Lung Cancer

Tumor spread through air spaces in non-small-cell lung cancer: 18F-fluorodeoxyglucose PET-based tumoral and peritumoral radiomics analysis with machine learning.

OBJECTIVE: To investigate the utility of tumoral and peritumoral [18F]-fluorodeoxyglucose PET-based radiomics models for predicting tumor spread through air spaces (STAS) in non-small-cell lung cancer (NSCLC). METHODS: A total of 104 patients with NSCLC were retrospectively included and classified as STAS-positive or STAS-negative according to postoperative histopathology. Three radiomics models w...

Prediction of Side Effects from Breast Radiation Therapy - Integration of Clinical and Genomic Data.

OBJECTIVES: To compare the ability of different machine learning models to predict the risk of side effects in patients with breast cancer undergoing radiation therapy. METHODS: Data from the multicentre REQUITE cohort (n=2067) was analysed retrospectively. Side effects (8 endpoints) were assessed 24 months post radiation therapy. Clinical, treatment and genetic data were available. Predictive per...

Integrating Cardiovascular Screening in Lung Cancer Screening.

Cardiovascular risk assessment is a natural extension of lung cancer screening (LCS) because individuals eligible for low-dose computed tomography oft...

Next generation graphene based MXene metamaterial multicylinder resonator solar absorber optimized with machine learning for conceptual solar dryer mining applications.

In the field of industry and mining sectors, energy demand is rapidly increasing, and it is very necessary to develop a durable, scalable, and broadba...

Integration of single-cell transcriptomics and genomic mutation analysis identifies an immunotherapy-resistant tumor subcluster and validates ARNTL2 as a malignant driver in lung adenocarcinoma.

BACKGROUND: Immunotherapy resistance in lung adenocarcinoma (LUAD) remains a critical clinical challenge, and the mechanisms underlying resistance-ass...

BraMARS: An Interpretable Histopathology-Driven Deep Learning Model for Brain Metastasis Risk Stratification in Surgically Resected Limited-Stage SCLC.

Brain metastasis (BM) is a major cause of mortality in limited-stage small-cell lung cancer (LS-SCLC). Prophylactic cranial irradiation (PCI) reduces ...

Impact of oncological biomarkers and clinical factors on survival outcomes in renal cell carcinoma with spinal metastasis: a retrospective analysis.

OBJECTIVE: Renal cell carcinoma (RCC) is a common malignancy that metastasizes to the spine, leading to complex treatment challenges and reduced survi...

From optimization of radiation dose distributions to optimal cancer treatments.

The history of optimization in radiation oncology is closely intertwined with the history of Physics in Medicine & Biology (PMB). Over the past four d...

Proximity-confined DNA walking-nanozyme cascades for multiplexed urinary extracellular vesicle phenotyping and machine learning-assisted disease stratification.

Urinary extracellular vesicles (uEVs) provide noninvasive biomarkers for liquid biopsy owing to their ability to reflect disease-associated molecular ...

Radiomics-Based AI for Predicting Neoadjuvant Immunochemotherapy Pathological Response in Non-Small Cell Lung Cancer: Systematic Review and Meta-Analysis.

BACKGROUND: Non-small cell lung cancer (NSCLC) remains the leading cause of cancer-related mortality worldwide. Accurate early prediction of response ...

AI-driven dual-task prediction model for co-stratifying efficacy and toxicity in NSCLC immunotherapy.

While effective against non-small cell lung cancer (NSCLC), PD-1 inhibitors can induce immune-related adverse events (irAEs), occurring in up to 15.2%...

Dosimetric parameter-based machine learning to predict radiation pneumonitis following breast radiotherapy.

Objective.Radiation pneumonitis (RP) is an important toxicity following breast radiotherapy. Although modern treatment techniques limit lung exposure,...

A radiomic approach to non-invasively decode tumor immune microenvironmental features in surgically resected non-small cell lung cancer.

INTRODUCTION: This study aimed to develop radiomics-based multivariate classifiers able to non-invasively decipher the tumor immune microenvironment (...

Biomarkers of nivolumab benefit in resectable non-small cell lung cancer.

Perioperative nivolumab significantly improved event-free survival (EFS) compared with placebo in patients with resectable non-small cell lung cancer ...

Frailty prediction in heart failure patients with acute infections: the potential role of thiazide diuretics?

BACKGROUND: Frailty remains a significant risk factor for adverse health outcomes in hospitalized patients. Few have evaluated frailty risk and its in...

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...

NRP1 silencing induces ROS-mediated cell cycle arrest and mitochondrial apoptosis in non-small cell lung cancer via upregulation of AGER.

OBJECTIVE: The specific role of Neuropilin-1 (NRP1) and its link to oxidative stress in Non-Small Cell Lung Cancer (NSCLC) progression remains unclear...

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...