Acoustic neuroma (vestibular schwannoma)

This dataset is a perfusion imaging study of vestibular schwannomas (VS), aiming to explore perfusion characteristics and their influencing factors. It includes perfusion-weighted imaging parameters from 20 patients with sporadic vestibular schwannomas, specifically parameters related to the extravascular extracellular space (EES): the volume transfer constant between a vessel and the EES (Ktrans), the EES volume per unit of tissue volume (Ve), the rate transfer constant between EES and blood plasma (Kep), and the relative cerebral blood volume (rCBV). The data were derived from medical imaging calculations and correlated with tumor size (small vs. large) and structure (solid, cystic, or heterogeneous). Findings indicate that Ktrans, Ve, and Kep were measurable in all tumors, while rCBV was only measurable in large tumors; Ktrans showed a positive correlation with rCBV, Ve had a negative correlation with Kep, and in solid VSs, Ktrans and Ve were positively correlated. The dataset is primarily used in neuro-oncology, medical image analysis, and clinical research to assess perfusion profiles of vestibular schwannomas, providing imaging-based insights into tumor biology and treatment strategies.

This dataset is a proteomic study of perilymph from patients with vestibular schwannoma (acoustic neuroma). It includes perilymph samples collected intraoperatively via the round window from 15 patients undergoing translabyrinthine surgery. The samples were analyzed using an online tandem LTQ-Orbitrap mass spectrometer, with protein identification and quantification performed using MaxQuant software. A total of 314 proteins were identified, including 60 proteins present in all patients and 130 proteins detected only in individual patients. The dataset focuses on functional analysis of proteins (using the PANTHER Overrepresentation tool) and associations between protein content and clinical parameters, particularly tumor-associated hearing loss and tumor diameter. Random Forest and Boruta analyses identified alpha-2-HS-glycoprotein (P02765) as an independent variable for tumor-associated hearing loss. The dataset is primarily used to investigate the molecular mechanisms of inner ear disorders, discover potential biomarkers for hearing loss, and study the pathophysiology of vestibular schwannoma.

This dataset is derived from a retrospective clinical study designed to determine the incidence of cochlear fibrosis after vestibular schwannoma (acoustic neuroma) resection via the middle cranial fossa (MCF) approach. It includes information from patients who underwent surgery between 2013 and 2018, comprising pre- and postoperative audiometric test results (pure-tone audiometry and speech discrimination scores), magnetic resonance imaging (MRI) scans taken one year after surgery, and clinical follow-up records. The data were collected from a tertiary care academic medical center through medical chart review. The dataset is primarily used for investigating the relationship between otoneurosurgical postoperative complications (specifically cochlear fibrosis) and hearing preservation, providing evidence for understanding postoperative hearing recovery mechanisms, assessing the feasibility of cochlear implantation, and optimizing surgical strategies.

This dataset comprises research data from a study on Gamma Knife radiosurgery planning for vestibular schwannomas (acoustic neuromas), focusing on the relationship between the sphericity degree of the target volume and dose distribution. It includes clinical data from 64 patients who underwent stereotactic radiosurgery, with calculations of sphericity parameters and analysis of dosimetric metrics such as coverage, selectivity, gradient index, Paddick conformity index, and isodose volume/target volume ratio. The data is derived from clinical treatment planning systems, with spherical target volumes in a phantom used as reference plans for comparison. The primary research direction is the optimization of dose distribution in radiosurgery planning, investigating sphericity as a novel parameter for evaluating Gamma Knife plan quality, thereby providing theoretical support for precise treatment of vestibular schwannomas.

This dataset comprises transcriptomic data and associated analysis code for investigating the role of oxidative stress in vestibular schwannoma. It integrates two GEO series (GSE54934 and GSE56597) and provides a normalized gene-expression matrix after batch-effect removal (62 vestibular schwannoma samples vs. 18 control nerve samples). The dataset includes comprehensive R scripts for differential expression analysis, GO/KEGG enrichment analysis, GSEA, PPI hub gene identification, immune infiltration analysis (ssGSEA), and ROC analysis. Notably, it contains 15 oxidative-stress-related differentially expressed genes and nine hub genes (CDKN2A, CYBB, EGFR, IL6, ADIPOQ, HMOX1, NAMPT, PTGS2, TXN). Data are provided in plain text and RDS formats to ensure full reproducibility of research findings. The dataset is primarily used in neuro-oncology, oxidative stress mechanism studies, and bioinformatics methodology development.

This dataset is a transcriptomic resource supporting research on oxidative stress contributions in vestibular schwannoma. It includes a normalized gene-expression matrix after batch-effect removal, comprising 62 vestibular schwannoma samples and 18 control nerve samples, derived from GEO series GSE54934 and GSE56597. The dataset also provides all R scripts used for differential expression analysis, GO/KEGG enrichment, GSEA, PPI-hub gene identification, immune-infiltration (ssGSEA), and ROC analyses, along with 15 oxidative-stress-related differentially expressed genes (OSRDEGs) and nine hub genes (e.g., CDKN2A, CYBB). Data are supplied as plain text and RDS objects to facilitate reproduction of figures and tables, primarily applied in neuro-oncology, bioinformatics, and oxidative stress mechanism investigations.

This dataset focuses on genetic analysis of sporadic vestibular schwannomas (also known as acoustic neuromas), containing data on loss of heterozygosity (LOH) and gene mutations in tumor samples. The data is derived from molecular genetic studies of patients with sporadic vestibular schwannomas, obtained through experimental assays such as genotyping and sequencing. It is primarily used to investigate genetic variation characteristics, tumorigenesis mechanisms, and explore potential biomarkers or therapeutic targets, applicable to research in tumor genetics, neuro-oncology, and precision medicine.

This dataset contains demographic characteristics of 100 patients with vestibular schwannoma, including basic clinical and demographic information such as age and gender. The data were collected from clinical research and are publicly shared via the Figshare platform. The dataset is primarily used for neuro-oncology epidemiological studies, particularly for clinical demographic analysis of vestibular schwannoma, providing data support for disease characterization, risk factor exploration, and clinical management strategy development.

This dataset is an open annotated medical imaging collection for vestibular schwannoma (VS), comprising MRI images from 242 consecutive patients who underwent Gamma Knife stereotactic radiosurgery (GK SRS). The data modalities primarily include contrast-enhanced T1-weighted (ceT1) and high-resolution T2-weighted (hrT2) images, with each patient's imaging data accompanied by radiation therapy (RT) datasets such as RT dose, RT structures, and RT plans. The dataset is designed for developing and evaluating medical image segmentation algorithms, particularly for automated tumor segmentation, radiotherapy planning, and imaging analysis of vestibular schwannoma.

This dataset contains clinical characteristics and detailed information of patients with vestibular schwannoma (VS). The data includes demographic information, clinical presentations, diagnostic details, and relevant clinical indicators, potentially sourced from single-center or multi-center clinical studies or medical record reviews. It is suitable for research in neurosurgery, otolaryngology, and oncology, and can be used for disease characterization, prognostic factor exploration, clinical decision support, and epidemiological studies.

This dataset is a systematic review of clinical studies on intralabyrinthine schwannomas, a rare benign tumor affecting the terminal portions of the vestibular and cochlear nerves. It includes data from 27 studies screened from PubMed, Web of Science, and Scopus up to October 2017, covering clinical manifestations of 10 subtypes (e.g., intracochlear, intravestibular) such as hearing loss (typically progressive), with analysis based on high-resolution magnetic resonance imaging (MRI) and temporal bone findings. The data was extracted through systematic literature review by three independent researchers, aiming to correlate tumor subtypes with clinical presentations, supporting diagnosis, pathophysiological research, and clinical management of intralabyrinthine schwannomas.

This dataset focuses on treatment plan parameters for vestibular schwannoma (acoustic neuroma), containing key clinical parameters related to radiation therapy and other treatment regimens. It includes data such as dose distribution, target delineation, irradiation techniques, and optimization metrics extracted from clinical treatment planning systems. The dataset is primarily used for research in radiotherapy parameter optimization, treatment plan comparison, and clinical decision support for vestibular schwannoma, providing standardized data references for medical physics and radiation oncology.