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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 [ABSTRACT FROM AUTHOR]

Background and Objectives: Integrating large language models (LLMs) such as GPT-4 Turbo into diagnostic imaging faces a significant challenge, with current misdiagnosis rates ranging from 30–50%. This study evaluates how prompt engineering and confidence thresholds can improve diagnostic accuracy in neuroradiology. Methods: We analyze 751 neuroradiology cases from the American Journal of Neuroradiology using GPT-4 Turbo with customized prompts to improve diagnostic precision. Results: Initially, GPT-4 Turbo achieved a baseline diagnostic accuracy of 55.1%. By reformatting responses to list five diagnostic candidates and applying a 90% confidence threshold, the highest precision of the diagnosis increased to 72.9%, with the candidate list providing the correct diagnosis at 85.9%, reducing the misdiagnosis rate to 14.1%. However, this threshold reduced the number of cases that responded. Conclusions: Strategic prompt engineering and high confidence thresholds significantly reduce misdiagnoses and improve the precision of the LLM diagnostic in neuroradiology. More research is needed to optimize these approaches for broader clinical implementation, balancing accuracy and utility. [ABSTRACT FROM AUTHOR]

Rett syndrome (RTT) is a severe progressive neurodevelopmental disorder characterized by various neurological symptoms. Almost all RTT cases are caused by mutations in the X-linked methyl-CpG-binding protein 2 (MeCP2) gene, and several mouse models have been established to understand the disease. However, the neuroanatomical abnormalities in each brain region of RTT mouse models have not been fully understood. Here, we investigated the global and local neuroanatomy of the Mecp2 gene-deleted RTT model (Mecp2 -KO) mouse brain using T2-weighted 3D magnetic resonance imaging with different morphometry to clarify the brain structural abnormalities that are involved in the pathophysiology of RTT. We found a significant reduction in global and almost all local volumes in the brain of Mecp2 -KO mice. In addition, a detailed comparative analysis identified specific volume reductions in several brain regions in the Mecp2 -deficient brain. Our analysis also revealed that the Mecp2 -deficient brain shows changes in hemispheric asymmetry in several brain regions. These findings suggest that MeCP2 affects not only the whole-brain volume but also the region-specific brain structure. Our study provides a framework for neuroanatomical studies of a mouse model of RTT. [ABSTRACT FROM AUTHOR]

Differentiating corticobasal degeneration presenting with corticobasal syndrome (CBD-CBS) from progressive supranuclear palsy with Richardson's syndrome (PSP-RS), particularly in early stages, is often challenging because the neurodegenerative conditions closely overlap in terms of clinical presentation and pathology. Although volumetry using brain magnetic resonance imaging (MRI) has been studied in patients with CBS and PSP-RS, studies assessing the progression of brain atrophy are limited. Therefore, we aimed to reveal the difference in the temporal progression patterns of brain atrophy between patients with CBS and those with PSP-RS purely based on cross-sectional data using Subtype and Stage Inference (SuStaIn)—a novel, unsupervised machine learning technique that integrates clustering and disease progression modeling. We applied SuStaIn to the cross-sectional regional brain volumes of 25 patients with CBS, 39 patients with typical PSP-RS, and 50 healthy controls to estimate the two disease subtypes and trajectories of CBS and PSP-RS, which have distinct atrophy patterns. The progression model and classification accuracy of CBS and PSP-RS were compared with those of previous studies to evaluate the performance of SuStaIn. SuStaIn identified distinct temporal progression patterns of brain atrophy for CBS and PSP-RS, which were largely consistent with previous evidence, with high reproducibility (99.7%) under cross-validation. We classified these diseases with high accuracy (0.875) and sensitivity (0.680 and 1.000, respectively) based on cross-sectional structural brain MRI data; the accuracy was higher than that reported in previous studies. Moreover, SuStaIn stage correctly reflected disease severity without the label of disease stage, such as disease duration. Furthermore, SuStaIn also showed the genialized performance of differentiation and reflection for CBS and PSP-RS. Thus, SuStaIn has potential for improving our understanding of disease mechanisms, accurately stratifying patients, and providing prognoses for patients with CBS and PSP-RS. [ABSTRACT FROM AUTHOR]

White matter abnormalities may reflect cerebral microvessel disease. Diffusion tensor imaging (DTI) can help detect early changes in white matter integrity in each tract. However, studies investigating the relationship between subclinical atherosclerosis markers and white matter alterations in DTI findings are limited. This study aimed to examine associations between cardiovascular risk factors and indices of subclinical atherosclerosis—ankle brachial index (ABI), brachial-ankle pulse wave velocity (baPWV), and carotid artery intima-media thickness (IMT)—and altered white matter integrity in older patients. A total of 224 patients (aged ≥65 years) with cardiometabolic disease who underwent magnetic resonance imaging (MRI) and either plethysmography or cervical ultrasound at the start of the 3-year observational study period were included in this study. We measured fractional anisotropy (FA) and mean diffusivity (MD), which are indices of white matter integrity in seven white matter tracts. In a univariate analysis, lower ABI and higher baPWV values were associated with FA or MD abnormalities in several tracts, whereas IMT was scarcely associated with such change. In addition, high blood pressure and glycoalbumin/glycohemoglobin ratio (GA/HbA1c) and low body mass index (BMI) and triglyceride (TG) levels were associated with FA or MD abnormalities. In a multivariate analysis adjusted for age, sex, BMI, diastolic blood pressure, TG, and GA/HbA1c, the associations between ABI and FA or MD remained in all of either side of the following tracts: anterior thalamic radiation, forceps minor, inferior frontooccipital fasciculus (p < 0.001 for all) and superior longitudinal fasciculus (SLF; p < 0.05), whereas most of those between baPWV and FA or MD disappeared except for SLF (p < 0.05). These results indicate that low ABI could be an indicator of white matter abnormalities. [ABSTRACT FROM AUTHOR]

Aims/Introduction: Older adults with diabetes mellitus are susceptible to sarcopenia. Diffusion tensor imaging studies have also shown that patients with diabetes have altered white matter integrity. However, the relationship between these structural changes in white matter and sarcopenia remains poorly understood. Materials and Methods: The study included 284 older patients (aged ≥65 years) who visited the Tokyo Metropolitan Geriatric Hospital Frailty Clinic. We used diffusion tensor imaging to measure fractional anisotropy (FA) and mean diffusivity (MD) to evaluate changes in white matter integrity. We investigated the associations between sarcopenia, or its diagnostic components, and FA or MD in seven white matter tracts considered to be associated with sarcopenia according to the patients' diabetes status. Results: We found significantly low FA or high MD values in the bilateral anterior thalamic radiations (ATR) and right inferior fronto‐occipital fasciculus (IFOF) of patients with Asian Working Group for Sarcopenia 2019‐defined sarcopenia, in all patients and those with diabetes. Using binominal regression analyses, we associated low FA values in the left ATR and right IFOF with sarcopenia in all patients and those with diabetes, after adjusting for age, gender, HbA1c, blood pressure, cognitive function, physical activity, depression, nutritional status, and inflammation. Conclusions: White matter alterations in left ATR and right IFOF are associated with the prevalence of sarcopenia in patients with diabetes. Specific changes to the left ATR and right IFOF tracts could play critical roles in the occurrence of sarcopenia in patients with diabetes. [ABSTRACT FROM AUTHOR]

Aim: Gait impairment implies subtle cognitive impairment (CI) and is associated with severity of white matter hyperintensities (WMHs). However, cognitive differences in such an association are not yet fully understood. This study examined the association between WMHs and gait performance among three cognitively different older groups. Methods: Gait performance and WMHs were assessed in 150 community‐dwelling older adults, comprising 53 with CI (Mini‐Mental State Examination [MMSE] score <24), 63 with mild CI (MMSE score ≥24 and Montreal Cognitive Assessment [MoCA] score <25), and 34 who were cognitively normal or preserved (MMSE ≥24 and MoCA score ≥25). Gait velocity and variability were assessed on a 5‐m electronic walkway. Furthermore, WMH volume was derived by automated segmentation using 1.5 T magnetic resonance imaging. Results: Adjusted multiple regression analyses showed that greater WMHs were associated with slower gait velocity and greater temporal (stride time) and spatial (stride and step lengths) variabilities among older adults with CI. In contrast, WMH was only associated with spatial variability in older adults with mild CI and in cognitively normal or preserved older adults. Conclusions: Our findings suggest that gait variability measures are more sensitive to subtle underlying neurological pathologies including WMHs in older adults. The cognitive‐dependent differences found in the association between WMHs and gait performance suggests that the level of cognitive function interferes with the association between WMH and gait performance. Geriatr Gerontol Int 2021; ••: ••–••. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. © 2013 S. Karger AG, Basel [ABSTRACT FROM AUTHOR]

We report the clinical and neuroradiological imaging findings of a 26-year-old man who presented with lumbago related to high flow paraspinal osseous epidural arteriovenous fistulas in the thoracic spine. This case was of particular interest because of his exclusive epidural and paraspinal venous drainage and the presence of a prominent dilated venous pouch in the spinal canal. Angiography demonstrated multiple high flow arteriovenous fistulas with an osseous nidus. Transarterial glue embolization was performed by multistage sessions. Clinical symptoms improved dramatically. The unusual features of this case have important implications for therapeutic management. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]