Oncology ImagingArchives
[18F]AlF-NOTA-PCP2 PET/CT to Assess PD-L1 Status in Head and Neck Cancer: Head-to-Head Comparison With [18F]FDG PET/CT.
Oncology Imaging 1 min.
While PD-L1 expression heterogeneity limits the predictive value of localized biopsies, molecular imaging offers a dynamic alternative. We developed [18F]AlF-NOTA-PCP2, a hydrophilic PD-L1-targeted peptide tracer, and first evaluated its clinical utility in head and neck (HNC) cancer through a head-to-head...
Interpretable deep learning for multicenter gastric cancer T staging from CT images
Oncology Imaging 5 min.
Gastric cancer is a major global health burden and remains among the top causes of cancer-related deaths worldwide1. Despite advances, many patients still present with advanced disease due to limited early detection, complicating treatment2. Accurate preoperative T staging guides decisions from endoscopic...
An integrated radiomics and deep learning model on multisequence MRI for preoperative prediction of lymphovascular space invasion in endometrial cancer
Oncology Imaging 5 min.
Endometrial cancer (EC) is the second most common gynecologic malignancy in China, with an increasing incidence [1]. Contemporary treatment strategies increasingly emphasize personalized care. The 2021 joint guidelines from the European Society of Gynecological Oncology (ESGO), the European Society for...
Development and validation of a CT-radiomics model for the diagnosis of lung cancer associated with cystic airspaces: a multicenter study
Oncology Imaging 4 min.
Lung cancer associated with cystic airspaces (LCCA) is a relatively uncommon form of lung malignancy. The Fleischner Society initially defined lung cystic airspace in 1996 as an enlarged peripheral air-containing unit surrounded by a variable thickness wall [1]. In the early stages, cystic airspaces...
