Deep Learning Prediction of Ovarian Malignancy at US Compared with O-RADS and Expert Assessment.

Background Deep learning (DL) algorithms could improve the classification of ovarian tumors assessed with multimodal US. Purpose To develop DL algorithms for the automated classification of benign versus malignant ovarian tumors assessed with US and to compare algorithm performance to Ovarian-Adnexal Reporting and Data System (O-RADS) and subjective expert assessment for malignancy. Materials and Methods This retrospective study included consecutive women with ovarian tumors undergoing gray scale and color Doppler US from January 2019 to November 2019. Histopathologic analysis was the reference standard. The data set was divided into training (70%), validation (10%), and test (20%) sets. Algorithms modified from residual network (ResNet) with two fusion strategies (feature fusion [hereafter, DLfeature] or decision fusion [hereafter, DLdecision]) were developed. DL prediction of malignancy was compared with O-RADS risk categorization and expert assessment by area under the receiver operating characteristic curve (AUC) analysis in the test set. Results A total of 422 women (mean age, 46.4 years ± 14.8 [SD]) with 304 benign and 118 malignant tumors were included; there were 337 women in the training and validation data set and 85 women in the test data set. DLfeature had an AUC of 0.93 (95% CI: 0.85, 0.97) for classifying malignant from benign ovarian tumors, comparable with O-RADS (AUC, 0.92; 95% CI: 0.85, 0.97; P = .88) and expert assessment (AUC, 0.97; 95% CI: 0.91, 0.99; P = .07), and similar to DLdecision (AUC, 0.90; 95% CI: 0.82, 0.96; P = .29). DLdecision, DLfeature, O-RADS, and expert assessment achieved sensitivities of 92%, 92%, 92%, and 96%, respectively, and specificities of 80%, 85%, 89%, and 87%, respectively, for malignancy. Conclusion Deep learning algorithms developed by using multimodal US images may distinguish malignant from benign ovarian tumors with diagnostic performance comparable to expert subjective and Ovarian-Adnexal Reporting and Data System assessment. © RSNA, 2022 Online supplemental material is available for this article.

Ovarian sex cord stromal tumours: analysis of the clinical and sonographic characteristics of different histopathologic subtypes.

BACKGROUND: Ovarian sex cord stromal tumours (OSCSTs) are rare ovarian tumours and include different histopathologic subtypes. This study aimed to analyse the clinical and sonographic characteristics of different histopathologic OSCST subtypes. METHODS: A total of 63 patients with surgically proven OSCSTs were enrolled in this retrospective study to analyse their clinical and sonographic features. Ultrasound examinations and predictive models were performed before surgery. The clinical and sonographic findings were compared according to the type of OSCST based on the histopathological diagnosis. RESULTS: The mean age of 63 patients was 52.17 years (range: 17-78 years). Eighteen patients experienced irregular vaginal bleeding (28.57% 18/63), 7 patients exhibited abnormal body hair (11.11%). 2 patients (3.17%) showed an increased level of CA125, and 25 patients (39.68%, 25/63) showed an increased level of testosterone. Forty-two patients had ovarian thecoma-fibroma groups (OTFGs). Six patients had Sertoli-Leydig cell tumours (S-LCTs), 4 patients had Leydig cell tumours (LCTs), 8 patients had ovarian granulosa cell tumours (OGCTs), 2 patients had ovarian steroid cell tumours, not otherwise specified (OSCTs-NOS), and one patient had sclerosing stromal tumours (SSTs). The mean diameter of the tumour was 47.9 mm (range: 10-258 mm). Forty-seven masses were hypoechoic (74.60%). Twenty-eight masses had posterior echo attenuation, 22 masses exhibited abundant Doppler flow signals (34.92%), and one patient had ascites (1.59%). The diagnostic accuracy of the Simple Rules (SR) and the Assessment of Different NEoplasias in the adneXa (ADNEX) model in distinguishing benign and malignant OSCSTs was 44% (30/63) and 84% (53/63), respectively. The diagnostic accuracy of the SR for OTFGs, S-LCTs & LCTs & OSCTs-NOS, OGCTs, and SSTs was 47.6% (20/42), 16.67% (2/12), 100% (8/8), and 0% (0/1), respectively. The diagnostic accuracy of the ADNEX model for OTFGs, S-LCTs & LCTs & OSCTs-NOS, OGCTs, and SSTs was 93% (31/42), 58.33% (7/12), 75% (6/8), and 100% (1/1), respectively. CONCLUSIONS: OSCSTs generally appear as a solid mass on ultrasound. Posterior echo attenuation indicates an OTFG. A solid mass with abundant Doppler flow signals indicates an S-LCT, LCT, OSCT-NOS or OGCT. Current predictive models are not very effective, but symptoms, sonographic features and serum hormones are helpful for diagnosis.

Ovarian thecoma-fibroma groups: clinical and sonographic features with pathological comparison.

BACKGROUND: Ovarian thecoma-fibroma groups (OTFG) are uncommon sex cord-stromal neoplasms. The objective of the study was to demonstrate clinical and sonographic features of OTFG and compare with surgical histopathology. METHODS: A total of 61 patients with surgically proven OTFG were enrolled in this retrospective study to demonstrate its clinical and sonographic features and to compare with pathological findings. Gray scale and color Doppler sonography were performed presurgically with either transabdominal or transvaginal approach to image pelvic structures and lesions. The clinical findings and sonographic appearances were compared with the types of the OTFG tumors based on the histopathological diagnosis. RESULTS: The mean patient age was 53.57 (range, 26-86) years. There were 63.93% (39/61) patients in postmenopausal and 63.93% (39/61) patients with no clinical symptoms. Ultrasound findings of OTFG revealed as solid tumors with a typical feature of well-demarcated hypoechoic masses in 70.49% (43/61), among which 74.41% (32/43) tumors were smaller than 5 cm in diameter. There were 17 mixed echogenic masses with calcification, hemorrhage, or cyst, among which 70.59% (12/17) lesions were larger than 5 cm in diameter. Acoustic attenuation of the tumor was presented in 44.26% (27/61) of the cases. Doppler flow signals within the tumors were found in 20 cases (32.79%), in which 80% (16/20) had minimal or moderate flow signals. Ascites was detected in 32.79% (20/61) of the cases, Megi's syndrome was found in 1 case. Final pathology revealed 41 (67.21%) thecoma-fibromas, 15 (24.59%) fibromas, 4 (6.56%) thecomas and 1 (1.64%) fibrosarcoma. There were 58 patients underwent cancer antigen 125 (CA125) test, and 20.69% (12/58) showed an elevated level. The diameter of tumors was found to be significantly correlated with CA125 level (p < 0.01) and the amount of ascites fluid (p < 0.05). CONCLUSIONS: The typical sonographic features of OTFG include adnexal hypoechoic masses with clear border and acoustic attenuation as well as minimal Doppler flow signals. All the aforementioned features could make ultrasound imaging as a assistent tool improve the preoperative diagnostic accuracy.