Cargando…
IETA Ultrasonic Features Combined with GI-RADS Classification System and Tumor Biomarkers for Surveillance of Endometrial Carcinoma: An Innovative Study
SIMPLE SUMMARY: Endometrial cancer (EC) is one of the most common malignant tumors in gynecology. The prognosis of patients with early EC is good; however, high-risk EC patients have a poor prognosis because they have a higher risk of tumor recurrence, lymph node metastasis, and distant tumor spread...
Autores principales: | , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9688181/ https://www.ncbi.nlm.nih.gov/pubmed/36428723 http://dx.doi.org/10.3390/cancers14225631 |
_version_ | 1784836202557341696 |
---|---|
author | Lin, Dongmei Wang, Hui Liu, Lu Zhao, Liang Chen, Jing Tian, Hongyan Gao, Lei Wu, Beibei Zhang, Jing Guo, Xia Hao, Yi |
author_facet | Lin, Dongmei Wang, Hui Liu, Lu Zhao, Liang Chen, Jing Tian, Hongyan Gao, Lei Wu, Beibei Zhang, Jing Guo, Xia Hao, Yi |
author_sort | Lin, Dongmei |
collection | PubMed |
description | SIMPLE SUMMARY: Endometrial cancer (EC) is one of the most common malignant tumors in gynecology. The prognosis of patients with early EC is good; however, high-risk EC patients have a poor prognosis because they have a higher risk of tumor recurrence, lymph node metastasis, and distant tumor spread. At present, there are no structured ultrasound reporting standards for endometrial lesions. The high specificity of serum tumor biomarkers for EC has not been found in current studies. The present results show that the international endometrial tumor analysis (IETA) ultrasonic features combined with gynecologic imaging reporting and data system (GI-RADS) and tumor biomarkers provides a novel, safe, real-time technology for surveillance of EC. This study is clinically significant since it shows that the IETA ultrasonic features combined with the GI-RADS classification system and tumor biomarkers method have good performance in discriminating EC. It has the potential to be used as a screening tool to distinguish the benign and malignant lesions of the uterine cavity or endometrium very well. ABSTRACT: 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. |
format | Online Article Text |
id | pubmed-9688181 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-96881812022-11-25 IETA Ultrasonic Features Combined with GI-RADS Classification System and Tumor Biomarkers for Surveillance of Endometrial Carcinoma: An Innovative Study Lin, Dongmei Wang, Hui Liu, Lu Zhao, Liang Chen, Jing Tian, Hongyan Gao, Lei Wu, Beibei Zhang, Jing Guo, Xia Hao, Yi Cancers (Basel) Article SIMPLE SUMMARY: Endometrial cancer (EC) is one of the most common malignant tumors in gynecology. The prognosis of patients with early EC is good; however, high-risk EC patients have a poor prognosis because they have a higher risk of tumor recurrence, lymph node metastasis, and distant tumor spread. At present, there are no structured ultrasound reporting standards for endometrial lesions. The high specificity of serum tumor biomarkers for EC has not been found in current studies. The present results show that the international endometrial tumor analysis (IETA) ultrasonic features combined with gynecologic imaging reporting and data system (GI-RADS) and tumor biomarkers provides a novel, safe, real-time technology for surveillance of EC. This study is clinically significant since it shows that the IETA ultrasonic features combined with the GI-RADS classification system and tumor biomarkers method have good performance in discriminating EC. It has the potential to be used as a screening tool to distinguish the benign and malignant lesions of the uterine cavity or endometrium very well. ABSTRACT: 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. MDPI 2022-11-16 /pmc/articles/PMC9688181/ /pubmed/36428723 http://dx.doi.org/10.3390/cancers14225631 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Lin, Dongmei Wang, Hui Liu, Lu Zhao, Liang Chen, Jing Tian, Hongyan Gao, Lei Wu, Beibei Zhang, Jing Guo, Xia Hao, Yi IETA Ultrasonic Features Combined with GI-RADS Classification System and Tumor Biomarkers for Surveillance of Endometrial Carcinoma: An Innovative Study |
title | IETA Ultrasonic Features Combined with GI-RADS Classification System and Tumor Biomarkers for Surveillance of Endometrial Carcinoma: An Innovative Study |
title_full | IETA Ultrasonic Features Combined with GI-RADS Classification System and Tumor Biomarkers for Surveillance of Endometrial Carcinoma: An Innovative Study |
title_fullStr | IETA Ultrasonic Features Combined with GI-RADS Classification System and Tumor Biomarkers for Surveillance of Endometrial Carcinoma: An Innovative Study |
title_full_unstemmed | IETA Ultrasonic Features Combined with GI-RADS Classification System and Tumor Biomarkers for Surveillance of Endometrial Carcinoma: An Innovative Study |
title_short | IETA Ultrasonic Features Combined with GI-RADS Classification System and Tumor Biomarkers for Surveillance of Endometrial Carcinoma: An Innovative Study |
title_sort | ieta ultrasonic features combined with gi-rads classification system and tumor biomarkers for surveillance of endometrial carcinoma: an innovative study |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9688181/ https://www.ncbi.nlm.nih.gov/pubmed/36428723 http://dx.doi.org/10.3390/cancers14225631 |
work_keys_str_mv | AT lindongmei ietaultrasonicfeaturescombinedwithgiradsclassificationsystemandtumorbiomarkersforsurveillanceofendometrialcarcinomaaninnovativestudy AT wanghui ietaultrasonicfeaturescombinedwithgiradsclassificationsystemandtumorbiomarkersforsurveillanceofendometrialcarcinomaaninnovativestudy AT liulu ietaultrasonicfeaturescombinedwithgiradsclassificationsystemandtumorbiomarkersforsurveillanceofendometrialcarcinomaaninnovativestudy AT zhaoliang ietaultrasonicfeaturescombinedwithgiradsclassificationsystemandtumorbiomarkersforsurveillanceofendometrialcarcinomaaninnovativestudy AT chenjing ietaultrasonicfeaturescombinedwithgiradsclassificationsystemandtumorbiomarkersforsurveillanceofendometrialcarcinomaaninnovativestudy AT tianhongyan ietaultrasonicfeaturescombinedwithgiradsclassificationsystemandtumorbiomarkersforsurveillanceofendometrialcarcinomaaninnovativestudy AT gaolei ietaultrasonicfeaturescombinedwithgiradsclassificationsystemandtumorbiomarkersforsurveillanceofendometrialcarcinomaaninnovativestudy AT wubeibei ietaultrasonicfeaturescombinedwithgiradsclassificationsystemandtumorbiomarkersforsurveillanceofendometrialcarcinomaaninnovativestudy AT zhangjing ietaultrasonicfeaturescombinedwithgiradsclassificationsystemandtumorbiomarkersforsurveillanceofendometrialcarcinomaaninnovativestudy AT guoxia ietaultrasonicfeaturescombinedwithgiradsclassificationsystemandtumorbiomarkersforsurveillanceofendometrialcarcinomaaninnovativestudy AT haoyi ietaultrasonicfeaturescombinedwithgiradsclassificationsystemandtumorbiomarkersforsurveillanceofendometrialcarcinomaaninnovativestudy |