Automatic Spatial Linking of Lesions in Breast MRI Follow-up Images

PURPOSE Automatically linking the lesions detected in breast MRI follow-up examinations is required for the development of a computer-aided diagnosis (CAD) system to quantify characteristic changes of the lesions. In this work, we develop a registration-based method that enables automatic linking of lesions detected in breast MRI follow-up studies. METHOD AND MATERIALS From 51 subjects participating in a MRI screening program, we collected 102 dynamic contrast enhanced MRI (DCE-MRI) images, forming 51 pairs of follow-up studies. Current and prior examinations were acquired in different scanners with a time interval of one year, using transversal and coronal views, respectively. One experienced radiologist manually placed 71 pairs of markers, indicating the center locations of 71 pairs of lesions found in both current and prior studies. Automatic lesion linking is achieved by registering current and prior MRI examinations. First, a motion correction algorithm is performed on both current and prior DCE-MRI. Then, fully automatic breast segmentation is applied on the current and prior pre-contrast images to extract breast masks, which are used to obtain an initial affine transform. Then, a non-rigid registration algorithm using normalized gradient fields as similarity measure together with curvature regularization is exploited to register the current and prior pre-contrast images. Since the follow-up scans may have inconsistent field of views, the registration only focuses on the segmented breast regions to enforce the alignment accuracy in breast areas, such that non-breast regions will not attract and influence the registration process. RESULTS Based on the deformation fields obtained by registration, markers labeling the lesions in the current image were transformed to the prior image frame, where the distance between the transformed markers and the markers originally labeled in prior images was computed. The average distance error was 9.6 A,A+- 9.3 mm. CONCLUSION The proposed system is potentially applicable to automatically link the lesions detected in a CAD system to investigate the characteristic changes. CLINICAL RELEVANCE/APPLICATION Visual assessment and comparison of characteristic change of the lesions in breast DCE-MRI follow-up exams is time consuming, and computer-aided lesion comparison may increase clinical effectiveness.