Establishment a prediction model of chest wall recurrent nodules after modified radical mastectomy using ultrasound characteristics

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Establishment a prediction model of chest wall recurrent nodules after modified radical mastectomy using ultrasound characteristics

更新时间：2023-10-11

- Establishment a prediction model of chest wall recurrent nodules after modified radical mastectomy using ultrasound characteristics
- Journal of Clinical Ultrasound in Medicine Vol. 25, Issue 2, (2023)
- 作者机构：
  
  佛山市第一人民医院
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2023，
  
  Published Online：6 March 2023，
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Establishment a prediction model of chest wall recurrent nodules after modified radical mastectomy using ultrasound characteristics. [J]. Journal of Clinical Ultrasound in Medicine 25(2).(2023)
DOI：

Establishment a prediction model of chest wall recurrent nodules after modified radical mastectomy using ultrasound characteristics. [J]. Journal of Clinical Ultrasound in Medicine 25(2).(2023) DOI：

摘要

目的探讨乳腺癌改良根治术后胸壁复发结节的超声图像特征，并建立预测模型。方法回顾性分析我院102例乳腺癌改良根治术后患者胸壁新发结节的超声图像特征，其中复发结节57例，良性结节45例，通过回归分析得出有鉴别意义的特征性指标，建立Logistic回归模型。结果乳腺癌改良根治术后胸壁复发结节超声图像常表现为单发或多发、累及多层组织结构、边界不清、形态不规则、少-中量血流信号的低回声实性结节。多因素回归分析显示胸壁病灶最大径、数目、边界、血流信号、术后间隔时间是乳腺癌术后胸壁结节恶性风险的独立预测因素（均P<0.05）。建立的Logistic回归模型判断术后胸壁结节为复发病灶的风险灵敏度为91.2%、特异度为82.2%、准确度为87.3%、曲线下面积为0.935。结论利用超声图像特征建立的风险预测模型能有效鉴别乳腺癌改良根治术后胸壁结节的良恶性，提高超声诊断准确率。

Abstract

Objective To explore the ultrasound image features of chest wall recurrent nodules after modified radical mastectomy and to establish a prediction model. Methods Ultrasound image features of chest wall nodules of 102 patients(57 patients with recurrent nodules and 45 patients with benign nodules) after mastectomy were retrospectively analyzed. The ultrasound features were screened using regression analysis

and then the screened features were used to build a regression model. Results Chest wall recurrent nodules after mastectomy often show single or multiple hypoechoic solid masses with multilayer tissue structure implication

poorly defined borders

irregular morphology

and low to medium blood flow signals. Multifactorial analysis showed that maximum diameter

number

borders

blood flow signal and postoperative intervals were independent predictors of the risk of malignant nodules（P<0.05）. The logistic regression model showed that the risk sensitivity

specificity and accuracy was 91.2%

82.2% and 87.3%

with the area under curve 0.935. Conclusions Prediction model based on ultrasound features can effectively evaluate the malignant risk of chest wall nodules after modified radical mastectomy.

关键词

超声检查乳腺癌胸壁复发预测模型

Keywords

UltrasonographyBreast cancerChest wall recurrencePrediction model

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