Elastic transformation of histological slices allows precise co-registration with microCT data sets for a refined virtual histology approach

Abstract

Although X-ray based 3D virtual histology is an emerging tool for the analysis of biological tissue, it falls short in terms of specificity when compared to conventional histology. Thus, the aim was to establish a novel approach that combines 3D information provided by microCT with high specificity that only (immuno-)histochemistry can offer. For this purpose, we developed a software frontend, which utilises an elastic transformation technique to accurately co-register various histological and immunohistochemical stainings with free propagation phase contrast synchrotron radiation microCT. We demonstrate that the precision of the overlay of both imaging modalities is significantly improved by performing our elastic registration workflow, as evidenced by calculation of the displacement index. To illustrate the need for an elastic co-registration approach we examined specimens from a mouse model of breast cancer with injected metal-based nanoparticles. Using the elastic transformation pipeline, we were able to co-localise the nanoparticles to specifically stained cells or tissue structures into their three-dimensional anatomical context. Additionally, we performed a semi-automated tissue structure and cell classification. This workflow provides new insights on histopathological analysis by combining CT specific three-dimensional information with cell/tissue specific information provided by classical histology.

Current Approaches for Image Fusion of Histological Data with Computed Tomography and Magnetic Resonance Imaging

“…Tus, in all cases, the approach can be split into the identifcation of the in silico cutting plane in the 3D data set and subsequent registration with the histological slice. Albers et al used elastic image registration, treating the a priori acquired micro-CT as ground truth for that [5]. In order to reduce deformations Figure 3: A fow diagram of a basic registration approach.…”

“…Thus, in all cases, the approach can be split into the identification of the in silico cutting plane in the 3D data set and subsequent registration with the histological slice. Albers et al used elastic image registration, treating the a priori acquired micro-CT as ground truth for that [ 5 ]. In order to reduce deformations between the individual sectioned planes, the integration of 3D printing slicers or cutting boxes has been proposed [ 13 ], where the sectioning process is optimized through the inclusion of a 3D segmented model of the tissue.…”

“…Based on their previous work [ 1 , 4 ], Albers et al [ 5 ] used an inverted individual or overall color channel representation of the histological image to match the slide with the corresponding CT-plane. Following the aforementioned coarse matching using the Fourier-Mellin algorithm [ 56 , 57 ], the fine alignment was achieved through the means of a B-spline deformation model implemented by elastic [ 9 ] and optimized through MI.…”

“…In the scope of this review, we assessed and grouped these strategies according to their dimensionality in three different chapters: (i) extracting a corresponding 2D cut section from the 3D data set for subsequent 2D-2D registration with the histological slice, (ii) placing the 2D histological slice into a 3D data set, and (iii) fusion of 3D serial sectioning with the 3D-imaging data. There is also a large variety of algorithms that are used in each of the different scenarios, starting from a simple manual registration of the data as performed by Mourad et al [ 3 ] for the fusion of histology and micro-CT down to elastic image registration as employed by, for instance, Albers et al [ 1 , 4 , 5 ]. Thus, the three chapters are subdivided into applications of elastic and nonelastic methods.…”

Towards a Smart Multi-Modal Image Registration Process

“…In addition, the research of Albers et al [2] is a recent work dealing with registration of 2D histological data to 3D CT volume based on an elastic image registration. This type of registration requires to be performed following 2 steps: First, retrieve the orientation of the 2D histology section to extract the appropriate section within the CT volume (manually).…”