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Journal Of Modern Oncology[ISSN:1672-4992/CN:61-1415/R]

Issue:

2024 16

Page:

3085-3092

Research Field:

Publishing date:

Info

Title:

Preoperative prediction of axillary lymph node metastasis in T1 breast cancer based on ABVS imaging nomogram

Author(s):

ZHANG Yu¹; WANG Junli¹; FAN Lifang²; CHEN Guoxian²

1.Department of Ultrasound Medicine,Wuhu Hospital Affiliated to East China Normal University (Wuhu Second People's Hospital),Anhui Wuhu 241000,China;2.Wannan Medical College,Anhui Wuhu 241002,China.

Keywords:

breast cancer; axillary lymph nodes; radiomics; automatic breast volume scanner

PACS:

R737.9

DOI:

10.3969/j.issn.1672-4992.2024.16.023

Abstract:

Objective:To evaluate the value of a nomogram model based on automatic breast volume scanner (ABVS) imaging for predicting axillary lymph node (ALN) metastasis in T1 breast cancer.Methods:Clinical pathological and imaging data of 158 patients with T1 breast cancer in Wuhu Hospital Affiliated to East China Normal University were collected.The patients were randomly divided into training group (n=110) and validation group (n=48) according to 7∶3.Using MaZda texture analysis software to extract radiomics features from ABVS maximum coronal images,and the least absolute shrinkage and selection operator (LASSO) regression dimension reduction algorithm was used to screen the best features.The radiomics label score (radscore) was constructed.The independent risk factors for predicting ALN metastasis in T1 breast cancer were screened by univariate and multivariate Logistic regression analysis,and the combined prediction model was constructed and a nomogram of the model was drawn.Receiver operating characteristic (ROC) curve and area under curve (AUC) were used to evaluate the diagnostic efficiency of the model.The goodness of fit of the model was evaluated by Hosmer-Lemeshow test.Calibration curve was used to evaluate the calibration degree of the model,the Delong test was used to compare the diagnostic efficiency of the model,and the decision curve analysis (DCA) was used to evaluate the clinical utility of the model.Results:Univariate and multivariate Logistic regression found that quadrant,coronal convergence sign,and ultrasound lymph node positivity were independent risk factors.The AUC of the combined model in training group and validation group were 0.944 and 0.862,respectively.Delong test combined model has the highest diagnostic efficiency.Hosmer-Lemeshow test model fits well (Training group χ2=6.877，P=0.550;Validation group χ2=13.904，P=0.084).The calibration curve and DCA indicate that the nomogram has high calibration accuracy and good clinical applicability.Conclusion:ABVS imaging nomogram can effectively predict the risk of ALN metastasis in T1 breast cancer before operation.The constructed nomogram can visualize and predict the results,providing non-invasive means for precision diagnosis and treatment.

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Memo

Memo:

安徽省高校重点科研项目（编号：2023AH051743）;皖南医学院中青年科研基金项目（编号：WK202213）;安徽省高等学校质量工程项目（编号：2022xsxx243）

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