Home-Based Cognitive Intervention for Healthy Older Adults Through Asking Robots Questions: Randomized Controlled Trial.

Background: Asking questions is common in conversations, and while asking questions, we need to listen carefully to what others say and consider the perspective our questions adopt. However, difficulties persist in verifying the effect of asking questions on older adults' cognitive function due to the lack of a standardized system for conducting experiments at participants' homes. Objective: This study examined the intervention effect of cognitive training moderated by robots on healthy older adults. A focus on the feasibility of the intervention at participants' homes was also maintained. Feasibility was evaluated by considering both the dropout rate during the intervention and the number of questions posed to each participant during the experiment. Methods: We conducted a randomized controlled trial with 81 adults older than 65 years. Participants were recruited through postal invitations and then randomized into 2 groups. The intervention group (n=40) received sessions where participants listened to photo-integrated stories and posed questions to the robots. The control group (n=41) received sessions where participants listened to photo-integrated stories and only thanked the robots for confirming participation. The participants participated in 12 dialogue sessions for 2-3 weeks. Scores of global cognitive functioning tests, recall tests, and verbal fluency tasks measured before and after the intervention were compared between the 2 groups. Results: There was no significant intervention effect on the Telephone Interview for Cognitive Status-Japanese scores, recall tests, and verbal fluency tasks. Additionally, our study successfully concluded with no participant dropouts at follow-up, confirming the feasibility of our approach. Conclusions: There was no statistically significant evidence indicating intervention benefits for cognitive functioning. Although the feasibility of home-based interventions was demonstrated, we identified areas for improvement in the future, such as setting up more efficient session themes. Further research is required to identify the effectiveness of an improved cognitive intervention involving the act of asking questions.

Mild Cognitive Impairment Detection with Machine Learning and Topological Data Analysis Applied to EEG Time-series in Facial Emotion Oddball Paradigm.

We report a novel approach to dementia neurobiomarker development from EEG time series using topological data analysis (TDA) methodology and machine learning (ML) tools in the 'AI for social good' application domain, with possible following application to home-based point of care diagnostics and cognitive intervention monitoring. We propose a new approach to a digital dementia neurobiomarker for early-onset mild cognitive impairment (MCI) prognosis. We report the best median accuracies in a range of upper 85% linear discriminant analysis (LDA), as well above 90% for linear SVM and deep fully connected neural network classifier models in leave-one-out-subject cross-validation, which presents very encouraging results in a binary healthy cognitive aging versus MCI stages using TDA features applied to brainwave time series patterns captured from a four-channel EEG wearable.Clinical relevance- The reported study offers an objective dementia early onset neurobiomarker prospect to replace traditional subjective paper and pencil tests with an application of EEG-wearable-based and topological data analysis machine learning tools in a possibly successive home-based point-of-care environment.

Metagenomic analysis of ecological niche overlap and community collapse in microbiome dynamics.

Species utilizing the same resources often fail to coexist for extended periods of time. Such competitive exclusion mechanisms potentially underly microbiome dynamics, causing breakdowns of communities composed of species with similar genetic backgrounds of resource utilization. Although genes responsible for competitive exclusion among a small number of species have been investigated in pioneering studies, it remains a major challenge to integrate genomics and ecology for understanding stable coexistence in species-rich communities. Here, we examine whether community-scale analyses of functional gene redundancy can provide a useful platform for interpreting and predicting collapse of bacterial communities. Through 110-day time-series of experimental microbiome dynamics, we analyzed the metagenome-assembled genomes of co-occurring bacterial species. We then inferred ecological niche space based on the multivariate analysis of the genome compositions. The analysis allowed us to evaluate potential shifts in the level of niche overlap between species through time. We hypothesized that community-scale pressure of competitive exclusion could be evaluated by quantifying overlap of genetically determined resource-use profiles (metabolic pathway profiles) among coexisting species. We found that the degree of community compositional changes observed in the experimental microbiome was correlated with the magnitude of gene-repertoire overlaps among bacterial species, although the causation between the two variables deserves future extensive research. The metagenome-based analysis of genetic potential for competitive exclusion will help us forecast major events in microbiome dynamics such as sudden community collapse (i.e., dysbiosis).

Machine learning approach for early onset dementia neurobiomarker using EEG network topology features.

Introduction: Modern neurotechnology research employing state-of-the-art machine learning algorithms within the so-called "AI for social good" domain contributes to improving the well-being of individuals with a disability. Using digital health technologies, home-based self-diagnostics, or cognitive decline managing approaches with neuro-biomarker feedback may be helpful for older adults to remain independent and improve their wellbeing. We report research results on early-onset dementia neuro-biomarkers to scrutinize cognitive-behavioral intervention management and digital non-pharmacological therapies. Methods: We present an empirical task in the EEG-based passive brain-computer interface application framework to assess working memory decline for forecasting a mild cognitive impairment. The EEG responses are analyzed in a framework of a network neuroscience technique applied to EEG time series for evaluation and to confirm the initial hypothesis of possible ML application modeling mild cognitive impairment prediction. Results: We report findings from a pilot study group in Poland for a cognitive decline prediction. We utilize two emotional working memory tasks by analyzing EEG responses to facial emotions reproduced in short videos. A reminiscent interior image oddball task is also employed to validate the proposed methodology further. Discussion: The proposed three experimental tasks in the current pilot study showcase the critical utilization of artificial intelligence for early-onset dementia prognosis in older adults.

Facilitative interaction networks in experimental microbial community dynamics.

Facilitative interactions between microbial species are ubiquitous in various types of ecosystems on the Earth. Therefore, inferring how entangled webs of interspecific interactions shift through time in microbial ecosystems is an essential step for understanding ecological processes driving microbiome dynamics. By compiling shotgun metagenomic sequencing data of an experimental microbial community, we examined how the architectural features of facilitative interaction networks could change through time. A metabolic modeling approach for estimating dependence between microbial genomes (species) allowed us to infer the network structure of potential facilitative interactions at 13 time points through the 110-day monitoring of experimental microbiomes. We then found that positive feedback loops, which were theoretically predicted to promote cascade breakdown of ecological communities, existed within the inferred networks of metabolic interactions prior to the drastic community-compositional shift observed in the microbiome time-series. We further applied "directed-graph" analyses to pinpoint potential keystone species located at the "upper stream" positions of such feedback loops. These analyses on facilitative interactions will help us understand key mechanisms causing catastrophic shifts in microbial community structure.

Alternative stable states, nonlinear behavior, and predictability of microbiome dynamics.

BACKGROUND: Microbiome dynamics are both crucial indicators and potential drivers of human health, agricultural output, and industrial bio-applications. However, predicting microbiome dynamics is notoriously difficult because communities often show abrupt structural changes, such as "dysbiosis" in human microbiomes. METHODS: We integrated theoretical frameworks and empirical analyses with the aim of anticipating drastic shifts of microbial communities. We monitored 48 experimental microbiomes for 110 days and observed that various community-level events, including collapse and gradual compositional changes, occurred according to a defined set of environmental conditions. We analyzed the time-series data based on statistical physics and non-linear mechanics to describe the characteristics of the microbiome dynamics and to examine the predictability of major shifts in microbial community structure. RESULTS: We confirmed that the abrupt community changes observed through the time-series could be described as shifts between "alternative stable states" or dynamics around complex attractors. Furthermore, collapses of microbiome structure were successfully anticipated by means of the diagnostic threshold defined with the "energy landscape" analysis of statistical physics or that of a stability index of nonlinear mechanics. CONCLUSIONS: The results indicate that abrupt microbiome events in complex microbial communities can be forecasted by extending classic ecological concepts to the scale of species-rich microbial systems. Video Abstract.

Three-Dimensional Amide Proton Transfer-Weighted Imaging for Differentiating between Glioblastoma, IDH-Wildtype and Primary Central Nervous System Lymphoma.

Distinguishing primary central nervous system lymphoma (PCNSL) from glioblastoma, isocitrate dehydrogenase (IDH)-wildtype is sometimes hard. Because the role of operation on them varies, accurate preoperative diagnosis is crucial. In this study, we evaluated whether a specific kind of chemical exchange saturation transfer imaging, i.e., amide proton transfer-weighted (APTw) imaging, was useful to distinguish PCNSL from glioblastoma, IDH-wildtype. A total of 14 PCNSL and 27 glioblastoma, IDH-wildtype cases were evaluated. There was no significant difference in the mean APTw signal values between the two groups. However, the percentile values from the 1st percentile to the 20th percentile APTw signals and the width1-100 APTw signals significantly differed. The highest area under the curve was 0.796, which was obtained from the width1-100 APTw signal values. The sensitivity and specificity values were 64.3% and 88.9%, respectively. APTw imaging was useful to distinguish PCNSL from glioblastoma, IDH-wildtype. To avoid unnecessary aggressive surgical resection, APTw imaging is recommended for cases in which PCNSL is one of the differential diagnoses.

Administration of spermidine attenuates concanavalin A-induced liver injury.

A previous study revealed that treatment with the anticoagulant heparin attenuated concanavalin A (ConA)-induced liver injury. The administration of spermidine (SPD) increased urokinase-type plasminogen activator (uPA) levels in the serum. uPA is clinically used for the treatment of some thrombotic diseases such as cerebral infarction. Therefore, SPD may attenuate ConA-induced liver injury that is exacerbated by blood coagulation. The present study investigated the effect of SPD on liver injury in mice with autoimmune hepatopathy induced by ConA. A model of liver injury was created by intravenous injection of ConA into mice. SPD was administered in free drinking water and was biochemically and pathologically examined over time. The administration of SPD to ConA-treated mice significantly reduced liver injury. However, SPD treatment upregulated the mRNA expression of TNF-α and IFN-ϒ in the livers of ConA-treated mice. In contrast, the mRNA expression of tissue factor in the livers of SPD-treated mice was decreased after ConA injection. The frequency of lymphocytes and lymphocyte activation were not affected by SPD administration in ConA-treated mice. SPD treatment increased uPA levels in the serum and decreased the level of D-dimer in ConA-treated mice. Moreover, SPD decreased fibrin in the livers of ConA-treated mice. These results indicated that SPD treatment increased anticoagulant ability by increasing of uPA and attenuated ConA-induced liver injury.

Word-producing brain: Contribution of the left anterior middle temporal gyrus to word production patterns in spoken language.

Vocabulary is based on semantic knowledge. The anterior temporal lobe (ATL) has been considered an essential region for processing semantic knowledge; nonetheless, the association between word production patterns and the structural and functional characteristics of the ATL remains unclear. To examine this, we analyzed over one million words from group conversations among community-dwelling older adults and their multimodal magnetic resonance imaging data. A quantitative index for the word production patterns, namely the exponent ß of Heaps' law, positively correlated with the left anterior middle temporal gyrus volume. Moreover, ß negatively correlated with its resting-state functional connectivity with the precuneus. There was no significant correlation with the diffusion tensor imaging metrics in any fiber. These findings suggest that the vocabulary richness in spoken language depends on the brain status characterized by the semantic knowledge-related brain structure and its activation dissimilarity with the precuneus, a core region of the default mode network.

Discordance of microsatellite instability and mismatch repair immunochemistry occurs depending on the cancer type.

Microsatellite instability (MSI) and deficiency of mismatch repair (dMMR) are key markers for predicting the response of immune checkpoint inhibitors (ICIs) and screening for Lynch syndrome (LS). This study examined the incidences of and factors associated with the concordance of MSI and MMR in human cancers. A total of 518 formalin-fixed cancer tissues were analyzed for MSI and MMR immunohistochemistry (IHC). MSI was analyzed by a PCR-based method using Promega markers. Concordance with MMR expression and factors associated with concordance were analyzed. In 2 colorectal cancer samples, MMR IHC failed due to inadequate staining conditions. In the remaining 516 cancers, a high level of MSI (MSI-H) was identified in 113 cases, and dMMR was identified in 112. The concordance of MSI and MMR IHC was 98.3%. Only 9 cases (4 pancreatobiliary, 3 colorectal, and 2 endometrial cancers) were discordant. Of the 113 MSI-H cases, 4 (3.5%) were proficient MMR (pMMR); of the 403 microsatellite stability (MSS) cases, 5 (1.2%) were dMMR. The independent factors associated with MSI-H/dMMR included meeting Amsterdam II criteria, assay purpose, and sampling method. Multivariate analysis revealed that cancer type (gastrointestinal cancers or others) was associated with concordance of MSI and MMR IHC. Three LS cases with pancreatic or endometrial cancer demonstrated MSS and dMMR, and one biliary cancer showed MSI-H and pMMR. Discordance between MSI and MMR IHC occasionally occurs in pancreaticobiliary and endometrial cancers. When suspected, both MSI and MMR IHC should be done to judge the ICI indication and screen for LS.

Testicular teratomagenesis from primordial germ cells with overexpression of germinal center-associated nuclear protein.

Testicular teratomas are the major histologic type of testicular germ cell tumors and their incidence continues to grow. Moreover, teratomas can develop from undifferentiated cells in induced pluripotent stem (iPS) cell transplantation therapy, seriously hampering the progress of regenerative medicine. Germinal center-associated nuclear protein (GANP) is thought to be important to the biogenetic control of primordial germ cells and is among the genes susceptible to testicular germ cell tumors. Thus, we analyzed the expression of GANP in human testicular postpubertal-type teratomas and established a novel mouse model to reveal the association between GANP and teratomagenesis. We analyzed 31 cases of human testicular postpubertal-type teratomas and, in all cases, GANP was overexpressed. The aberrant expression was also detected in germ cell neoplasia in situ accompanied by the teratoma. GANP expression was particularly high in the epithelia of the epidermis, cutaneous appendages, and trachea-like ciliated epithelium. To further clarify the association between GANP and teratomagenesis, we established a novel teratomagenesis mouse model (CAG-ganpTg mice). In the GANP-teratoma mice, GANP-overexpressing teratomas were more frequent at the testes and the middle portion of the uterus than has been seen in the previously established mouse models. In conclusion, GANP is overexpressed in testicular postpubertal-type teratomas and is an essential teratomagenic factor. We also found that CAG-ganpTg mice are useful mouse models of teratomagenesis that mimics human midline teratomas and that teratomas may originate from the overexpression of GANP in primordial germ cells.

Dementia Digital Neuro-biomarker Study from Theta-band EEG Fluctuation Analysis in Facial and Emotional Identification Short-term Memory Oddball Paradigm.

An efficient machine learning (ML) implementation in the so-called 'AI for social good' domain shall contribute to dementia digital neuro-biomarker development for early-onset prognosis of a possible cognitive decline. We report encouraging initial developments of wearable EEG-derived theta-band fluctuations examination and a successive classification embracing a time-series complexity examination with a multifractal detrended fluctuation analysis (MFDFA) in the face or emotion video-clip identification short-term oddball memory tasks. We also report findings from a thirty-five elderly volunteer pilot study that EEG responses to instructed to ignore (inhibited) oddball paradigm stimulation results in more informative MFDFA features, leading to better machine learning classification results. The reported pilot project showcases vital social assistance of artificial intelligence (AI) application for an early-onset dementia prognosis. Clinical Relevance- This introduces a candidate for an objective digital neuro-biomarker from theta-band EEG recorded by a wearable for a plausible replacement of biased 'paper & pencil' tests for a mild cognitive impairment (MCI) evaluation.

Morphologic Analysis of M2 Macrophage in Glioblastoma: Involvement of Macrophage Extracellular Traps (METs).

Macrophages are classified into two phenotypes, M1 and M2, based on their roles. M2 macrophages suppress inflammation and increase in proportion to the malignancy of brain tumors. Recently, macrophage extracellular traps (METs), which change into a network, have been reported as a unique form of macrophage cell death. In this study, immunohistochemical analysis of macrophages in METs in human glioblastoma was performed. To distinguish between M1 and M2 macrophages, multiple immunostainings with Iba1 combined with CD163 or CD204 were performed. M2 macrophages were present in small amounts in normal and borderline areas but showed an increasing trend as they shifted to tumor areas, and most of them were the activated- or phagocytic-type. We also successfully detected METs coexisting with fibrin and lactoferrin near the border between the tumor and necrotic area. M2 macrophages not only suppressed inflammation but also were involved in the formation of METs. This study found that M2 macrophages play various roles in unstable situations.

Hydrocephalus in Neurofibromatosis Type 1 Caused by a Cyst Formation Similar to Late-Onset Aqueductal Membranous Occlusion: A Case Report and Review of Literature.

Cyst formation in the third ventricle and the histopathological findings were rarely reported. We report a similar case of late-onset aqueductal membranous occlusion (LAMO) caused by a thin gliotic cyst and a review of related literature. A 28-year-old woman with enlarged lateral ventricles was referred to our hospital with complaints of headache and dizziness. In our hospital, the obvious cause of the hydrocephalus was unknown on any examination and we decided performing endoscopic third ventriculostomy for hydrocephalus. A thin cyst covering the entrance of the aqueduct was identified and we perforated it. Histopathological finding of the cyst wall was gliosis and our case was similar to LAMO, although not typical. The postoperative symptoms and ventricle size improved for 4 years. When suspecting cases similar to definition of LAMO, neuroendoscopic surgery would be the first-choice treatment and might detect causes undetectable on preoperative imaging such as our thin membrane.

Intracranial phosphaturic mesenchymal tumors. A case report and review of literature.

Most osteomalacia-inducing tumors (OITs) are phosphaturic mesenchymal tumors (PMTs) that secrete fibroblast growth factor 23 (FGF23). These tumors usually occur in the bone and soft tissues, and intracranial OITs are rare. Therefore, intracranial OIT is difficult to diagnose and treat. This paper presents a case of intracranial OIT and shows a review of previous cases. A 45-year-old man underwent nasal cavity biopsy and treatment with active vitamin D3 and neutral phosphate for hypophosphatemia. Amplification of FGF23 mRNA level within the tumor was detected. Subsequently, the surgical specimen was diagnosed with a PMT and was considered the cause of the patient's osteomalacia. The patient was referred to a neurosurgery department for the excision of the intracranial tumor extending to the nasal cavity. After tumor removal, the serum levels of FGF23 and phosphorus were normalized as compared to preoperative those. The patient remains disease-free, without additional treatment, approximately 10 years after surgery, with no tumor recurrence. As per the literature, intracranial OITs usually occur in patients aged 8-69 years. Bone and muscle pain are major complaints. Approximately 60% of the patients reported previously had symptoms because of intracranial tumors. In some cases, it took several years to diagnose OIT after the onset of the osteomalacia symptoms. Laboratory data in such cases show hypophosphatemia and elevated FGF23 levels. Because FGF23 levels are associated with the severity of osteomalacia symptoms, total tumor resection is recommended. PMT and hemangiopericytoma (HPC) are histologically similar, but on immunochemistry, PMT is negative for signal transducer and activator of transcription 6 (STAT6), whereas HPC is positive. FGF23 amplification is seen in PMTs but not in HPCs. Therefore, the analysis of FGF23 and STAT6 was helpful in distinguishing PMTs from HPCs. In cases of hypophosphatemia and osteomalacia without a history of metabolic, renal, or malabsorptive diseases, the possibility of oncogenic osteomalacia should be considered.

The Dark Side of Social Media: Content Effects on the Relationship Between Materialism and Consumption Behaviors.

This study contributes to the emerging literature on the negative effects over consumption that social media users may develop as a consequence of being engaged on social media platforms. The authors tested materialism's direct and indirect impacts on compulsive, conspicuous, and impulsive buying, adding two novel mediators: attitudes toward social media content (SCM) and social media intensity (SMI). The study uses a convenience sample of 400 Thai social media users analyzed using structural equation modeling. The results confirmed the well-established positive relationships between materialism and each of the three-negative consumption behaviors also in the social media domain. A novel finding showed the important role played by SMI which was found to be a strong predictor of each of the three negative consumption behaviors and it was also found to significantly mediate the relationship between materialism and the three-negative consumption behaviors. An additional contribution of the study was found on the role of attitudes which, contrary to what is commonly believed, were often not significant in predicting any negative behavior.

Crucial importance of length of fatty-acyl chains bound to the sn-2 position of phosphatidylglycerol for growth and photosynthesis of Synechocystis sp. PCC 6803.

Phosphatidylglycerol (PG) in thylakoid membrane is essential for growth and photosynthesis of photosynthetic organisms. Although the sn-2 position of PG in thylakoid membrane is exclusively esterified with C16 fatty acids, the functional importance of the C16 fatty-acyl chains at the sn-2 position has not been clarified. In this study, we chemically synthesized non-metabolizable PG molecules: we introduced linoleic acid (18:2, fatty acid containing 18 carbons with 2 double bonds) and one of the saturated fatty acids with different chain length (12:0, 14:0, 16:0, 18:0 and 20:0) by ether linkage to the sn-1 and sn-2 positions, respectively. With the synthesized ether-linked PG molecules, we checked whether they could complement the growth and photosynthesis of pgsA mutant cells of Synechocystis sp. PCC 6803 to understand the importance of length of fatty chains at the sn-2 position of PG. The pgsA mutant is incapable of synthesizing PG, so it requires exogenous PG added to medium for growth. The growth rate and photosynthetic activity of mutant cells depended on the length of fatty chains: the PG molecular species binding 16:0 most effectively complemented the growth and photosynthesis of mutant cells, and other PG molecular species with fatty chains shorter or longer than 16:0 were less effective; especially, those binding 12:0 inhibited the growth and photosynthetic activity of the mutant cells. These data demonstrate that length of fatty chains bound to the sn-2 position of PG is critical for PG performance in growth and photosynthesis.

Chemical-Mediated Microbial Interactions Can Reduce the Effectiveness of Time-Series-Based Inference of Ecological Interaction Networks.

Network-based assessments are important for disentangling complex microbial and microbial-host interactions and can provide the basis for microbial engineering. There is a growing recognition that chemical-mediated interactions are important for the coexistence of microbial species. However, so far, the methods used to infer microbial interactions have been validated with models assuming direct species-species interactions, such as generalized Lotka-Volterra models. Therefore, it is unclear how effective existing approaches are in detecting chemical-mediated interactions. In this paper, we used time series of simulated microbial dynamics to benchmark five major/state-of-the-art methods. We found that only two methods (CCM and LIMITS) were capable of detecting interactions. While LIMITS performed better than CCM, it was less robust to the presence of chemical-mediated interactions, and the presence of trophic competition was essential for the interactions to be detectable. We show that the existence of chemical-mediated interactions among microbial species poses a new challenge to overcome for the development of a network-based understanding of microbiomes and their interactions with hosts and the environment.

Histology of Cardiac Sarcoidosis with Novel Considerations Arranged upon a Pathologic Basis.

Sarcoidosis is a rare disease of isolated or diffuse granulomatous inflammation. Although any organs can be affected by sarcoidosis, cardiac sarcoidosis is a fatal disorder, and it is crucial to accurately diagnose it to prevent sudden death due to dysrhythmia. Although endomyocardial biopsy is invasive and has limited sensitivity for identifying granulomas, it is the only modality that yields a definitive diagnosis of cardiac sarcoidosis. It is imperative to develop novel pathological approaches for the precise diagnosis of cardiac sarcoidosis. Here, we aimed to discuss commonly used diagnostic criteria for cardiac sarcoidosis and to summarize useful and novel histopathologic criteria of cardiac sarcoidosis. While classical histologic observations including noncaseating granulomas and multinucleated giant cells (typically Langhans type) are the most important findings, others such as microgranulomas, CD68+ CD163- pro-inflammatory (M1) macrophage accumulation, CD4/CD8 T-cell ratio, Cutibacterium acnes components, lymphangiogenesis, confluent fibrosis, and fatty infiltration may help to improve the sensitivity of endomyocardial biopsy for detecting cardiac sarcoidosis. These novel histologic findings are based on the pathology of cardiac sarcoidosis. We also discussed the principal histologic differential diagnoses of cardiac sarcoidosis, such as tuberculosis myocarditis, fungal myocarditis, giant cell myocarditis, and dilated cardiomyopathy.

Contrast-Enhanced Magnetic Resonance Imaging, Perfusion Magnetic Resonance Imaging, and 1H-Magnetic Resonance Spectroscopy Distinguish Primary Central Nervous System Vasculitis from Glioblastoma.

BACKGROUND: We investigated the ability of magnetic resonance imaging (MRI) to distinguish primary central nervous system vasculitis (PCNSV) from glioblastoma to facilitate the development of an appropriate treatment for PCNSV. METHODS: We enrolled patients who were treated for PCNSV or glioblastoma at our center between January 2007 and August 2018. We compared the diagnoses of the 2 conditions by retrospectively reviewing patients' data for contrast-enhanced MRI, perfusion MRI, flow-sensitive black-blood (FSBB) imaging, and 1H-magnetic resonance spectroscopy (MRS). RESULTS: We evaluated 108 patients (6 PCNSV; 102 glioblastoma). We found a statistically significant correlation between diagnosis and the contrast pattern on MRI. Perivascular enhancement was observed in all cases of PCNSV as follows: ring-like, homogeneous, and irregular patterns were observed in 53 (60%), 18 (20%), and 17 (19%) cases of glioblastoma, respectively. We identified a statistically significant correlation between diagnosis and cerebral blood volume (CBV) in 3 patients with PCNSV who underwent perfusion MRI; and all had low CBVs. Among the 55 patients with glioblastoma who underwent perfusion MRI, low and high CBVs were detected in 3 and 52 patients, respectively. There was no significant correlation between diagnosis and FSBB findings. Evaluation of 1H-MRS data showed statistically significant differences between PCNSV and glioblastoma as functions of neuronal amino acid levels on long echo time MRS, with a slightly different amino acid profile, including glutamine + glutamate on short echo time MRS. CONCLUSIONS: Contrast-enhanced MRI, perfusion MRI, and quantitative analysis of 1H-MRS are valuable techniques for distinguishing PCNSV from glioblastoma before surgery.