Monitoring Breast Cancer Response to Neoadjuvant Chemotherapy Using Ultrasound Strain Elastography

• Main Authors: Jason Fernandes, Lakshmanan Sannachi, William T. Tran, Alexander Koven, Elyse Watkins, Farnoosh Hadizad, Sonal Gandhi, Frances Wright, Belinda Curpen, Ahmed El Kaffas, Joanna Faltyn, Ali Sadeghi-Naini, Gregory Czarnota
• Format: Article
• Language: English
• Published: Elsevier 2019-09-01
• Series: Translational Oncology
• Online Access: http://www.sciencedirect.com/science/article/pii/S1936523318306259

Strain elastography was used to monitor response to neoadjuvant chemotherapy (NAC) in 92 patients with biopsy-proven, locally advanced breast cancer. Strain elastography data were collected before, during, and after NAC. Relative changes in tumor strain ratio (SR) were calculated over time, and responder status was classified according to tumor size changes. Statistical analyses determined the significance of changes in SR over time and between response groups. Machine learning techniques, such as a naïve Bayes classifier, were used to evaluate the performance of the SR as a marker for Miller-Payne pathological endpoints. With pathological complete response (pCR) as an endpoint, a significant difference (P < .01) in the SR was observed between response groups as early as 2 weeks into NAC. Naïve Bayes classifiers predicted pCR with a sensitivity of 84%, specificity of 85%, and area under the curve of 81% at the preoperative scan. This study demonstrates that strain elastography may be predictive of NAC response in locally advanced breast cancer as early as 2 weeks into treatment, with high sensitivity and specificity, granting it the potential to be used for active monitoring of tumor response to chemotherapy.