Automated Semi-Quantitative Analysis of Breast MRI: Potential Imaging Biomarker for the Prediction of Tissue Response to Neoadjuvant Chemotherapy

Language
en
Document Type
Article
Issue Date
2019-03-20
Issue Year
2017
Authors
Dietzel, Matthias
Kaiser, Clemens
Pinker, Katja
Wenkel, Evelyn
Hammon, Matthias
Uder, Michael
Bennani Baiti, Barbara
Clauser, Paola
Schulz-Wendtland, Rüdiger
Baltzer, Pascal
Editor
Abstract

Background: We aimed to investigate an automated semi-quantitative software as an imaging biomarker for the prediction of tissue response (TR) after completion of neoadjuvant chemotherapy (NAC). Methods: Breast magnetic resonance imaging (MRI) (1.5T, protocol according to international recommendations) of 67 patients with biopsy-proven invasive breast cancer were examined before and after NAC. After completion of NAC, histopathologic assessments of TR were classified according to the Chevallier grading system (CG1/4: full/non-responder; CG2/C3: partial responder). A commercially available fully automatic software (CADstream) extracted MRI parameters of tumor extension (tumor diameter/volume: TD/TV). Pre- versus post-NAC values were compared (ΔTV and ΔTD). Additionally, the software performed volumetric analyses of vascularization (VAV) after NAC. Accuracy of MRI parameters to predict TR were identified (cross-tabs, ROC, AUC, Kruskal-Wallis). Results: There were 37 (34.3%) CG1, 7 (6.5%) CG2, 53 (49.1%) CG3, and 11 (10.2%) CG4 lesions. The software reached area under the curve levels of 79.5% (CG1/complete response: ΔTD), 68.6% (CG2, CG3/partial response: VAV), and 88.8% to predict TR (CG4/non-response: ΔTV). Conclusion: Semi-quantitative automated analysis of breast MRI data enabled the prediction of tissue response to NAC.

Journal Title
Breast Care
Volume
12
Issue
4
Citation

Breast Care 12.4 (2017): S. 231 - 236 https://www.karger.com/Article/FullText/480226 © 2017 S. Karger GmbH, Freiburg

Zugehörige ORCIDs