Lymph Node Predictive Model with in Vitro Ultrasound Features for Breast Cancer Lymph Node Metastasis

Han, Ping; Yang, Houpu; Liu, Miao; Cheng, Lin; Wang, Siyuan; Tong, Fuzhong; Liu, Peng; Zhou, Bo; Cao, Yimei; Liu, Hongjun; Wang, Chaobin; Yuan, Peng; Shen, Danhua; Wang, Shu

doi:10.1016/j.ultrasmedbio.2020.01.030

Cited by 9 publications

(7 citation statements)

References 19 publications

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“…The number of suspicious LNs detected was also related to outcome when using LN >2 as the cutoff in the prediction of high burden (38). In this paper, one LN was used as the cutoff for prediction because one abnormal LN on AUS can be predictive of a low burden of LNs (N 1-2 ), as demonstrated by Puri et al (39) Other USdependent characteristics, such as the maximum LN axis and the effacement of the lymphatic hilum, are closely related to a negative LN status (40). The lymphatic hilum is an entrance for lymphatic vessels and nerves.…”

Section: Discussionmentioning

confidence: 86%

Establishment and Validation of The Axillary Lymph Node Burden Using Cone-Beam Computerized Tomography and Ultrasound-Based Prediction Models in T1-2 Breast Cancer Patients

Shen

Cai

et al. 2021

Preprint

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Background: This study aimed to develop and validate models to preoperatively predict the risk of the lymph node (LN) burden based on the Z0011 clinical trial to assist breast cancer surgical decision-making.Methods: Data on 1394 consecutive patients who presented at Sun Yat-sen University Cancer Center for Cone-beam breast computerized tomography (CBBCT) examinations between April 3, 2019, and July 17, 2020, were retrospectively collected. 387 patients who met the inclusion criteria were included and randomly divided into training and validation cohorts. Clinical-pathological information of all patients was recorded, and images were reinterpreted in this study. A bidirectional stepwise method followed by multi-variable analysis was used to incorporate preoperative features and build optimal model sets with the training cohort for prediction of N0 versus N+ and N＜3 versus N≥3.Results: The ROC curves of two models were generated with the training cohort, and their calibration abilities were estimated using 1000 bootstrap resamples. The bias-corrected C-index of the models were 0.779 (95% CI, 0.752–0.793) in model one and 0.809 (95% CI, 0.794–0.833) in model two for the training cohort. Decision curves and clinical impact curves were plotted to evaluate prediction performance for further clinical application. Delong’s test showed comparable performance of both cohorts.Conclusions: Our models were developed as reliable and noninvasive tools for the preoperative prediction of nodal status, and we hope that they can serve as useful tools for the early planning of treatment strategies for breast cancer patients.

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Section: Discussionmentioning

confidence: 86%

Establishment and Validation of The Axillary Lymph Node Burden Using Cone-Beam Computerized Tomography and Ultrasound-Based Prediction Models in T1-2 Breast Cancer Patients

Shen

Cai

et al. 2021

Preprint

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“…Patients could be informed of the possibility of SLN metastasis and decide how to manage the ALNs. According to this nomogram, if the diagnostic probability of SLN metastasis is >0.429, the SLN is considered metastatic ( 27 ), and targeted biopsy can be performed under US guidance. Then, if a patient has more than 2 SLNs with metastasis, the ALND may be directly operated on instead of the patient undergoing an SLNB.…”

Section: Discussionmentioning

confidence: 99%

Diagnosing sentinel lymph node metastasis of T1/T2 breast cancer with conventional ultrasound combined with double contrast-enhanced ultrasound: a preliminary study

Zheng¹,

Sun²,

Zhu³

et al. 2023

Quant Imaging Med Surg

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Background: In patients with T1/T2 breast cancer (BC), sentinel lymph node (SLN) status is essential for prognosis and treatment. This study investigated the value of conventional ultrasound combined with double contrast-enhanced ultrasound in diagnosing the metastasis of SLNs in patients with T1/T2 BC.Methods: This study employed a prospective design (this diagnostic study was not registered on a clinical trial platform), and the participants formed a convenience series. Based on the inclusion and exclusion criteria, 163 patients with BC who received treatment in the First Affiliated Hospital of Soochow University from July 2017 to December 2021 were included in this study. A total of 165 SLNs from 163 patients with T1/T2 BC were analyzed. All patients underwent percutaneous contrast-enhanced ultrasound (PCEUS) to trace SLNs before the operation. Subsequently, all patients underwent conventional ultrasound and intravenous contrast-enhanced ultrasound (ICEUS) examinations to observe the SLNs. The results of the conventional ultrasound, ICEUS, and PCEUS of the SLNs were analyzed. The associations between the risk of SLN metastasis and imaging features were evaluated via a nomogram based on the pathological results.Results: Overall, 54 metastatic SLNs and 111 nonmetastatic SLNs were evaluated. Metastatic SLNs displayed a greater cortical thickness, area ratio, eccentric fatty hilum, and hybrid blood flow on conventional ultrasound compared with nonmetastatic SLNs (P<0.001). According to PCEUS, 75.93% of metastatic SLNs showed heterogeneous enhancement (type II and III), and 73.88% of nonmetastatic SLNs showed homogeneous enhancement (type I; P<0.001). According to ICEUS, heterogeneous enhancement (type B/ C, 20.37% vs. 11.71%) and overall enhancement (55.56% vs. 23.42%) were more common in metastatic SLNs than in nonmetastatic SLNs (P<0.001). Logistic regression analysis showed that the cortical thickness and enhancement type of PCEUS were independent predictors of SLN metastasis. Moreover, a nomogram combining these factors showed a high diagnostic ability for SLN metastasis (unadjusted concordance index 0.860, 95% CI: 0.730-0.990; bootstrap-corrected concordance index 0.853). Conclusions:The nomogram of cortical thickness and enhancement type of PCEUS could effectively ^ ORCID: Yan Zheng, 0000-0002-1599-4293; Feng-Lin Dong, 0000-0003-2457-663X. diagnose SLN metastasis in patients with T1/T2 BC.

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“…However, up to now, the optimal cut-off value of each parameter of SWE has not yet reached agreement. It may be affected by many factors, such as pre-compression, the machine model and the depth of the lesion, and the progression of the patient’s disease ( 56 , 57 ). Therefore, studies with a larger sample size involving multiple units should be considered.…”

Section: Discussionmentioning

confidence: 99%

The Value of Shear Wave Elastography in the Diagnosis of Breast Cancer Axillary Lymph Node Metastasis and Its Correlation With Molecular Classification of Breast Masses

Luo

Zhang

et al. 2022

Front. Oncol.

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ObjectiveTo explore the diagnostic value of shear wave elastography examination (SWE) on axillary node metastasis (ANM) in breast cancer, this study aimed to evaluate the correlation between the SWE features and different molecular types of breast cancer, and to check the elastic modulus differences among the molecular types.MethodsBreast cancer patients from November 2020 to December 2021 were subjected to both conventional ultrasonic examination (CUE) and SWE before ultrasound-guided percutaneous biopsy or axillary lymph node dissection (ALND). We used the pathological results as the gold standard to draw the receiver operating characteristic (ROC) curve.ResultsSWE outperforms CUE, but their conjunctive use is the best option. No significant correlation was found between the elastic modulus values and the molecular types of breast cancer.ConclusionSWE can be used as an routine auxiliary method of CUE for ANM.

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Lymph Node Predictive Model with in Vitro Ultrasound Features for Breast Cancer Lymph Node Metastasis

Cited by 9 publications

References 19 publications

Establishment and Validation of The Axillary Lymph Node Burden Using Cone-Beam Computerized Tomography and Ultrasound-Based Prediction Models in T1-2 Breast Cancer Patients

Establishment and Validation of The Axillary Lymph Node Burden Using Cone-Beam Computerized Tomography and Ultrasound-Based Prediction Models in T1-2 Breast Cancer Patients

Diagnosing sentinel lymph node metastasis of T1/T2 breast cancer with conventional ultrasound combined with double contrast-enhanced ultrasound: a preliminary study

The Value of Shear Wave Elastography in the Diagnosis of Breast Cancer Axillary Lymph Node Metastasis and Its Correlation With Molecular Classification of Breast Masses

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