAD. In a direct comparison between PD and AD patients, we observed significantly higher Brain-EAD values in AD patients for both GM and WM. A comparison of the Brain-EAD between PD and AD patients revealed that AD patients may have a significantly "older-appearing" brain than PD patients.

Voxel-based correlation of 18F-THK5351 accumulation and gray matter volume in the brain of cognitively normal older adults

Backgrounds

Although neurofibrillary tangles (NFTs) mainly accumulate in the medial temporal lobe with human aging, only a few imaging studies have investigated correlations between NFT accumulation and gray matter (GM) volume in cognitively normal older adults. Here, we investigated the correlations between ¹⁸F-THK5351 accumulation and GM volume at the voxel level.

Material and methods

We recruited 47 amyloid-negative, cognitively normal, older adults (65.0 ± 7.9 years, 26 women), who underwent structural magnetic resonance imaging, ¹¹C-Pittsburgh compound-B and ¹⁸F-THK5351 PET scans, and neuropsychological assessment. The magnetic resonance and ¹⁸F-THK5351 PET images were spatially normalized using Statistical Parametric Mapping 12. Voxel-wise correlations between ¹⁸F-THK5351 accumulation and GM volume were evaluated using the Biological Parametric Mapping toolbox.

Results

A significant negative correlation (p < 0.001) between ¹⁸F-THK5351 accumulation and GM volume was detected in the bilateral medial temporal lobes.

Conclusions

Voxel-wise correlation analysis revealed a significant negative correlation between ¹⁸F-THK5351 accumulation and GM volume in the medial temporal lobe in individuals without amyloid-β deposits. These results may contribute to a better understanding of the pathophysiology of primary age-related tauopathy in human aging.

Longitudinal analysis of risk factors for dementia based on Mild Cognitive Impairment Screen results and questionnaire responses from healthy Japanese individuals registered in an online database

Introduction

Despite an urgent need for developing remedial measures against dementia, no disease-modifying drugs have been developed. Efficient protocols for participant recruitment need to be established for conducting clinical trials. To meet this need, a large-scale online registry system, the Integrated Registry of Orange Plan (IROOP®), was created for healthy individuals. Although the risk factors for dementia have been discussed in our previous studies for a short interval of 6 months, some factors remain controversial. The present study aimed to explore factors affecting longitudinal changes in cognitive function for a longer interval of 18 months using the IROOP® data.

Methods

This study assessed the longitudinal changes in the collated data for predicting the risk of dementia and included 473 individuals (175 men and 298 women; mean age 59.6 ± 10.1 years) registered in the IROOP® between July 5, 2016 and January 15, 2018 who completed the initial questionnaire and brief assessment of cognitive function (Mild Cognitive Impairment Screen) at baseline and the regular questionnaire and the Mild Cognitive Impairment Screen at least once after baseline. Statistical analyses were performed using IBM SPSS, version 23.0, for Windows for demographic data and the MIXED procedure in SAS, version 9.4, for the linear mixed-effect model. In each analysis, the statistical significance level was set at P < .05.

Results

Mood, sleep, quality of life, and medical histories including cognition were found to influence longitudinal changes in cognitive function.

Discussion

Given the multifactorial etiology of dementia, preventive measures targeting multiple domains are required for maintaining cognitive function, instead of focusing on one lifestyle factor.

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Mood consistently influences on longitudinal changes of cognitive function.

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Sleep is also an important factor for maintaining cognitive function.

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Given the multifactorial etiology of dementia, multidomain prevention is required.

Association between subfield volumes of the medial temporal lobe and cognitive assessments

Cognitive assessments and neuroimaging are routinely combined in clinical practice to diagnose dementia represented by Alzheimer's disease (AD). The Montreal Cognitive Assessment (MoCA) is reported to be more suitable than the Mini-Mental State Examination (MMSE) for screening mild cognitive impairment (MCI) and mild AD. On the other hand, attention to the subfield volumes of the medial temporal lobe has recently been considered important for the differential diagnosis and early detection of AD. The aim of this study was to uncover which specific hippocampal subfields and adjacent extrahippocampal structures contribute to deficits in cognitive assessment scores in patients with MCI and AD. We recruited from our institute 31 Japanese patients—14 with amnestic MCI and 17 with probable AD, with a clinical dementia rating (CDR) of 0.5 and 1, respectively—and 50 healthy elderly individuals with a CDR of 0. All participants underwent magnetic resonance imaging and cognitive assessments with the MMSE, Wechsler Memory Scale-Revised Logical Memory I and II, and Japanese version of the MoCA (MoCA-J). With adjustment for age and sex, we performed partial correlation analysis of the cognitive assessment scores with the subfield volumes of the medial temporal lobe measured by software-mediated automatic segmentation of hippocampal subfields using high-resolution T1-and T2-weighted images. Compared with normal controls, patients with MCI and AD showed subfield volume reductions in cornu ammonis (CA) 1, CA2, Brodmann area (BA) 35, BA36, the dentate gyrus (DG), the subiculum, and the entorhinal cortex (ERC). All participants showed high correlation coefficients (above 0.6) between cognitive assessment scores and subfield volumes in CA1, the DG, the subiculum, the ERC, and BA36. In patients with MCI and AD, the MoCA-J showed higher correlations than the MMSE with subfield volumes in CA1, the DG, the subiculum, and the ERC. These results suggest that the combination of the in vivo analysis of subfield morphometry of the medial temporal lobe with the MoCA-J paradigm provides important insights into whether changes within specific subfields are related to the cognitive profile in MCI and AD.

Disrupted cortico-ponto-cerebellar pathway in patients with hemimegalencephaly

OBJECTIVE

Cerebellar dysmaturation and injury is associated with a wide range of neuromotor, neurocognitive and behavioral disorders as well as with preterm birth. We used diffusion tensor MR imaging to investigate a disruption in structural cortico-ponto-cerebellar (CPC) connectivity in children with infantile-onset severe epilepsy.

METHODS

We performed CPC tract reconstructions in 24 hemimegalencephaly (HME) patients, 28 West syndrome (WS) of unknown etiology patients, and 25 pediatric disease control subjects without a history of epilepsy nor brain abnormality on MRI. To identify the CPC tract, we placed a seeding ROI separately in each right and left cerebral peduncle. We evaluated the distribution patterns of the CPC tracts to the cerebellum and their correlation with clinical findings.

RESULTS

In control and WS of unknown etiology groups, both sides' CPC tracts descended to bilateral hemispheres in 20 (80.0%) and 21 (75.0%); mixed (bilateral on one side and unilateral on the other side) in five (20.0%) and five (17.9%); and unilateral in zero (0.0%) and two (7.1%), respectively. However, in the HME, both sides' CPC tracts descended to bilateral hemispheres in four (16.7%); mixed in 13 (54.1%); and unilateral in seven (29.2%). These CPC patterns differed significantly between the HME and other groups (p < 0.001). Among HME patients, those with a unilateral cerebellar distribution on both sides had significantly earlier seizure onset (p = 0.049) and more frequent seizures (p = 0.052) at a trend level compared to those with bilateral and mixed distributions.

CONCLUSION

Disrupted CPC tracts were observed more frequently in HME patients than in WS of unknown etiology patients and controls, and they may be correlated with earlier seizure onset and more frequent seizures in HME patients. DTI is a useful and non-invasive method for speculating the pathology in the developing brain.

Similar and Differing Distributions Between 18F-FDG-PET and Arterial Spin Labeling Imaging in Temporal Lobe Epilepsy

Background: Despite the increasing use of arterial spin labeling (ASL) in patients with epilepsy, little is known about its brain regional distribution pattern, including diaschisis, and its correspondence with FDG-PET. Here, we investigated the regional match and mismatch between FDG-PET and ASL in temporal lobe epilepsy (TLE). Methods: We recruited 27 patients with unilateral TLE, who underwent inter-ictal ASL and FDG-PET scans. These images were spatially normalized using Statistical Parametric Mapping 12, and the regional values in both ASL and FDG-PET were calculated using PMOD software within 20 volumes of interest (VOIs), including the temporal lobe, adjacent cortices, subcortical structures, and cerebellum. ASL images of 37 healthy controls were also analyzed and compared. Results: Whereas, ASL showed significant side differences, mainly in the temporal and frontal lobes, the significant abnormalities in FDG-PET were more widespread and included the insula and supramarginal gyrus. Ipsilateral thalamic reduction was found in FDG-PET only. The detectability of the focus side compared with the contralateral side was generally higher in FDG-PET. The discriminative values in ASL compared with healthy controls were higher in temporal neocortex and amygdala VOIs. Conclusions: There are similar and differing regional distributions between FDG-PET and ASL in TLE, possibly reflecting regional match and mismatch of cerebral blood flow and metabolism. At this stage, it seems that ASL couldn't present comparable clinical usefulness with FDG-PET. These findings deepen our knowledge of ASL imaging and are potentially useful for its further application.

Reduced resilience of brain gray matter networks in idiopathic generalized epilepsy: A graph-theoretical analysis

Purpose

The pathophysiology of idiopathic generalized epilepsy (IGE) is still unclear, but graph theory may help to understand it. Here, we examined the graph-theoretical findings of the gray matter network in IGE using anatomical covariance methods.

Materials and methods

We recruited 33 patients with IGE and 35 age- and sex-matched healthy controls. Gray matter images were obtained by 3.0-T 3D T1-weighted MRI and were normalized using the voxel-based morphometry tools of Statistical Parametric Mapping 12. The normalized images were subjected to graph-theoretical group comparison using the Graph Analysis Toolbox with two different parcellation schemes. Initially, we used the Automated Anatomical Labeling template, whereas the Hammers Adult atlas was used for the second analysis.

Results

The resilience analyses revealed significantly reduced resilience of the IGE gray matter networks to both random failure and targeted attack. No significant between-group differences were found in global network measures, including the clustering coefficient and characteristic path length. The IGE group showed several changes in regional clustering, including an increase mainly in wide areas of the bilateral frontal lobes. The second analysis with another region of interest (ROI) parcellation generated the same results in resilience and global network measures, but the regional clustering results differed between the two parcellation schemes.

Conclusion

These results may reflect the potentially weak network organization in IGE. Our findings contribute to the accumulation of knowledge on IGE.

Widely Impaired White Matter Integrity and Altered Structural Brain Networks in Psychogenic Non-Epileptic Seizures

OBJECTIVE

The underlying neural correlates of psychogenic non-epileptic seizures (PNES) are still unknown and their identification would be helpful for clinicians and patients. This study aimed to reveal details of white matter microstructure and alterations in brain structural networks in patients with PNES by using diffusion tensor imaging (DTI) and graph theoretical connectivity analysis.

METHODS

Seventeen patients with PNES and 26 age- and sex-matched healthy controls were enrolled. All participants underwent DTI on a 3.0-T MRI scanner, and fractional anisotropy (FA) and mean diffusivity (MD) maps were compared by tract-based spatial statistics. Additionally, the structural networks derived from DTI data were analyzed using graph theory and two different parcellation schemes.

RESULTS

Patients with PNES showed widespread decreases in FA and increases in MD, particularly in the deep white matter. In addition, graph theoretical analysis revealed impaired brain networks in PNES, including increased path length, decreased network efficiency, altered nodal topology, and reduced regional connectivity in the right posterior areas.

CONCLUSION

We found widely impaired white matter integrity and impaired brain structural networks in Japanese patients with PNES. These findings contribute to the accumulation of evidence on PNES and may improve understanding of this condition.

Association of deposition of tau and amyloid-β proteins with structural connectivity changes in cognitively normal older adults and Alzheimer's disease spectrum patients

INTRODUCTION

Alzheimer's disease (AD) is characterized by accumulation of extracellular amyloid-β and intracellular tau neurofibrillary tangles. The recent advent of tau positron emission tomography (PET) has enabled in vivo assessment of tau pathology. The aim of this study was to explore whether tau deposition influences the structural connectivity in amyloid-negative and amyloid-positive groups, and further explore the difference between the groups.

METHODS

We investigated 18 patients with amnestic mild cognitive impairment/mild AD (AD-spectrum group) and 35 cognitively normal older adults (CN group) using diffusion MRI, amyloid, and tau PET imaging. Diffusion connectometry was performed to identify white matter pathways correlated with each of the six variables of tau deposition in the bilateral hippocampi, temporal lobes, posterior and anterior cingulate cortices, precunei, orbitofrontal lobes, and entire cerebrum.

RESULTS

The CN group showed increased connectivity along with an increased tau deposition in the bilateral hippocampi, temporal lobes, and entire cerebrum, whereas the AD-spectrum group showed decreased connectivity in the bilateral hippocampi, temporal lobes, anterior and posterior cingulate cortices, precunei, and entire cerebrum.

CONCLUSION

These findings suggest that tau deposition in the CN group seems to induce a compensatory response against early neuronal injury or chronic inflammation associated with normal aging, whereas the coexistence of amyloid and tau in the AD-spectrum group seems to outweigh the compensatory response leading to decreased connectivity, suggesting that amyloid plays a crucial role in alternating structural connectivity.

Voxel-based Specific Regional Analysis System for Alzheimer's Disease (VSRAD) on 3-tesla Normal Database: Diagnostic Accuracy in Two Independent Cohorts with Early Alzheimer's Disease

Voxel-based specific regional analysis system for Alzheimer’s disease (VSRAD) software is widely used in clinical practice in Alzheimer’s disease (AD). The existing VSRAD is based on the normal database with 1.5-tesla MRI scans (VSRAD-1.5T), and its utility for patients have undergone 3-tesla MRI is still controversial. We recruited 19 patients with early AD and 28 healthy controls who had undergone 3-tesla MRI scans at our institute (Cohort 1). We also used the 3-tesla MRI data of 30 patients with early AD and 13 healthy controls from the Japanese Alzheimer’s Disease Neuroimaging Initiative (Cohort 2). We also created a new VSRAD based on 65 normal subjects’ 3-tesla MRI scans (VSRAD-3T), and compared the detectability of AD between VSRAD-1.5T and VSRAD-3T, using receiver operating characteristic curve and area under the curve (AUC) analyses. As a result, there were no significant differences in the detectability of AD between VSRAD-3T and VSRAD-1.5T, except for the whole white matter atrophy score, which showed significantly better AUC in VSRAD-3T than in VSRAD-1.5T in both Cohort 1 (p=0.04) and 2 (p<0.01). Generally, there were better diagnostic values in Cohort 2 than in Cohort 1. The optimal cutoff values varied but were generally lower than in the previously published data. In conclusion, for patients with 3-tesla MRI, the detectability of early AD by the existing VSRAD was not different from that by the new VSRAD based on 3-tesla database. We should exercise caution when using the existing VSRAD for 3-tesla white matter analyses or for setting cutoff values.

Dissociation of Tau Deposits and Brain Atrophy in Early Alzheimer's Disease: A Combined Positron Emission Tomography/Magnetic Resonance Imaging Study

The recent advent of tau-specific positron emission tomography (PET) has enabled in vivo assessment of tau pathology in Alzheimer’s disease (AD). However, because PET scanners have limited spatial resolution, the measured signals of small brain structures or atrophied areas are underestimated by partial volume effects (PVEs). The aim of this study was to determine whether partial volume correction (PVC) improves the precision of measures of tau deposits in early AD. We investigated tau deposits in 18 patients with amyloid-positive early AD and in 36 amyloid-negative healthy controls using ¹⁸F-THK5351 PET. For PVC, we applied the SPM toolbox PETPVE12. The PET images were then spatially normalized and subjected to voxel-based group analysis using SPM12 for comparison between the early AD patients and healthy controls. We also compared these two groups in terms of brain atrophy using voxel-based morphometry of MRI. We found widespread neocortical tracer retention predominantly in the posterior cingulate and precuneus areas, but also in the inferior temporal lobes, inferior parietal lobes, frontal lobes, and occipital lobes in the AD patients compared with the controls. The pattern of tracer retention was similar between before and after PVC, suggesting that PVC had little effect on the precision of tau load measures. Gray matter atrophy was detected in the medial/lateral temporal lobes and basal frontal lobes in the AD patients. Interestingly, only a few associations were found between atrophy and tau deposits, even after PVC. In conclusion, PVC did not significantly affect ¹⁸F-THK5351 PET measures of tau deposits. This discrepancy between tau deposits and atrophy suggests that tau load precedes atrophy.

Analysis of risk factors for mild cognitive impairment based on word list memory test results and questionnaire responses in healthy Japanese individuals registered in an online database

Although the development of effective therapeutic drugs and radical treatment options for dementia and Alzheimer’s disease (AD) remains urgent, progress in recent clinical trials of AD drugs has been less than adequate. In order to advance the progress of clinical trials, it is necessary to establish more efficient methods of recruitment. In Japan, there are registration systems stratified by mild cognitive impairment and preclinical and clinical stages of early and advanced stage dementia, but there is no registration system for healthy individuals yet. Therefore, in the present study, we developed a large-scale, internet-based health registry to investigate factors associated with cognitive function among registered participants. A total of 1038 participants completed the initial questionnaire and word list memory test. Among these participants, 353 individuals completed a second questionnaire and memory test. Stepwise multiple regression analysis was performed using IBM SPSS version 23.0 for Windows at a statistical significance level of p<0.05. We found that mood, motivation, and a decreased ability to perform activities of daily living were significantly associated with cognitive function. The results of the present study suggest that maintaining social involvement is important to prevent decreases in physical activity, daily function, mood, and motivation.

Gray Matter and White Matter Abnormalities in Temporal Lobe Epilepsy Patients with and without Hippocampal Sclerosis

The presentation and distribution of gray matter (GM) and white matter (WM) abnormalities in temporal lobe epilepsy (TLE) have been widely studied. Here, we investigated the GM and WM abnormalities in TLE patients with and without hippocampal sclerosis (HS) in five groups of participants: healthy controls (HCs) (n = 28), right TLE patients with HS (n = 26), right TLE patients without HS (n = 30), left TLE patients with HS (n = 25), and left TLE patients without HS (n = 27). We performed a flexible factorial statistical test in a whole-brain voxel-based morphometry analysis to identify significant GM and WM abnormalities and analysis of variance of hippocampal and amygdala regions among the five groups using the FreeSurfer procedure. Furthermore, we conducted multiple regression analysis to assess regional GM and WM changes with disease duration. We observed significant ipsilateral mesiotemporal GM and WM volume reductions in TLE patients with HS compared with HCs. We also observed a slight GM amygdala swelling in right TLE patients without HS. The regression analysis revealed significant negative GM and WM changes with disease duration specifically in left TLE patients with HS. The observed GM and WM abnormalities may contribute to our understanding of the root of epilepsy mechanisms.

The use of diffusional kurtosis imaging and neurite orientation dispersion and density imaging of the brain in major depressive disorder

Diffusional kurtosis imaging (DKI) and neurite orientation dispersion and density imaging (NODDI) are new diffusional magnetic resonance imaging (dMRI) techniques for the characterization of neural tissues in human brain. In this study, we used these dMRI techniques to evaluate the whole-brain microstructural changes in patients with major depressive disorder (MDD). Twenty-three patients with MDD and 26 healthy subjects underwent dMRI. We compared the dMRI metrics between the 2 groups and examined the relationships between the metrics and the clinical symptoms of MDD. The MDD patients showed significant fractional anisotropy reduction in the bilateral parietal, right parieto-occipital, and right superior temporal corti, compared with the controls. Mean kurtosis values were significantly reduced in MDD patients in the right superior temporal cortex and bilateral posterior thalamic radiation. Neurite density index reductions were found in the right superior temporal cortex, bilateral insulae, right inferior frontal cortex, left parahippocampal region, left middle cerebellar peduncle, and right cerebellum. Regarding the orientation dispersion index (ODI), we detected significant decreases in the left thalamus and left occipital cortex, and significant increases in the bilateral superior longitudinal fasciculi and left posterior thalamic radiation tract. Further, there were significant positive correlations between the total Hamilton Depression Rating scale-21 scores and the ODI values in the right frontal gyri. These results suggest that the DKI and NODDI methods may provide more information about microstructural abnormalities in patients with MDD than the DTI method. It is thus expected that these techniques will be adopted as the informative methods for neuroimaging study.

MR findings in the substantia nigra on phase difference enhanced imaging in neurodegenerative parkinsonism

INTRODUCTION

In Parkinson's disease (PD) patients, magnetic resonance (MR) imaging studies using phase difference enhanced imaging (PADRE) and susceptibility-weighted imaging (SWI) showed the obscuration of the boundary between the crural fibers and substantia nigra, and the absence of dorsolateral nigral hyperintensity, respectively. PADRE images have not been evaluated in other types of neurodegenerative parkinsonism, and PADRE and SWI images have not been compared. Here we evaluated PADRE and SWI images in patients with progressive supranuclear palsy (PSP), multiple system atrophy (MSA), or PD and controls, and we compared the diagnostic values.

METHODS

PADRE and SWI-like MR images were visually assessed focusing on the substantia nigra in 39 PD patients, eight with PSP, 13 with MSA, and 34 normal controls.

RESULTS

The obscuration of the boundary between the crural fibers and substantia nigra on PADRE was observed in: the PD group, 62%; PSP, 100%; MSA, 60%, and controls, 19%. The overall collect classification for neurodegenerative parkinsonism was 74%. The absence of dorsolateral nigral hyperintensity on SWI-like images was present in: PD, 97%; PSP, 100%; MSA, 67%; and controls, 6%, resulting in the overall correct classification of 96%.

CONCLUSIONS

The MR feature on PADRE was observed not only in PD but also in other neurodegenerative parkinsonism, especially in PSP with high sensitivity. The finding in substantia nigra on SWI had greater discrimination power than that of PADRE in neurodegenerative parkinsonism, especially in PD.

Brain gray matter structural network in myotonic dystrophy type 1

This study aimed to investigate abnormalities in structural covariance network constructed from gray matter volume in myotonic dystrophy type 1 (DM1) patients by using graph theoretical analysis for further clarification of the underlying mechanisms of central nervous system involvement. Twenty-eight DM1 patients (4 childhood onset, 10 juvenile onset, 14 adult onset), excluding three cases from 31 consecutive patients who underwent magnetic resonance imaging in a certain period, and 28 age- and sex- matched healthy control subjects were included in this study. The normalized gray matter images of both groups were subjected to voxel based morphometry (VBM) and Graph Analysis Toolbox for graph theoretical analysis. VBM revealed extensive gray matter atrophy in DM1 patients, including cortical and subcortical structures. On graph theoretical analysis, there were no significant differences between DM1 and control groups in terms of the global measures of connectivity. Betweenness centrality was increased in several regions including the left fusiform gyrus, whereas it was decreased in the right striatum. The absence of significant differences between the groups in global network measurements on graph theoretical analysis is consistent with the fact that the general cognitive function is preserved in DM1 patients. In DM1 patients, increased connectivity in the left fusiform gyrus and decreased connectivity in the right striatum might be associated with impairment in face perception and theory of mind, and schizotypal-paranoid personality traits, respectively.

Marked accumulation of oligodendroglia-like cells in temporal lobe epilepsy with amygdala enlargement and hippocampal sclerosis

Although an increasing number of cases of temporal lobe epilepsy (TLE) with ipsilateral amygdala enlargement (AE) have been reported, there are few pathological reports, and no clear consensus has been established. Oligodendroglia or oligodendroglia-like cells (OLCs) have recently attracted attention in epilepsy studies. Here, we report the clinical and pathological findings of a 40-year-old male TLE patient with AE and hippocampal sclerosis, in whom histopathological study demonstrated remarkable clustering of OLCs around the uncus. The patient began to have refractory seizures at the age of 14, and preoperative MRI revealed left amygdala enlargement and left hippocampal atrophy. Other examinations were consistent with left mesial temporal epileptogenicity. He underwent surgical resection and achieved seizure freedom. Histopathological study of the amygdala showed swollen neurons with relatively large bodies and thick neurites, accompanied by vacuolar degeneration in the background. Additionally, there were marked clusters of OLCs with round nuclei and densely stained chromatin around the uncus. The OLCs were Olig2-positive. In the hippocampus, severe cell loss in CA1 and granule cell dispersion in the dentate gyrus were found. These findings may provide some insights for further pathological investigations of TLE with non-neoplastic AE.