肌萎缩
医学
三阴性乳腺癌
乳腺癌
乳房磁振造影
新辅助治疗
单变量分析
肿瘤科
单变量
无线电技术
内科学
癌症
放射科
多元分析
机器学习
多元统计
计算机科学
乳腺摄影术
作者
Jiamin Guo,Wenjun Meng,Qian Li,Yichen Zheng,Hongkun Yin,Ying Liu,Shuang Zhao,Ji Ma
出处
期刊:Bioengineering
[MDPI AG]
日期:2024-06-28
卷期号:11 (7): 663-663
被引量:1
标识
DOI:10.3390/bioengineering11070663
摘要
The association between sarcopenia and the effectiveness of neoadjuvant chemotherapy (NAC) in triple-negative breast cancer (TNBC) remains uncertain. This study aims to examine the potential of sarcopenia as a predictive factor for the response to NAC in TNBC, and to assess whether its combination with MRI radiomic signatures can improve the predictive accuracy. We collected clinical and pathological information, as well as pretreatment breast MRI and abdominal CT images, of 121 patients with TNBC who underwent NAC at our hospital between January 2012 and September 2021. The presence of pretreatment sarcopenia was assessed using the L3 skeletal muscle index. Clinical models were constructed based on independent risk factors identified by univariate regression analysis. Radiomics data were extracted on breast MRI images and the radiomics prediction models were constructed. We integrated independent risk factors and radiomic features to build the combined models. The results of this study demonstrated that sarcopenia is an independent predictive factor for NAC efficacy in TNBC. The combination of sarcopenia and MRI radiomic signatures can further improve predictive performance.
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