What Is Medical Extended Reality? A Taxonomy Defining the Current Breadth and Depth of an Evolving Field.

Medical extended reality (MXR) has emerged as a dynamic field at the intersection of health care and immersive technology, encompassing virtual, augmented, and mixed reality applications across a wide range of medical disciplines. Despite its rapid growth and recognition by regulatory bodies, the field lacks a standardized taxonomy to categorize its diverse research and applications. This American Medical Extended Reality Association guideline, authored by the editorial board of the Journal of Medical Extended Reality, introduces a comprehensive taxonomy for MXR, developed through a multidisciplinary and international collaboration of experts. The guideline seeks to standardize terminology, categorize existing work, and provide a structured framework for future research and development in MXR. An international and multidisciplinary panel of experts was convened, selected based on publication track record, contributions to MXR, and other objective measures. Through an iterative process, the panel identified primary and secondary topics in MXR. These topics were refined over several rounds of review, leading to the final taxonomy. The taxonomy comprises 13 primary topics that jointly expand into 180 secondary topics, demonstrating the field's breadth and depth. At the core of the taxonomy are five overarching domains: (1) technological integration and innovation; (2) design, development, and deployment; (3) clinical and therapeutic applications; (4) education, training, and communication; and (5) ethical, regulatory, and socioeconomic considerations. The developed taxonomy offers a framework for categorizing the diverse research and applications within MXR. It may serve as a foundational tool for researchers, clinicians, funders, academic publishers, and regulators, facilitating clearer communication and categorization in this rapidly evolving field. As MXR continues to grow, this taxonomy will be instrumental in guiding its development and ensuring a cohesive understanding of its multifaceted nature.

Clinical Evaluation of a 2-Minute Ultrafast Brain MR Protocol for Evaluation of Acute Pathology in the Emergency and Inpatient Settings.

BACKGROUND AND PURPOSE: The use of MR imaging in emergency settings has been limited by availability, long scan times, and sensitivity to motion. This study assessed the diagnostic performance of an ultrafast brain MR imaging protocol for evaluation of acute intracranial pathology in the emergency department and inpatient settings. MATERIALS AND METHODS: Sixty-six adult patients who underwent brain MR imaging in the emergency department and inpatient settings were included in the study. All patients underwent both the reference and the ultrafast brain MR protocols. Both brain MR imaging protocols consisted of T1-weighted, T2/T2*-weighted, FLAIR, and DWI sequences. The ultrafast MR images were reconstructed by using a machine-learning assisted framework. All images were reviewed by 2 blinded neuroradiologists. RESULTS: The average acquisition time was 2.1 minutes for the ultrafast brain MR protocol and 10 minutes for the reference brain MR protocol. There was 98.5% agreement on the main clinical diagnosis between the 2 protocols. In head-to-head comparison, the reference protocol was preferred in terms of image noise and geometric distortion (P < .05 for both). The ultrafast ms-EPI protocol was preferred over the reference protocol in terms of reduced motion artifacts (P < .01). Overall diagnostic quality was not significantly different between the 2 protocols (P > .05). CONCLUSIONS: The ultrafast brain MR imaging protocol provides high accuracy for evaluating acute pathology while only requiring a fraction of the scan time. Although there was greater image noise and geometric distortion on the ultrafast brain MR protocol images, there was significant reduction in motion artifacts with similar overall diagnostic quality between the 2 protocols.

Phase 2 study using low dose cytarabine for adult patients with newly diagnosed Langerhans cell histiocytosis.

Langerhans cell histiocytosis (LCH) lacks a standardized first-line therapy. This single-center, phase 2 prospective study (NCT04121819) enrolled 61 newly diagnosed adult LCH patients with multisystem or multifocal single system disease from October 2019 to June 2022. Subcutaneous cytarabine (100 mg/m2 for 5 days) was administered in 35-day cycles for 12 total cycles. The primary endpoint was event-free survival (EFS). The median age was 33 years (range 18-66). Twelve patients (19.7%) had liver involvement, of which 2 also had spleen involvement. Among 43 patients undergoing next-generation sequencing, BRAF alterations (44.2%) were most frequent, followed by TP53 (16.3%), MAP2K1 (14.0%) and IDH2 (11.6%). MAPK pathway alterations occurred in 28 patients (65.1%). The overall response rate was 93.4%, with 20 (32.7%) achieving complete response and 37 (60.7%) partial response. After a median 30 months follow-up, 21 (34.4%) relapsed without deaths. Estimated 3-year OS and EFS were 100.0% and 58.5%, respectively. Multivariate analysis identified ≥3 involved organs (P = 0.007; HR 3.937, 95% CI: 1.456-9.804) and baseline lung involvement (P = 0.028; HR 2.976, 95% CI: 1.126-7.874) as poor prognostic factors for EFS. The most common grade 3-4 toxicities were neutropenia (27.9%), thrombocytopenia (1.6%), and nausea (1.6%). In conclusion, cytarabine monotherapy is an effective and safe regimen for newly diagnosed adults, while baseline lung or ≥3 involved organs confers poor prognosis.

Diagnostic evaluation of deep learning accelerated lumbar spine MRI.

BACKGROUND AND PURPOSE: Deep learning (DL) accelerated MR techniques have emerged as a promising approach to accelerate routine MR exams. While prior studies explored DL acceleration for specific lumbar MRI sequences, a gap remains in comprehending the impact of a fully DL-based MRI protocol on scan time and diagnostic quality for routine lumbar spine MRI. To address this, we assessed the image quality and diagnostic performance of a DL-accelerated lumbar spine MRI protocol in comparison to a conventional protocol. METHODS: We prospectively evaluated 36 consecutive outpatients undergoing non-contrast enhanced lumbar spine MRIs. Both protocols included sagittal T1, T2, STIR, and axial T2-weighted images. Two blinded neuroradiologists independently reviewed images for foraminal stenosis, spinal canal stenosis, nerve root compression, and facet arthropathy. Grading comparison employed the Wilcoxon signed rank test. For the head-to-head comparison, a 5-point Likert scale to assess image quality, considering artifacts, signal-to-noise ratio (SNR), anatomical structure visualization, and overall diagnostic quality. We applied a 15% noninferiority margin to determine whether the DL-accelerated protocol was noninferior. RESULTS: No significant differences existed between protocols when evaluating foraminal and spinal canal stenosis, nerve compression, or facet arthropathy (all p > .05). The DL-spine protocol was noninferior for overall diagnostic quality and visualization of the cord, CSF, intervertebral disc, and nerve roots. However, it exhibited reduced SNR and increased artifact perception. Interobserver reproducibility ranged from moderate to substantial (κ = 0.50-0.76). CONCLUSION: Our study indicates that DL reconstruction in spine imaging effectively reduces acquisition times while maintaining comparable diagnostic quality to conventional MRI.

Telehealth and Virtual Reality Technologies in Chronic Pain Management: A Narrative Review.

PURPOSE OF REVIEW: This review provides medical practitioners with an overview of the present and emergent roles of telehealth and associated virtual reality (VR) applications in chronic pain (CP) management, particularly in the post-COVID-19 healthcare landscape. RECENT FINDINGS: Accumulated evidence points to the efficacy of now well-established telehealth modalities, such as videoconferencing, short messaging service (SMS), and mobile health (mHealth) applications in complementing remote CP care. More recently, and although still in early phases of clinical implementation, a wide range of VR-based interventions have demonstrated potential for improving the asynchronous remote management of CP. Additionally, VR-associated technologies at the leading edge of science and engineering, such as VR-assisted biofeedback, haptic technology, high-definition three-dimensional (HD3D) conferencing, VR-enabled interactions in a Metaverse, and the use of wearable monitoring devices, herald a new era for remote, synchronous patient-physician interactions. These advancements hold the potential to facilitate remote physical examinations, personalized remote care, and innovative interventions such as ultra-realistic biofeedback. Despite the promise of VR-associated technologies, several limitations remain, including the paucity of robust long-term effectiveness data, heterogeneity of reported pain-related outcomes, challenges with scalability and insurance coverage, and demographic-specific barriers to patient acceptability. Future research efforts should be directed toward mitigating these limitations to facilitate the integration of telehealth-associated VR into the conventional management of CP. Despite ongoing barriers to widespread adoption, recent evidence suggests that VR-based interventions hold an increasing potential to complement and enhance the remote delivery of CP care.

Virtual reading room for diagnostic radiology.

RATIONALE AND OBJECTIVE: To assess the perceptions of radiology staff regarding the role of virtual reality technology in diagnostic radiology after using a virtual reality (VR) headset METHODS: Participants completed a pre-study questionnaire assessing their familiarity with VR technology and its potential role in radiology. Using a VR headset, participants entered a simulated reading room (SieVRt, Luxsonic Technologies) with three large virtual monitors. They were able to view plain radiographs, ultrasound, CT, and MRI images and pull up and compare multiple images simultaneously. They then completed a post-study questionnaire to re-assess their perception about the role of VR technology for diagnostic radiology. RESULTS: Fifteen participants were enrolled, with 33.3 % attendings, 40 % fellows, and 26.7 % residents. Pre-study, 60 % reported they were "not familiar" with VR technology and 66.7 % had never used it. On a 1 to 5 scale, the median perceived likelihood of VR having a role in radiology significantly increased from 3 (IQR 2-3) pre-study to 4 (IQR 4-4) post-study; p = 0.014. Image contrast and resolution were adequate according to most participants, with 53.3 % strongly agreeing and 33.3 % agreeing. The headset was comfortable for 73.3 % and did not induce nausea in any participant. Confidence in VR technology improved after using the headset for 80 %. According to 80 %, future VR technology could replace a PACS workstation. DISCUSSION: Radiologists' perception regarding the role of virtual reality in diagnostic interpretation improves after a hands-on trial of the technology, and VR has the potential to replace a traditional workstation in certain situations.

An imaging review of the hippocampus and its common pathologies.

The hippocampus is a complex structure located in the mesial temporal lobe that plays a critical role in cognitive and memory-related processes. The hippocampal formation consists of the dentate gyrus, hippocampus proper, and subiculum, and its importance in the neural circuitry makes it a key anatomic structure to evaluate in neuroimaging studies. Advancements in imaging techniques now allow detailed assessment of hippocampus internal architecture and signal features that has improved identification and characterization of hippocampal abnormalities. This review aims to summarize the neuroimaging features of the hippocampus and its common pathologies. It provides an overview of the hippocampal anatomy on magnetic resonance imaging and discusses how various imaging techniques can be used to assess the hippocampus. The review explores neuroimaging findings related to hippocampal variants (incomplete hippocampal inversion, sulcal remnant and choroidal fissure cysts), and pathologies of neoplastic (astrocytoma and glioma, ganglioglioma, dysembryoplastic neuroepithelial tumor, multinodular and vacuolating neuronal tumor, and metastasis), epileptic (mesial temporal sclerosis and focal cortical dysplasia), neurodegenerative (Alzheimer's disease, progressive primary aphasia, and frontotemporal dementia), infectious (Herpes simplex virus and limbic encephalitis), vascular (ischemic stroke, arteriovenous malformation, and cerebral cavernous malformations), and toxic-metabolic (transient global amnesia and opioid-associated amnestic syndrome) etiologies.

Clinical features, genomic profiling, and outcomes of adult patients with unifocal Langerhans cell histiocytosis.

BACKGROUND: Langerhans cell histiocytosis (LCH) is a rare highly heterogeneous histiocytosis, which can be divided into single system and multiple system disease according to site of involvement. There is a paucity of studies examining unifocal LCH in adults in the molecular era. RESULTS: We retrospectively analysed records from 70 patients with unifocal LCH. The median age at diagnosis was 36 years (18-69). The most common organ involved was the bone (70.0%), followed by pituitary gland (7.1%). Target gene sequencing of lesion tissues was performed on 32 of the 70 patients. MAPK/PI3K pathway alterations were observed in 78.1% of the patients; the most common mutations included BRAFV600E (28.1%), MAP2K1 (18.8%) and PIK3CA (9.4%). After a median follow-up time of 39.4 months (0.7-211.8), 10 (14.3%) patients developed disease progression, of whom 4 had local recurrence, 2 progressed to single-system multifocal and 4 progressed to multiple system LCH. The 3-year progression-free survival (PFS) was 81.9%. Univariate analysis showed that age < 30 years at diagnosis was associated with worse 3-year PFS (52.2% vs. 97.0%, p = 0.005). The 3-year overall survival was 100%. CONCLUSIONS: In our large cohort of adults with unifocal LCH, we found that prognosis of unifocal LCH in adults was very good, and age < 30 years at diagnosis was associated with increased relapse risk.

Cancer stem cell-derived CHI3L1 activates the MAF/CTLA4 signaling pathway to promote immune escape in triple-negative breast cancer.

BACKGROUND: Triple-negative breast cancer (TNBC) development may be associated with tumor immune escape. This study explores whether the CHI3L1/MAF/CTLA4/S100A4 axis affects immune escape in TNBC through interplay with triple-negative breast cancer stem cells (TN-BCSCs). OBJECTIVE: The aim of this study is to utilize single-cell transcriptome sequencing (scRNA-seq) to uncover the molecular mechanisms by which the CHI3L1/MAF/CTLA4 signaling pathway may mediate immune evasion in triple-negative breast cancer through the interaction between tumor stem cells (CSCs) and immune cells. METHODS: Cell subsets in TNBC tissues were obtained through scRNA-seq, followed by screening differentially expressed genes in TN-BCSCs and B.C.s (CD44+ and CD24-) and predicting the transcription factor regulated by CHI3L1. Effect of CHI3L1 on the stemness phenotype of TNBC cells investigated. Effects of BCSCs-231-derived CHI3L1 on CTLA4 expression in T cells were explored after co-culture of BCSCs-231 cells obtained from microsphere culture of TN-BCSCs with T cells. BCSCs-231-treated T cells were co-cultured with CD8+ T cells to explore the resultant effect on T cell cytotoxicity. An orthotopic B.C. transplanted tumor model in mice with humanized immune systems was constructed, in which the Role of CHI3L1/MAF/CTLA4 in the immune escape of TNBC was explored. RESULTS: Eight cell subsets were found in the TNBC tissues, and the existence of TN-BCSCs was observed in the epithelial cell subset. CHI3L1 was related to the stemness phenotype of TNBC cells. TN-BCSC-derived CHI3L1 increased CTLA4 expression in T cells through MAF, inhibiting CD8+ T cell cytotoxicity and inducing immunosuppression. Furthermore, the CTLA4+ T cells might secrete S100A4 to promote the stemness phenotype of TNBC cells. CONCLUSIONS: TN-BCSC-derived CHI3L1 upregulates CTLA4 expression in T cells through MAF, suppressing the function of CD8+ T cells, which promotes the immune escape of TNBC.

Comprehensive insights into the genetic background of Chinese populations using Y chromosome markers.

China is located in East Asia. With a high genetic and cultural diversity, human migration in China has always been a hot topic of genetics research. To explore the origins and migration routes of Chinese males, 3333 Chinese individuals (Han, Hui, Mongolia, Yi and Kyrgyz) with 27 Y-STRs and 143 Y-SNPs from published literature were analysed. Our data showed that there are five dominant haplogroups (O2-M122, O1-F265, C-M130, N-M231, R-M207) in China. Combining analysis of haplogroup frequencies, geographical positions and time with the most recent common ancestor (TMRCA), we found that haplogroups C-M130, N-M231 and R1-M173 and O1a-M175 probably migrated into China via the northern route. Interestingly, we found that haplogroup C*-M130 in China may originate in South Asia, whereas the major subbranches C2a-L1373 and C2b-F1067 migrated from northern China. The results of BATWING showed that the common ancestry of Y haplogroup in China can be traced back to 17 000 years ago, which was concurrent with global temperature increases after the Last Glacial Maximum.

Optimized flow compensation for contrast-enhanced T1-weighted Wave-CAIPI 3D MPRAGE imaging of the brain.

Flow-related artifacts have been observed in highly accelerated T1-weighted contrast-enhanced wave-controlled aliasing in parallel imaging (CAIPI) magnetization-prepared rapid gradient-echo (MPRAGE) imaging and can lead to diagnostic uncertainty. We developed an optimized flow-mitigated Wave-CAIPI MPRAGE acquisition protocol to reduce these artifacts through testing in a custom-built flow phantom. In the phantom experiment, maximal flow artifact reduction was achieved with the combination of flow compensation gradients and radial reordered k-space acquisition and was included in the optimized sequence. Clinical evaluation of the optimized MPRAGE sequence was performed in 64 adult patients, who all underwent contrast-enhanced Wave-CAIPI MPRAGE imaging without flow-compensation and with optimized flow-compensation parameters. All images were evaluated for the presence of flow-related artifacts, signal-to-noise ratio (SNR), gray-white matter contrast, enhancing lesion contrast, and image sharpness on a 3-point Likert scale. In the 64 cases, the optimized flow mitigation protocol reduced flow-related artifacts in 89% and 94% of the cases for raters 1 and 2, respectively. SNR, gray-white matter contrast, enhancing lesion contrast, and image sharpness were rated as equivalent for standard and flow-mitigated Wave-CAIPI MPRAGE in all subjects. The optimized flow mitigation protocol successfully reduced the presence of flow-related artifacts in the majority of cases.Relevance statementAs accelerated MRI using novel encoding schemes become increasingly adopted in clinical practice, our work highlights the need to recognize and develop strategies to minimize the presence of unexpected artifacts and reduction in image quality as potential compromises to achieving short scan times.Key points• Flow-mitigation technique led to an 89-94% decrease in flow-related artifacts.• Image quality, signal-to-noise ratio, enhancing lesion conspicuity, and image sharpness were preserved with the flow mitigation technique.• Flow mitigation reduced diagnostic uncertainty in cases where flow-related artifacts mimicked enhancing lesions.

Transformer versus traditional natural language processing: how much data is enough for automated radiology report classification?

OBJECTIVES: Current state-of-the-art natural language processing (NLP) techniques use transformer deep-learning architectures, which depend on large training datasets. We hypothesized that traditional NLP techniques may outperform transformers for smaller radiology report datasets. METHODS: We compared the performance of BioBERT, a deep-learning-based transformer model pre-trained on biomedical text, and three traditional machine-learning models (gradient boosted tree, random forest, and logistic regression) on seven classification tasks given free-text radiology reports. Tasks included detection of appendicitis, diverticulitis, bowel obstruction, and enteritis/colitis on abdomen/pelvis CT reports, ischemic infarct on brain CT/MRI reports, and medial and lateral meniscus tears on knee MRI reports (7,204 total annotated reports). The performance of NLP models on held-out test sets was compared after training using the full training set, and 2.5%, 10%, 25%, 50%, and 75% random subsets of the training data. RESULTS: In all tested classification tasks, BioBERT performed poorly at smaller training sample sizes compared to non-deep-learning NLP models. Specifically, BioBERT required training on approximately 1,000 reports to perform similarly or better than non-deep-learning models. At around 1,250 to 1,500 training samples, the testing performance for all models began to plateau, where additional training data yielded minimal performance gain. CONCLUSIONS: With larger sample sizes, transformer NLP models achieved superior performance in radiology report binary classification tasks. However, with smaller sizes (<1000) and more imbalanced training data, traditional NLP techniques performed better. ADVANCES IN KNOWLEDGE: Our benchmarks can help guide clinical NLP researchers in selecting machine-learning models according to their dataset characteristics.

"Refusing appearance anxiety": A content analysis of body positive posts on Chinese social media.

"Body positivity" is a global movement trending on social media. It aims to challenge predominant appearance ideals in media and encourage women to accept and appreciate all bodies regardless of appearance. In Western contexts, an increasing number of research has explored the potential of body positive social media to benefit young women's body image. However, similar research in China is lacking. This study aimed to explore the content of body positivity posts on Chinese social media. Eight hundred eighty-eight posts from Xiaohongshu (one of China's most popular social media platforms) were coded for positive body image themes, physical appearance-related attributes, and self-compassion themes. The results showed that these posts depicted diverse body sizes and appearances. Additionally, while over 40% of the posts conveyed appearance-focused messages, most contained positive body image themes, and nearly half contained self-compassion themes. The study clarified the content of body positivity posts on Chinese social media and provides theoretical support for future research on body positivity in social media content in China.

Trends in oncological imaging during the COVID-19 pandemic through the vaccination era.

BACKGROUND: This study examines the impact that the COVID-19 pandemic has had on computed tomography (CT)-based oncologic imaging utilization. METHODS: We retrospectively analyzed cancer-related CT scans during four time periods: pre-COVID (1/5/20-3/14/20), COVID peak (3/15/20-5/2/20), post-COVID peak (5/3/20-12/19/20), and vaccination period (12/20/20-10/30/21). We analyzed CTs by imaging indication, setting, and hospital type. Using percentage decrease computation and Student's t-test, we calculated the change in mean number of weekly cancer-related CTs for all periods compared to the baseline pre-COVID period. This study was performed at a single academic medical center and three affiliated hospitals. RESULTS: During the COVID peak, mean CTs decreased (-43.0%, p < 0.001), with CTs for (1) cancer screening, (2) initial workup, (3) cancer follow-up, and (4) scheduled surveillance of previously treated cancer dropping by 81.8%, 56.3%, 31.7%, and 45.8%, respectively (p < 0.001). During the post-COVID peak period, cancer screenings and initial workup CTs did not return to prepandemic imaging volumes (-11.4%, p = 0.028; -20.9%, p = 0.024). The ED saw increases in weekly CTs compared to prepandemic levels (+31.9%, p = 0.008), driven by increases in cancer follow-up CTs (+56.3%, p < 0.001). In the vaccination period, cancer screening CTs did not recover to baseline (-13.5%, p = 0.002) and initial cancer workup CTs doubled (+100.0%, p < 0.001). The ED experienced increased cancer-related CTs (+75.9%, p < 0.001), driven by cancer follow-up CTs (+143.2%, p < 0.001) and initial workups (+46.9%, p = 0.007). CONCLUSIONS AND RELEVANCE: The pandemic continues to impact cancer care. We observed significant declines in cancer screening CTs through the end of 2021. Concurrently, we observed a 2× increase in initial cancer workup CTs and a 2.4× increase in cancer follow-up CTs in the ED during the vaccination period, suggesting a boom of new cancers and more cancer examinations associated with emergency level acute care.

Motion guidance lines for robust data consistency-based retrospective motion correction in 2D and 3D MRI.

PURPOSE: To develop a robust retrospective motion-correction technique based on repeating k-space guidance lines for improving motion correction in Cartesian 2D and 3D brain MRI. METHODS: The motion guidance lines are inserted into the standard sequence orderings for 2D turbo spin echo and 3D MPRAGE to inform a data consistency-based motion estimation and reconstruction, which can be guided by a low-resolution scout. The extremely limited number of required guidance lines are repeated during each echo train and discarded in the final image reconstruction. Thus, integration within a standard k-space acquisition ordering ensures the expected image quality/contrast and motion sensitivity of that sequence. RESULTS: Through simulation and in vivo 2D multislice and 3D motion experiments, we demonstrate that respectively 2 or 4 optimized motion guidance lines per shot enables accurate motion estimation and correction. Clinically acceptable reconstruction times are achieved through fully separable on-the-fly motion optimizations (˜1 s/shot) using standard scanner GPU hardware. CONCLUSION: The addition of guidance lines to scout accelerated motion estimation facilitates robust retrospective motion correction that can be effectively introduced without perturbing standard clinical protocols and workflows.

Evaluation of the Aggregated Time Savings in Adopting Fast Brain MRI Techniques for Outpatient Brain MRI.

INTRODUCTION: Clinical validation studies have demonstrated the ability of accelerated MRI sequences to decrease acquisition time and motion artifact while preserving image quality. The operational benefits, however, have been less explored. Here, we report our initial clinical experience in implementing fast MRI techniques for outpatient brain imaging during the COVID-19 pandemic. METHODS: Aggregate acquisition times were extracted from the medical record on consecutive imaging examinations performed during matched pre-implementation (7/1/2019-12/31/2019) and post-implementation periods (7/1/2020-12/31/2020). Expected acquisition time reduction for each MRI protocol was calculated through manual collection of acquisition times for the conventional and accelerated sequences performed during the pre- and post-implementation periods. Aggregate and expected acquisition times were compared for the five most frequently performed brain MRI protocols: brain without contrast (BR-), brain with and without contrast (BR+), multiple sclerosis (MS), memory loss (MML), and epilepsy (EPL). RESULTS: The expected time reductions for BR-, BR+, MS, MML, and EPL protocols were 6.6 min, 11.9 min, 14 min, 10.8 min, and 14.1 min, respectively. The overall median aggregate acquisition time was 31 [25, 36] min for the pre-implementation period and 18 [15, 22] min for the post-implementation period, with a difference of 13 min (42%). The median acquisition time was reduced by 4 min (25%) for BR-, 14.0 min (44%) for BR+, 14 min (38%) for MS, 11 min (52%) for MML, and 16 min (35%) for EPL. CONCLUSION: The implementation of fast brain MRI sequences significantly reduced the acquisition times for the most commonly performed outpatient brain MRI protocols.

Inference of population structure and admixture proportion from Y chromosomal data of Chinese population.

In the past two decades, Y chromosome data has been generated for human population genetic studies. These Y chromosome datasets were produced with various testing methods and markers, thus difficult to combine them for a comprehensive analysis. In this study, we combine four human Y chromosomal datasets of Han, Tibetan, Hui, and Li ethnic groups. The dataset contains 27 microsatellites and 137 single nucleotide polymorphisms these populations share in common. We assembled a single dataset containing 2439 individuals from 25 nationwide populations in China. A systematic analysis of genetic distance and clustering was performed. To determine the gene flow of the studied population with worldwide populations, we modeled the ancestry informative markers. The reference panel was regarded as a mixture of South Asian (SAS), East Asian (EAS), European (EUR), African (AFR), and American (AMR) populations from 1000 Genomes data of Y chromosome using nonlinear data-fitting. We then calculated the admixture proportion of these four studied populations with 26 worldwide populations. The results showed that the Han and Hui have great genetic affinity, and Hui is the most admixed ethnic group, with 61.53% EAS, 34.65% SAS, 1.91% AFR, 1.56% AMR, and 0.04% EUR ancestry component (the AMR is highly admixed and thus should be ignored). All the other three ethnic groups contained more than 97% EAS ancestry component. The Li is the least admixed population in this study. The combined dataset in this study is the largest of this kind reported to date and proposes reference population data for use in future paternal genetic studies and forensic genealogical identification.