1. Diagnosis of skull-base invasion by nasopharyngeal tumors on CT with a deep-learning approach.
- Author
-
Nakagawa, Junichi, Fujima, Noriyuki, Hirata, Kenji, Harada, Taisuke, Wakabayashi, Naoto, Takano, Yuki, Homma, Akihiro, Kano, Satoshi, Minowa, Kazuyuki, and Kudo, Kohsuke
- Abstract
Purpose: To develop a convolutional neural network (CNN) model to diagnose skull-base invasion by nasopharyngeal malignancies in CT images and evaluate the model's diagnostic performance. Materials and methods: We divided 100 malignant nasopharyngeal tumor lesions into a training (n = 70) and a test (n = 30) dataset. Two head/neck radiologists reviewed CT and MRI images and determined the positive/negative skull-base invasion status of each case (training dataset: 29 invasion-positive and 41 invasion-negative; test dataset: 13 invasion-positive and 17 invasion-negative). Preprocessing involved extracting continuous slices of the nasopharynx and clivus. The preprocessed training dataset was used for transfer learning with Residual Neural Networks 50 to create a diagnostic CNN model, which was then tested on the preprocessed test dataset to determine the invasion status and model performance. Original CT images from the test dataset were reviewed by a radiologist with extensive head/neck imaging experience (senior reader: SR) and another less-experienced radiologist (junior reader: JR). Gradient-weighted class activation maps (Grad-CAMs) were created to visualize the explainability of the invasion status classification. Results: The CNN model's diagnostic accuracy was 0.973, significantly higher than those of the two radiologists (SR: 0.838; JR: 0.595). Receiver operating characteristic curve analysis gave an area under the curve of 0.953 for the CNN model (versus 0.832 and 0.617 for SR and JR; both p < 0.05). The Grad-CAMs suggested that the invasion-negative cases were present predominantly in bone marrow, while the invasion-positive cases exhibited osteosclerosis and nasopharyngeal masses. Conclusions: This CNN technique would be useful for CT-based diagnosis of skull-base invasion by nasopharyngeal malignancies. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF