Cardiovascular

Linear screening and machine learning to identify suitable candidates for active breathing control after mastectomy in left-sided breast cancer.

PURPOSE: To evaluate the dosimetric benefit of deep inspiration breath-hold (DIBH) using the Active Breathing Coordinator (ABC) for left-sided breast cancer radiotherapy and to identify patients most likely to benefit based on free-breathing (FB) anatomical and clinical features. METHODS: Thirty-one postmastectomy patients underwent FB and ABC CT scans for volumetric modulated arc therapy planning...

Screening of shared molecular markers between cervical cancer and major depressive disorder and the mechanism of CRAT/CLIC4 regulating EMT in cervical cancer cells.

BACKGROUND: Cervical cancer (CC) ranks among the most prevalent malignant neoplasms affecting women worldwide. Tumor recurrence, distant metastases, and chemotherapy resistance significantly hinder long-term clinical survival and therapeutic outcomes. Clinical studies indicate a heightened prevalence of depressive symptoms and major depressive disorder (MDD) among CC patients, suggesting the possi...

Exosomes in cancer drug resistance: dual roles in therapy failure and emerging precision therapeutics.

Exosomes play a key role in cancer, functioning both as drivers of drug resistance and as tools for therapy. Tumor-derived exosomes facilitate interce...

Predicting breast cancer pathological complete response with clinical and imaging data.

INTRODUCTION: Pathological complete response (pCR) is a key prognostic indicator in breast cancer (BC) patients receiving neoadjuvant chemotherapy (NA...

UK recommendations for Ki-67 immunohistochemical staining and interpretation in breast cancer.

Ki-67 is a well-established marker of tumour proliferation and an important prognostic and predictive biomarker in breast cancer, particularly in horm...

Tumor cells escape from therapy-induced senescence: from molecular mechanisms to targeted intervention.

Tumor recurrence represents a significant challenge in the field of tumor therapy, severely affecting patients' survival rates and quality of life. Ev...

PanMB2-Net: a deep learning framework for preoperative MB2 canal risk assessment on panoramic radiographs.

OBJECTIVES: This study aimed to develop and validate a clinically motivated artificial intelligence framework for preoperative risk assessment of the ...

Metabolic signatures of triple-negative breast cancer.

Triple-negative breast cancer (TNBC), being one of the most aggressive subtypes of breast malignancies, is characterized by poor prognosis and limited...

Radiation-induced erectile dysfunction in prostate cancer: A systematic review of pathophysiology, clinical radiobiology, and predictive modeling.

BACKGROUND: Radiation-induced erectile dysfunction (RIED) remains one of the most prevalent and distressing late toxicities among prostate cancer surv...

A Machine-Learning Model Using Pre-treatment Multimodal Data to Predict Sentinel Lymph Node Status After Neoadjuvant Chemotherapy in Operable Early-stage Breast Cancer.

RATIONALE AND OBJECTIVES: Although accurate preoperative prediction of sentinel lymph node (SLN) status in operable early-stage breast cancer (EBC) af...

Artificial intelligence for systemic therapy selection and prediction of outcomes in advanced gynecological cancers.

PURPOSE OF REVIEW: Advanced gynecologic cancers are treated broadly, with variable outcomes, even when selected by traditional precision oncology biom...

BoltzOmics: Predicting genetic variant effects on drug binding with Boltz-2.

A mechanistic understanding of how genetic variants alter drug-receptor binding is central to precision medicine, drug response prediction, and drug d...

Evaluating Risk Factors Associating With Late Recurrence After Low-Dose-Rate Brachytherapy for Prostate Cancer Using Machine Learning.

BACKGROUND: The Phoenix definition is widely used to define biochemical recurrence (BCR) after radiation therapy for prostate cancer; however, a defin...

Next-generation precision oncology in microsatellite stable colorectal cancer: integrated targeting beyond RAS and RAF.

The therapeutic landscape of colorectal cancer (CRC) has evolved with the identification of molecular subtypes, including mismatch repair-deficient/mi...

A Multimodal Deep Learning Model for Preoperative Prediction of Postoperative Complications in Gastric Cancer.

BACKGROUND: Clavien-Dindo (CD) grade ≥II complications occur in roughly one in five patients after curative gastrectomy for gastric cancer and indepen...

Deep Learning Predicts Imminent Tumor Progression in Advanced Pancreatic Adenocarcinoma Using Serial CT Scans During Chemotherapy.

Advanced pancreatic ductal adenocarcinoma (PDAC) often progresses rapidly during chemotherapy despite initial assessments of stable disease or partial...

A prospective development and evaluation of a 2D convolutional neural network-based auto-segmentation model for cervical cancer radiotherapy.

BACKGROUND: Accurate delineation of target volumes and organs at risk (OAR) is essential in radiotherapy planning for cervical cancer. Deep learning (...

Image optimization for low-dose 18F-FDG breast PET/MRI using deep learning: a pilot study.

BACKGROUND: Positron emission tomography with magnetic resonance imaging (PET/MRI) provides noninvasive molecular characterization of breast cancer an...

CMTM3 links inflammation-related transcriptional dysregulation to immune and therapeutic stratification in gastric cancer.

Gastric cancer (GC) shows strong biological heterogeneity and frequent disruption of inflammatory and metabolic programs, which affect tumor progressi...

The Promise of Machine Learning-Guided Adjuvant Chemotherapy for Resected Gallbladder Cancer.