Breast Cancer

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 navigation, and robotic assistance, has progressively expanded its role in the management of a broad spectrum of spinal disorders. These approaches were developed to limit muscular disruption and soft tissue damage while maintaining clinical and radio...

Comparison of Left Ventricular Ejection Fraction Among 18F-FDG Dual-Gated PET/CT, Single-Gated PET/MRI, and Cardiac MRI.

Left ventricular ejection fraction (LVEF) is a critical parameter in the evaluation of cardiac function, and its measurement can guide treatment decisions in patients with breast cancer undergoing chemotherapy. We obtained LVEF measurements with gated PET-based methods to determine if they produced comparable results to those obtained with cardiac MRI. Methods: Patients with breast cancer who visi...

Composite pathway-guided Cox modeling for interpretable survival prediction in breast cancer.

Accurate survival prediction in breast cancer is essential for patient risk stratification and personalized treatment planning. Although transcriptomi...

Predicting intrahepatic recurrence of colorectal cancer liver metastases after curative hepatectomy using a machine learning model with data integration of ultrasound radiomics and clinicopathological parameters.

OBJECTIVES: To develop and validate a machine learning model integrating ultrasound radiomics and clinicopathological parameters to predict intrahepat...

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...

Identification of potential biomarkers and therapeutic targets for liver cirrhosis based on Mendelian randomization and machine learning.

BACKGROUND: Liver cirrhosis(LC) represents the end stage of chronic liver disease, yet reliable molecular markers remain limited. This study aimed to ...

Homologous recombination deficiency in Ovarian cancer: The game-changer for first-line maintenance therapy.

Homologous recombination deficiency (HRD) plays a central role in the pathogenesis and therapeutic vulnerability of epithelial ovarian cancer (EOC), p...

Artificial intelligence-based analysis of thrombotic and infectious risk factors in peripherally inserted central catheters (PICCs).

INTRODUCTION: Peripherally inserted central catheters (PICCs) are increasingly used in France for prolonged intravenous therapies such as chemotherapy...

Optimizing material composition determination in dual-energy computed tomography: a comparative study of a linear model and a fully connected neural network.

Accurate elemental decomposition in dual-energy computed tomography (DECT) is crucial for precision in radiation therapy planning. We present a compar...

Improving visibility of small anatomical details on low and ultra-low dose computed tomography with artificial intelligence-based image reconstructions.

To assess how computed tomography (CT) image reconstruction techniques affect perceived diagnostic image quality at varying radiation dose levels in c...

Functional-based multi-omics early prediction of radiation pneumonitis in NSCLC using AI-generated perfusion and ventilation from planning CT.

ObjectiveThis study aims to develop a functional-based multi-omics model for early prediction of radiation pneumonitis (RP) by extracting radiomic and...

Hulled Rice or husk? Synchrotron radiation XRF and deep learning approach for the determination of the geographical origin of Chinese rice samples.

Accurate authentication of rice geographical origin is crucial for food safety and fraud prevention. Synchrotron radiation X-ray fluorescence (SR-XRF)...

MuTriM: A multiscale deep learning model integrating longitudinal radiomics and pathomic features for predicting recurrence and adjuvant radiation benefit in breast cancer.

PURPOSE: We present MuTriM, a multimodal deep learning model integrating DCE-MRI and whole-slide pathology to predict survival and radiation benefit i...

CT-based radiomics for predicting the treatment response to PD-1/PD-L1 inhibitors combined with chemotherapy in unresectable gastric cancer.

OBJECTIVE: To develop and validate a CT-based radiomics model to predict immunotherapy response in unresectable gastric cancer and explore its underly...

Deep learning on histopathological images to predict breast cancer recurrence risk and chemotherapy benefit: a multicentre, model development and validation study.

BACKGROUND: Genomic assays such as Oncotype DX have transformed adjuvant treatment selection for hormone receptor-positive, HER2-negative, early breas...

Assessment Tools of Radiation Skin Injury in Head and Neck Cancer: A Narrative Review of Preclinical and Clinical Studies.

Radiation skin injury (RSI) is an unavoidable side effect of radiotherapy that delays the treatment process and affects patients' quality of life. How...

Automatic segmentation of clinical target volume for radiation therapy in breast-conserving patients and exploration of clinical factors influential to its performance.

OBJECTIVES: To develop and validate a deep learning model for whole breast clinical target volume (CTV) contouring and evaluate clinical features affe...

Machine learning and logistic regression in estimating survival in patients with high-malignant deep-seated soft tissue sarcomas: development and analysis based on a population-based retrospective cohort.

BACKGROUND AND PURPOSE:  Soft tissue sarcomas are a heterogeneous group of malignant tumors with a high risk of metastasis, primarily to the lungs, ma...

SMC4/SMAD3/NF-κB axis drives cervical cancer progression and radioresistance via DNA damage repair and immune modulation.

OBJECTIVE: Cervical cancer remains a significant global health burden, with the molecular determinants of its progression and therapeutic resistance n...