Deconvolution-based dynamic contrast-enhanced MR imaging of breast tumors: correlation of tumor blood flow with human epidermal growth factor receptor 2 status and clinicopathologic findings--preliminary results.
OBJECTIVE
To prospectively determine whether breast carcinomas possess characteristic values of tumor blood flow (TBF) that correlate with pathologic and molecular prognostic markers.


METHODS
The institutional ethics committee approved this study. After informed consent was obtained, 57 women (age range, 31-80 years) with histologically proved breast cancer underwent routine magnetic resonance (MR) mammography, which included a whole-breast dynamic contrast material-enhanced (DCE) sequence. A second contrast material bolus was injected during dynamic single-section turbo field-echo imaging of the section where the lesion was maximally enhanced. The relative signal intensity changes were deconvolved in a pixelwise fashion to yield the TBF. Formalin-fixed paraffin-embedded tumor specimens on slides were evaluated for histologic size and grade, as well as for estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) protein. In patients with a HER2 protein score of 2+ or 3+, HER2 gene status was assessed. For all prognostic parameters, the Mann-Whitney U test was used to compare median TBF in the HER2-positive group with that in the HER2-negative group.


RESULTS
Significantly higher TBF was observed in tumors larger than 2 cm in diameter and in PR-negative and HER2 gene-amplified tumors (P < .05). In the HER2-positive and HER2-negative groups, ER-positive PR-positive tumors had a lower median TBF than did ER-negative PR-negative tumors, and the difference was significant in the HER2-positive group (P < .05).


CONCLUSIONS
Pixelwise deconvolution analysis of DCE MR data in patients with breast cancer can provide preoperative information regarding TBF. These results also support the hypothesis that there is increased TBF in HER2-positive tumors.
Makkat
Smitha
S
Department of Radiology, UZ Brussel, Vrije Universiteit Brussel, Laarbeeklaan 101, 1090 Brussels, Belgium. Smitha.Makkat@vub.ac.be
Luypaert
Robert
R
Stadnik
Tadeusz
T
Bourgain
Claire
C
Sourbron
Steven
S
Dujardin
Martine
M
De Greve
Jacques
J
De Mey
Johan
J
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D014408:Biomarkers, Tumor / Q000378:metabolism; D001943:Breast Neoplasms / Q000378:metabolism / Q000473:pathology*; D016009:Chi-Square Distribution; D003287:Contrast Media; D066246:ErbB Receptors / Q000378:metabolism*; D005260:Female; D019786:Gadolinium DTPA; D018734:Genes, erbB-2; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D007150:Immunohistochemistry; D017404:In Situ Hybridization, Fluorescence; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008875:Middle Aged; D009389:Neovascularization, Pathologic / Q000175:diagnosis*; D018709:Statistics, Nonparametric
D014408:Biomarkers, Tumor; D003287:Contrast Media; D066246:ErbB Receptors; D019786:Gadolinium DTPA