With recent technological advances, the contribution that imaging makes to the care
of cancer patients goes well beyond tumor morphology. Advanced MRI sequences and sophisticated
image analysis software have enabled the detection of specific biological processes,
which reflect cancer behavior, including tumor aggressiveness and response to treatment.
In breast imaging, dynamic contrast enhanced (DCE) sequences play key roles in cancer
detection and characterization (
1
). Thus, advanced DCE sequences have the potential to revolutionize breast cancer
imaging. Indeed, such MRI sequences are characterized by high temporal resolution,
enabling the acquisition of multiple repeated images in a short time interval and,
through the application of a pharmacokinetic model, to analyze the transfer of contrast
agent through the capillary vessel wall, a process strongly related to tissue permeability
and neoangiogenesis. Such biological phenomena are described by quantitative values,
such as the contrast transfer from the vessel to the extravascular extracellular space
(Ktrans) and vice-versa (Kep), the amount of contrast agent within the vessel (plasma
volume) and in the EES (Ve) (
- Pinker K
- Helbich TH
- Morris EA.
The potential of multiparametric MRI of the breast.
Br J Radiol. 2017; https://doi.org/10.1259/bjr.20160715
2
). Several studies explored the role of such parameters in different imaging tasks,
including differentiating benign from malignant breast lesions, characterizing breast
cancer aggressiveness, predicting patients’ prognosis and the early assessment of
the response to neoadjuvant chemotherapy (
- Bernstein JM
- Kershaw LE
- Withey SB
- et al.
Tumor plasma flow determined by dynamic contrast-enhanced MRI predicts response to
induction chemotherapy in head and neck cancer.
Oral Oncol. 2015; https://doi.org/10.1016/j.oraloncology.2015.01.013
3
,
- Kim Y
- Kim SH
- Song BJ
- et al.
Early prediction of response to neoadjuvant chemotherapy using dynamic contrast-enhanced
MRI and ultrasound in breast cancer.
Korean J Radiol. 2018; https://doi.org/10.3348/kjr.2018.19.4.682
4
,
- Margolis NE
- Moy L
- Sigmund EE
- et al.
Assessment of aggressiveness of breast cancer using simultaneous 18F-FDG-PET and DCE-MRI.
Clin Nucl Med. 2016; https://doi.org/10.1097/RLU.0000000000001254
5
,
- Liu F
- Wang M
- Li H.
Role of perfusion parameters on DCE-MRI and ADC values on DWMRI for invasive ductal
carcinoma at 3.0 Tesla.
World J Surg Oncol. 2018; https://doi.org/10.1186/s12957-018-1538-8
6
). This last possible application represents one of the most fascinating uses of quantitative
DCE-MRI parameters, if we consider that changes in tumor biology are supposed to occur
earlier than the morphologic ones (
- Lee J
- Kim SH
- Kang BJ.
Pretreatment prediction of pathologic complete response to neoadjuvant chemotherapy
in breast cancer: perfusion metrics of dynamic contrast enhanced MRI.
Sci Rep. 2018; https://doi.org/10.1038/s41598-018-27764-9
7
). Thus, changes of perfusion parameters after the first chemotherapy cycles may early
reflect tumor response or resistance. Moreover, pre-treatment values might reflect
the tumor vascular asset, providing important information related to drug delivery
and, therefore, treatment response.- Romeo V
- Accardo G
- Perillo T
- et al.
Assessment and prediction of response to neoadjuvant chemotherapy in breast cancer:
A comparison of imaging modalities and future perspectives.
Cancers (Basel). 2021; https://doi.org/10.3390/cancers13143521
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References
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Article info
Publication history
Published online: January 03, 2022
Accepted:
December 5,
2021
Received:
December 5,
2021
Identification
Copyright
© 2021 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.
