Monitoring Breast Cancer Response to Neoadjuvant Chemotherapy Using Ultrasound Strain Elastography
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 resp...
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2019-09-01
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Series: | Translational Oncology |
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doaj-05addd7765d3426599384d5ceae4aeb82020-11-24T21:11:29ZengElsevierTranslational Oncology1936-52332019-09-0112911771184Monitoring Breast Cancer Response to Neoadjuvant Chemotherapy Using Ultrasound Strain ElastographyJason Fernandes0Lakshmanan Sannachi1William T. Tran2Alexander Koven3Elyse Watkins4Farnoosh Hadizad5Sonal Gandhi6Frances Wright7Belinda Curpen8Ahmed El Kaffas9Joanna Faltyn10Ali Sadeghi-Naini11Gregory Czarnota12Department of Radiation Oncology, Sunnybrook Health Sciences Centre, Toronto, CADepartment of Radiation Oncology, Sunnybrook Health Sciences Centre, Toronto, CA; Physical Sciences, Sunnybrook Research Institute, Toronto, CADepartment of Radiation Oncology, Sunnybrook Health Sciences Centre, Toronto, CA; Department of Radiation Oncology, University of Toronto, Toronto, CA; Centre for Health and Social Care Research, Sheffield Hallam University, Sheffield, UK; Institute of Clinical Evaluative Sciences, Sunnybrook Research Institute, Toronto, CADepartment of Radiation Oncology, Sunnybrook Health Sciences Centre, Toronto, CADepartment of Radiation Oncology, Sunnybrook Health Sciences Centre, Toronto, CADepartment of Radiation Oncology, Sunnybrook Health Sciences Centre, Toronto, CADivision of Medical Oncology, Sunnybrook Health Sciences Centre, Toronto, CADivision of Surgical Oncology, Sunnybrook Health Sciences Centre, Toronto, CADepartment of Medical Imaging, Sunnybrook Health Sciences Centre, Toronto, CAPhysical Sciences, Sunnybrook Research Institute, Toronto, CAPhysical Sciences, Sunnybrook Research Institute, Toronto, CADepartment of Radiation Oncology, Sunnybrook Health Sciences Centre, Toronto, CA; Department of Radiation Oncology, University of Toronto, Toronto, CA; Department of Medical Imaging, Sunnybrook Health Sciences Centre, Toronto, CA; Physical Sciences, Sunnybrook Research Institute, Toronto, CADepartment of Radiation Oncology, Sunnybrook Health Sciences Centre, Toronto, CA; Department of Radiation Oncology, University of Toronto, Toronto, CA; Department of Medical Biophysics, University of Toronto, Toronto, CA; Department of Medical Imaging, Sunnybrook Health Sciences Centre, Toronto, CA; Physical Sciences, Sunnybrook Research Institute, Toronto, CA; Address all correspondence to: Dr. Gregory J. Czarnota, PhD, MD, Department of Radiation Oncology, 2075 Bayview Avenue, T2, Toronto, Ontario, Canada M4N3M5.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.http://www.sciencedirect.com/science/article/pii/S1936523318306259 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
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 |
spellingShingle |
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 Monitoring Breast Cancer Response to Neoadjuvant Chemotherapy Using Ultrasound Strain Elastography Translational Oncology |
author_facet |
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 |
author_sort |
Jason Fernandes |
title |
Monitoring Breast Cancer Response to Neoadjuvant Chemotherapy Using Ultrasound Strain Elastography |
title_short |
Monitoring Breast Cancer Response to Neoadjuvant Chemotherapy Using Ultrasound Strain Elastography |
title_full |
Monitoring Breast Cancer Response to Neoadjuvant Chemotherapy Using Ultrasound Strain Elastography |
title_fullStr |
Monitoring Breast Cancer Response to Neoadjuvant Chemotherapy Using Ultrasound Strain Elastography |
title_full_unstemmed |
Monitoring Breast Cancer Response to Neoadjuvant Chemotherapy Using Ultrasound Strain Elastography |
title_sort |
monitoring breast cancer response to neoadjuvant chemotherapy using ultrasound strain elastography |
publisher |
Elsevier |
series |
Translational Oncology |
issn |
1936-5233 |
publishDate |
2019-09-01 |
description |
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. |
url |
http://www.sciencedirect.com/science/article/pii/S1936523318306259 |
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