INTRODUCTION: Primary refractory disease affects 30-40% of patients diagnosed with DLBCL and is a significant challenge in disease management due to its poor prognosis. Predicting refractory status could greatly inform treatment strategies, enabling ...
PURPOSE: This study aimed to investigate a deep learning model to classify amyloid plaque deposition in the brain PET images of patients suspected of Alzheimer's disease.
INTRODUCTION: Lutetium-177 (Lu-177) prostate-specific membrane antigen (PSMA) therapy is a radionuclide treatment that prolongs overall survival in metastatic castration-resistant prostate cancer (MCRPC). We aimed to predict lesion-based treatment re...
The standard method for identifying active Brown Adipose Tissue (BAT) is [F]-Fluorodeoxyglucose ([F]-FDG) PET/CT imaging, which is costly and exposes patients to radiation, making it impractical for population studies. These issues can be addressed w...
BACKGROUND: Cardiovascular disease affects the carotid arteries, coronary arteries, aorta and the peripheral arteries. Radiomics involves the extraction of quantitative data from imaging features that are imperceptible to the eye. Radiomics analysis ...
Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico
39304599
PURPOSE: The objective of this study is to assess the prognostic efficacy of F-fluorodeoxyglucose (F-FDG) positron emission tomography/computed tomography (PET-CT) parameters in nasopharyngeal carcinoma (NPC) and identify the best machine learning (M...
OBJECTIVES: To develop and identify machine learning (ML) models using pretreatment 2-deoxy-2-[F]fluoro-D-glucose ([F]-FDG)-positron emission tomography (PET)-based radiomic features to differentiate benign from malignant parotid gland diseases (PGDs...
RATIONALE AND OBJECTIVE: To compare the performance of large language model (LLM) based Gemini and Generative Pre-trained Transformers (GPTs) in data mining and generating structured reports based on free-text PET/CT reports for breast cancer after u...
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
39236985
BACKGROUND AND PURPOSE: To evaluate the impact of a deep learning (DL)-assisted interactive contouring tool on inter-observer variability and the time taken to complete tumour contouring.
The purpose of this paper is to provide an overview of the cutting-edge applications of artificial intelligence (AI) technology in total-body positron emission tomography/computed tomography (PET/CT) scanning technology and its profound impact on the...