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Harnessing immunotherapy for brain metastases: insights into tumor–brain microenvironment interactions and emerging treatment modalities
Brain metastases signify a deleterious milestone in the progression of several advanced cancers, predominantly originating from lung, breast and...
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Frailty and postoperative outcomes in brain tumor patients: a systematic review subdivided by tumor etiology
PurposeFrailty has gained prominence in neurosurgical oncology, with more studies exploring its relationship to postoperative outcomes in brain tumor...
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Patient-Centered Management of Brain Tumor-Related Epilepsy
Purpose of ReviewBrain tumor-related epilepsy is a heterogenous syndrome involving variability in incidence, timing, pathophysiology, and clinical...
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Brain tumor image segmentation based on improved FPN
PurposeAutomatic segmentation of brain tumors by deep learning algorithm is one of the research hotspots in the field of medical image segmentation....
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AI-assisted Segmentation Tool for Brain Tumor MR Image Analysis
TumorPrism3D software was developed to segment brain tumors with a straightforward and user-friendly graphical interface applied to two- and...
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Coordination of anti-CTLA-4 with whole-brain radiation therapy decreases tumor burden during treatment in a novel syngeneic model of lung cancer brain metastasis
Lung cancer is the most common primary tumor to metastasize to the brain. Although advances in lung cancer therapy have increased rates of survival...
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Mechanical characteristics of glioblastoma and peritumoral tumor-free human brain tissue
BackgroundThe diagnosis of brain tumor is a serious event for the affected patient. Surgical resection is a crucial part in the treatment of brain...
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A bis-boron boramino acid PET tracer for brain tumor diagnosis
PurposeBoramino acids are a class of amino acid biomimics that replace the carboxylate group with trifluoroborate and can achieve the 18 F-labeled...
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Hippocampus segmentation after brain tumor resection via postoperative region synthesis
PurposeAccurately segmenting the hippocampus is an essential step in brain tumor radiotherapy planning. Some patients undergo brain tumor resection...
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NeuroIGN: Explainable Multimodal Image-Guided System for Precise Brain Tumor Surgery
Precise neurosurgical guidance is critical for successful brain surgeries and plays a vital role in all phases of image-guided neurosurgery (IGN)....
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Short and long-term prognostic value of intraoperative motor evoked potentials in brain tumor patients: a case series of 121 brain tumor patients
PurposeIatrogenic neurologic deficits adversely affect patient outcomes following brain tumor resection. Motor evoked potential (MEP) monitoring...
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Towards machine learning-based quantitative hyperspectral image guidance for brain tumor resection
BackgroundComplete resection of malignant gliomas is hampered by the difficulty in distinguishing tumor cells at the infiltration zone. Fluorescence...
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Refining neural network algorithms for accurate brain tumor classification in MRI imagery
Brain tumor diagnosis using MRI scans poses significant challenges due to the complex nature of tumor appearances and variations. Traditional methods...
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Integrated approach of federated learning with transfer learning for classification and diagnosis of brain tumor
Brain tumor classification using MRI images is a crucial yet challenging task in medical imaging. Accurate diagnosis is vital for effective treatment...
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Efficient brain tumor segmentation using Swin transformer and enhanced local self-attention
PurposeFully convolutional neural networks architectures have proven to be useful for brain tumor segmentation tasks. However, their performance in...
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Brain Tumor Segmentation for Multi-Modal MRI with Missing Information
Deep convolutional neural networks (DCNNs) have shown promise in brain tumor segmentation from multi-modal MRI sequences, accommodating heterogeneity...
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Robust brain tumor classification by fusion of deep learning and channel-wise attention mode approach
Diagnosing brain tumors is a complex and time-consuming process that relies heavily on radiologists’ expertise and interpretive skills. However, the...
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A hybrid deep CNN model for brain tumor image multi-classification
The current approach to diagnosing and classifying brain tumors relies on the histological evaluation of biopsy samples, which is invasive,...
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Artificial intelligence in neuro-oncology: advances and challenges in brain tumor diagnosis, prognosis, and precision treatment
This review delves into the most recent advancements in applying artificial intelligence (AI) within neuro-oncology, specifically emphasizing work on...
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Association between elevated preoperative red cell distribution width and mortality after brain tumor craniotomy
Background: Red cell distribution width (RDW) has been recognized as a potential inflammatory biomarker, with elevated levels associated with adverse...