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Correlation between voxel-wise enhancement parameters on DCE-MRI and pathological prognostic factors in invasive breast cancers

  • BREAST RADIOLOGY
  • Published:
La radiologia medica Aims and scope Submit manuscript

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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Authors and Affiliations

  1. Integrative Biomedical Research PhD Program, Department of Biomedical Science for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133, Milan, Italy

    Rubina Manuela Trimboli

  2. Unit of Radiology, IRCCS Policlinico San Donato, Via Morandi 30, 20097, San Donato Milanese, Italy

    Marina Codari, Luca Alessandro Carbonaro & Francesco Sardanelli

  3. Postgraduate School in Radiodiagnostics, Università degli Studi di Milano, Via Festa del Perdono 7, 20122, Milan, Italy

    Katia Khouri Chalouhi, Ileana Ioan & Giovanna Lo Bue

  4. Università degli Studi di Milano, Corso di Laurea in Medicina e Chirurgia, Via Festa del Perdono 7, 20122, Milan, Italy

    Arianna Ottini

  5. MTS s.r.l.-Olea Medical e Vital Images Italian Distributor, via Morandi 2, 20077, Melegnano, Italy

    Daniela Casolino

  6. Department of Biomedical Science for Health, Università degli Studi di Milano, Via Morandi 30, 20097, San Donato Milanese, Italy

    Francesco Sardanelli

Authors
  1. Rubina Manuela Trimboli
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  2. Marina Codari
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  3. Katia Khouri Chalouhi
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  4. Ileana Ioan
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  5. Giovanna Lo Bue
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  6. Arianna Ottini
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  7. Daniela Casolino
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  8. Luca Alessandro Carbonaro
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  9. Francesco Sardanelli
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Corresponding author

Correspondence to Rubina Manuela Trimboli.

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Conflict of interest

Daniela Casolino is product manager for Olea Sphere software at MTS s.r.l. Other authors declare that they have no conflict of interest.

Ethical standards

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

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