Mapping Breast Cancer Between Clinical X-Ray and MR Images

Abstract

Characterizing a breast lesion can involve comparing X-ray and magnetic resonance (MR) images of a patient’s breast. Tracking a lesion between these imaging modalities is nontrivial because of the different types of deformation the breast undergoes during these imaging procedures. We present a retrospective clinical validation study to assess the performance of a biomechanical modeling framework for mapping lesion locations between clinical MR images and cranio-caudal X-ray mammograms. MR images from four patients were used to create customized finite element models. The unloaded configuration of each breast was then determined, and mammographic compression was simulated using finite deformation elasticity coupled with contact mechanics. The predicted location of each patient’s tumor(s) in the simulated compressed breast was compared with the true tumor locations on the mammogram as identified by clinicians. The degree of overlap between the true lesion area and the predicted lesion area, estimated using the Jaccard coefficient, ranged between 14 and 75%. The results indicate that biomechanical modeling can provide reliable co-location of lesions between MR images and mammograms.