AIMC Topic: Central Nervous System Neoplasms
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Metabolic pathway alterations in cerebrospinal fluid as diagnostic biomarkers for primary central nervous system lymphoma.
Clinica chimica acta; international journal of clinical chemistry
May 19, 2025
Primary Central Nervous System Lymphoma (PCNSL) is a rare and aggressive type of hematological malignancy that can pose diagnostic challenges. Early detection is critical for effective treatment and better patient outcomes. The goal of this study was...
Machine Learning-Enhanced Cerebrospinal Fluid N-Glycome for the Diagnosis and Prognosis of Primary Central Nervous System Lymphoma.
Journal of proteome research
Apr 21, 2025
The diagnosis and prognosis of Primary Central Nervous System Lymphoma (PCNSL) present significant challenges. In this study, the potential use of machine learning algorithms in diagnosing and predicting the prognosis for PCNSL based on cerebrospinal...
Prediction of early recurrence in primary central nervous system lymphoma based on multimodal MRI-based radiomics: A preliminary study.
European journal of radiology
Apr 18, 2025
OBJECTIVES: To evaluate the role of multimodal magnetic resonance imaging radiomics features in predicting early recurrence of primary central nervous system lymphoma (PCNSL) and to investigate their correlation with patient prognosis.
Spatially resolved transcriptomics and graph-based deep learning improve accuracy of routine CNS tumor diagnostics.
Nature cancer
Jan 29, 2025
The diagnostic landscape of brain tumors integrates comprehensive molecular markers alongside traditional histopathological evaluation. DNA methylation and next-generation sequencing (NGS) have become a cornerstone in central nervous system (CNS) tum...
Detecting B-cell lymphoma-6 overexpression status in primary central nervous system lymphoma using multiparametric MRI-based machine learning.
Neuroradiology
Jan 24, 2025
PURPOSE: In primary central nervous system lymphoma (PCNSL), B-cell lymphoma-6 (BCL-6) is an unfavorable prognostic biomarker. We aim to non-invasively detect BCL-6 overexpression in PCNSL patients using multiparametric MRI and machine learning techn...
Multicenter investigation of preoperative distinction between primary central nervous system lymphomas and glioblastomas through interpretable artificial intelligence models.
Neuroradiology
Sep 3, 2024
OBJECTIVE: Research into the effectiveness and applicability of deep learning, radiomics, and their integrated models based on Magnetic Resonance Imaging (MRI) for preoperative differentiation between Primary Central Nervous System Lymphoma (PCNSL) a...
Artificial intelligence innovations in neurosurgical oncology: a narrative review.
Journal of neuro-oncology
Jul 3, 2024
PURPOSE: Artificial Intelligence (AI) has become increasingly integrated clinically within neurosurgical oncology. This report reviews the cutting-edge technologies impacting tumor treatment and outcomes.
Prediction of DNA methylation-based tumor types from histopathology in central nervous system tumors with deep learning.
Nature medicine
May 17, 2024
Precision in the diagnosis of diverse central nervous system (CNS) tumor types is crucial for optimal treatment. DNA methylation profiles, which capture the methylation status of thousands of individual CpG sites, are state-of-the-art data-driven mea...
A multicenter proof-of-concept study on deep learning-based intraoperative discrimination of primary central nervous system lymphoma.
Nature communications
May 4, 2024
Accurate intraoperative differentiation of primary central nervous system lymphoma (PCNSL) remains pivotal in guiding neurosurgical decisions. However, distinguishing PCNSL from other lesions, notably glioma, through frozen sections challenges pathol...
Machine learning-based pathomics signature of histology slides as a novel prognostic indicator in primary central nervous system lymphoma.
Journal of neuro-oncology
Apr 1, 2024
PURPOSE: To develop and validate a pathomics signature for predicting the outcomes of Primary Central Nervous System Lymphoma (PCNSL).
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