A model combining BI-RADS® descriptors from pre-treatment B-mode breast ultrasound with clinicopathological tumor features shows promise in the prediction of residual disease after neoadjuvant chemotherapy Journal Article

  

Authors:	Kapetas, P.; Aggarwal, R.; Altuwayjiri, B.; Pinker, K.; Clauser, P.; Helbich, T. H.; Baltzer, P. A. T.
Article Title:	A model combining BI-RADS® descriptors from pre-treatment B-mode breast ultrasound with clinicopathological tumor features shows promise in the prediction of residual disease after neoadjuvant chemotherapy
Abstract:	Purpose: To create a simple model using standard BI-RADS® descriptors from pre-treatment B-mode ultrasound (US) combined with clinicopathological tumor features, and to assess the potential of the model to predict the presence of residual tumor after neoadjuvant chemotherapy (NAC) in breast cancer (BC) patients. Method: 245 female BC patients receiving NAC between January 2017 and December 2019 were included in this retrospective study. Two breast imaging fellows independently evaluated representative B-mode tumor images from baseline US. Additional clinicopathological tumor features were retrieved. The dataset was split into 170 training and 83 validation cases. Logistic regression was used in the training set to identify independent predictors of residual disease post NAC and to create a model, whose performance was evaluated by ROC curve analysis in the validation set. The reference standard was postoperative histology to determine the absence (pathological complete response, pCR) or presence (non-pCR) of residual invasive tumor in the breast or axillary lymph nodes. Results: 100 patients (40.8%) achieved pCR. Logistic regression demonstrated that tumor size, microlobulated margin, spiculated margin, the presence of calcifications, the presence of edema, HER2-positive molecular subtype, and triple-negative molecular subtype were independent predictors of residual disease. A model using these parameters demonstrated an area under the ROC curve of 0.873 in the training and 0.720 in the validation set for the prediction of residual tumor post NAC. Conclusions: A simple model combining standard BI-RADS® descriptors from pre-treatment B-mode breast US with clinicopathological tumor features predicts the presence of residual disease after NAC. © 2024 The Authors
Keywords:	adult; treatment response; aged; middle aged; retrospective studies; major clinical study; chemotherapy, adjuvant; neoadjuvant therapy; sensitivity and specificity; breast cancer; breast; echomammography; tumor volume; pathology; diagnostic imaging; breast neoplasms; retrospective study; information processing; ultrasound; statistical analysis; training; minimal residual disease; neoplasm, residual; multicenter study; adjuvant chemotherapy; breast tumor; predictive value of tests; cross-sectional study; neoadjuvant chemotherapy; drug therapy; chi square test; trastuzumab; therapy; predictive value; receiver operating characteristic; ultrasonography, mammary; triple negative breast cancer; procedures; response prediction; humans; human; female; article; b-mode ultrasound
Journal Title:	European Journal of Radiology
Volume:	178
ISSN:	0720-048X
Publisher:	Elsevier B.V
Date Published:	2024-09-01
Start Page:	111649
Language:	English
DOI:	10.1016/j.ejrad.2024.111649
PUBMED:	39094464
PROVIDER:	scopus
DOI/URL:	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200162464&doi=10.1016%2fj.ejrad.2024.111649&partnerID=40&md5=299454e22aff4b8c10cc20ebe842f2c6
Notes:	Article -- Source: Scopus

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