This study aimed to determine the optimized scan time and injected activity regimen for clinical Ga DOTATATE PET/CT in neuroendocrine tumor imaging through an experimental approach without using machine learning techniques.A NEMA PET body phantom was...
Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Nov 3, 2025
This study aimed to explore the prognostic value of the artificial intelligence-assisted lesion tracking applied to prostate-specific membrane antigen (PSMA) PET in patients with metastatic castration-resistant prostate cancer (mCRPC) treated with PS...
OBJECTIVE: This study investigated the relationship between anatomical and metabolic characteristics of large arterial perivascular adipose tissue (PVAT) and hypertensive clinical outcomes using positron emission tomography-computed tomography (PET/C...
BACKGROUND: Neuroimaging is crucial in the diagnosis of Alzheimer disease (AD). In recent years, artificial intelligence (AI)-based neuroimaging technology has rapidly developed, providing new methods for accurate diagnosis of AD, but its performance...
This study aimed to evaluate diffuse large B-cell lymphoma (DLBCL) patients who have refractory/relapsed disease and characterize the heterogeneity of DLBCL using patient-level radiomics analysis based on F-FDG PET/CT. A total of 132 patients diagnos...
BACKGROUND AND PURPOSE: Delta biomarkers that reflect changes in tumour burden over time can support personalised follow-up in head and neck cancer. However, their clinical use can be limited by the need for manual image segmentation. This study exte...
Cancer imaging : the official publication of the International Cancer Imaging Society
Aug 26, 2025
BACKGROUND: Machine learning (ML) applied to radiomics has revolutionized neuro-oncological imaging, yet the diagnostic performance of ML models based specifically on ^18F-FDG PET features in glioma remains poorly characterized.
Cancer imaging : the official publication of the International Cancer Imaging Society
Aug 19, 2025
OBJECTIVE: This study aimed to construct a multimodal imaging deep learning (DL) model integrating mpMRI and F-PSMA-PET/CT for the prediction of extraprostatic extension (EPE) in prostate cancer, and to assess its effectiveness in enhancing the diagn...
Medical oncology (Northwood, London, England)
Aug 11, 2025
Enhancing the accuracy of tumor response predictions enables the development of tailored therapeutic strategies for patients with breast cancer. In this study, we developed deep radiomic models to enhance the prediction of chemotherapy response after...
BMC medical informatics and decision making
Jul 15, 2025
PURPOSE: Accurate identification of bone marrow invasion (BMI) is critical for determining the prognosis of and treatment strategies for lymphoma. Although bone marrow biopsy (BMB) is the current gold standard, its invasive nature and sampling errors...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.