Abstract
Purpose
To investigate the correlation between enhancement parameters on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and pathologic prognostic factors in invasive breast cancers (BCs).
Materials and methods
A total of 25 invasive BCs were included: 22 invasive ductal, 2 invasive lobular and 1 invasive mucinous. The tumor volume was segmented using a semi-automatic software (Olea Sphere). The following voxel-wise enhancement parameters were extracted: (1) time to peak enhancement; (2) signal intensity at peak (SIP); (3) peak enhancement percentage (PEP); (4) post-initial enhancement percentage (PIEP). The following pathological prognostic factors were considered for potential correlation: tumor (pT) and nodal (pN) stage, grading, perivascular/perineural invasion, estrogen/progesterone receptor status, Ki-67 proliferation, and HER2 expression. Spearman and Pearson correlation coefficients were calculated according with type of variable and data distribution.
Results
Tumor volume was 2.8 ± 2.0 cm3 (mean ± standard deviation [SD]). Mean SIP correlated with pT (ρ = 0.424, p = 0.035); mean PEP correlated with HER2 overexpression (ϕ = 0.471, p = 0.017) and pT (ρ = 0.449, p = 0.024). The percentage of voxels with fast PEP directly correlated with pT (ρ = 0.482, p = 0.015) and pN (ρ = 0.446, p = 0.026), while the percentage of voxels with slow PEP inversely correlated with pT (ρ = −0.421, p = 0.039) and pN (ρ = −0.481, p = 0.015). Segmentation time was 14.6 ± 1.3 min (mean ± SD).
Conclusion
In invasive BCs, DCE-MRI voxel-wise enhancement parameters correlated with HER2, pT, and pN.
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Daniela Casolino is product manager for Olea Sphere software at MTS s.r.l. Other authors declare that they have no conflict of interest.
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The work has been approved by the Local Ethical Committee, protocol code OLEA_01 on June 2, 2016. For this type of study formal consent is not required.
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Trimboli, R.M., Codari, M., Khouri Chalouhi, K. et al. Correlation between voxel-wise enhancement parameters on DCE-MRI and pathological prognostic factors in invasive breast cancers. Radiol med 123, 91–97 (2018). https://doi.org/10.1007/s11547-017-0809-8
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DOI: https://doi.org/10.1007/s11547-017-0809-8