Deep Learning-Driven Transformation: A Novel Approach for Mitigating Batch Effects in Diffusion MRI Beyond Traditional Harmonization.

BACKGROUND: "Batch effect" in MR images, due to vendor-specific features, MR machine generations, and imaging parameters, challenges image quality and hinders deep learning (DL) model generalizability. PURPOSE: We aim to develop a DL model using contrast adjustment and super-resolution to reduce diffusion-weighted images (DWIs) diversity across magnetic field strengths and imaging parameters. STUDY TYPE: Retrospective. SUBJECTS: The DL model was built using an open dataset from one individual. The MR machine identification model was trained and validated on a dataset of 1134 adults (54% females, 46% males), with 1050 subjects showing no DWI abnormalities and 84 with conditions like stroke and tumors. The 21,000 images were divided into 80% for training, 20% for validation, and 3500 for testing. FIELD STRENGTH/SEQUENCE: Seven MR scanners from four manufacturers with 1.5 T and 3 T magnetic field strengths. DWIs were acquired using spin-echo sequences and high-resolution T2WIs using the T2-SPACE sequence. ASSESSMENT: An experienced, board-certified radiologist evaluated the effectiveness of restoring high-resolution T2WI and harmonizing diverse DWI with metrics such as PSNR and SSIM, and the texture and frequency attributes were further analyzed using gray-level co-occurrence matrix and 1-dimensional power spectral density. The model's impact on machine-specific characteristics was gauged through the performance metrics of a ResNet-50 model. Comprehensive statistical tests were employed for statistical robustness, including McNemar's test and the Dice index. RESULTS: Our DL protocol reduced DWI contrast and resolution variation. ResNet-50 model's accuracy decreased from 0.9443 to 0.5786, precision from 0.9442 to 0.6494, recall from 0.9443 to 0.5786, and F1 score from 0.9438 to 0.5587. The t-SNE visualization indicated more consistent image features across multiple MR devices. Autoencoder halved learning iterations; Dice coefficient >0.74 confirmed signal reproducibility in 84 lesions. CONCLUSION: This study presents a DL strategy to mitigate batch effects in diffusion MR images, improving their quality and generalizability. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 1.

Corrigendum to "Predictors of Recovery from Traumatic Brain Injury-Induced Prolonged Consciousness Disorder".

[This corrects the article DOI: 10.1155/2017/9358092.].

Altered functional connectivity of the default mode network by glucose loading in young, healthy participants.

BACKGROUND: The functional connectivity of the default mode network (DMN) decreases in patients with Alzheimer's disease (AD) as well as in patients with type 2 diabetes mellitus (T2DM). Altered functional connectivity of the DMN is associated with cognitive impairment. T2DM is a known cause of cognitive dysfunction and dementia in the elderly, and studies have established that T2DM is a risk factor for AD. In addition, recent studies with positron emission tomography demonstrated that increased plasma glucose levels decrease neuronal activity, especially in the precuneus/posterior cingulate cortex (PC/PCC), which is the functional core of the DMN. These findings prompt the question of how increased plasma glucose levels decrease neuronal activity in the PC/PCC. Given the association among DMN, AD, and T2DM, we hypothesized that increased plasma glucose levels decrease the DMN functional connectivity, thus possibly reducing PC/PCC neuronal activity. We conducted this study to test this hypothesis. RESULTS: Twelve young, healthy participants without T2DM and insulin resistance were enrolled in this study. Each participant underwent resting-state functional magnetic resonance imaging in both fasting and glucose loading conditions to evaluate the DMN functional connectivity. The results showed that the DMN functional connectivity in the PC/PCC was significantly lower in the glucose loading condition than in the fasting condition (P = 0.014). CONCLUSIONS: Together with previous findings, the present results suggest that decreased functional connectivity of the DMN is possibly responsible for reduced PC/PCC neuronal activity in healthy individuals with increased plasma glucose levels.

Prevalence of frailty, cognitive impairment, and sarcopenia in outpatients with cardiometabolic disease in a frailty clinic.

BACKGROUND: Although frailty and cognitive impairment are critical risk factors for disability and mortality in the general population of older inhabitants, the prevalence and incidence of these factors in individuals treated in the specialty outpatient clinics are unknown. METHODS: We recently established a frailty clinic for comprehensive assessments of conditions such as frailty, sarcopenia, and cognition, and planned 3-year prospective observational study to identify the risk factors for progression of these aging-related statuses. To date, we recruited 323 patients who revealed symptoms suggestive of frailty mainly from a specialty outpatient clinic of cardiology and diabetes. Frailty status was diagnosed by the modified Cardiovascular Health Study (mCHS) criteria and some other scales. Cognitive function was assessed by Mini-Mental State Examination (MMSE), Japanese version of the Montreal Cognitive Assessment (MoCA-J), and some other modalities. Sarcopenia was defined by the criteria of the Asian Working Group for Sarcopenia (AWGS). In this report, we outlined our frailty clinic and analyzed the background characteristics of the subjects. RESULTS: Most patients reported hypertension (78%), diabetes mellitus (57%), or dyslipidemia (63%), and cardiovascular disease and probable heart failure also had a higher prevalence. The prevalence of frailty diagnosed according to the mCHS criteria, cognitive impairment defined by MMSE (≤27) and MoCA-J (≤25), and of AWGS-defined sarcopenia were 24, 41, and 84, and 31%, respectively. The prevalence of frailty and cognitive impairment increased with aging, whereas the increase in sarcopenia prevalence plateaued after the age of 80 years. No significant differences were observed in the prevalence of frailty, cognitive impairment, and sarcopenia between the groups with and without diabetes mellitus, hypertension, or dyslipidemia with a few exceptions, presumably due to the high-risk subjects who had multiple cardiovascular comorbidities. A majority of the frail and sarcopenic patients revealed cognitive impairment, whereas the frequency of suspected dementia among these patients were both approximately 20%. CONCLUSIONS: We found a high prevalence of frailty, cognitive impairment, and sarcopenia in patients with cardiometabolic disease in our frailty clinic. Comprehensive assessment of the high-risk patients could be useful to identify the risk factors for progression of frailty and cognitive decline.

Gray Matter Abnormalities in Idiopathic Parkinson's Disease: Evaluation by Diffusional Kurtosis Imaging and Neurite Orientation Dispersion and Density Imaging.

Mapping gray matter (GM) pathology in Parkinson's disease (PD) with conventional MRI is challenging, and the need for more sensitive brain imaging techniques is essential to facilitate early diagnosis and assessment of disease severity. GM microstructure was assessed with GM-based spatial statistics applied to diffusion kurtosis imaging (DKI) and neurite orientation dispersion imaging (NODDI) in 30 participants with PD and 28 age- and gender-matched controls. These were compared with currently used assessment methods such as diffusion tensor imaging (DTI), voxel-based morphometry (VBM), and surface-based cortical thickness analysis. Linear discriminant analysis (LDA) was also used to test whether subject diagnosis could be predicted based on a linear combination of regional diffusion metrics. Significant differences in GM microstructure were observed in the striatum and the frontal, temporal, limbic, and paralimbic areas in PD patients using DKI and NODDI. Significant correlations between motor deficits and GM microstructure were also noted in these areas. Traditional VBM and surface-based cortical thickness analyses failed to detect any GM differences. LDA indicated that mean kurtosis (MK) and intra cellular volume fraction (ICVF) were the most accurate predictors of diagnostic status. In conclusion, DKI and NODDI can detect cerebral GM abnormalities in PD in a more sensitive manner when compared with conventional methods. Hence, these methods may be useful for the diagnosis of PD and assessment of motor deficits. Hum Brain Mapp 38:3704-3722, 2017. © 2017 Wiley Periodicals, Inc.

Dinosaur Tail Sign: A Useful Spinal MRI Finding Indicative of Cerebrospinal Fluid Leakage.

OBJECTIVE: To evaluate the imaging characteristics and diagnostic utility of the "Dinosaur tail sign" in the diagnosis of cerebrospinal fluid (CSF) leakage. BACKGROUND: The authors propose the "Dinosaur tail sign," defined as a combination of the dorsal epidural hyperintensities, fat tissue, spinal cord, and cauda equine on lumbosacral sagittal fat-suppressed T2-weighted image (FST2WI), as a sensitive indicator for diagnosing CSF leakage. METHODS: Imaging characteristics of the "Dinosaur tail sign" was evaluated in seven spontaneous intracranial hypotension (SIH) and 23 iatrogenic CSF leakage (ICSFL) patients. Additionally, the diagnostic index was compared between the "Dinosaur tail sign" and other previously reported useful magnetic resonance imaging (MRI) and magnetic resonance myelography (MRM) findings. RESULTS: In contrast to other imaging findings including the epidural expansion, floating dural sac sign, and distension of the spinal epidural veins on MRI, and paraspinal fluid collections (PFC) on MRM, the "Dinosaur tail sign" was found equally in both SIH and ICSFL patients (6 SIH and 19 ICSFL; 83% of all patients with CSF leakage). The "Dinosaur tail sign" showed sufficient diagnostic utility (sensitivity 83%, specificity 94%, accuracy 89%) that was comparable to that of PFC. CONCLUSION: The "Dinosaur tail sign" is a useful imaging finding suggestive of CSF leakage. Evaluation of subtle interspinous arched hyperintensities on spinal MRI is mandatory for the diagnosis of SIH and ICSFL.

Beyond the midbrain atrophy: wide spectrum of structural MRI finding in cases of pathologically proven progressive supranuclear palsy.

PURPOSE: Recently, it has been recognized that pathologically proven progressive supranuclear palsy (PSP) cases are classified into various clinical subtypes with non-uniform symptoms and imaging findings. This article reviews essential imaging findings, general information, and advanced magnetic resonance imaging (MRI) techniques for PSP and presents these MRI findings of pathologically proven typical and atypical PSP cases for educational purposes. METHODS: With the review of literatures, notably including atypical pathologically proven PSP cases, MRI and clinical information of 15 pathologically proven typical and atypical PSP cases were retrospectively evaluated. RESULTS: In addition to typical symptoms, PSP patients can exhibit atypical symptoms including levodopa-responsive parkinsonism, pure akinesia, non-fluent aphasia, corticobasal syndrome, and predominant cerebellar ataxia. As well as clinical symptoms, the degree of midbrain atrophy, a well-known imaging hallmark, is not consistent in atypical PSP cases. This fact has important implications for the limitation of midbrain atrophy as a diagnostic imaging biomarker of PSP pathology. Additional evaluation of other imaging findings including various regional atrophies of the globus pallidus, frontal lobe, cerebral peduncle, and superior cerebellar peduncle is essential for the diagnosis of atypical PSP cases. CONCLUSION: It is necessary for radiologists to recognize the wide clinical and radiological spectra of typical and atypical PSP cases.

Adverse effects of metallic artifacts on voxel-wise analysis and tract-based spatial statistics in diffusion tensor imaging.

Background Diffusion tensor imaging (DTI) is a magnetic resonance imaging (MRI) technique that reflects the Brownian motion of water molecules constrained within brain tissue. Fractional anisotropy (FA) is one of the most commonly measured DTI parameters, and can be applied to quantitative analysis of white matter as tract-based spatial statistics (TBSS) and voxel-wise analysis. Purpose To show an association between metallic implants and the results of statistical analysis (voxel-wise group comparison and TBSS) for fractional anisotropy (FA) mapping, in DTI of healthy adults. Material and Methods Sixteen healthy volunteers were scanned with 3-Tesla MRI. A magnetic keeper type of dental implant was used as the metallic implant. DTI was acquired three times in each participant: (i) without a magnetic keeper (FAnon1); (ii) with a magnetic keeper (FAimp); and (iii) without a magnetic keeper (FAnon2) as reproducibility of FAnon1. Group comparisons with paired t-test were performed as FAnon1 vs. FAnon2, and as FAnon1 vs. FAimp. Results Regions of significantly reduced and increased local FA values were revealed by voxel-wise group comparison analysis (a P value of less than 0.05, corrected with family-wise error), but not by TBSS. Conclusion Metallic implants existing outside the field of view produce artifacts that affect the statistical analysis (voxel-wise group comparisons) for FA mapping. When statistical analysis for FA mapping is conducted by researchers, it is important to pay attention to any dental implants present in the mouths of the participants.

Predictors of Recovery from Traumatic Brain Injury-Induced Prolonged Consciousness Disorder.

We investigated the clinical predictors of the degree of recovery in patients with prolonged disorders of consciousness (PDC) caused by traumatic brain injury. Fourteen patients with PDC underwent two diffusion tensor imaging (DTI) studies; the first and second scans were performed at 345.6 ± 192.6 and 689.1 ± 272.2 days after the injury, respectively. In addition to the temporal changes in each of these diffusion parameters, fractional anisotropy (FA), mean diffusivity, axial diffusivity (AD), and radial diffusivity were assessed over a 1-year period. Relationship of clinical and DTI parameters with recovery from PDC (RPDC) was evaluated using Spearman's rank-correlation and stepwise multiple linear regression analysis. The mean FA and number of voxels with FA values > 0.4 (VsFA0.4) were significantly decreased at the second scan. A significant positive correlation was observed between the degree of RPDC and mean FA (r = 0.60) and VsFA0.4 (r = 0.68) as well as between the difference in VsFA0.4 (r = 0.63) and AD (r = 0.54) between the first and second scans. On multiple linear regression analysis, initial severity of PDC and the difference in AD remained significantly associated with the degree of RPDC. The microstructural white matter changes observed in this study indicate their potential relation with the degree of RPDC over the longer term.

Longitudinal study examining abnormal white matter integrity using a tract-specific analysis in individuals with a high risk for psychosis.

AIM: Although volume reductions in the grey matter have been previously observed in individuals with an at-risk mental state (ARMS) for psychosis, the features of white matter integrity and their correlation with psychiatric symptoms remain unclear. METHODS: Forty-six ARMS subjects were examined using magnetic resonance imaging (MRI) to acquire diffusion tensor imaging (DTI); the subjects were also evaluated using the Scale of Prodromal Symptoms at baseline and at 52 weeks. Sixteen healthy controls also underwent MRI scanning. The DTI results were longitudinally analyzed using a tract-specific analysis to measure the fractional anisotropy (FA) values of the entire corpus callosum (CC), as well as its genu, trunk, and splenium. RESULTS: During the 52-week study period, seven patients developed psychosis (ARMS-P) and 39 did not (ARMS-NP). In the entire CC and the genu, trunk, and splenium of the CC, the FA values of the ARMS subjects were each significantly smaller than the respective values of the healthy controls at baseline. In the genu and trunk, the baseline FA values in the ARMS-NP group were, paradoxically, smaller than those of the ARMS-P group at baseline. Regarding the association between the FA values and psychiatric symptoms, a reduction in the FA value in the genu was significantly correlated with a deterioration of negative symptoms among the ARMS subjects. CONCLUSION: Abnormal white matter integrity in the CC may predict the long-term outcome of patients with prodromal psychosis, since negative symptoms are associated with poor functioning.

Neurite orientation dispersion and density imaging in the substantia nigra in idiopathic Parkinson disease.

OBJECTIVES: We used neurite orientation dispersion and density imaging (NODDI) to quantify changes in the substantia nigra pars compacta (SNpc) and striatum in Parkinson disease (PD). METHODS: Diffusion-weighted magnetic resonance images were acquired from 58 PD patients and 36 age- and sex-matched controls. The intracellular volume fraction (Vic), orientation dispersion index (OD), and isotropic volume fraction (Viso) of the basal ganglia were compared between groups. Multivariate logistic regression analysis determined which diffusion parameters were independent predictors of PD. Receiver operating characteristic (ROC) analysis compared the diagnostic accuracies of the evaluated indices. Pearson coefficient analysis correlated each diffusional parameter with disease severity. RESULTS: Vic in the contralateral SNpc and putamen were significantly lower in PD patients than in healthy controls (P < 0.00058). Vic and OD in the SNpc and putamen showed significant negative correlations (P < 0.05) with disease severity. Multivariate logistic analysis revealed that Vic (P = 0.0000046) and mean diffusivity (P = 0.019) in the contralateral SNpc were the independent predictors of PD. In the ROC analysis, Vic in the contralateral SNpc showed the best diagnostic performance (mean cutoff, 0.62; sensitivity, 0.88; specificity, 0.83). CONCLUSION: NODDI is likely to be useful for diagnosing PD and assessing its progression. KEY POINTS: • Neurite orientation dispersion and density imaging (NODDI) is a new diffusion MRI technique • NODDI estimates neurite microstructure more specifically than diffusion tensor imaging • By using NODDI, nigrostriatal alterations in PD can be evaluated in vivo • NOODI is useful for diagnosing PD and assessing its disease progression.

A preliminary diffusional kurtosis imaging study of Parkinson disease: comparison with conventional diffusion tensor imaging.

INTRODUCTION: Diffusional kurtosis imaging (DKI) is a more sensitive technique than conventional diffusion tensor imaging (DTI) for assessing tissue microstructure. In particular, it quantifies the microstructural integrity of white matter, even in the presence of crossing fibers. The aim of this preliminary study was to compare how DKI and DTI show white matter alterations in Parkinson disease (PD). METHODS: DKI scans were obtained with a 3-T magnetic resonance imager from 12 patients with PD and 10 healthy controls matched by age and sex. Tract-based spatial statistics were used to compare the mean kurtosis (MK), mean diffusivity (MD), and fractional anisotropy (FA) maps of the PD patient group and the control group. In addition, a region-of-interest analysis was performed for the area of the posterior corona radiata and superior longitudinal fasciculus (SLF) fiber crossing. RESULTS: FA values in the frontal white matter were significantly lower in PD patients than in healthy controls. Reductions in MK occurred more extensively throughout the brain: in addition to frontal white matter, MK was lower in the parietal, occipital, and right temporal white matter. The MK value of the area of the posterior corona radiata and SLF fiber crossing was also lower in the PD group. CONCLUSION: DKI detects changes in the cerebral white matter of PD patients more sensitively than conventional DTI. In addition, DKI is useful for evaluating crossing fibers. By providing a sensitive index of brain pathology in PD, DKI may enable improved monitoring of disease progression.

Prognostic value of post-treatment (18)F-FDG PET/CT for advanced head and neck cancer after combined intra-arterial chemotherapy and radiotherapy.

OBJECTIVE: To clarify the prognostic value of post-treatment (18)F-fluorodeoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT) in patients with advanced head and neck squamous cell carcinoma (HNSCC) after combined intra-arterial chemotherapy and radiotherapy (IACR). METHODS: Thirty-six patients with HNSCC who underwent IACR were recruited. The period from the end of IACR to the last post-treatment (18)F-FDG PET/CT examination was 8-12 weeks. Both patient-based and lesion-based analyses were used to evaluate the PET/CT images. For lesion-based analysis, 36 regions (12 lesions of recurrences and 24 scars at primary sites) were selected. The Kaplan-Meier method was used to assess the overall survival (OS) stratified by (18)F-FDG uptake or visual interpretation results. RESULTS: Twelve patients with recurrence were identified by six months after IACR. The sensitivity and specificity in the patient-based analysis were 67% (8/12) and 88% (21/24), respectively. The mean OS was estimated to be 12.1 months (95% CI, 6.3-18.0 months) for the higher maximum standardized uptake value (SUVmax) group (n=7) and 44.6 months (95% CI, 39.9-49.3 months) for the lower SUVmax group (n=29). OS in the higher SUVmax group (cut-off point, 6.1) or positive visual interpretation group was significantly shorter than that in the lower SUVmax or negative visual interpretation group (P<0.001 and P<0.05, respectively). CONCLUSIONS: The SUVmax and visual interpretation of HNSCC on post-IACR (18)F-FDG PET/CT can provide prognostic survival estimates.

Lipocalin-type prostaglandin D synthase: a glymphopathy marker in idiopathic hydrocephalus.

Idiopathic normal pressure hydrocephalus in elderly people is considered a form of glymphopathy caused by malfunction of the waste clearance pathway, called the glymphatic system. Tau is a representative waste material similar to amyloid-ß. During neurodegeneration, lipocalin-type prostaglandin D synthase (L-PGDS), a major cerebrospinal fluid (CSF) protein, is reported to act as a chaperone that prevents the neurotoxic aggregation of amyloid-ß. L-PGDS is also a CSF biomarker in idiopathic normal pressure hydrocephalus and significantly correlates with tau concentration, age, and age-related brain white matter changes detected by magnetic resonance imaging. To investigate this glymphopathy, we aimed to analyze white matter changes and contributing factors in vivo and their interactions ex vivo. Cerebrospinal tap tests were performed in 60 patients referred for symptomatic ventriculomegaly. Patients were evaluated using an idiopathic normal pressure hydrocephalus grading scale, mini-mental state examination, frontal assessment battery, and timed up-and-go test. The typical morphological features of high convexity tightness and ventriculomegaly were measured using the callosal angle and Evans index, and parenchymal white matter properties were evaluated with diffusion tensor imaging followed by tract-based spatial statistics. Levels of CSF biomarkers, including tau, amyloid-ß, and L-PGDS, were determined by ELISA, and their interaction, and localization were determined using immunoprecipitation and immunohistochemical analyses. Tract-based spatial statistics for fractional anisotropy revealed clusters that positively correlated with mini-mental state examination, frontal assessment battery, and callosal angle, and clusters that negatively correlated with age, disease duration, idiopathic normal pressure hydrocephalus grading scale, Evans index, and L-PGDS. Other parameters also indicated clusters that correlated with symptoms, microstructural white matter changes, and L-PGDS. Tau co-precipitated with L-PGDS, and colocalization was confirmed in postmortem specimens of neurodegenerative disease obtained from the human Brain Bank. Our study supports the diagnostic value of L-PGDS as a surrogate marker for white matter integrity in idiopathic normal pressure hydrocephalus. These results increase our understanding of the molecular players in the glymphatic system. Moreover, this study indicates the potential utility of enhancing endogenous protective factors to maintain brain homeostasis.

Relationship between cognitive impairment and white-matter alteration in Parkinson's disease with dementia: tract-based spatial statistics and tract-specific analysis.

OBJECTIVES: We investigated the relationship between white-matter alteration and cognitive status in Parkinson's disease (PD) with and without dementia by using diffusion tensor imaging. METHODS: Twenty PD patients, 20 PDD (Parkinson's disease with dementia) patients and 20 age-matched healthy controls underwent diffusion tensor imaging. The mean diffusivity and fractional anisotropy (FA) map of each patient group were compared with those of the control group by using tract-based spatial statistics. Tractography images of the genu of the corpus callosum fibre tracts were generated, and mean diffusivity and FA were measured. RESULTS: FA values in many major tracts were significantly lower in PDD patients than in control subjects; in the prefrontal white matter and the genu of the corpus callosum they were significantly lower in PDD patients than in PD patients. There was a significant correlation between the Mini-Mental State Examination (MMSE) scores and the FA values of the prefrontal white matter and the genu of the corpus callosum in patients with PD. CONCLUSIONS: Our study shows a relationship between cognitive impairment and alteration of the prefrontal white matter and genu of the corpus callosum. These changes may be useful in assessing the onset of dementia in PD patients. KEY POINTS: • Dementia is a common and important non-motor sign of Parkinson's disease (PD). • The neuropathological basis of dementia in PD is not clear. • DTI shows abnormalities in the prefrontal white matter in PD with dementia. • Prefrontal white matter alteration may be useful biomarker of dementia in PD.

Anterior cingulate abnormality as a neural correlate of mismatch negativity in schizophrenia.

BACKGROUND: Limbic circuitry, especially the anterior cingulate gyrus, has been implicated in the pathophysiology and cognitive changes of schizophrenia. Previous diffusion tensor imaging studies have demonstrated that the integrity of the anterior cingulum (AC) is abnormal in schizophrenia. However, the relationship between the abnormal AC tract integrity and the pathophysiology of schizophrenia has not been fully studied. METHODS: We performed a voxelwise group comparison of white matter fractional anisotropy (FA) by using tract-based spatial statistics in 9 patients with schizophrenia and 9 matched controls. We then measured FA specifically in the AC by using a tract-specific measurement. The latency and amplitude of the mismatch negativity (MMN) were also evaluated in all subjects. RESULTS: In patients with schizophrenia, tract-based spatial statistics showed a reduction in FA in broad white matter areas, including the bilateral AC, compared with controls. Tract-specific measurements confirmed the specific reduction of FA in the region of the bilateral AC. The decreased FA in the AC was correlated with prolonged MMN latency in the patient group. CONCLUSION: Our study of AC structure and electrophysiological changes in schizophrenia suggest that the disruption of limbic-cortical structural networks may be part of the neural basis underlying the changes in MMN in schizophrenia.

Review of Performance Improvement of a Noninvasive Brain-computer Interface in Communication and Motor Control for Clinical Applications.

Brain-computer interfaces (BCI) enable direct communication between the brain and a computer or other external devices. They can extend a person's degree of freedom by either strengthening or substituting the human peripheral working capacity. Moreover, their potential clinical applications in medical fields include rehabilitation, affective computing, communication, and control. Over the last decade, noninvasive BCI systems such as electroencephalogram (EEG) have progressed from simple statistical models to deep learning models, with performance improvement over time and enhanced computational power. However, numerous challenges pertaining to the clinical use of BCI systems remain, e.g., the lack of sufficient data to learn more possible features for robust and reliable classification. However, compared with fields such as computer vision and speech recognition, the training samples in the medical BCI field are limited as they target patients who face difficulty generating EEG data compared with healthy control. Because deep learning models incorporate several parameters, they require considerably more data than other conventional methods. Thus, deep learning models have not been thoroughly leveraged in medical BCI. This study summarizes the state-of-the-art progress of the BCI system over the last decade, highlighting critical challenges and solutions.

Glymphatic system impairment in corticobasal syndrome: diffusion tensor image analysis along the perivascular space (DTI-ALPS).

PURPOSE: This study aimed to evaluate the along the perivascular space (ALPS) index based on the diffusion tensor image ALPS (DTI-ALPS) in corticobasal degeneration with corticobasal syndrome (CBD-CBS) and investigate its correlation with motor and cognitive functions. MATERIALS AND METHODS: The data of 21 patients with CBD-CBS and 17 healthy controls (HCs) were obtained from the 4-Repeat Tauopathy Neuroimaging Initiative and the Frontotemporal Lobar Degeneration Neuroimaging Initiative databases. Diffusion magnetic resonance imaging was performed using a 3-Tesla MRI scanner. The ALPS index based on DTI-ALPS was automatically calculated after preprocessing. The ALPS index was compared between the CBD-CBS and HC groups via a general linear model analysis, with covariates such as age, sex, years of education, and intracranial volume (ICV). Furthermore, to confirm the relation between the ALPS index and the motor and cognitive score in CBD-CBS, the partial Spearman's rank correlation coefficient was calculated with covariates such as age, sex, years of education, and ICV. A p value of < 0.05 was considered as statistically significant in all statistical analyses. RESULTS: The ALPS index of CBD-CBS was significantly lower than that of HC (Cohen's d = - 1.53, p < 0.005). Moreover, the ALPS index had a significant positive correlation with the mini mental state evaluation score (rs = 0.65, p < 0.005) and a significant negative correlation with the unified Parkinson's Disease Rating Scale III score (rs = - 0.75, p < 0.001). CONCLUSION: The ALPS index of patients with CBD-CBS, which is significantly lower than that of HCs, is significantly associated with motor and cognitive functions.

Reproducibility of automated calculation technique for diffusion tensor image analysis along the perivascular space.

PURPOSE: The method of diffusion tensor image analysis along the perivascular space (DTI-ALPS) was gathering attention to evaluate the brain's glymphatic function or interstitial fluid dynamics. However, to the best knowledge, no study was conducted on the reproducibility of these automated methods for ALPS index values. Therefore, the current study evaluated the ALPS index reproducibility based on DTI-ALPS using two major automated calculation techniques in scan and rescan of the same subject on the same day. MATERIALS AND METHODS: This study included 23 participants, including 2 with Alzheimer's disease, 15 with mild cognitive impairment, and 6 with cognitive normals. Scan and rescan data of diffusion magnetic resonance images were obtained, as well as automatically index for ALPS (ALPS index) and ALPS index maintaining tensor vector orientation information (vALPS index) with region of interest on the template fractional anisotropy map calculated by FSL software.These ALPS indices were compared in terms of scan and rescan reproducibility. RESULTS: The absolute difference in ALPS-index values between scan and rescan was larger in the ALPS index than in the vALPS index by approximately 0.6% as the relative difference. Cohen's d for the left and right ALPS indices between methods were 0.121 and 0.159, respectively. CONCLUSION: The vALPS index based on DTI-ALPS maintaining tensor vector orientation information has higher reproducibility than the ALPS index. This result encourages a multisite study on the ALPS index with a large sample size and helps detect a subtle pathological change in the ALPS index.

Traveling Subject-Informed Harmonization Increases Reliability of Brain Diffusion Tensor and Neurite Mapping.

Diffusion-weighted magnetic resonance imaging (dMRI) of brain has helped elucidate the microstructural changes of psychiatric and neurodegenerative disorders. Inconsistency between MRI models has hampered clinical application of dMRI-based metrics. Using harmonized dMRI data of 300 scans from 69 traveling subjects (TS) scanning the same individuals at multiple conditions with 13 MRI models and 2 protocols, the widely-used metrics such as diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) were evaluated before and after harmonization with a combined association test (ComBat) or TS-based general linear model (TS-GLM). Results showed that both ComBat and TS-GLM significantly reduced the effects of the MRI site, model, and protocol for diffusion metrics while maintaining the intersubject biological effects. The harmonization power of TS-GLM based on TS data model is more powerful than that of ComBat. In conclusion, our research demonstrated that although ComBat and TS-GLM harmonization approaches were effective at reducing the scanner effects of the site, model, and protocol for DTI and NODDI metrics in WM, they exhibited high retainability of biological effects. Therefore, we suggest that, after harmonizing DTI and NODDI metrics, a multisite study with large cohorts can accurately detect small pathological changes by retaining pathological effects.