Rationale and Objectives
To determine whether kinetics measured with ultrafast dynamic contrast-enhanced magnetic
resonance imaging in tumor and normal parenchyma pre- and post-neoadjuvant therapy
(NAT) can predict the response of breast cancer to NAT.
Materials and Methods
Twenty-four patients with histologically confirmed invasive breast cancer were enrolled.
They were scanned with ultrafast dynamic contrast-enhanced magnetic resonance imaging
(3-7 seconds/frame) pre- and post-NAT. Four kinetic parameters were calculated in
the segmented tumors, and ipsi- and contra-lateral normal parenchyma: (1) tumor (tSE30)
or background parenchymal relative enhancement at 30 seconds (BPE30), (2) maximum
relative enhancement slope (MaxSlope), (3) bolus arrival time (BAT), and (4) area
under relative signal enhancement curve for the initial 30 seconds (AUC30). The tumor
kinetics and the differences between ipsi- and contra-lateral parenchymal kinetics
were compared for patients achieving pathologic complete response (pCR) vs those who
had residual disease after NAT. The chi-squared test and two-sided t-test were used
for baseline demographics. The Wilcoxon rank sum test and one-way analysis of variance
were used for differential responses to therapy.
Results
Patients with similar pre-NAT mean BPE30, median BAT and mean AUC30 in the ipsi- and
contralateral normal parenchyma were more likely to achieve pCR following NAT (p < 0.02). Patients classified as having residual cancer burden (RCB) II after NAT
showed higher post-NAT tSE30 and tumor AUC30 and higher post-NAT MaxSlope in ipsilateral
normal parenchyma compared to those classified as RCB I or pCR (p < 0.05).
Conclusion
Bilateral asymmetry in normal parenchyma could predict treatment outcome prior to
NAT. Post-NAT tumor kinetics could evaluate the aggressiveness of residual tumor.
Key Words
Abbreviations:
AUC30 (initial area under signal enhancement curve over 30 seconds), BAT (bolus arrival time), BPE (background parenchymal enhancement), BPE30 (initial background parenchymal enhancement at 30 seconds), DCE-MRI (Dynamic contrast-enhanced magnetic resonance imaging), IDC (invasive ductal carcinoma), MaxSlope (maximum relative enhancement slope), NAT (Neoadjuvant therapy), pCR (pathologic complete response), PSE (percent signal enhancement), RCB (residual cancer burden), ROI (Region of interest), tSE30 (initial relative signal enhancement in tumor at 30 seconds)To read this article in full you will need to make a payment
Purchase one-time access:
Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online accessOne-time access price info
- For academic or personal research use, select 'Academic and Personal'
- For corporate R&D use, select 'Corporate R&D Professionals'
Subscribe:
Subscribe to Academic RadiologyAlready a print subscriber? Claim online access
Already an online subscriber? Sign in
Register: Create an account
Institutional Access: Sign in to ScienceDirect
REFERENCES
- Neoadjuvant trials in early breast cancer: pathological response at surgery and correlation to longer term outcomes - what does it all mean?.BMC Med. 2015; 13: 234
- Pathologic complete response after neoadjuvant chemotherapy and impact on breast cancer recurrence and survival: a comprehensive meta-analysis.Clin Cancer Res. 2020; 26: 2838-2848
- Role of dynamic contrast-enhanced MRI in evaluating the association between contralateral parenchymal enhancement and survival outcome in ER-positive, HER2-negative, node-negative invasive breast cancer.J Magn Reson Imaging. 2018; 48: 1678-1689
- Defining the benefits of neoadjuvant chemotherapy for breast cancer.J Clin Oncol. 2012; 30: 1747-1749
- Pembrolizumab for early triple-negative breast cancer.N Engl J Med. 2020; 382: 810-821
- Neoadjuvant systemic therapy in breast cancer: association of contrast-enhanced MR imaging findings, diffusion-weighted imaging findings, and tumor subtype with tumor response.Radiology. 2017; 283: 663-672
- Early prediction of breast cancer therapy response using multiresolution fractal analysis of DCE-MRI parametric maps.Tomography. 2019; 5: 90-98
- Kinetic analysis of benign and malignant breast lesions with ultrafast dynamic contrast-enhanced MRI: comparison with standard kinetic assessment.AJR Am J Roentgenol. 2016; 207: 1159-1166
- Ultrafast bilateral DCE-MRI of the breast with conventional fourier sampling: preliminary evaluation of semi-quantitative analysis.Acad Radiol. 2016; 23: 1137-1144
- Background parenchymal enhancement at breast MR imaging: normal patterns, diagnostic challenges, and potential for false-positive and false-negative interpretation.Radiographics. 2014; 34: 234-247
- Breast stromal enhancement on MRI is associated with response to neoadjuvant chemotherapy.AJR Am J Roentgenol. 2008; 190: 1630-1636
- Background parenchymal enhancement in breast MRI before and after neoadjuvant chemotherapy: correlation with tumour response.Eur Radiol. 2016; 26: 1590-1596
- Relationship between background parenchymal enhancement on breast MRI and pathological tumor response in breast cancer patients receiving neoadjuvant chemotherapy.Br J Radiol. 2018; 9120170550
- Quantitative background parenchymal enhancement to predict recurrence after neoadjuvant chemotherapy for breast cancer.Sci Rep. 2019; 9: 19185
- Background parenchymal enhancement of the contralateral normal breast: association with tumor response in breast cancer patients receiving neoadjuvant chemotherapy.Transl Oncol. 2015; 8: 204-209
- Background parenchymal enhancement on preoperative magnetic resonance imaging: association with recurrence-free survival in breast cancer patients treated with neoadjuvant chemotherapy.Medicine (Baltimore). 2016; 95: e3000
- Predicting the response to neoadjuvant chemotherapy for breast cancer: wavelet transforming radiomics in MRI.BMC Cancer. 2020; 20: 100
- Multiparametric magnetic resonance imaging for predicting pathological response after the first cycle of neoadjuvant chemotherapy in breast cancer.Invest Radiol. 2015; 50: 195-204
- Decreased background parenchymal enhancement of the contralateral breast after two cycles of neoadjuvant chemotherapy is associated with tumor response in HER2-positive breast cancer.Acta Radiol. 2018; 59: 806-812
- Background parenchymal enhancement on breast MRI: association with recurrence-free survival in patients with newly diagnosed invasive breast cancer.Breast Cancer Res Treat. 2017; 163: 573-586
- Breast MRI phenotype and background parenchymal enhancement may predict tumor response to neoadjuvant endocrine therapy.Breast J. 2018; 24: 1010-1014
- High-background parenchymal enhancement in the contralateral breast is an imaging biomarker for favorable prognosis in patients with triple-negative breast cancer treated with chemotherapy.Am J Transl Res. 2021; 13: 4422-4436
- Background parenchymal enhancement on breast MRI: a comprehensive review.J Magn Reson Imaging. 2020; 51: 43-61
- Nonmass enhancement breast lesions: diagnostic performance of kinetic assessment on ultrafast and standard dynamic contrast-enhanced MRI in comparison with morphologic evaluation.AJR Am J Roentgenol. 2020; 215: 511-518
- Quantitative analysis of vascular properties derived from ultrafast DCE-MRI to discriminate malignant and benign breast tumors.Magn Reson Med. 2019; 81: 2147-2160
- Long-term prognostic risk after neoadjuvant chemotherapy associated with residual cancer burden and breast cancer subtype.J Clin Oncol. 2017; 35: 1049-1060
- 3D Slicer as an image computing platform for the quantitative imaging network.Magn Reson Imaging. 2012; 30: 1323-1341
- Diffeomorphic demons: efficient non-parametric image registration.Neuroimage. 2009; 45: S61-S72
- Predicting breast cancer response to neoadjuvant treatment using multi-feature MRI: results from the I-SPY 2 TRIAL.NPJ Breast Cancer. 2020; 6: 63
- Fast temporal resolution dynamic contrast-enhanced MRI: histogram analysis versus visual analysis for differentiating benign and malignant breast lesions.AJR Am J Roentgenol. 2018; 211: 933-939
- Comparison of DCE-MRI of murine model cancers with a low dose and high dose of contrast agent.Phys Med. 2020; 81: 31-39
- Patterns of nonmasslike enhancement at screening breast MR imaging of high-risk premenopausal women.Radiographics. 2013; 33: 1343-1360
- Molecular magnetic resonance contrast agents for the detection of cancer: past and present.Semin Oncol. 2011; 38: 42-54
- Magnetic resonance angiography reveals increased arterial blood supply and tumorigenesis following high fat feeding in a mouse model of triple-negative breast cancer.NMR Biomed. 2020; 33: e4363
- Vascular abnormalities of the breast: arterial and venous disorders, vascular masses, and mimic lesions with radiologic-pathologic correlation.Radiographics. 2011; 31: E117-E136
- Aging-associated cardiovascular changes and their relationship to heart failure.Heart Fail Clin. 2012; 8: 143-164
- Computer-aided diagnosis of breast DCE-MRI images using bilateral asymmetry of contrast enhancement between two breasts.J Digit Imaging. 2014; 27: 152-160
- MRI kinetics with volumetric analysis in correlation with hormonal receptor subtypes and histologic grade of invasive breast cancers.AJR Am J Roentgenol. 2015; 204: W348-W356
- MRI phenotype of breast cancer: Kinetic assessment for molecular subtypes.J Magn Reson Imaging. 2015; 42: 920-924
- Comparison of pathologic response evaluation systems after neoadjuvant chemotherapy in breast cancers: correlation with computer-aided diagnosis of MRI features.AJR Am J Roentgenol. 2019; 213: 944-952
- Dynamic field-of-view imaging to increase temporal resolution in the early phase of contrast media uptake in breast DCE-MRI: a feasibility study.Med Phys. 2018; 45: 1050-1058
- Comparison of a reference region model with direct measurement of an AIF in the analysis of DCE-MRI data.Magn Reson Med. 2007; 57: 353-361
- Temporal sampling requirements for the tracer kinetics modeling of breast disease.Magn Reson Imaging. 1998; 16: 1057-1073
Article info
Publication history
Published online: March 26, 2022
Accepted:
February 8,
2022
Received in revised form:
February 2,
2022
Received:
October 25,
2021
Identification
Copyright
© 2022 Published by Elsevier Inc. on behalf of The Association of University Radiologists.