Breast Cancer

What practicing pathologists and oncologists should know about the new computational pathology-based companion diagnostic tools.

The integration of artificial intelligence into pathology is transforming the assessment of histological and immunohistochemical (IHC) slides, offering opportunities to reduce variability and streamline diagnostics. In practical terms, most available tools and research models emulate the diagnostic capabilities of pathologists by detecting, grading, and classifying tumours and other diseases. More...

Research trends of tumor-associated macrophages in colorectal cancer: a bibliometric analysis.

BACKGROUND: Colorectal cancer (CRC) represents the third most prevalent malignancy worldwide and accounts for the second-highest cancer-related mortality rate. Accumulating evidence over the past decade has established the pivotal role of tumor-associated macrophages (TAMs) in CRC tumorigenesis and disease progression. This study employs bibliometric analysis to delineate the research landscape an...

Computational Fluid Dynamics Simulations to Inform Cancer Therapeutics.

Cancer therapies such as chemotherapy, radiopharmaceutical therapy, and transarterial embolization rely on effective drug or radiation delivery throug...

ALDH1L2 induces resistance to chemotherapy in small cell lung cancer by inhibiting ferroptosis.

Small cell lung cancer (SCLC) is known for its rapid growth and early metastasis, and SCLC patients are highly susceptible to chemoresistance. Studies...

Experiences of Medical Imaging and Radiation Sciences students regarding an assessment based on an artificial intelligence-generated research concept paper.

INTRODUCTION: Artificial intelligence (AI) can complete tasks that once required human cognitive effort. As a result, assessments that traditionally m...

The emerging role of antibody-drug conjugates in EGFR-mutant non-small cell lung cancer with acquired resistance to third-generation EGFR tyrosine kinase inhibitors.

Resistance to third-generation epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) presents a significant clinical challenge for...

Clinically interpretable machine-learning model for predicting heart mean dose using simple BEV-based metrics.

Radiation-induced cardiac toxicity remains a major concern in left-sided breast cancer radiotherapy, with mean heart dose (MHD) serving as a key predi...

Emerging trends and converging evidence in tumor evolution: A comprehensive review.

BACKGROUND: Tumor evolution is a spatiotemporal dynamic process orchestrated by the interplay of genetic mutations, epigenetic reprogramming, and bidi...

Immunotherapy in Triple-Negative Breast Cancer: From Molecular Mechanisms to Precision Medicine-Overcoming Resistance and Optimizing Clinical Outcomes.

Triple-negative breast cancer (TNBC) is the most violent type of breast cancer, in which estrogen receptors (ER), progesterone receptors (PR), and hum...

Single-cell transcriptomic analysis and machine learning identify ATAD3A as a key gene that stabilizes mitochondrial-endoplasmic reticulum membranes, promoting bladder cancer progression.

BACKGROUND: Mitochondria-associated endoplasmic reticulum membranes (MAM) play a critical regulatory role in cancer, yet their function in bladder can...

Predicting treatment response to neoadjuvant chemotherapy in locally advanced rectal cancer: A combined deep learning and machine learning approach utilizing longitudinal multi-sequence MRI.

PURPOSE: To develop and validate deep leaning-based machine learning models using longitudinal multi-sequence MRI for predicting treatment response of...

Flow rate determination in a two-phase system using radioactive particle tracking and deep learning.

In the oil industry, accurate flow rate determination and control in pipelines are critical for ensuring operational efficiency. However, most convent...

Non-invasive screening for ovarian cancer by combining serum SERS with interpretable machine learning models.

Early identification of malignant ovarian tumors is critical for informing treatment decisions and enhancing patients' quality of life. As the third m...

Neoadjuvant Radiation is Causally Linked to Increased Operative Time and Perioperative Blood Transfusion in Pancreatic Ductal Adenocarcinoma.

INTRODUCTION: Blood transfusion in patients undergoing surgical resection for pancreatic ductal adenocarcinoma (PDAC) is associated with worse outcome...

Deep Learning Integration of Endoscopic Ultrasound Features and Serum Data Reveals LTB4 as a Diagnostic and Therapeutic Target in ESCC.

BACKGROUND: Early diagnosis and accurate prediction of treatment response in esophageal squamous cell carcinoma (ESCC) remain major clinical challenge...

Prediction of Symptomatic Radiation Pneumonitis in Lung Cancer Patients: A Radiomics and Dosiomics Machine Learning Approach Using the Prospective Multicenter RTOG 0617 and REQUITE Trials.

PURPOSE: Radiation-induced pneumonitis (RP) is a side effect after thoracic radiation therapy (RT). The ability to predict RP would facilitate treatme...

Contemporary Management of Radiation Necrosis: Insights and Avenues.

Radiation necrosis (RN) remains a challenging complication of upfront radiation therapy for both brain metastases and primary tumors. Despite developm...

An odyssey of monoclonal gammopathies: focusing on precursors and the progression from MGUS and SMM to multiple Myeloma, with a brief overview of novel therapeutic strategies.

Monoclonal gammopathies span a continuum from monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM) to overt...

Artificial Intelligence for radiation dose reduction in computed tomography: a narrative synthesis of clinical evidence from 2020 to 2025.

Computed tomography (CT) is essential to modern clinical practice but contributes substantially to population radiation exposure, particularly in onco...

Systemic immunometabolic profiling classifies cisplatin sensitivity states using interpretable machine learning.

Cisplatin resistance limits the effectiveness of platinum-based chemotherapy for lung adenocarcinoma, yet practical systemic diagnostics for cisplatin...