Brain Cancer

Explainable machine learning to predict muscle loss during radiotherapy for oral cavity cancer.

BACKGROUND AND PURPOSE: Muscle loss during adjuvant radiotherapy is associated with poor survival outcomes in patients with oral cavity cancer (OCC). This study aimed to develop and validate an explainable machine learning model to predict muscle loss. MATERIALS AND METHODS: This study included 1,024 patients with OCC (derivation cohort, 636 patients; external validation cohort, 388 patients) who ...

mRNA vaccines in cancer immunotherapy: current progress and perspectives in solid tumors and hematologic malignancies.

The unprecedented success of mRNA vaccines during the COVID-19 pandemic has accelerated the development of nucleic acid-based therapeutics, particularly in oncology. Decades of foundational research on mRNA design, delivery, and immunogenicity have laid the groundwork for the application of mRNA vaccines in cancer treatment. Herein, we summarize the key principles of synthetic mRNA engineering, in...

Enhanced Glioma Genotype Prediction Using CEST MRI With Full Z-Spectrum Input, Pixel-Level Learning, and Majority Voting.

Accurate glioma genotype prediction, such as the isocitrate dehydrogenase (IDH) mutation and O6-methylguanine-DNA methyltransferase (MGMT) promoter me...

Automated identification of radiotherapy treatment sites from unstructured physician notes.

PURPOSE: Ambiguous or incomplete documentation is a recurrent bottleneck in radiation oncology workflows, leading to inefficiencies in communication a...

Key Measures for Evaluating Diagnostic Accuracy in Multi-Class Classification: An Overview and Simulation-Based Comparison.

Recent advancements in artificial intelligence have led to increased interest in predictive modeling across various domains, including medicine. Altho...

Arrhythmias and cardiac devices management in oncology patients.

Cardiac arrhythmia is increasingly encountered in patients with cancer, not only as a result of shared risk factors but also as a direct consequence o...

Explainable Machine Learning for Performance Assessment of Fiber-Nanoparticle Concrete in High-Altitude Cold Environments.

The construction of concrete structures in high-altitude cold regions faces unique challenges, including intense radiation, low atmospheric pressure, ...

Neurosurgical Application of Artificial Intelligence in Pediatric Neuro-Oncology.

Pediatric neuro-oncology is a critical field of neurosurgery, representing the leading cause of disease-related mortality in children. Despite its rar...

Testosterone-Sparing Treatment Strategies for Biochemically Recurrent Prostate Cancer After Radical Prostatectomy.

PURPOSE OF REVIEW: Biochemical recurrence (BCR) after radical prostatectomy occurs in up to one-third of patients and increases the risk of metastasis...

Integrating multi-omics data and artificial intelligence for personalized medicine in glioblastoma.

Glioblastoma (GBM) is one of the most lethal primary brain tumors and is characterized by profound molecular heterogeneity, rapid progression, and lim...

A Comparative Study of IVIM-MRI Fitting Techniques in Glioma Grading: Conventional, Bayesian, and Voxel-Wise and Spatially-Aware Deep Learning Approaches.

BACKGROUND: Intravoxel incoherent motion (IVIM) analysis of diffusion-weighted MRI (DWI) provides microvascular perfusion and diffusion information. H...

Integration of protein and metabolomic blood biomarkers enhances classification of radiation exposure in X-irradiated humanized mice.

PURPOSE: The general population is at risk of exposure to ionizing radiation due to nuclear warfare, terrorism, or radiological accidents. Such exposu...

Cardioprotection in oncology: Mechanisms, risks and therapeutic strategies.

Objectives of this review is to conduct an analysis of current data of cardiotoxicity of anticancer drugs and radiation therapy, methods of cardiovasc...

Reinforcement learning for real-time adaptive radiotherapy.

State-of-the-art radiotherapy machines with integrated magnetic resonance (MR) imaging, known as MR-Linacs, provide the capability to track tumors in ...

Fast 3D whole-body occupational dose estimation in interventional radiology using physics-informed deep learning.

Occupational radiation exposure in interventional radiology is spatially heterogeneous and inadequately captured by conventional point-based dosimetry...

PTBP1 knockdown reprograms glioma stem cells into neuronal-like cells and suppresses tumorigenesis via the DUSP5-ERK1/2 signaling pathway.

BACKGROUND: Glioblastoma (GBM), the most prevalent and aggressive primary brain tumor in adults, has a median survival of merely 14 months. Current th...

Long term evolutions of hard exudates after anti-VEGF therapy for diabetic macular oedema.

PURPOSE: To evaluate longitudinal change in hard exudate (HEs) volume over 5-years following anti-VEGF treatment for diabetic macular oedema (DMO). ME...

DBSCAN applied to EHRs data from patients with glioblastoma clusters patients based on cytosolic Hsp70 protein, sex, and brain subventricular zone.

Radiation Dose Optimisation Through Artificial Intelligence (AI)-based Auto-Thorax Collimation.

INTRODUCTION: Artificial intelligence (AI) is increasingly adopted in digital radiography to enhance workflow efficiency, standardisation and support ...

Natural Language Processing Methods Automate Molecular Marker Extraction From Glioma Pathology Reports.

BACKGROUND AND OBJECTIVES: Molecular markers such as isocitrate dehydrogenase (IDH) and alpha-thalassemia/mental retardation syndrome X-linked (ATRX) ...