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Objectives: We were the first to combine IETA ultrasonic features with GI-RADS and tumor biomarkers for the surveillance of endometrial carcinoma. The aim was to evaluate the efficacy of single IETA ultrasonography GI-RADS classification and combined tumor biomarkers in differentiating benign and malignant lesions in the uterine cavity and endometrium. Methods: A total of 497 patients with intrauterine and endometrial lesions who had been treated surgically between January 2017 and December 2021 were enrolled; all of them had undergone ultrasound examinations before surgery. We analyzed the correlation between the terms of ultrasonic signs of the uterine cavity and endometrial lesions defined by the expert consensus of IETA and the benign and malignant lesions and then classified these ultrasonic signs by GI-RADS. In addition, the tumor biomarkers CA125, CA15-3, CA19-9 and HE4 were combined by adjusting the classification. The results of the comprehensive analysis were compared with pathological results to analyze their diagnostic efficacy. Results: (1) The statistic analysis confirmed that there were seven independent predictors of malignant lesions, including thickened endometrium (premenopause ≥ 18.5 mm, postmenopause ≥ 15.5 mm), non-uniform endometrial echogenicity (heterogeneous with irregular cysts), endometrial midline appearance (not defined), the endometrial-myometrial junction (interrupted or not defined), intracavitary fluid (ground glass or "mixed" echogenicity), color score (3~4 points) and vascular pattern (focal origin multiple vessels or multifocal origin multiple vessels). (2) In traditional ultrasound GI-RADS (U-T-GI-RADS), if category 4a was taken as the cut-off value of benign and malignant, the diagnostic sensitivity, specificity, PPV, NPV and diagnostic accuracy were 97.2%, 65.2%, 44.0%, 98.8% and 72.2%, respectively, and the area under the ROC curve (AUC) was 0.812. If 4b was taken as the cut-off value, the diagnostic sensitivity, specificity, PPV, NPV diagnostic accuracy and AUC were 88.1%, 92.0%, 75.6%, 96.5% and 91.2%, 0.900, respectively. The diagnostic sensitivity, specificity, PPV, NPV diagnostic accuracy and AUC were 75.2%, 98.5%, 93.2%, 93.4%, 93.4% and 0.868, respectively, when taking category 5 as the cutoff point. In modified ultrasound GI-RADS (U-M-GI-RADS), if 4a was taken as the cut-off value, The diagnostic efficacy was the same as U-T-GI-RADS. If 4b was taken as the cut-off value, the diagnostic sensitivity, specificity, PPV, NPV, diagnostic accuracy and AUC were 88.1%, 92.3%, 76.2%, 96.5%, 91.3% and 0.902, respectively. If 4c was taken as the cutoff point, the diagnostic sensitivity, specificity, PPV, NPV diagnostic accuracy and AUC were 75.2%, 98.7%, 94.3%, 93.4%, 93.6% and 0.870, respectively. The diagnostic sensitivity, specificity, PPV, NPV diagnostic accuracy and AUC were 66.1%, 99.7%, 98.6%, 91.3%, 92.4% and 0.829, respectively, if taking category 5 as the cutoff point. (3) In the comprehensive diagnostic method of U-T-GI-RADS combined tumor biomarkers results, the AUC of class 4a, 4b and 5 as the cutoff value was 0.877, 0.888 and 0.738, respectively. The AUC of class 4a, 4b, 4c and 5 as the cutoff value in the comprehensive diagnostic method of U-M-GI-RADS combined tumor biomarkers results was 0.877, 0.888, 0.851 and 0.725, respectively. There was no significant difference in diagnostic efficiency between the two comprehensive diagnostic methods. Conclusions: In this study, no matter which diagnostic method was used, the best cutoff value for predicting malignant EC was ≥GI-RADS 4b. The GI-RADS classification had good performance in discriminating EC. The tumor biomarkers, CA125, CA19-9, CA15-3 and HE4, could improve the diagnostic efficacy for preoperative endometrial carcinoma assessment.
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BACKGROUND: Adnexal masses, mostly benign, are common in the female genital system. However, adnexal masses are the leading cause of death among women with gynecologic cancer. Ultrasound is a common imaging method for diagnosing adnexal masses. Gynecologic Imaging Reporting and Data System (GI-RADS) is a useful diagnostic tool based on objective ultrasound features to diagnose the malignancy of the female genital system. Therefore, we conducted a meta-analysis to evaluate the ability of GI-RADS to differentiate adnexal masses. METHODS: Published articles were searched in PubMed, Medline, and Embase from 1990 to February 2020. Pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio, and area under the curve (AUC) were estimated via the extracted data from the selected studies. RESULTS: Ten studies and 2,474 patients were included in this meta-analysis. The pooled sensitivity of selected studies was 0.95 [95% confidence intervals (CI): 0.94-0.97], and the pooled specificity was 0.86 (95% CI: 0.84-0.88). The pooled NLR and PLR were 0.06 (95% CI: 0.04-0.10), and 8.30 (95% CI: 4.93-13.97), respectively. Moreover, the pooled diagnostic odds ratio for GI-RADS was 174.59 (95% CI: 76.70-397.42), and the AUC was 0.9806. CONCLUSIONS: This research indicates that GI-RADS might be a valuable tool to distinguish malignancies from adnexal masses.
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OBJETIVO: evaluar la experiencia en la utilización del método GIRADS para clasificar masas anexiales a diez años de su primera publicación. MÉTODO: Se realizó búsqueda de estudios que utilizan el sistema GIRADS: Medline (Pubmed), Google Scholar y Web of Science, desde enero de 2009 hasta diciembre de 2019. Se calculó la sensibilidad y especificidad agrupada, Likelihood ratio (LR) (+) y LR (-) y Odds ratio de diagnóstico (DOR). La calidad de los estudios se evaluó con QUADAS-2. RESULTADOS: Se identificaron 15 estudios y se incluyeron 13 de ellos con 4473 masas, 878 de ellas malignas. La prevalencia media de malignidad ovárica fue del 23 % y la agrupada de 19.6%. El riesgo de sesgo fue alto en cuatro estudios para el dominio "selección de pacientes" y fue bajo en todos en todos los estudios para los dominios "prueba índice" y "prueba de referencia". La sensibilidad, especificidad, LR (+) y LR (-) agrupadas y el DOR del sistema GIRADS para clasificar las masas anexiales fueron: 96.8% (intervalo de confianza [IC] 95% = 94% - 98%), 91.2 % (IC 95 % = 85% - 94%), 11.0 (IC 95% = 6.9 -13.4) y 0.035 (IC 95% = 0.02- 0.09), y 209 (IC 95% = 99-444), respectivamente. La heterogeneidad fue alta para la sensibilidad y especificidad. De acuerdo a la metaregresión, la heterogeneidad entre los estudios se explica por la prevalencia de malignidad, múltiples observadores y la ausencia de diagnóstico histopatológico para todos los casos incluidos en un determinado estudio. CONCLUSIÓN: el sistema GIRADS tiene un buen rendimiento diagnóstico para clasificar masas anexiales.
OBJECTIVE: to evaluate the experience of using GIRADS method to classify adnexal masses ten years after its publication. METHOD: A search was carried out for studies reporting on the use of the GIRADS system in the Medline (Pubmed), Google Scholar and Web of Science databases, from January 2009 to December 2019. Pooled sensitivity and specificity, Likelihood ratio (LR) (+) and LR (-) and Diagnostic Odds ratio (DOR) were calculated. The quality of the studies was assessed by QUADAS-2. RESULTS: 15 studies were identified, and 13 of them were included with 4473 masses, of which 878 were malignant. The mean prevalence of ovarian malignancy was 23% and the prevalence pooled. of 19.6%. The risk of bias was high in four studies for the domain 'patient selection' and low for all studies for the domains 'index test' and 'reference test'. The sensitivity, specificity, pooled LR (+) and LR (-) and the DOR of the GIRADS system to classify adnexal masses were 96.8% (95% confidence interval [CI] = 94% -98%), 91.2 % (95% CI = 85% -94%), 11.0 (95% CI = 6.9-13.4) and 0.035 (95% CI = 0.02-0.09), and 209 (95% CI = 99-444), respectively. Heterogeneity was high for both sensitivity and specificity. According to meta-regression, this heterogeneity was explained by the prevalence of malignancy, the use of multiple observers, and the absence of histopathological diagnosis for all cases included in a given study. CONCLUSION: the GIRADS system has a good diagnostic performance to classify adnexal masses.
Subject(s)
Humans , Female , Ovarian Neoplasms/diagnostic imaging , Adnexal Diseases/pathology , Adnexal Diseases/diagnostic imaging , Radiology Information Systems , ROC Curve , Sensitivity and Specificity , Publication Bias , Risk AssessmentABSTRACT
Objective To evaluate the efficacy of the combination of gynecologic imaging reporting and data system (GI-RADS) uhrasonographic stratification and 3D contrast-enhanced ultrasonography (3D-CEUS) in identifying malignant lesions from benign ovarian masses.Methods Both of 2D ultrasound (2D-US) and 3D-CEUS were performed on 102 patients with ovarian masses.The perfusion characteristics of ovarian masses were observed with 3D-CEUS,and the 2D-US features of ovarian masses were analyzed based on GI-RADS.Simple and multiple Logistic regression analysis were used to investigate whether the independent risk predictors in differential diagnosis of benign and malignant ovarian could be confirmed.In addition,ROC curves were drawn.The diagnostic efficacy of GI-RADS combined with 3D-CEUS scoring system was evaluated and compared with that of only GI-RADS.Results Simple and multiple Logistic regression analysis confirmed that there were 8 independent predictors of malignant masses,including large papillary projections (≥7 mm),separated or wall thickness ≥3 mm,central blood flow,the proportion of solid part ≥50％,combination of ascites,high level enhancement,uneven distribution of contrast media in enhanced solid part and the vascular with characteristics as dense,tortuous and anfractuous.When using 4 points as the cut-off,the area under the curve (AUC) of GI-RADS combined with 3D-CEUS scoring system in identifying malignant ovarian masses was 0.969,higher than that of only GI-RADS (0.839;Z=1.64,P=0.029).Furthermore,the scoring system showed higher sensitivity,specificity,positive predictive value,negative predictive value and accuracy (all P＜0.001).Conclusion The combination of GI-RADS with 3D-CEUS can be more effective to distinguish malignant lesions from benign ovarian masses.
