Ultrasonic prediction model using three-dimensional power doppler for endometrial cancer detection in women with postmenopausal bleeding

Distinguishing benign and malignant endometrial lesions on the basis of endometrial thickness (ET) may lead to a missed diagnosis of endometrial carcinoma (EC) in women with postmenopausal bleeding (PMB) or increased invasive examination and pain in women with benign endometrial lesions. Our research aims to establish an ultrasonic prediction model for differentiating between benign endometrial lesions and EC in women with PMB. PMB women with ET ≥ 5 mm (n = 412) or ET < 5 mm who presented with recurrent vaginal bleeding (n = 57) were enrolled in this prospective observational study. According to the pathological examination results of the endometrium, women with PMB were divided into endometrial atrophy (EA) (n = 231), endometrial polyp (EP) (n = 98), endometrial hyperplasia (EH) (n = 58) and EC (n = 82) groups. Ultrasonic parameters were compared among the four groups. The predictive value of different parameters for differentiation between benign endometrial lesions and EC in women with PMB was determined via receiver operating characteristic (ROC) curves. The best cut-off of ultrasonic parameters analyzed by ROC curves was used to establish prediction model. Women with EC had significantly thicker endometrium and higher endometrial volume (EV), vascularization index (VI), flow index (FI) and vascularization-flow index (VFI) than women with other pathological types of endometrium (P < 0.05). The endometrial VI, FI and VFI of women with EH were significantly higher compared with those in women with EA and EP (P < 0.05). For patients with ET ≥ 5 mm, the best parameter for distinguishing between benign lesions and EC was the FI, with an area under the curve (AUC) of 0.86, a sensitivity of 86.7% and a specificity of 81.4%. In addition, for patients with ET < 5 mm, the best parameter for distinguishing between benign lesions and EC was the VI, with an AUC of 0.92, a sensitivity of 92.1% and a specificity of 72.9%. The ultrasonic prediction model based on the FI and VI had better predictive value for EC in both patients with ET ≥ 5 mm and patients with ET < 5 mm. The ultrasonic parameters differed among the different pathological types of the endometrium in women with PMB. The ultrasonic prediction model based on the endometrial FI and VI was clinically useful for differentiating between benign endometrial lesions and EC, especially in postmenopausal patients with recurrent vaginal bleeding presenting with ET of less than 5 mm.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2025-05-26
DOI
https://doi.org/10.1038/s41598-025-02067-y
Citations
1
Primary Topic
Endometrial and Cervical Cancer Treatments
Type
article
Field-Weighted Citation Impact
2.06
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Ultrasonic prediction model using three-dimensional power doppler for endometrial cancer detection in women with postmenopausal bleeding

Shimin Quan, Li Wang, Xiaofeng Yang
1 citations
Scientific Reports
Endometrial and Cervical Cancer Treatments
2.06
article

Ultrasonic prediction model using three-dimensional power doppler for endometrial cancer detection in women with postmenopausal bleeding

Shimin Quan, Li Wang, Xiaofeng Yang
article en
1 citations

Abstract

Distinguishing benign and malignant endometrial lesions on the basis of endometrial thickness (ET) may lead to a missed diagnosis of endometrial carcinoma (EC) in women with postmenopausal bleeding (PMB) or increased invasive examination and pain in women with benign endometrial lesions. Our research aims to establish an ultrasonic prediction model for differentiating between benign endometrial lesions and EC in women with PMB. PMB women with ET ≥ 5 mm (n = 412) or ET < 5 mm who presented with recurrent vaginal bleeding (n = 57) were enrolled in this prospective observational study. According to the pathological examination results of the endometrium, women with PMB were divided into endometrial atrophy (EA) (n = 231), endometrial polyp (EP) (n = 98), endometrial hyperplasia (EH) (n = 58) and EC (n = 82) groups. Ultrasonic parameters were compared among the four groups. The predictive value of different parameters for differentiation between benign endometrial lesions and EC in women with PMB was determined via receiver operating characteristic (ROC) curves. The best cut-off of ultrasonic parameters analyzed by ROC curves was used to establish prediction model. Women with EC had significantly thicker endometrium and higher endometrial volume (EV), vascularization index (VI), flow index (FI) and vascularization-flow index (VFI) than women with other pathological types of endometrium (P < 0.05). The endometrial VI, FI and VFI of women with EH were significantly higher compared with those in women with EA and EP (P < 0.05). For patients with ET ≥ 5 mm, the best parameter for distinguishing between benign lesions and EC was the FI, with an area under the curve (AUC) of 0.86, a sensitivity of 86.7% and a specificity of 81.4%. In addition, for patients with ET < 5 mm, the best parameter for distinguishing between benign lesions and EC was the VI, with an AUC of 0.92, a sensitivity of 92.1% and a specificity of 72.9%. The ultrasonic prediction model based on the FI and VI had better predictive value for EC in both patients with ET ≥ 5 mm and patients with ET < 5 mm. The ultrasonic parameters differed among the different pathological types of the endometrium in women with PMB. The ultrasonic prediction model based on the endometrial FI and VI was clinically useful for differentiating between benign endometrial lesions and EC, especially in postmenopausal patients with recurrent vaginal bleeding presenting with ET of less than 5 mm.

Scientific ReportsVol. 15(1)
First Affiliated Hospital of Xi'an Jiaotong University (CN)
Openalex Percentile: Top 15%
Endometrial and Cervical Cancer Treatments
2.06
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.