Lung Cancer

The Wnt receptor Frizzled3 (FZD3) drives aggressive phenotypes in small cell lung cancer.

BACKGROUND: Small cell lung cancer (SCLC) is an aggressive neuroendocrine malignancy characterized by rapid progression and poor prognosis. This study integrates bioinformatics with experimental validation to characterize the role of Frizzled-3 (FZD3), a Wnt receptor, in SCLC progression. METHODS: We analyzed transcriptomic data from 102 SCLC and 55 normal lung tissues retrieved from the Gene Expr...

AI chatbots for patient education in localized prostate cancer radiotherapy: A comparative quality and readability analysis.

OBJECTIVES: This study aimed to conduct a comparative quality assessment of information provided by widely used artificial intelligence chatbots (AICs) regarding radiotherapy for localized prostate cancer, with a focus on reliability, readability, and patient-centeredness. METHODS: Five publicly accessible AICs (ChatGPT, Perplexity, Gemini, DeepSeek, and Copilot) were evaluated using three standar...

Optimizing pediatric chest CT: superior image quality and lower radiation dose with deep learning reconstruction.

OBJECTIVES: To compare image quality and radiation dose between deep learning reconstruction (DLIR) and hybrid iterative reconstruction (HIR) algorith...

The impact of emerging technologies on education, roles and career progression of radiation therapists: a delphi consensus based on the ESTRO RTT workshop.

Rapid technological advances in radiation oncology, including artificial intelligence (AI), online adaptive radiotherapy, and advanced imaging, are tr...

HOW GENETICS CHANGED OR WILL CHANGE THE THERAPY IN THYROID NODULES WITH INDETERMINATE CYTOLOGY.

The incidence of thyroid cancer has risen in recent decades, largely due to the widespread use of increasingly sensitive imaging techniques that have ...

Stereotactic Body Radiotherapy for Spinal Metastases: Outcomes and Development of a Risk Assessment Score to Predict Local Tumor Progression.

BACKGROUND AND OBJECTIVES: Stereotactic body radiotherapy (SBRT) has emerged as an effective treatment modality for spinal metastases. However, high-p...

Artificial intelligence models for osteoporosis risk prediction in postmenopausal women with CKD: A cross-sectional analysis of NHANES 2005 to 2018.

Artificial intelligence (AI) can transform osteoporosis (OP) screening, but its application in high-risk, complex populations like postmenopausal wome...

Estimating major pathological response in non-small cell lung cancer patients with post-neoadjuvant therapy using MMT-net.

Neoadjuvant therapy (NAT) has demonstrated considerable effectiveness in treating locally advanced non-small cell lung cancer (NSCLC). Major pathologi...

Exploration of network-based, machine learning, MD simulations, and MM/GBSA approaches revealed luteolin from Gynura procumbens as key inhibitor of MMP9 in NSCLC.

The primary leading reason for cancer death is non-small-cell lung cancer (NSCLC) still up to date globally. Even with today's advanced technology, it...

Detecting Distant Metastases in Prostate Cancer Using Whole-body MR Imaging Together with DWIBS (Diffusion-weighted Imaging with Background Body Signal Suppression).

Whole-body MRI (WB-MRI) has evolved over the past 2 decades as a noninvasive imaging technique for detecting distant metastases in prostate cancer. Si...

Multiview 2.5D Deep Learning Outperforms 2D and 3D Models for Preoperative Prediction of Visceral Pleural Invasion in Stage IA Lung Adenocarcinoma.

OBJECTIVE: This study evaluated the predictive performance of 2 novel 2.5-dimensional (2.5D) deep learning (DL) models for visceral pleural invasion (...

AI-Derived Electronic Tumor Marker For Cancer Antigen 19-9 Nonproducers With Pancreatic Ductal Adenocarcinoma.

IMPORTANCE: Cancer antigen 19-9 (CA19-9) is used to assess treatment response among patients with pancreatic ductal adenocarcinoma (PDAC); however, ne...

Pretreatment Radiation Esophagitis Prediction Using Quantum Machine Learning in Patients With Esophageal Cancer.

PURPOSE: To introduce a hybrid quantum-classical machine learning approach and validate its feasibility and accuracy for pretreatment radiation-induce...

The role of clinical competency-based education in training in radiation science: A scoping review.

BACKGROUND: Clinical competency-based education (CBE) has emerged as a critical strategy to enhance workforce readiness in radiation sciences. Despite...

BKDRP: a biological knowledge-driven approach for drug response prediction using multi-omics data in cancer cell lines.

BACKGROUND: Cancer heterogeneity results in patients with the same diagnosis responding differently to drugs, making treatments extremely challenging....

Minimally invasive spine surgery: current advantages, limitations, and future directions.

Minimally invasive spine surgery (MISS), supported by advancements in endoscopic systems, tubular retractors, lateral access corridors, image-guided n...

Ganglioside-Mediated Neural-Acinar Crosstalk Facilitates Pancreatic Carcinogenesis via Metaplastic Niche Remodeling.

BACKGROUND & AIMS: Neural networks constitute a crucial component of the tumor microenvironment that remains underexplored in pancreatic carcinogenesi...

Robust Histopathology Subtyping via Perturbation Fidelity in Deep Classifier.

Deep learning for invasive lung adenocarcinoma subtyping remains vulnerable to real-world imaging perturbations. We present a margin consistency frame...

CT acquisition protocols in lung cancer screening: implications for guideline development from a worldwide survey.

OBJECTIVES: To assess the currently applied CT image acquisition protocols in lung cancer screening (LCS) and thereby fill a knowledge gap to support ...

Zero Echo Time Magnetic Resonance Imaging of the Spine.

Zero echo time magnetic resonance imaging is an ultrashort echo time technique that enables computed tomography-like visualization of cortical and tra...