Early Prediction and Evaluation of Breast Cancer Response to Neoadjuvant Chemotherapy Using Quantitative DCE-MRI

The purpose is to compare quantitative dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) metrics with imaging tumor size for early prediction of breast cancer response to neoadjuvant chemotherapy (NACT) and evaluation of residual cancer burden (RCB). Twenty-eight patients with 29 prim...

Full description

Bibliographic Details
Main Authors: Alina Tudorica, Karen Y Oh, Stephen Y-C Chui, Nicole Roy, Megan L Troxell, Arpana Naik, Kathleen A Kemmer, Yiyi Chen, Megan L Holtorf, Aneela Afzal, Charles S Springer Jr., Xin Li, Wei Huang
Format: Article
Language:English
Published: Elsevier 2016-02-01
Series:Translational Oncology
Online Access:http://www.sciencedirect.com/science/article/pii/S1936523315300176
id doaj-468bae42366040c4916c3cf1068b9463
record_format Article
spelling doaj-468bae42366040c4916c3cf1068b94632020-11-25T00:29:54ZengElsevierTranslational Oncology1936-52331944-71242016-02-019181710.1016/j.tranon.2015.11.016Early Prediction and Evaluation of Breast Cancer Response to Neoadjuvant Chemotherapy Using Quantitative DCE-MRIAlina Tudorica0Karen Y Oh1Stephen Y-C Chui2Nicole Roy3Megan L Troxell4Arpana Naik5Kathleen A Kemmer6Yiyi Chen7Megan L Holtorf8Aneela Afzal9Charles S Springer Jr.10Xin Li11Wei Huang12Diagnostic Radiology, Oregon Health & Science University, Portland, OR, USADiagnostic Radiology, Oregon Health & Science University, Portland, OR, USAMedical Oncology, Oregon Health & Science University, Portland, OR, USADiagnostic Radiology, Oregon Health & Science University, Portland, OR, USAKnight Cancer Institute, Oregon Health & Science University, Portland, OR, USAKnight Cancer Institute, Oregon Health & Science University, Portland, OR, USAMedical Oncology, Oregon Health & Science University, Portland, OR, USAKnight Cancer Institute, Oregon Health & Science University, Portland, OR, USAKnight Cancer Institute, Oregon Health & Science University, Portland, OR, USAAdvanced Imaging Research Center, Oregon Health & Science University, Portland, OR, USAKnight Cancer Institute, Oregon Health & Science University, Portland, OR, USAAdvanced Imaging Research Center, Oregon Health & Science University, Portland, OR, USAKnight Cancer Institute, Oregon Health & Science University, Portland, OR, USAThe purpose is to compare quantitative dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) metrics with imaging tumor size for early prediction of breast cancer response to neoadjuvant chemotherapy (NACT) and evaluation of residual cancer burden (RCB). Twenty-eight patients with 29 primary breast tumors underwent DCE-MRI exams before, after one cycle of, at midpoint of, and after NACT. MRI tumor size in the longest diameter (LD) was measured according to the RECIST (Response Evaluation Criteria In Solid Tumors) guidelines. Pharmacokinetic analyses of DCE-MRI data were performed with the standard Tofts and Shutter-Speed models (TM and SSM). After one NACT cycle the percent changes of DCE-MRI parameters Ktrans (contrast agent plasma/interstitium transfer rate constant), ve (extravascular and extracellular volume fraction), kep (intravasation rate constant), and SSM-unique τi (mean intracellular water lifetime) are good to excellent early predictors of pathologic complete response (pCR) vs. non-pCR, with univariate logistic regression C statistics value in the range of 0.804 to 0.967. ve values after one cycle and at NACT midpoint are also good predictors of response, with C ranging 0.845 to 0.897. However, RECIST LD changes are poor predictors with C = 0.609 and 0.673, respectively. Post-NACT Ktrans, τi, and RECIST LD show statistically significant (P < .05) correlations with RCB. The performances of TM and SSM analyses for early prediction of response and RCB evaluation are comparable. In conclusion, quantitative DCE-MRI parameters are superior to imaging tumor size for early prediction of therapy response. Both TM and SSM analyses are effective for therapy response evaluation. However, the τi parameter derived only with SSM analysis allows the unique opportunity to potentially quantify therapy-induced changes in tumor energetic metabolism.http://www.sciencedirect.com/science/article/pii/S1936523315300176
collection DOAJ
language English
format Article
sources DOAJ
author Alina Tudorica
Karen Y Oh
Stephen Y-C Chui
Nicole Roy
Megan L Troxell
Arpana Naik
Kathleen A Kemmer
Yiyi Chen
Megan L Holtorf
Aneela Afzal
Charles S Springer Jr.
Xin Li
Wei Huang
spellingShingle Alina Tudorica
Karen Y Oh
Stephen Y-C Chui
Nicole Roy
Megan L Troxell
Arpana Naik
Kathleen A Kemmer
Yiyi Chen
Megan L Holtorf
Aneela Afzal
Charles S Springer Jr.
Xin Li
Wei Huang
Early Prediction and Evaluation of Breast Cancer Response to Neoadjuvant Chemotherapy Using Quantitative DCE-MRI
Translational Oncology
author_facet Alina Tudorica
Karen Y Oh
Stephen Y-C Chui
Nicole Roy
Megan L Troxell
Arpana Naik
Kathleen A Kemmer
Yiyi Chen
Megan L Holtorf
Aneela Afzal
Charles S Springer Jr.
Xin Li
Wei Huang
author_sort Alina Tudorica
title Early Prediction and Evaluation of Breast Cancer Response to Neoadjuvant Chemotherapy Using Quantitative DCE-MRI
title_short Early Prediction and Evaluation of Breast Cancer Response to Neoadjuvant Chemotherapy Using Quantitative DCE-MRI
title_full Early Prediction and Evaluation of Breast Cancer Response to Neoadjuvant Chemotherapy Using Quantitative DCE-MRI
title_fullStr Early Prediction and Evaluation of Breast Cancer Response to Neoadjuvant Chemotherapy Using Quantitative DCE-MRI
title_full_unstemmed Early Prediction and Evaluation of Breast Cancer Response to Neoadjuvant Chemotherapy Using Quantitative DCE-MRI
title_sort early prediction and evaluation of breast cancer response to neoadjuvant chemotherapy using quantitative dce-mri
publisher Elsevier
series Translational Oncology
issn 1936-5233
1944-7124
publishDate 2016-02-01
description The purpose is to compare quantitative dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) metrics with imaging tumor size for early prediction of breast cancer response to neoadjuvant chemotherapy (NACT) and evaluation of residual cancer burden (RCB). Twenty-eight patients with 29 primary breast tumors underwent DCE-MRI exams before, after one cycle of, at midpoint of, and after NACT. MRI tumor size in the longest diameter (LD) was measured according to the RECIST (Response Evaluation Criteria In Solid Tumors) guidelines. Pharmacokinetic analyses of DCE-MRI data were performed with the standard Tofts and Shutter-Speed models (TM and SSM). After one NACT cycle the percent changes of DCE-MRI parameters Ktrans (contrast agent plasma/interstitium transfer rate constant), ve (extravascular and extracellular volume fraction), kep (intravasation rate constant), and SSM-unique τi (mean intracellular water lifetime) are good to excellent early predictors of pathologic complete response (pCR) vs. non-pCR, with univariate logistic regression C statistics value in the range of 0.804 to 0.967. ve values after one cycle and at NACT midpoint are also good predictors of response, with C ranging 0.845 to 0.897. However, RECIST LD changes are poor predictors with C = 0.609 and 0.673, respectively. Post-NACT Ktrans, τi, and RECIST LD show statistically significant (P < .05) correlations with RCB. The performances of TM and SSM analyses for early prediction of response and RCB evaluation are comparable. In conclusion, quantitative DCE-MRI parameters are superior to imaging tumor size for early prediction of therapy response. Both TM and SSM analyses are effective for therapy response evaluation. However, the τi parameter derived only with SSM analysis allows the unique opportunity to potentially quantify therapy-induced changes in tumor energetic metabolism.
url http://www.sciencedirect.com/science/article/pii/S1936523315300176
work_keys_str_mv AT alinatudorica earlypredictionandevaluationofbreastcancerresponsetoneoadjuvantchemotherapyusingquantitativedcemri
AT karenyoh earlypredictionandevaluationofbreastcancerresponsetoneoadjuvantchemotherapyusingquantitativedcemri
AT stephenycchui earlypredictionandevaluationofbreastcancerresponsetoneoadjuvantchemotherapyusingquantitativedcemri
AT nicoleroy earlypredictionandevaluationofbreastcancerresponsetoneoadjuvantchemotherapyusingquantitativedcemri
AT meganltroxell earlypredictionandevaluationofbreastcancerresponsetoneoadjuvantchemotherapyusingquantitativedcemri
AT arpananaik earlypredictionandevaluationofbreastcancerresponsetoneoadjuvantchemotherapyusingquantitativedcemri
AT kathleenakemmer earlypredictionandevaluationofbreastcancerresponsetoneoadjuvantchemotherapyusingquantitativedcemri
AT yiyichen earlypredictionandevaluationofbreastcancerresponsetoneoadjuvantchemotherapyusingquantitativedcemri
AT meganlholtorf earlypredictionandevaluationofbreastcancerresponsetoneoadjuvantchemotherapyusingquantitativedcemri
AT aneelaafzal earlypredictionandevaluationofbreastcancerresponsetoneoadjuvantchemotherapyusingquantitativedcemri
AT charlessspringerjr earlypredictionandevaluationofbreastcancerresponsetoneoadjuvantchemotherapyusingquantitativedcemri
AT xinli earlypredictionandevaluationofbreastcancerresponsetoneoadjuvantchemotherapyusingquantitativedcemri
AT weihuang earlypredictionandevaluationofbreastcancerresponsetoneoadjuvantchemotherapyusingquantitativedcemri
_version_ 1725329172439498752