Breast Cancer

Digital skills of therapeutic radiographers/radiation therapists - Document analysis for a European educational curriculum.

INTRODUCTION: It is estimated that around 50% of cancer patients require Radiotherapy (RT) at some point during their treatment, hence Therapeutic Radiographers/Radiation Therapists (TR/RTTs) have a key role to play in patient management. It is essential for TR/RTTs to keep abreast with new technologies and continuously develop the digital skills necessary for safe RT practice. The RT profession a...

The Effect of Salvage Radiation Therapy on Survival, Functional Outcomes, and Quality of Life in Men with Persistent Prostate-specific Antigen After Robot-Assisted Radical Prostatectomy: Which Patient Benefits More?

PURPOSE: The aim of this study was to evaluate the effect of salvage radiation therapy (sRT) on survival, functional outcomes, and quality of life in men with persistent prostate-specific antigen (PSA >0.1 ng/mL) after a robot-assisted radical prostatectomy (RARP) and reveal subgroups that benefit more from sRT.

A deep learning and Monte Carlo based framework for bioluminescence imaging center of mass-guided glioblastoma targeting.

Bioluminescence imaging (BLI) is a valuable tool for non-invasive monitoring of glioblastoma multiforme (GBM) tumor-bearing small animals without incu...

Predicting the outcome of radiotherapy in brain metastasis by integrating the clinical and MRI-based deep learning features.

BACKGROUND: A considerable proportion of metastatic brain tumors progress locally despite stereotactic radiation treatment, and it can take months bef...

Eliminating CT radiation for clinical PET examination using deep learning.

Clinical PET/CT examinations rely on CT modality for anatomical localization and attenuation correction of the PET data. However, the use of CT signif...

MVFStain: Multiple virtual functional stain histopathology images generation based on specific domain mapping.

To the best of our knowledge, artificial intelligence stain generation is an urgent requirement for histopathology images. Pathological examinations u...

Weakly supervised deep learning for prediction of treatment effectiveness on ovarian cancer from histopathology images.

Despite the progress made during the last two decades in the surgery and chemotherapy of ovarian cancer, more than 70 % of advanced patients are with ...

Vomiting Management and Effect Prediction after Early Chemotherapy of Lung Cancer with Diffusion-Weighted Imaging under Artificial Intelligence Algorithm and Comfort Care Intervention.

This aim of this research was to explore the evaluation and prediction value of diffusion-weighted imaging (DWI) under artificial intelligence algorit...

Deep learning based analysis of microstructured materials for thermal radiation control.

Microstructured materials that can selectively control the optical properties are crucial for the development of thermal management systems in aerospa...

Liver Attenuation Assessment in Reduced Radiation Chest Computed Tomography.

OBJECTIVE: This study aimed to evaluate the reliability of liver and spleen Hounsfield units (HU) measurements in reduced radiation computed tomograph...

Analysis of robot-assisted nipple-sparing mastectomy using the da Vinci SP system.

BACKGROUND: As patients tend to be diagnosed with breast cancer at an early stage, the demand for better cosmetic outcomes has increased. Several stud...

A deep learning-based radiomics approach to predict head and neck tumor regression for adaptive radiotherapy.

Early regression-the regression in tumor volume during the initial phase of radiotherapy (approximately 2 weeks after treatment initiation)-is a commo...

Prediction of the position of external markers using a recurrent neural network trained with unbiased online recurrent optimization for safe lung cancer radiotherapy.

BACKGROUND AND OBJECTIVE: During lung cancer radiotherapy, the position of infrared reflective objects on the chest can be recorded to estimate the tu...

Deep learning with whole slide images can improve the prognostic risk stratification with stage III colorectal cancer.

BACKGROUND AND OBJECTIVE: Adjuvant chemotherapy is recommended as standard treatment for colorectal cancer (CRC) with stage III according to TNM stage...

Robotic nephroureterectomy in the management of upper tract urothelial cancer: inching toward standard of care?

Upper-tract urothelial carcinoma is a relatively rare malignancy. Current guidelines strongly recommend radical nephroureterectomy with bladder cuff e...

Computed Tomography Texture Features and Risk Factor Analysis of Postoperative Recurrence of Patients with Advanced Gastric Cancer after Radical Treatment under Artificial Intelligence Algorithm.

Computer tomography texture analysis (CTTA) based on the V-Net convolutional neural network (CNN) algorithm was used to analyze the recurrence of adva...

Design of Nuclear Radiation Monitoring System in Floor Exploration Based on Deep Learning.

Nuclear radiation environmental monitoring has become an important issue in floor surveys. From the perspective of regional environmental nuclear radi...

AI-based optimization for US-guided radiation therapy of the prostate.

OBJECTIVES: Fast volumetric ultrasound presents an interesting modality for continuous and real-time intra-fractional target tracking in radiation the...

End-to-end deep learning for interior tomography with low-dose x-ray CT.

There are several x-ray computed tomography (CT) scanning strategies used to reduce radiation dose, such as (1) sparse-view CT, (2) low-dose CT and (3...

Reversing radiation-induced immunosuppression using a new therapeutic modality.

Radiation-induced immune suppression poses significant health challenges for millions of patients undergoing cancer chemotherapy and radiotherapy trea...