医学
无线电技术
威尔科克森符号秩检验
逻辑回归
接收机工作特性
乳腺癌
队列
新辅助治疗
放射科
阶段(地层学)
完全响应
秩相关
核医学
癌症
内科学
机器学习
化疗
曼惠特尼U检验
古生物学
生物
计算机科学
作者
Ken Pin Hwang,Nabil Elshafeey,Aikaterini Kotrotsou,Huiqin Chen,Jong Bum Son,Medine Böge,Rania M. Mohamed,Abeer H Abdelhafez,Beatriz E. Adrada,Bikash Panthi,Jia Sun,Benjamin C. Musall,Shu Zhang,Rosalind P. Candelaria,Jason B. White,Elizabeth Ravenberg,Debu Tripathy,Clinton Yam,Jennifer K. Litton,Lei Huo,Alastair Thompson,Peng Wei,Wanli Yang,Marty Pagel,Jonathan Ma,Gaiane M. Rauch
出处
期刊:Radiology
日期:2023-07-01
卷期号:5 (4)
被引量:2
摘要
Purpose To determine if a radiomics model based on quantitative maps acquired with synthetic MRI (SyMRI) is useful for predicting neoadjuvant systemic therapy (NAST) response in triple-negative breast cancer (TNBC). Materials and Methods In this prospective study, 181 women diagnosed with stage I–III TNBC were scanned with a SyMRI sequence at baseline and at midtreatment (after four cycles of NAST), producing T1, T2, and proton density (PD) maps. Histopathologic analysis at surgery was used to determine pathologic complete response (pCR) or non-pCR status. From three-dimensional tumor contours drawn on the three maps, 310 histogram and textural features were extracted, resulting in 930 features per scan. Radiomic features were compared between pCR and non-pCR groups by using Wilcoxon rank sum test. To build a multivariable predictive model, logistic regression with elastic net regularization and cross-validation was performed for texture feature selection using 119 participants (median age, 52 years [range, 26–77 years]). An independent testing cohort of 62 participants (median age, 48 years [range, 23–74 years]) was used to evaluate and compare the models by area under the receiver operating characteristic curve (AUC). Results Univariable analysis identified 15 T1, 10 T2, and 12 PD radiomic features at midtreatment that predicted pCR with an AUC greater than 0.70 in both the training and testing cohorts. Multivariable radiomics models of maps acquired at midtreatment demonstrated superior performance over those acquired at baseline, achieving AUCs as high as 0.78 and 0.72 in the training and testing cohorts, respectively. Conclusion SyMRI-based radiomic features acquired at midtreatment are potentially useful for identifying early NAST responders in TNBC. Keywords: MR Imaging, Breast, Outcomes Analysis ClinicalTrials.gov registration no. NCT02276443 Supplemental material is available for this article. © RSNA, 2023 See also the commentary by Houser and Rapelyea in this issue.