To investigate the diagnostic consistency between physicians in differentiating malignant from benign ovarian tumors by using IOTA LR2 model.
Methods:
The ultrasonographic images of 876 ovarian tumors were retrospectively analyzed by two physicians with different seniorities in the absence of clinical and pathological data. The IOTA LR2 model was used to evaluate the ultrasonographic images. The results were compared with the pathological results to determine the diagnostic efficacy. Kappa test was used to determine the consisten
cy between two physicians.
Results:
Among 876 ovarian tumors
837 cases were benign and 39 were malignant. The sensitivity and specificity of the two physicians were 76.9%
67.0% and 71.8%
76.0%
respectively
and the area under the receiver operating characteristic (ROC) curve was 0.8680.040 and 0.8470.043
respectively. Kappa was 0.659 between the two physicians (
P
0.01).
Conclusion:
IOTA LR2 model has a high diagnostic value in differentiating malignant from benign ovarian tumors
and the diagnostic consistency between physicians is good.
The diagnostic value of conventional MRI in borderline ovarian tumor
CT and MRI features of ovarian cystic-solid tumors in children
Ultrasonic misdiagnosis of borderline ovarian endometrioid adenofibroma: a case report
A study on the value of contrast-enhanced ultrasound in adjusting O-RADS grading of ovarian adnexal masses
Value of color Doppler ultrasound Finkler scoring system combined with serum tumor markers in differential diagnosis of benign and malignant ovarian tumors in children
Related Author
Jun YANG
Jia LIU
Linchen ZHANG
Fenghua MA
Jinwei QIANG
Yajia GU
Haiming LI
Siwei LU
Related Institution
Department of Radiology, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University
Department of Radiology, Obstetrics & Gynecology Hospital, Fudan University
Department of Pathology, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University
Department of Radiology, Jinshan Hospital, Shanghai Medical College, Fudan University
Department of Radiology, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine