"Interactive system for exploration of multi-modal rat brain data"

Artem Khmelinskii, Luam Mengler, Pieter Kitslaar, Marius Staring, Chrystelle Po, Johan H.C. Reiber, Mathias Hoehn and Boudewijn P.F. Lelieveldt

Abstract

Introduction: In pre-clinical research, the combination of structural (MRI, CT, ultrasound), functional (PET, SPECT, specialized MRI protocols) and optical (BLI, FLI) imaging modalities enables longitudinal and cross-sectional studies in living organisms.
The goal of this work is to develop software for interactive exploration of heterogeneous multi-modal data in follow-up studies

Methods: To enable comparison and integration of follow-up multimodal data, image registration is required, where we differentiate inter-modal registration and intra-modal registration to detect changes over time.
To combine different modalities rigid registration is used to compensate for any rotation or translation that exists between different datasets. To detect the changes in different regions of the brain over the life-cycle (deformation, tumor growth, etc.), the different time-points are elastically/non-rigidly registered to each other. For each elastic registration, the deformation field and the correspondent determinant of the Jacobian (detJac) are calculated. When comparing 2 different time-points the information provided by the deformation field can be used: without distorting the original data one can automatically pin-point the exact same region/voxel in both datasets and understand what deformation the brain suffered from one time-point to another in all directions. Analyzing the detJac one can find whether a specific region of the brain suffered any local compression or expansion.
With the registration results for any possible combination of data at hand, one can easily choose what to visualize and compare side by side: same subject-same modality-different time-points, different subjects-same modality-same time-points, same subject-different modalities-different time-points, different subjects-different modalities-same time-point, etc.
In the proposed method the registration was performed using elastix [1] and the visualization interface was built using MeVisLab.

Results: The proposed approach was first tested using multi-modal follow-up data of 1 male Wistar rat (Harlan-Winkelmann). It was scanned repeatedly (every 2 months from 10 to 20 months of age) under 2% isoflurane anesthesia using a horizontal bore 11.7T Bruker BioSpec MRI scanner. Diffusion tensor imaging was used to calculate fractional anisotropy, mean diffusivity and eigenvalue maps; a multislice multiecho experiment was performed to calculate T2 maps; both datasets were acquired with identical geometry and spatial resolution. T2*maps were acquired with a multi gradient echo sequence, angiography scans with a FLASH-2D TOF sequence with or without saturation of venous blood.
It was used to identify and follow in time a spontaneous brain tumor growth, later identified ex vivo as a melingeom. The automatic linking of the same ROI/voxel in non-rigidly registered datasets and the use of the detJac to search for asymmetries in brain deformation allowed for a more accurate comparison of follow-up data.

Conclusions: In this work we describe the first step taken to build an interactive and intuitive to use exploration system for multi-modal longitudinal and cross-sectional studies. In the future, quantification tools will be added to the platform and an intensive validation will be performed with multi-modal life-span rat brain data.

References:
[1] Klein & Staring et al., "elastix: a toolbox for intensity based medical image registration," IEEE-TMI, 2010.

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