International journal of radiation oncology, biology, physics
31201897
PURPOSE: Xerostomia commonly occurs in patients who undergo head and neck radiation therapy and can seriously affect patients' quality of life. In this study, we developed a xerostomia prediction model with radiation treatment data using a 3-dimensio...
IMPORTANCE: Postoperative chemoradiation is the standard of care for cancers with positive margins or extracapsular extension, but the benefit of chemotherapy is unclear for patients with other intermediate risk features.
OBJECTIVES: This preliminary study aimed to develop a deep learning (DL) model using diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC) maps to predict local recurrence and 2-year progression-free survival (PFS) in laryngeal an...
OBJECTIVES: To use convolutional neural network for fully automated segmentation and radiomics features extraction of hypopharyngeal cancer (HPC) tumor in MRI.
OBJECTIVES: To develop and assess a radiomics-based prediction model for distinguishing T2/T3 staging of laryngeal and hypopharyngeal squamous cell carcinoma (LHSCC) METHODS: A total of 118 patients with pathologically proven LHSCC were enrolled in t...
International journal of radiation oncology, biology, physics
39788389
PURPOSE: Deep learning is a promising approach to increase reproducibility and time-efficiency of gross tumor volume (GTV) delineation in head and neck cancer, but model evaluation primarily relies on manual GTV delineations as reference annotation, ...