Interactive Local Super-Resolution Reconstruction of Whole-Body MRI Mouse Data: A Pilot Study with Applications to Bone and Kidney Metastases

Abstract

In small animal imaging studies, when the locations of the micro-structures of interest are unknown a priori, there is a simultaneous need for full-body coverage and high resolution. In MRI, additional requirements to image contrast and acquisition time will often make it impossible to acquire such images directly. Recently, a resolution enhancing post-processing technique called super-resolution reconstruction (SRR) has been demonstrated to improve visualization and localization of micro-structures in small animal MRI by combining multiple low-resolution acquisitions. However, when the field-of-view is large relative to the desired voxel size, solving the SRR problem becomes very expensive, in terms of both memory requirements and computation time. In this paper we introduce a novel local approach to SRR that aims to overcome the computational problems and allow researchers to efficiently explore both global and local characteristics in whole-body small animal MRI. The method integrates state-of-the-art image processing techniques from the areas of articulated atlas-based segmentation, planar reformation, and SRR. A proof-of-concept is provided with two case studies involving CT, BLI, and MRI data of bone and kidney tumors in a mouse model. We show that local SRR-MRI is a computationally efficient complementary imaging modality for the precise characterization of tumor metastases, and that the method provides a feasible high-resolution alternative to conventional MRI.

A novel imaging method for correlating 2D light microscopic data and 3D volume data based on block-face imaging

“…MRI is commonly used to observe neuronal tissue, although still not as familiar as µCT in the laboratory. MRI could visualize internal structures of larger specimens, such as the human 25 – 27 , cat 28 or mouse brainstem 29 . Our CoMBI system was developed utilizing block-face imaging to avoid deformation artifacts, which are seen in other optical based methods, so that it obtains the intact 3D anatomical data of the specimens.…”

Multimodal Correlative Preclinical Whole Body Imaging and Segmentation

“…Their approach was validated for registration on 26 non-contrast enhanced Micro-CT mice and the organ interpolation was evaluated using 15 contrast enhanced Micro-CT images. This approach was later applied by 13 for super-resolution reconstruction of MRI in whole-body mouse data in studies of tumor metastases. Recently 14 15 developed an automatic statistical atlas (multi-subject) approach to registration of micro-CT images in mice.…”