AIMC Topic: Meningeal Neoplasms

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Enhancing meningioma tumor classification accuracy through multi-task learning approach and image analysis of MRI images.

PloS one Aug 11, 2025
BACKGROUND: Accurate classification of meningioma brain tumors is crucial for determining the appropriate treatment plan and improving patient outcomes. However, this task is challenging due to the slow-growing nature of these tumors and the potentia...
Humans Machine Learning Female Deep Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging Meningioma Meningeal Neoplasms Aged Adult Male Middle Aged
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Large language models for extraction of OPS-codes from operative reports in meningioma surgery.

Acta neurochirurgica Jul 31, 2025
BACKGROUND: In the German medical billing system, surgical departments encode their procedures in OPS-codes. These OPS-codes have major impact on DRG grouping and thus mainly determine each case´s revenue. In our study, we investigate the ability of ...
Large Language Models Meningeal Neoplasms Language Neurosurgical Procedures Humans Germany Female Clinical Coding Male Meningioma
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Multiparameter MRI-based automatic segmentation and diagnostic models for the differentiation of intracranial solitary fibrous tumors and meningiomas.

Annals of medicine Jul 8, 2025
BACKGROUND: Intracranial solitary fibrous tumors (SFTs) and meningiomas are meningeal tumors with different malignancy levels and prognoses. Their similar imaging features make preoperative differentiation difficult, resulting in high misdiagnosis ra...
Humans Machine Learning Diagnosis, Differential Meningioma Meningeal Neoplasms Male Multiparametric Magnetic Resonance Imaging Middle Aged Retrospective Studies Deep Learning Solitary Fibrous Tumors Female Magnetic Resonance Imaging Aged Adult
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Multimodal deep learning-based radiomics for meningioma consistency prediction: integrating T1 and T2 MRI in a multi-center study.

BMC medical imaging Jul 1, 2025
BACKGROUND: Meningioma consistency critically impacts surgical planning, as soft tumors are easier to resect than hard tumors. Current assessments of tumor consistency using MRI are subjective and lack quantitative accuracy. Integrating deep learning...
Retrospective Studies Female Aged Adult Sensitivity and Specificity Humans Magnetic Resonance Imaging Meningioma Meningeal Neoplasms Radiomics Male Middle Aged Deep Learning
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Radiomic study of common sellar region lesions differentiation in magnetic resonance imaging based on multi-classification machine learning model.

BMC medical imaging May 3, 2025
OBJECTIVE: Pituitary adenomas (PAs), craniopharyngiomas (CRs), Rathke's cleft cysts (RCCs), and tuberculum sellar meningiomas (TSMs) are common sellar region lesions with similar imaging characteristics, making differential diagnosis challenging. Thi...
Sella Turcica Craniopharyngioma Central Nervous System Cysts Middle Aged Adolescent Support Vector Machine Magnetic Resonance Imaging Diagnosis, Differential Young Adult Meningioma Adult Machine Learning Meningeal Neoplasms Humans Radiomics Retrospective Studies Pituitary Neoplasms Male Female Adenoma Aged
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Deep learning for automated segmentation of brain edema in meningioma after radiosurgery.

BMC medical imaging Apr 22, 2025
BACKGROUND: Although gamma Knife radiosurgery (GKRS) is commonly used to treat benign brain tumors, such as meningioma, irradiating the surrounding brain tissue can lead to perifocal edema within a few months after the procedure. Volumetric assessmen...
Male Middle Aged Deep Learning Humans Magnetic Resonance Imaging Female Meningioma Brain Edema Aged Meningeal Neoplasms Radiosurgery Adult
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Machine learning based radiomics approach for outcome prediction of meningioma - a systematic review.

F1000Research Mar 25, 2025
INTRODUCTION: Meningioma is the most common brain tumor in adults. Magnetic resonance imaging (MRI) is the preferred imaging modality for assessing tumor outcomes. Radiomics, an advanced imaging technique, assesses tumor heterogeneity and identifies ...
Magnetic Resonance Imaging Humans Neoplasm Recurrence, Local Machine Learning Meningioma Prognosis Meningeal Neoplasms Radiomics
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Development of Hybrid radiomic Machine learning models for preoperative prediction of meningioma grade on multiparametric MRI.

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia Mar 5, 2025
PURPOSE: To develop and compare machine learning models for distinguishing low and high grade meningiomas on multiparametric MRI.
Humans Machine Learning Retrospective Studies Female Radiomics Male Middle Aged Aged Adult Multiparametric Magnetic Resonance Imaging Magnetic Resonance Imaging Neoplasm Grading Meningioma Meningeal Neoplasms
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Preoperative diagnosis of meningioma sinus invasion based on MRI radiomics and deep learning: a multicenter study.

Cancer imaging : the official publication of the International Cancer Imaging Society Feb 28, 2025
OBJECTIVE: Exploring the construction of a fusion model that combines radiomics and deep learning (DL) features is of great significance for the precise preoperative diagnosis of meningioma sinus invasion.
Meningioma Humans Meningeal Neoplasms Retrospective Studies Cranial Sinuses Female Adult Male Aged ROC Curve Radiomics Middle Aged Magnetic Resonance Imaging Deep Learning Neoplasm Invasiveness Preoperative Care
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Serum Metabolomics Profiling Coupled with Machine Learning Identifies Potential Diagnostic and Prognostic Candidate Markers in Meningioma Using Raman Spectroscopy, ATR-FTIR, and LC-MS/MS.

Journal of proteome research Feb 25, 2025
Meningioma, the most prevalent brain tumor, poses significant challenges due to its unclear transition from low-grade to aggressive forms, with limited knowledge about grade-specific markers. We have utilized vibrational spectroscopic techniques such...
Humans Liquid Chromatography-Mass Spectrometry Tandem Mass Spectrometry Machine Learning Spectrum Analysis, Raman Adult Male Spectroscopy, Fourier Transform Infrared Prognosis Meningioma Biomarkers, Tumor Middle Aged Metabolomics Female Meningeal Neoplasms Case-Control Studies Chromatography, Liquid Aged
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