Related Experiment Video
Updated: Jan 11, 2026
A Coregistered Ultrasound and Photoacoustic Imaging Protocol for the Transvaginal Imaging of Ovarian Lesions
Published on: March 3, 2023
OTC-NET: A Multimodal Method for Accurate Diagnosis of Ovarian Cancer in O-RADS Category 4 Masses
Peizhong Liu1, Yidan Ruan2, Yuling Fan1
1College of Engineering, Huaqiao University, Quanzhou 362021, China.
Background:
Ovarian cancer is the deadliest female reproductive malignancy. Accurate preoperative differentiation of benign and malignant ovarian masses is critical for appropriate treatment. O-RADS category 4 lesions present a wide range of malignant risk, challenging radiologists. Ultrasonic images are the primary focus of current deep learning models, with no consideration for clinical data.
Methods:
We proposed OTC-NET, a model that uses multimodal data for classification, which combines ultrasound images and clinical information to improve the classification ability of O-RADS 4 ovarian masses.
Results:
OTC-NET outperforms seven deep learning models and three radiologists of varying experience, with AUC significantly higher than junior (p < 0.001), intermediate (p < 0.01), and senior (p < 0.05) radiologists. Additionally, OTC-NET-assisted diagnosis notably improves AUC and accuracy of junior and senior radiologists (p < 0.05).
Conclusions:
These results indicate that OTC-NET provides superior diagnostic accuracy and has strong potential for clinical application.
