Diagnostic accuracy of ultrasound-based imaging modalities for assessing residual axillary lymph node disease after neoadjuvant chemotherapy in patients with breast cancer: a systematic review and meta-analysis.
- 1Department of Ultrasound, The First Affiliated Hospital of Shihezi University, Shihezi, China.
- 2Department of Ultrasound, Tongji Hospital, Affiliated to Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Abstract
Accurate identification of residual axillary lymph node (ALN) disease after neoadjuvant chemotherapy (NAC) is essential for treatment planning and for evaluating potential surgical de-escalation. We assessed the diagnostic performance of conventional ultrasonography (US), shear-wave elastography (SWE), artificial intelligence (AI)/radiomics, and multimodal ultrasound-based models for post-NAC axillary restaging. PubMed, Embase, the Cochrane Library, and Web of Science were searched from inception through December 2025. Histopathology after axillary surgery was the reference standard, and residual axillary nodal disease (ypN+) was uniformly defined as the positive target condition. Study-level 2×2 tables were harmonized to this direction. Risk of bias and applicability were assessed with the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool. Bivariate random-effects models and hierarchical summary receiver operating characteristic (HSROC) curves were used for modality groups with a sufficient number of independent studies; the positive likelihood ratio (PLR) and negative likelihood ratio (NLR) were pooled with random-effects models. Potentially overlapping cohorts were examined in sensitivity analyses. The study protocol was registered in PROSPERO (International Prospective Register of Systematic Reviews; registration No. CRD420251271199). A total of 14 articles were included in the systematic review, 10 of which contributed 12 test-level datasets to the quantitative synthesis. For conventional US (six studies), the pooled sensitivity was 0.55 [95% confidence interval (CI): 0.36-0.73], the pooled specificity was 0.79 (95% CI: 0.73-0.84), the area under the HSROC curve (AUC) was 0.78, and the pooled PLR and NLR were 2.47 (95% CI: 1.42-4.28) and 0.54 (95% CI: 0.30-0.95), respectively. AI/radiomics models (three studies) showed a pooled sensitivity of 0.93 (95% CI: 0.80-0.98), a specificity of 0.82 (95% CI: 0.60-0.94), and an AUC of 0.94; however, likelihood-ratio CIs were wide, and the bivariate covariance estimate reached the boundary. Evidence for SWE was limited to two potentially overlapping reports, and only one multimodal combined-model study had a complete harmonized 2×2 table. At a 40% pretest probability, a negative conventional US result reduced the posttest probability of residual nodal disease to approximately 26%. Conventional US alone does not reliably exclude residual axillary nodal disease after NAC. AI/radiomics approaches show promising diagnostic performance, but the evidence for this is sparse, heterogeneous, and imprecise. The currently available data do not support definitive modality ranking or omission of axillary surgery on the basis of imaging alone, and prospective multicenter external validation is required.
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BibTeX
@article{liu2026diagnostic,
title = {{Diagnostic accuracy of ultrasound-based imaging modalities for assessing residual axillary lymph node disease after neoadjuvant chemotherapy in patients with breast cancer: a systematic review and meta-analysis.}},
author = {Tianxin Liu and Yuchen He and Xiaowu Yuan and Jinli Wang and Yan Liu and Chunli Cao and Ming Chen and Wenxiao Li and Jun Li and Xinwu Cui},
journal = {Quantitative imaging in medicine and surgery},
year = {2026},
month = sep,
doi = {10.21037/qims-2026-1427},
url = {https://europepmc.org/article/MED/42997962},
note = {CC BY-NC-ND},
}
RIS
TY - JOUR
TI - Diagnostic accuracy of ultrasound-based imaging modalities for assessing residual axillary lymph node disease after neoadjuvant chemotherapy in patients with breast cancer: a systematic review and meta-analysis.
AU - Tianxin Liu
AU - Yuchen He
AU - Xiaowu Yuan
AU - Jinli Wang
AU - Yan Liu
AU - Chunli Cao
AU - Ming Chen
AU - Wenxiao Li
AU - Jun Li
AU - Xinwu Cui
PY - 2026
DA - 2026/09/29
JO - Quantitative imaging in medicine and surgery
DO - 10.21037/qims-2026-1427
UR - https://europepmc.org/article/MED/42997962
AB - Accurate identification of residual axillary lymph node (ALN) disease after neoadjuvant chemotherapy (NAC) is essential for treatment planning and for evaluating potential surgical de-escalation. We assessed the diagnostic performance of conventional ultrasonography (US), shear-wave elastography (SWE), artificial intelligence (AI)/radiomics, and multimodal ultrasound-based models for post-NAC axillary restaging. PubMed, Embase, the Cochrane Library, and Web of Science were searched from inception through December 2025. Histopathology after axillary surgery was the reference standard, and residual axillary nodal disease (ypN+) was uniformly defined as the positive target condition. Study-level 2×2 tables were harmonized to this direction. Risk of bias and applicability were assessed with the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool. Bivariate random-effects models and hierarchical summary receiver operating characteristic (HSROC) curves were used for modality groups with a sufficient number of independent studies; the positive likelihood ratio (PLR) and negative likelihood ratio (NLR) were pooled with random-effects models. Potentially overlapping cohorts were examined in sensitivity analyses. The study protocol was registered in PROSPERO (International Prospective Register of Systematic Reviews; registration No. CRD420251271199). A total of 14 articles were included in the systematic review, 10 of which contributed 12 test-level datasets to the quantitative synthesis. For conventional US (six studies), the pooled sensitivity was 0.55 [95% confidence interval (CI): 0.36-0.73], the pooled specificity was 0.79 (95% CI: 0.73-0.84), the area under the HSROC curve (AUC) was 0.78, and the pooled PLR and NLR were 2.47 (95% CI: 1.42-4.28) and 0.54 (95% CI: 0.30-0.95), respectively. AI/radiomics models (three studies) showed a pooled sensitivity of 0.93 (95% CI: 0.80-0.98), a specificity of 0.82 (95% CI: 0.60-0.94), and an AUC of 0.94; however, likelihood-ratio CIs were wide, and the bivariate covariance estimate reached the boundary. Evidence for SWE was limited to two potentially overlapping reports, and only one multimodal combined-model study had a complete harmonized 2×2 table. At a 40% pretest probability, a negative conventional US result reduced the posttest probability of residual nodal disease to approximately 26%. Conventional US alone does not reliably exclude residual axillary nodal disease after NAC. AI/radiomics approaches show promising diagnostic performance, but the evidence for this is sparse, heterogeneous, and imprecise. The currently available data do not support definitive modality ranking or omission of axillary surgery on the basis of imaging alone, and prospective multicenter external validation is required.
SN - 2223-4292
SN - 2223-4306
ER -