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This study evaluates the connection between first-trimester chorionic bump and early pregnancy loss and examines ultrasonographic features for risk stratification.

July 17, 2026BMC Medical Imaging0 citationsOpen Access

Association between first-trimester chorionic bump and early pregnancy loss: a two-center retrospective study with exploratory radiomics analysis

JSJie ShenWenzhou Medical University YZYipeng ZhaoHangzhou Dianzi University ZWZhina WuWenzhou Medical University

Key Points

This study evaluates the connection between first-trimester chorionic bump and early pregnancy loss and examines ultrasonographic features for risk stratification.
Two-center retrospective study involving 184 women with chorionic bump and 1052 matched controls
Participants underwent transvaginal ultrasound at 5–10 weeks of gestation
Analyzed ultrasonographic features using logistic regression, support vector machine, and random forest methods.
Chorionic bump was strongly associated with early pregnancy loss.
Optimized random forest model achieved accuracy of 0.538, AUROC of 0.573, and precision of 0.539.
Identified significant risk factors for pregnancy loss include lower grayscale minimum intensity, smaller gestational sac volume, and higher CB-to-GS volume ratio.

Abstract

The chorionic bump (CB) is a rare sonographic finding defined as an irregular protrusion from the choriodecidual surface into the gestational sac. Its prognostic significance regarding pregnancy loss remains controversial. This study aimed to evaluate the association between first-trimester CB and pregnancy outcomes and to investigate whether ultrasonographic radiomic features can support early risk stratification. This two-center retrospective study included 184 women diagnosed with a CB and 1052 matched controls between January 2020 and December 2024. All participants underwent transvaginal ultrasound at 5–10 weeks of gestation. Radiomic features were extracted from regions of interest using PyRadiomics. Furthermore, logistic regression, support vector machine (SVM), and random forest (RF) —alongside SHAP analysis, were employed to analyze the ultrasonographic radiomic features. Sonographically, CB exhibited variable echogenicity and an absence of internal blood flow on color Doppler flow imaging. While no significant differences were found in other secondary pregnancy outcomes, CB was strongly associated with early pregnancy loss. Following feature selection, the optimized RFSel model achieved an AUROC of 0. 573, accuracy of 0. 538, and a precision of 0. 539. SHAP analysis identified “originalfirstorderMinimum” (first-order minimum intensity) as the feature with the highest decision-making value. Furthermore, lower grayscale minimum intensity on ultrasound, smaller gestational sac (GS) volume, and a higher CB-to-GS volume ratio were identified as significant risk factors for pregnancy loss within the CB population. A first-trimester CB is a significant high-risk factor for early pregnancy loss. However, the radiomics-based model demonstrated limited predictive performance, indicating that radiomic features alone are currently insufficient for clinical risk stratification and should be considered hypothesis-generating. The early sonographic identification of a CB remains vital for assessing clinical risk and guiding obstetric management.

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