ArticleBMC cancer2025
Gradient perfusion features can effectively identify sentinel lymph node metastasis in early breast cancer.
Article in BMC cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundThis study aimed to determine whether contrast-enhanced ultrasound (CEUS) gradient perfusion features in identifying sentinel lymph node (SLN) metastasis burden in early breast cancer (EBC). MATERIALS AND
methodsData from 145 EBC patients who underwent preoperative CEUS and SLN biopsy were retrospectively collected. The initial time-intensity curve (TIC) parameters and gradient TIC parameters of the high-perfusion regions at the margins and low-perfusion regions inside SLNs in both positive and negative SLN lesions were analyzed to identify independent factors influencing SLN status, and to explore their potential relationship with the average SLN positivity rate and the number of positive SLNs.
resultsA total of 113 patients were included in the analysis, with 79 in the training set and 34 in the testing set. Significant differences were observed in the gradient TIC parameters, including gradient time-to-peak (△TTP) (t = 3.158, P = 0.002), gradient peak intensity (△PI) (t = 3.934, P<0.001), gradient rising slope (△RS) (t = 2.879, P = 0.005), and gradient area under the curve (△AUC) (t = 5.606, P<0.001) between the two groups. Multivariate logistic regression analysis showed that △PI (P = 0.009), △RS (P = 0.025), and △AUC (P<0.001) were independent factors influencing SLN status and were closely related to the average SLN positivity rate (r△PI=0.579; r△RS=0.624; r△AUC=0.698) and the number of positive SLNs (△PI: P = 0.029; △RS: P = 0.005). Moreover, the SLN status identification model and the classification model predicting whether the number of positive SLNs exceeded two, based on gradient TIC parameters, demonstrated good calibration and clinical applicability in both the training and testing sets.
conclusionCEUS gradient perfusion features can effectively identify SLN metastasis in EBC and are closely related to the number of positive SLNs.
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