医学
乳腺癌
活检
三阴性乳腺癌
新辅助治疗
乳房磁振造影
放射科
预测值
接收机工作特性
内科学
癌症
肿瘤科
乳腺摄影术
作者
Jorge E. Jimenez,Abeer H Abdelhafez,Elizabeth A. Mittendorf,Nabil Elshafeey,Joshua P. Yung,Jennifer K. Litton,Beatriz E. Adrada,Rosalind P. Candelaria,Jason B. White,Alastair Thompson,Lei Huo,Peng Wei,Debu Tripathy,Vicente Valero,Clinton Yam,John D. Hazle,Stacy L. Moulder,Wei Tse Yang,Gaiane M. Rauch
标识
DOI:10.1016/j.ejrad.2022.110220
摘要
We aimed to develop a predictive model based on pretreatment MRI radiomic features (MRIRF) and tumor-infiltrating lymphocyte (TIL) levels, an established prognostic marker, to improve the accuracy of predicting pathologic complete response (pCR) to neoadjuvant systemic therapy (NAST) in triple-negative breast cancer (TNBC) patients.This Institutional Review Board (IRB) approved retrospective study included a preliminary set of 80 women with biopsy-proven TNBC who underwent NAST, pretreatment dynamic contrast enhanced MRI, and biopsy-based pathologic assessment of TIL. A threshold of ≥ 20% was used to define high TIL. Patients were classified into pCR and non-pCR based on pathologic evaluation of post-NAST surgical specimens. pCR was defined as the absence of invasive carcinoma in the surgical specimen. Segmentation and MRIRF extraction were done using a Food and Drug Administration (FDA) approved software QuantX. The top five features were combined into a single MRIRF signature value.Of 145 extracted MRIRF, 38 were significantly correlated with pCR. Five nonredundant imaging features were identified: volume, uniformity, peak timepoint variance, homogeneity, and variance. The accuracy of the MRIRF model, P = .001, 72.7% positive predictive value (PPV), 72.0% negative predictive value (NPV), was similar to the TIL model (P = .038, 65.5% PPV, 72.6% NPV). When MRIRF and TIL models were combined, we observed improved prognostic accuracy (P < .001, 90.9% PPV, 81.4% NPV). The models area under the receiver operating characteristic curve (AUC) was 0.632 (TIL), 0.712 (MRIRF) and 0.752 (TIL + MRIRF).A predictive model combining pretreatment MRI radiomic features with TIL level on pretreatment core biopsy improved accuracy in predicting pCR to NAST in TNBC patients.
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