Oncology ImagingArchives
A SHAP-interpretable XGBoost model: MRI-based intratumoral perfusion heterogeneity predicts HER2-zero, -low, and -positive ternary expression status in breast cancer
Oncology Imaging 5 min.
Breast cancer is a prevalent malignant tumor among women worldwide, accounting for 11.6% of new cases annually [1]. Human epidermal growth factor receptor 2 (HER-2) is a significant factor influencing the prognosis of patients with breast cancer. It is a crucial gene target for breast cancer treatment...
Integrated primary tumor and all metastatic lymph nodes radiomics from 18 F-FDG PET/CT for precise M1 subclassification in nasopharyngeal carcinoma
Oncology Imaging 5 min.
Nasopharyngeal carcinoma (NPC) shows a markedly higher incidence in endemic regions––especially China and Southeast Asia––but remains relatively rare in Western populations [1, 2]. Its global incidence and mortality are projected to increase substantially by 2040, particularly...
Interpretable machine learning using CT radiomics predicts pathological upgrading after secondary resection in non-muscle-invasive bladder cancer
Oncology Imaging 5 min.
Bladder cancer is a common malignant tumor of the urinary system worldwide, with more than 600,000 new cases and over 200,000 deaths annually. Its incidence and mortality rates rank 10th and 13th among all malignant tumors, respectively [1, 2]. Pathologically, bladder cancer is primarily classified into...
Diagnostic accuracy of FDG-PET-CT to predict axillary lymph node response after neo-adjuvant chemotherapy in lymph node-positive breast cancer patients
Oncology Imaging 5 min.
Worldwide, breast cancer is the most commonly diagnosed malignancy in women [1]. The mainstay of treatment is surgery with adjuvant therapy including chemo, hormonal and radiotherapy. The aims of neo-adjuvant chemotherapy (NAC) include de-escalating surgery and potentially achieving pathological complete...
