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2018-05-09 - Article/Dans un journal avec peer-review - Anglais - 16 page(s)

El Adoui Mohammed , Drisis Stylianos, Benjelloun Mohammed , "A PRM approach for early prediction of breast cancer response to chemotherapy based on registered MR images" in International Journal of Computer Assisted Radiology and Surgery

  • Edition : Springer (Germany)
  • Codes CREF : Techniques d'imagerie et traitement d'images (DI2770)
  • Unités de recherche UMONS : Informatique (F114)
  • Instituts UMONS : Institut de Recherche en Technologies de l’Information et Sciences de l’Informatique (InforTech)
Texte intégral :

Abstract(s) :

(Anglais) Purpose: This study aims to provide and optimize a performing algorithm for predicting the breast cancer response rate to the first round of chemotherapy using Magnetic Resonance Imaging (MRI). This provides an early recognition of breast tumor reaction to chemotherapy by using the Parametric Response Map (PRM) method. Methods: PRM may predict the breast cancer response to chemotherapy by analyzing voxel by voxel temporal intratumor changes during one round of chemotherapy. Indeed, the tumor recognizes intra-tumor changes concerning its vascularity, which is an important criterion in the present study. This method is mainly based on spatial image affine registration between the breast tumor MRI volumes, acquired before and after the first cycle of chemotherapy, and region growing segmentation of the tumor volume. To evaluate our method, we used a retrospective study of 40 patients provided by a collaborating institute. Results: PRM allows a color map to be created with the percentages of positive, negative and stable breast tumor response during the first round of chemotherapy, identifying each region with its response rate. We assessed the accuracy of the proposed method using technical and medical validation methods. The technical validation was based on landmarks-based registration and fully manual segmentation. The medical evaluation was based on the accuracy calculation of the standard reference of anatomic pathology. The p-values and the Area Under the Curve (AUC) of the Receiver Operating Characteristics (ROC) were calculated to evaluate the proposed PRM method. Conclusion: We performed and evaluated the proposed PRM method to study and analyze the behavior of a tumor during the first round of chemotherapy, based on the intra-tumor changes of MR breast tumor images. The AUC obtained for the PRM method is considered as relevant in the early prediction of breast tumor response. Key Words: MRI breast cancer, Image registration, Affine registration, PRM, Image segmentation, Image classification

Notes :
  • (Anglais) This article has been accepted by the CARS 2018 conference as a talk presentation in Berlin, Germany