Deformable Registration for Longitudinal Breast MRI Screening

Abstract

MRI screening of high-risk patients for breast cancer provides very high sensitivity, but with a high recall rate and negative biopsies. Comparing the current exam to prior exams reduces the number of follow-up procedures requested by radiologists. Such comparison, however, can be challenging due to the highly deformable nature of breast tissues. Automated co-registration of multiple scans has the potential to aid diagnosis by providing 3D images for side-by-side comparison and also for use in CAD systems. Although many deformable registration techniques exist, they generally have a large number of parameters that need to be optimized and validated for each new application. Here, we propose a framework for such optimization and also identify the optimal input parameter set for registration of 3D T-weighted MRI of breast using Elastix, a widely used and freely available registration tool. A numerical simulation study was first conducted to model the breast tissue and its deformation through finite element (FE) modeling. This model generated the ground truth for evaluating the registration accuracy by providing the deformation of each voxel in the breast volume. An exhaustive search was performed over various values of 7 registration parameters (4050 different combinations of parameters were assessed) and the optimum parameter set was determined. This study showed that there was a large variation in the registration accuracy of different parameter sets ranging from 0.29 mm to 2.50 mm in median registration error and 3.71 mm to 8.90 mm in 95 percentile of the registration error. Mean registration errors of 0.32 mm, 0.29 mm, and 0.30 mm and 95 percentile errors of 3.71 mm, 5.02 mm, and 4.70 mm were obtained by the three best parameter sets. The optimal parameter set was applied to consecutive breast MRI scans of 13 patients. A radiologist identified 113 landmark pairs (~ 11 per patient) which were used to assess registration accuracy. The results demonstrated that using the optimal registration parameter set, a registration accuracy (in mm) of 3.4 [1.8 6.8] was achieved.

An investigation of the effect of fat suppression and dimensionality on the accuracy of breast MRI segmentation using U‐nets

“…Bilateral T1‐weighted (T1W) MR images were acquired on a 1.5‐T Scanner (Signa, General Electric Medical Systems, Milwaukee, WS) using a dedicated breast coil in a sagittal orientation with an average resolution of 0.39 mm by 0.39 mm in plane and 3.0 mm between slices. T1W images with fat suppression (FS) and without fat suppression (WOFS) were both acquired before contrast agent was administered and were coregistered using Elastix . The whole breast volumes were then divided into left and right breasts and resampled to 2 mm isotropic voxel size.…”

“…T1W images with fat suppression (FS) and without fat suppression (WOFS) were both acquired before contrast agent was administered and were coregistered using Elastix. 24,25 The whole breast volumes were then divided into left and right breasts and resampled to 2 mm isotropic voxel size. Finally, by using cropping and/or padding, all the volumes were resized to 64 9 128 9 128 pixels.…”

The application of multiple metrics in deformable image registration for target volume delineation of breast tumor bed

“…Stochastic gradient descent optimization was used with up to 500 iterations at each multi‐resolution level. The optimal weights of fiducial‐, region‐, and intensity‐based metrics were decided as 1, 1, and 100, respectively, through trial and error 31 . The PC equipped with Intel Core i5 CPU 3.4 GHz and 32 GB RAM was used to perform all the registration tasks.…”

Vascularity and Dynamic Contrast-Enhanced Breast Magnetic Resonance Imaging

“…Although co-registration is not required for detecting vascularity in a single DCE-MRI image, co-registration is required to detect changes in vascularity (or other imaging feature) over time. Breast registration is difficult because the breast is highly deformable which results in a complex combination of both affine and nonrigid transformations (135)(136)(137)(138). Additionally, many times the breast itself has changed over time either because of either natural biological cycles or malignant transformation.…”