Brain Cancer

Biochemically Constrained Multi-Omics Integration Reveals Protein-Metabolite Dependencies Across Diseases.

Integrating proteomic and metabolomic data is essential for understanding complex diseases, yet current approaches that rely primarily on statistical associations often overlook the structured biochemical relationships between molecular entities and suffer from discriminative instability in small clinical cohorts. Here, we present ProMetNet, a biochemically constrained framework that incorporates ...

Biological domain shift and statistical nesting concerns in generative AI-based spatial tumor growth prediction for pediatric diffuse midline glioma.

BACKGROUND: Laslo et al. recently reported a guided denoising diffusion implicit model for spatial tumor growth prediction on magnetic resonance imaging (MRI) in pediatric diffuse midline glioma. Their proof-of-principle study demonstrates the feasibility of generative artificial intelligence (AI) for producing patient-specific tumor growth maps as an early step toward informing personalized radio...

Biologically adaptive radiation oncology in oligometastatic and oligoprogressive disease: MR- and CBCT-guided adaptation, molecular imaging, dose painting, biomarkers, and AI.

Oligometastatic disease (OMD) and oligoprogression are clinically actionable states in which local treatment of limited tumour burden can prolong dise...

From Andes to the dry diagonal: phylogenomics and trait evolution elucidate the radiation of cacti in South American drylands.

The expansion of arid and dry ecosystems during the Miocene played a key role in the diversification of succulent plants; however, the relative contri...

Deep learning for CT-less attenuation correction synthesis in non-small cell lung cancer: A proof-of-concept evaluated for quantitative and physical characteristics.

To develop and rigorously validate a deep learning framework for CT-free positron emission tomography (PET) attenuation correction in non-small cell l...

Ultra-low dose chest-abdomen-pelvis CT with deep-learning image reconstruction for cancer follow-up: Impact on image quality and lesion detection.

PURPOSE: The purpose of this study was to compare the image quality and lesion detection between ultra-low dose (ULD) chest-abdomen-pelvis computed to...

Modeling and forecasting oyster norovirus outbreaks of long-range dependence on antecedent marine environmental conditions.

This study presents three artificial intelligence-based models - XGBoost, Random Forest (RF), and Deep Artificial Neural Network (DANN) - with 2-day l...

Prediction models for adverse events from prostate cancer curative radiotherapy: a systematic review of methodological quality.

BACKGROUND: Predicting risks of urinary, bowel, sexual, and other adverse effects following prostate cancer curative radiotherapy (PCa-RT) is essentia...

Interfractional Monitoring of Spacer Hydrogel Morphology in Patients With Prostate Cancer Receiving SBRT Treatment.

PURPOSE: The purpose of this study is to explore whether spacer hydrogel morphology changes during the course of stereotactic body radiation therapy (...

Local recurrence in rectal cancer: from detection to structured reporting.

Despite advances in total mesorectal excision and neoadjuvant therapy, locally recurrent rectal cancer remains a clinically important source of pelvic...

Machine learning-inspired design of a modified spider-shaped MIMO antenna for 5G-advanced wireless communications.

A modified Spider Shaped Four Element Multi Input Multi Output Antenna (SSFEMIMOA) is suggested for the 5G-advanced, and sub-6 GHz advanced wireless c...

Uncovering the molecular landscape of young-onset diffuse gastric cancer: A relieff-based feature selection analysis on RNA-Seq data.

BACKGROUND: Diffuse Gastric Cancer (DGC) is an aggressive subtype with a poor prognosis and a lack of specific biomarkers, representing a critical unm...

Radiation dose optimization and dosimetry in pediatric nuclear medicine: Current concepts and future directions.

Pediatric nuclear medicine plays an essential role in the diagnosis and treatment of a wide range of oncologic and non-oncologic diseases while requir...

Multimodal Radiomics Combined with Habitat Analysis for Precise Preoperative Differentiation of WHO Grade I Meningioma Subtypes.

BACKGROUND: Preoperative differentiation of World Health Organization (WHO) Grade I meningioma subtypes is clinically needed but limited with conventi...

A novel hybrid transformer-based framework (H-ConvNeXt-Swin) to classify brain tumors using MRI.

This paper introduces a hybrid deep learning model combining ConvNeXt and Swin Transformer for classifying brain tumors from MRI scans. The ConvNeXt b...

Online adaptive radiotherapy in pelvic and thoracic cancers - comparing toxicities, clinical outcomes and technical parameters between conventional image-guided radiotherapy and online adaptive radiotherapy - the study protocol for the prospective, registry-based cohort study (PRoART).

BACKGROUND: Conventional image-guided radiotherapy (IGRT) typically relies on a computed tomography (CT)-based treatment planning process (planning CT...

High-performance MXene/CuNWs/MH-TPU piezoresistive strain sensors fabricated via template-assisted phase separation with integrated thermal-EMI dual protection for emergency rescue.

In recent years, complex and extreme fire environments have posed a severe threat to the safety of front-line firefighters, urgently requiring high-pe...

Artificial intelligence-based diagnostic model for identifying PTPRZ1-MET fusion in a clinically defined secondary glioblastoma cohort.

Glioblastoma (GBM) is an aggressive and highly lethal brain tumor. Secondary glioblastoma (sGBM), which arises through malignant progression from lowe...

Fractal and Machine Learning Analyses of MALDI-TOF Mass Spectrometry Data in Glioblastoma.

Data preprocessing is a critical step in the analysis of matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI-TOF MS) s...

Identification of TNFRSF12A as a key regulator of stemness and immunosuppression in a novel glioma subtype via multi-omics analysis and experimental validation.

Glioma stem cells (GSCs) drive tumor heterogeneity, therapy resistance, and immunosuppression. This study identified molecular subtypes of glioma base...