Noninvasive Preoperative Assessment of Sentinel Lymph Node Metastasis in Breast Cancer Using Super‐Resolution Ultrasound Microvascular Imaging

PURPOSE: To develop and internally validate a super-resolution ultrasound microvascular imaging (SR-UMI) model for noninvasive preoperative prediction of sentinel lymph node (SLN) involvement in breast cancer and to assess incremental value over clinical variables. MATERIALS AND METHODS: In this prospective single-center study (January-June 2025), 162 consecutive patients with pathologically confirmed breast cancer underwent contrast-enhanced SR-UMI of the primary tumor prior to axillary surgery and SLNB. SonoVue (2.4 mL) was administered as an antecubital venous bolus. Examinations were performed on an Ultimus 9E ultrasound system using a 5-15 MHz linear transducer at low MI (0.08). Three predictor sets were evaluated: clinical-only (9 variables), SR-UMI-only (98 features), and combined (107 predictors). Elastic net-regularized logistic regression (EN-LR) was prespecified as the primary model and evaluated using nested stratified cross-validation (outer 5-fold, inner 3-fold) with pooled out-of-fold (OOF) predictions, assessing discrimination, calibration, and decision-curve analysis (DCA). RESULTS: SLN involvement was present in 55/162 patients (34.0%). EN-LR achieved AUC 0.662, PR-AUC 0.471, and Brier 0.232 for clinical-only predictors; SR-UMI-only improved performance (AUC 0.800; PR-AUC 0.572; Brier 0.185). The combined model performed similarly (AUC 0.802; PR-AUC 0.574; Brier 0.185). At the Youden operating point (threshold 0.514), the combined model yielded sensitivity 0.782, specificity 0.766, PPV 0.632, and NPV 0.872. Bootstrap OOF comparisons showed significant AUC improvements for SR-UMI-only versus clinical-only and combined vs. clinical-only, whereas combined vs. SR-UMI-only was not significant. Calibration showed a negative intercept and slope > 1 (combined: -0.637, 1.270). DCA demonstrated higher net benefit for EN-LR than treat-all/treat-none across threshold probabilities 0.05-0.60. CONCLUSION: SR-UMI microvascular features enabled good internal-validation performance and significantly improved discrimination over clinical/biopsy variables. The combined model offered no meaningful gain over SR-UMI only. External validation with recalibration is warranted.

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Publication Details

Journal
Journal of Clinical Ultrasound
Published
2026-06-28
DOI
https://doi.org/10.1002/jcu.70313
Primary Topic
Breast Cancer Treatment Studies
Type
article
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article

Noninvasive Preoperative Assessment of Sentinel Lymph Node Metastasis in Breast Cancer Using Super‐Resolution Ultrasound Microvascular Imaging

Linxue Qian, Junfeng Zhao, Ruifang Guo, X H Hu et al.
Journal of Clinical Ultrasound
Breast Cancer Treatment Studies
article

Noninvasive Preoperative Assessment of Sentinel Lymph Node Metastasis in Breast Cancer Using Super‐Resolution Ultrasound Microvascular Imaging

Linxue Qian, Junfeng Zhao, Ruifang Guo, X H Hu, Xi Liu
article en

Abstract

PURPOSE: To develop and internally validate a super-resolution ultrasound microvascular imaging (SR-UMI) model for noninvasive preoperative prediction of sentinel lymph node (SLN) involvement in breast cancer and to assess incremental value over clinical variables. MATERIALS AND METHODS: In this prospective single-center study (January-June 2025), 162 consecutive patients with pathologically confirmed breast cancer underwent contrast-enhanced SR-UMI of the primary tumor prior to axillary surgery and SLNB. SonoVue (2.4 mL) was administered as an antecubital venous bolus. Examinations were performed on an Ultimus 9E ultrasound system using a 5-15 MHz linear transducer at low MI (0.08). Three predictor sets were evaluated: clinical-only (9 variables), SR-UMI-only (98 features), and combined (107 predictors). Elastic net-regularized logistic regression (EN-LR) was prespecified as the primary model and evaluated using nested stratified cross-validation (outer 5-fold, inner 3-fold) with pooled out-of-fold (OOF) predictions, assessing discrimination, calibration, and decision-curve analysis (DCA). RESULTS: SLN involvement was present in 55/162 patients (34.0%). EN-LR achieved AUC 0.662, PR-AUC 0.471, and Brier 0.232 for clinical-only predictors; SR-UMI-only improved performance (AUC 0.800; PR-AUC 0.572; Brier 0.185). The combined model performed similarly (AUC 0.802; PR-AUC 0.574; Brier 0.185). At the Youden operating point (threshold 0.514), the combined model yielded sensitivity 0.782, specificity 0.766, PPV 0.632, and NPV 0.872. Bootstrap OOF comparisons showed significant AUC improvements for SR-UMI-only versus clinical-only and combined vs. clinical-only, whereas combined vs. SR-UMI-only was not significant. Calibration showed a negative intercept and slope > 1 (combined: -0.637, 1.270). DCA demonstrated higher net benefit for EN-LR than treat-all/treat-none across threshold probabilities 0.05-0.60. CONCLUSION: SR-UMI microvascular features enabled good internal-validation performance and significantly improved discrimination over clinical/biopsy variables. The combined model offered no meaningful gain over SR-UMI only. External validation with recalibration is warranted.

Journal of Clinical Ultrasound
Capital Medical University (CN), Beijing Friendship Hospital (CN)
Peace, Justice and strong institutions
Openalex Percentile: Top 8%
Breast Cancer Treatment Studies
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