Prediction of Microinvasion in Breast Ductal Carcinoma in Situ Using Conventional Ultrasound Combined with Contrast-Enhanced Ultrasound Features: A Two-Center Study
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Summary
This summary is machine-generated.A new model using conventional and contrast-enhanced ultrasound accurately predicts microinvasion in ductal carcinoma in situ (DCIS), aiding preoperative diagnosis. This tool helps identify invasive breast cancer before surgery.
Area Of Science
- Radiology
- Oncology
- Medical Imaging
Background
- Ductal carcinoma in situ (DCIS) is a non-invasive breast cancer.
- Microinvasion in DCIS can alter treatment strategies.
- Accurate preoperative prediction of microinvasion is crucial.
Purpose Of The Study
- To develop and validate a predictive model for microinvasion in DCIS.
- Utilize conventional ultrasound (CUS) and contrast-enhanced ultrasound (CEUS) features.
- Improve preoperative diagnostic accuracy.
Main Methods
- Retrospective analysis of 163 DCIS patients from an internal hospital and 56 from an external hospital.
- Development of a predictive model using logistic regression on CUS and CEUS features.
- Validation of the model's calibration, discrimination, and clinical utility.
Main Results
- Centripetal enhancement direction, enlarged enhancement range on CEUS, lesion size ≥20 mm, and calcification on CUS were independent predictors.
- The developed nomogram demonstrated high discrimination (AUCs 0.850-0.879) and good calibration.
- The nomogram outperformed standalone CUS and CEUS models and was clinically useful.
Conclusions
- A nomogram integrating CUS and CEUS features shows significant potential for preoperative microinvasion prediction in DCIS.
- This model can aid in surgical planning and patient management.
- Further validation in diverse populations is warranted.

