Elsevier

Journal of Neuroscience Methods

Volume 240, 30 January 2015, Pages 161-169
Journal of Neuroscience Methods

Computational Neuroscience
Anatomical landmarks for registration of experimental image data to volumetric rodent brain atlasing templates

https://doi.org/10.1016/j.jneumeth.2014.11.005Get rights and content

Highlights

  • 16 anatomical landmarks reliably recognized in T1, T2, and T2* mouse brain MRI.

  • All landmarks identified in Nissl histology and block-face images from the mouse brain.

  • Most landmarks identified in MRI and histological images from the rat brain.

  • Guidelines for locating each landmark presented in the Scalable Brain Atlas.

  • Facilitates landmark-based registration to Waxholm Space and thus worldwide datasharing.

Abstract

Background

Assignment of anatomical reference is a key step in integration of the rapidly expanding collection of rodent brain data. Landmark-based registration facilitates spatial anchoring of diverse types of data not suitable for automated methods operating on voxel-based image information.

New tool

Here we propose a standardized set of anatomical landmarks for registration of whole brain imaging datasets from the mouse and rat brain, and in particular for integration of experimental image data in Waxholm Space (WHS).

Results

Sixteen internal landmarks of the C57BL/6J mouse brain have been reliably identified: by different individuals, independent of their experience in anatomy; across different MRI contrasts (T1, T2, T2*) and other modalities (Nissl histology and block-face anatomy); in different specimens; in different slice acquisition angles; and in different image resolutions. We present a registration example between T1-weighted MRI and the mouse WHS template using these landmarks and reaching fairly high accuracy. Landmark positions identified in the mouse WHS template are shared through the Scalable Brain Atlas, accompanied by graphical and textual guidelines for locating each landmark. We identified 14 of the 16 landmarks in the WHS template for the Sprague Dawley rat.

Comparison with existing methods

This landmark set can withstand substantial differences in acquisition angle, imaging modality, and is less vulnerable to subjectivity.

Conclusions

This facilitates registration of multimodal 3D brain data to standard coordinate spaces for mouse and rat brain taking a step toward the creation of a common rodent reference system; raising data sharing to a qualitatively higher level.

Introduction

A rapid growth of data collection from the rodent brain has taken place over the recent years, strengthened by the extensive use of genetically engineered animals for various types of research. An initiative for providing universal and convenient access to and management of these huge amounts of data has been organized around anatomical reference systems. In 2008, the International Neuroinformatics Coordinating Facility (INCF) launched the Digital Atlasing Program (Bjaalie and Grillner, 2007, Boline et al., 2007), resulting in the development of Waxholm Space (WHS) (Johnson et al., 2010, Hawrylycz, 2009, Bowden et al., 2011) and the associated Digital Atlasing Infrastructure (DAI) (Zaslavsky et al., 2014, Hawrylycz et al., 2011). WHS is a reference space for the rodent brain based on a coordinate system anchored to anatomical landmarks within the brain. Anatomical context is provided by high resolution atlasing templates of multimodal volumetric image material, including MRI, from the brain of the mouse (Johnson et al., 2010) and rat (Papp et al., 2014). The WHS standard serves as a cornerstone of the DAI, a collection of services that provide interoperability between existing and newly arising brain atlases (Allen Brain Atlas, http://www.brain-map.org, Lein et al., 2007; Edinburgh Mouse Atlas Project, http://www.emouseatlas.org/emap, Baldock et al., 2003; Cell Centered Database, http://ccdb.ucsd.edu/index.shtm).

A key step to integrating diverse types of experimental data e.g. gene expression and protein distribution studies, electrophysiology, and functional imaging, is to link the data to a standard anatomical reference, in other words, to register these datasets to a known spatial standard, or atlas. The microscopic resolution Waxholm Space atlas templates provide a basis for spatial registration of diverse types of whole brain data. For MRI datasets, a variety of automated registration methods is available utilizing voxel-based information such as image intensity or contrast (Avants et al., 2011, Denton et al., 1999, Kroon and Slump, 2009, Schnabel et al., 2001; for review see Klein et al., 2009). Such registration methods require images of identical or similar modalities, are sensitive to large-scale distortions, and have limitations for matching anatomical features between brains, in particular between normal and lesioned or diseased brains (Pantazis et al., 2010). Landmark-based registration (Bookstein, 1989, Rohr et al., 2001; for comparison to voxel-based methods, see e.g. Zuk and Atkins, 1996) can be used as an alternative approach, especially when dealing with experimental images of different modalities, with various levels of anatomical detail or resolution with sufficient accuracy for many applications (Gaser et al., 2012, Hsu et al., 2002, Viceic et al., 2009; Weisbecker, 2012; West et al., 2001, Zhang et al., 2006). A landmark is an image feature that serves as a reference: an anatomical characteristic of the brain used for orientation and comparison of data from different experimental animals. When used in registration, landmarks are often reduced to single easily identifiable points to enhance spatial precision. Defining corresponding sets of landmarks in the source and target (reference) datasets determines how the source is mapped to the target. A set of landmarks can be also used for quantifying the accuracy of other registration methods (Castillo et al., 2009, Grachev et al., 1999, Jiang and Johnson, 2011).

The aim of this study was to establish a standardized set of anatomical landmarks in the rodent brain with a primary focus on facilitating registration of experimental datasets to volumetric rodent brain atlasing templates such as the WHS MRI template. As a result, we present 16 landmarks identified with high reliability in MRI of the mouse brain, accompanied by graphical and textual guidelines that allow easy localization of each landmark without particular anatomical experience. We present an example scenario for landmark-based registration to the WHS template based on these landmarks and evaluate the level of precision attained. Further, we successfully identified most landmarks in multiple types of image datasets from the mouse and rat brain representing a range of modalities, image resolutions, and acquisition angles.

Section snippets

Materials and methods

Six adult male C57BL/6J mice (age 24 weeks, weight 30 g, Franz-Penzoldt-Zentrum, Erlangen, Germany) were used in our measurements (Table 1). The animals were handled in accordance with the German Animal Protection Law of 2008 (paragraph 8.1), and all procedures were approved by the Institutional Animal Care and Use Committee of the Regierungspräsidium Mittelfranken.

Results

We defined a set of anatomical landmarks in the mouse brain using an MRI template with three different contrasts from two adult male C57BL/6J mice. We created standardized documentation in both written and graphical form as guidance for locating each landmark in anatomical images of the brain. The documentation, along with landmark positions marked in the mouse WHS template images, is made available to the public via the web-based atlasing tool Scalable Brain Atlas (//sba.incf.org/main/coronal3d.php?template=WHS12%26plugin=Landmarks

Discussion

Integration of various types of data from the brain is the focus of global research programs such as the Human Brain Project, which envisions building a knowledge base of the brain by accumulating and spatially linking imaging and other types of data from the human brain as well as from the brains of experimental animals (HBP Pilot Report, Ailamaki et al., 2012). The framework for linking and managing these large amounts of data is standard anatomical references, or atlases based on

Acknowledgements

We would like to acknowledge the International Neuroinformatics Coordinating Facility (INCF) for financial support of this work (Grant ZZCALINFLO). We thank Johannes Kaesser for technical assistance, animal preparation and scanning. We are grateful to INCF Waxholm Space Task Force members for creative input and suggestions, as well as to all the colleagues from the working group of Andreas Hess (Institute of Experimental and Clinical Pharmacology and Toxicology, FAU Erlangen-Nuremberg) who

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