期刊
EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING
卷 46, 期 7, 页码 1468-1477出版社
SPRINGER
DOI: 10.1007/s00259-019-04313-8
关键词
Breast cancer; Neoadjuvant chemotherapy; Radiomics; Advanced features; F-18-FDG PET; CT; Treatment response prediction
PurposeTo assess the role of radiomics parameters in predicting pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) in patients with locally advanced breast cancer.MethodsSeventy-nine patients who had undergone pretreatment staging F-18-FDG PET/CT and treatment with NAC between January 2010 and January 2018 were included in the study. Primary lesions on PET images were delineated, and extraction of first-, second-, and higher-order imaging features was performed using LIFEx software. The relationship between these parameters and pCR to NAC was analyzed by multiple logistic regression models.ResultsNineteen patients (24%) had pCR to NAC. Different models were generated on complete information and imputed datasets, using univariable and multivariable logistic regression and least absolute shrinkage and selection operator (lasso) regression. All models could predict pCR to NAC, with area under the curve values ranging from 0.70 to 0.73. All models agreed that tumor molecular subtype is the primary predictor of the primary endpoint.ConclusionsOur models predicted that patients with subtype 2 and subtype 3 (HER2+ and triple negative, respectively) are more likely to have a pCR to NAC than those with subtype 1 (luminal). The association between PET imaging features and pCR suggested that PET imaging features could be considered as potential predictors of pCR in locally advanced breast cancer patients.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据