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Texture analysis on MR images helps predicting non-response to NAC in breast cancer.

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Michoux, Nicolas [UCL] Van den Broeck, Stéphane [UCL] Lacoste, Laure [UCL] Fellah, Latifa [UCL] Galant, Christine [UCL] Berlière, Martine [UCL] Leconte, Isabelle [UCL]

(eng) BACKGROUND: To assess the performance of a predictive model of non-response to neoadjuvant chemotherapy (NAC) in patients with breast cancer based on texture, kinetic, and BI-RADS parameters measured from dynamic MRI. METHODS: Sixty-nine patients with invasive ductal carcinoma of the breast who underwent pre-treatment MRI were studied. Morphological parameters and biological markers were measured. Pathological complete response was defined as the absence of invasive and in situ cancer in breast and nodes. Pathological non-responders, partial and complete responders were identified. Dynamic imaging was performed at 1.5 T with a 3D axial T1W GRE fat-suppressed sequence. Visual texture, kinetic and BI-RADS parameters were measured in each lesion. ROC analysis and leave-one-out cross-validation were used to assess the performance of individual parameters, then the performance of multi-parametric models in predicting non-response to NAC. RESULTS: A model based on four pre-NAC parameters (inverse difference moment, GLN, LRHGE, wash-in) and k-means clustering as statistical classifier identified non-responders with 84 % sensitivity. BI-RADS mass/non-mass enhancement, biological markers and histological grade did not contribute significantly to the prediction. CONCLUSION: Pre-NAC texture and kinetic parameters help predicting non-benefit to NAC. Further testing including larger groups of patients with different tumor subtypes is needed to improve the generalization properties and validate the performance of the predictive model.

Document type Article de périodique (Journal article) – Article de recherche
Access type Accès libre
Publication date 2015
Language Anglais
Journal information "BMC Cancer" - Vol. 15, no. 1, p. 574 [1-13] (2015)
Peer reviewed yes
Publisher BioMed Central Ltd. ((United Kingdom) London)
e-issn 1471-2407
Publication status Publié
Affiliations UCL - SSS/IREC/IMAG - Pôle d'imagerie médicale
UCL - SSS/IREC/GYNE - Pôle de Gynécologie
UCL - SSS/IREC/MORF - Pôle de Morphologie
UCL - (SLuc) Service d'anatomie pathologique
UCL - (SLuc) Service de radiologie
UCL - (SLuc) Service de gynécologie et d'andrologie
UCL - SSS/IONS - Institute of NeuroScience
UCL - SSS/IONS/NEUR - Clinical Neuroscience
Keywords Breast cancer ; Neoadjuvant chemotherapy ; MRI ; Texture analysis
Links
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Bibliographic reference Michoux, Nicolas ; Van den Broeck, Stéphane ; Lacoste, Laure ; Fellah, Latifa ; Galant, Christine ; et. al. Texture analysis on MR images helps predicting non-response to NAC in breast cancer.. In: BMC Cancer, Vol. 15, no. 1, p. 574 [1-13] (2015)
Permanent URL http://hdl.handle.net/2078.1/165085