Lung Cancer

Elucidating the pathway activity and prognostic significance of diverse regulatory cell death patterns in pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy with a five-year survival rate below 10%. Regulatory cell death (RCD) plays a critical role in tumor progression and therapy response, yet its prognostic implications in PDAC remain underexplored. In this study, we systematically investigated RCD-related genes using bulk RNAseq and single-cell RNAseq cohorts. By integrating ...

Pan-cancer analysis identifies immunoproteasome as the predominant survival-associated component of antigen processing machinery.

Neoantigens are critical targets for cancer immunotherapy, yet the relationship between experimentally validated neoantigen burden and antigen processing machinery (APM) expression in determining clinical outcomes remains unclear. We mapped CEDAR-annotated neoantigens (CENs) onto mutation data from 43,980 patients across 14 cancer types using cBioPortal. APM gene expression was correlated with sur...

Phase-only synthesis of cosecant-squared patterns with reduced sidelobes in large planar arrays via physics-informed deep neural networks.

This paper introduces a deep learning-based framework for phase-only synthesis of cosecant-squared (csc²) radiation patterns in planar antenna arrays ...

Radiation scatter at fluoroscopy-guided endoscopic procedures: Building towards further optimization.

INTRODUCTION: Exposure to ionizing radiation by endoscopy personnel during fluoroscopy-guided procedures remains a health hazard. We aimed to evaluate...

A Machine-Learning Model for Accurate Diuresis Prediction in Acute Heart Failure (DRC-AHF).

AIMS: We aimed to develop a machine learning-based tool for accurate quantitative prediction of diuretic response in acute heart failure (AHF). METHOD...

Tracer-agnostic diffusion model-based CT-free attenuation correction for brain PET: Comprehensive evaluation across 14 tracers.

OBJECTIVE: Accurate attenuation correction (AC) is critical in quantitative brain PET imaging. Conventional CT-based AC methods increase radiation exp...

CT-based radiomics as a non-invasive virtual biopsy for high PD-L1 expression prediction in non-small cell lung cancer.

PURPOSE: Non-small cell lung cancer (NSCLC) remains a major clinical challenge, with Programmed death-ligand 1 (PD-L1) expression serving as a crucial...

[Computational medicine empowers multi-dimensional diagnosis and treatment of pancreatic cancer].

Due to its high genomic heterogeneity and dense desmoplastic microenvironment, traditional diagnosis and treatment for pancreatic ductal adenocarcinom...

Optimising chest computed tomography (CT) scan ranges in paediatric patients to reduce radiation exposure.

AIM: The aim of this study was to accurately position the scan range of unenhanced chest computed tomography (CT) scans for paediatric patients by cla...

Review Article: Advances in the Diagnosis of Dysplasia in Barrett's Oesophagus.

BACKGROUND: Barrett's oesophagus (BE), the precursor to oesophageal adenocarcinoma, progresses through a stepwise dysplastic sequence. Accurate dyspla...

Delta radiomics for predicting early radiation-induced lung injury after thoracic radiotherapy: a retrospective paired-CT study.

PURPOSE: Early radiation-induced lung injury remains a clinically relevant complication after thoracic radiotherapy. We compared pretreatment, posttre...

CT in adult patients with Polytrauma: current practices, protocol optimization, structured reporting and future directions.

Computed tomography [CT] is the frontline imaging modality for the assessment of polytrauma patients because of its speed, diagnostic accuracy and inf...

The complementary roles of oversight, education, and collaboration in the responsible integration of artificial intelligence in radiation medicine: White paper of (CADRA).

Artificial intelligence (AI) is poised to fundamentally transform radiation medicine, with growing influence across clinical decision-making, workflow...

AI-driven discovery of GPNMB CAR T cells as a multi-cancer therapy.

Chimeric antigen receptor (CAR) T cells have demonstrated curative potential in hematologic cancers and increasing efficacy in solid tumors and non-ma...

Integrative multi-omics and single-cell analysis identifies EGFR pathway activation and metabolic reprogramming as potential synthetic lethal vulnerabilities in resistance to the FGFR inhibitor AZD4547.

BACKGROUND: Although fibroblast growth factor receptor (FGFR) inhibitors (FGFRi) have demonstrated clinical promise, the inevitable emergence of acqui...

Multimodal deep learning-based prediction of radiation-induced temporal lobe injury via anatomical imaging and spatial dose: A multicenter study.

BACKGROUND: To develop and validate a multimodal deep learning model for pre-treatment prediction of radiation-induced temporal lobe injury (RTLI), an...

Automated measurement of CD8+ T-cell distribution at the tumor epithelial-stromal interface is associated with NSCLC immunotherapy benefit and transcriptomic pathways.

Whereas anti-PD-(L)1 therapies are widely used in cancer treatment, only a subset of patients achieve long-term survival. Companion diagnostics based ...

High-fidelity super-resolution CT radiomics for non-invasive EGFR mutation prediction in lung adenocarcinoma: a multi-center pooled analysis.

OBJECTIVE: To develop and validate a high-fidelity super-resolution (SR)-enhanced radiomics framework using a Residual Channel Attention Network (RCAN...

Stochastic Expansion of Radionuclide Inhalation Dosimetry for Consequence Management Application: Uncertainty and Sensitivity Analysis in the ICRP 130 Human Respiratory Tract Model.

Releases from nuclear or radiological security events can result in significant internal radiation contamination through inhalation of particulate con...

Interpretable machine learning for preoperative prediction of ground-glass nodules invasiveness in lung adenocarcinoma: a multicenter study.

Accurate, noninvasive prediction of invasiveness in ground-glass nodules (GGNs) is important for surgical planning in lung adenocarcinoma. This multic...