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Nomogram for preoperative differentiation of benign and malignant breast tumors using contrast-enhanced cone-beam breast CT (CE CB-BCT) quantitative imaging and assessment features

  • Breast Radiology
  • Published:
La radiologia medica Aims and scope Submit manuscript

Abstract

Purpose

Breast cancer's impact necessitates refined diagnostic approaches. This study develops a nomogram using radiology quantitative features from contrast-enhanced cone-beam breast CT for accurate preoperative classification of benign and malignant breast tumors.

Material and methods

A retrospective study enrolled 234 females with breast tumors, split into training and test sets. Contrast-enhanced cone-beam breast CT-images were acquired using Koning Breast CT-1000. Quantitative assessment features were extracted via 3D-slicer software, identifying independent predictors. The nomogram was constructed to preoperative differentiation benign and malignant breast tumors. Calibration curve was used to assess whether the model showed favorable correspondence with pathological confirmation. Decision curve analysis confirmed the model's superiority.

Results

The study enrolled 234 female patients with a mean age of 50.2 years (SD ± 9.2). The training set had 164 patients (89 benign, 75 malignant), and the test set had 70 patients (29 benign, 41 malignant). The nomogram achieved excellent predictive performance in distinguishing benign and malignant breast lesions with an AUC of 0.940 (95% CI 0.900–0.940) in the training set and 0.970 (95% CI 0.940–0.970) in the test set.

Conclusion

This study illustrates the effectiveness of quantitative radiology features derived from contrast-enhanced cone-beam breast CT in distinguishing between benign and malignant breast tumors. Incorporating these features into a nomogram-based diagnostic model allows for breast tumor diagnoses that are objective and possess good accuracy. The application of these insights could substantially increase reliability and efficacy in the management of breast tumors, offering enhanced diagnostic capability.

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Abbreviations

AUC:

Area under the receiver operating curve

BI-RADS:

Breast imaging reporting and data system

CB-BCT:

Cone-beam breast CT

CE CB-BCT:

Contrast-enhanced cone-beam breast CT

CI:

Confidence interval

DCA:

Decision curve analysis

DCIS:

Ductal carcinoma in situ

ICC:

Intraclass correlation coefficient

IQR:

Interquartile range

MG:

Mammography

MRI:

Magnetic resonance imaging

NCE CB-BCT:

Non-contrast-enhanced cone-beam breast CT

NME:

Non-mass enhancement

OR:

Odds ratio

ROC:

Receiver operating characteristic

ROI:

Region of interest

SD:

Standard deviation

US:

Ultrasound

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Acknowledgements

The authors thank the patients for their willingness to cooperate with our study. The authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article. This work was supported by the National Key R&D Program of China (2020YFA0714002). The funders had no role in study design, data analysis, decision to publish, or preparation of the manuscript.

Funding

This work was supported by the National Key R&D Program of China (2020YFA0714002) and Joint project of Chongqing Health Commission and Science and Technology Bureau (No. 2022ZDXM006 and 2022QNXM015) and Key Project of Technological Innovation and Application Development of Chongqing Science and Technology Bureau (No. CSTC2021jscxksbN0030).

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Author notes

  1. Tong Su and Yineng Zheng have contributed equally to this work.

Authors and Affiliations

  1. Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, No.1, Youyi Road, Yuanjiagang, Yuzhong District, Chongqing, China

    Tong Su, Yineng Zheng, Zubin Ouyang, Jun Fan, Lin Lin & Fajin Lv

  2. Department of Radiology, Chongqing Changshou District People’s Hospital, Chongqing, China

    Hongyu Yang

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  1. Tong Su
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Contributions

TS contributed to the conception and design of the study, completed image acquisition and analysis, interpreted the data, drafted the manuscript, and provided substantial manuscript revisions. YZ contributed to the study's conception and design, data interpretation, and manuscript revision. HY contributed to the image acquisition and analysis. ZO contributed to the completed image acquisition and analysis, the conception and design of the study. JF and LL contributed to the image acquisition. FL contributed to the study's conception and design, and manuscript revision.

Corresponding author

Correspondence to Fajin Lv.

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The authors declare that they have no competing interests.

Ethical approval

Institutional Review Board approval was obtained (2022-K313).

Consent to participation

This retrospective study was approved by the institutional review board of our hospital (2022-K313). The requirement for the patients’ informed consent was waived.

Consent for publication

In this manuscript, all images analyzed are entirely unidentifiable, and the only individual detail provided is the age of the participants.

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Su, T., Zheng, Y., Yang, H. et al. Nomogram for preoperative differentiation of benign and malignant breast tumors using contrast-enhanced cone-beam breast CT (CE CB-BCT) quantitative imaging and assessment features. Radiol med 129, 737–750 (2024). https://doi.org/10.1007/s11547-024-01803-0

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