Validation of in vitro probabilistic tractography
Introduction
Detailed knowledge of the complex anatomical connections in the human central nervous system is pivotal in elucidating and understanding normal and pathological brain function. Our current understanding of the architecture of neuronal circuitry is mainly based upon histological visualization of fiber tracts or neuronal tracing techniques using fluorescent or histochemically detectable tracers (for a review see Kobbert et al., 2000, Oztas, 2003, Zaborszky et al., 2006). Additionally, a new magnetic resonance imaging (MRI) detectable neuronal tracing method has recently been introduced in animal models (Leergaard et al., 2003, Lin et al., 2001, Murayama et al., 2006, Pautler et al., 1998, Saleem et al., 2002). Manganese enhanced MRI (meMRI) exploits the anterograde transport of paramagnetic manganese (Mn2+) and visualizes projection pathways in vivo (Pautler et al., 1998). However, although considered gold standards for assessing brain connectivity, the invasive nature of these techniques restricts their application to experimental animals or post mortem human brain research.
Recently, it has become possible to evaluate anatomical brain connectivity non-invasively by taking advantage of the restricted self-diffusion of water molecules within tissue using diffusion MRI, or diffusion weighted imaging (DWI). Diffusion tensor imaging (DTI) (Basser et al., 1994) and related methods such as q-ball imaging (Tuch, 2004), tensor-mixture models (Alexander, 2005, Assaf et al., 2004, Tuch et al., 2002), PASMRI (Jansons and Alexander, 2003) and spherical deconvolution (Frank, 2002, Tournier et al., 2004) quantify water-diffusion anisotropy in the intra and extra-cellular spaces of the neural environment. Fiber tracking algorithms then use the directions of greatest diffusion as estimates of white matter fiber orientation. Several fiber tracking algorithms have emerged in the last few years that provide reproducible visualizations of three-dimensional fiber tracts (Basser et al., 2000, Jiang et al., 2006, Parker et al., 2002, Parker et al., 2003). One class of these algorithms is probabilistic tractography (Behrens et al., 2003, Parker et al., 2003, Parker and Alexander, 2003, Parker and Alexander, 2005).
Although probabilistic tractography currently holds great promise as a powerful non-invasive connectivity-measurement tool, its accuracy and limitations remain to be evaluated. In particular, a strong correlation between the information about the anatomical connectivity provided by tractgraphy methods and independent anatomical data is still lacking (Behrens et al., 2007, Ciccarelli et al., 2003, Heiervang et al., 2006, Jones et al., 2005). Additionally, the accuracy and precision of tractography results are restricted by limitations on spatial resolution, thermal and physiological noise (for example cardiac pulsation (Skare and Andersson, 2001), respiration-induced signal fluctuations), brain motion and image artefacts (for a review see Le Bihan et al., 2006).
The present study aims to validate the anatomical accuracy of tractography by overcoming most of the known limitations. To this end probabilistic tractography was assessed post mortem in an in vitro environment. Post mortem imaging benefits from high-field (> 3 T) MR scanners and long scanning times, thereby significantly improving the signal-to-noise ratio (SNR) and spatial resolution. Moreover, many of the degrading effects observed in vivo are not present post mortem. Specifically, we evaluated the ability of probabilistic tractography to reconstruct functionally specific pathways detected by invasive neuron tract tracing in the gyrated Göttingen minipig brain.
Section snippets
Tracer injections
Three young male Göttingen minipigs (Ellegaard Göttingen Minipigs A/S, Dalmose, Denmark) were used in the study (age 3 months, weight between 5 and 6 kg). Each pig received a single simultaneous injection of 0.5 μl MnCl2 (0.8 M MnCl2 Tetrahydratem, Sigma-Aldrich, Denmark) and 4.5 μl biotinylated dextran amine (BDA, 10,000 molecular weight, Molecular Probes, Eugene, OR) aimed at the right somatosensory cortex (SC), the right prefrontal cortex (PFC), or the left motor cortex (MC) based on
In vivo tracing
Pathways emanating from the simultaneous injection of two in vivo tracers in the right SC of brain 1, in the right PFC of brain 2 or in the left MC of brain 3 were described anatomically and compared. Injections of BDA into the SC of brain 1 (Fig. 1A) revealed several specific ipsilateral and contralateral corticothalamic, corticostriatal and corticocortical pathways. Dense corticothalamic innervations were observed in the ipsilateral VP nuclei of the thalamus (Figs. 1B, C, F, G). Other fibers
Discussion
In the present study the porcine brain was used as a gyrated brain model in order to quantitatively and qualitatively assess the anatomical validity, consistency and reliability of in vitro probabilistic tractography. Previous validation studies of tractography methods have been based on e.g. simulations (Lazar and Alexander, 2003, Leemans et al., 2005) or groups of human subjects (Behrens et al., 2007, Ciccarelli et al., 2003, Heiervang et al., 2006). Using the porcine brain we demonstrate
Acknowledgments
We thank Matthew G. Liptrot, MSc and Torben Lund, MSc PhD for critical technical input and Birgitte R. Kornum, MSc for assisting during surgery. Thanks to Dr. Klaus Qvortrup and Dr. Maibritt B. Andersen for placing perfusion and stereotaxic equipment at our disposal. Thanks to DVM Nanna Grand and Lars Ellegaard at Ellegaard Minipigs Aps for donating experimental animals. We would like to express our gratitude for the financial support from the Lundbeck Foundation, the Gangsted Foundation, the
References (43)
- et al.
Probabilistic segmentation of white matter lesions in MR imaging
NeuroImage
(2004) - et al.
MR diffusion tensor spectroscopy and imaging
Biophys. J.
(1994) - et al.
Probabilistic diffusion tractography with multiple fibre orientations: what can we gain?
NeuroImage
(2007) - et al.
From diffusion tractography to quantitative white matter tract measures: a reproducibility study
NeuroImage
(2003) - et al.
Between session reproducibility and between subject variability of diffusion MR and tractography measures
NeuroImage
(2006) - et al.
The prefrontal cortex in the Gottingen minipig brain defined by neural projection criteria and cytoarchitecture
Brain Res. Bull.
(2006) - et al.
DtiStudio: resource program for diffusion tensor computation and fibre bundle tracking
Comput. Methods Programs Biomed.
(2006) - et al.
Current concepts in neuroanatomical tracing
Prog. Neurobiol.
(2000) - et al.
An error analysis of white matter tractography methods: synthetic diffusion tensor field simulations
NeuroImage
(2003) - et al.
In vivo tracing of major rat brain pathways using manganese-enhanced magnetic resonance imaging and three-dimensional digital atlasing
NeuroImage
(2003)
Validation of diffusion tensor magnetic resonance axonal fibre imaging with registered manganese-enhanced optic tracts
NeuroImage
The use of pigs in neuroscience: modeling brain disorders
Neurosci. Biobehav. Rev.
Tracing neural circuits in vivo with Mn-enhanced MRI
Magn. Reson. Imaging
Magnetic resonance imaging of neuronal connections in the macaque monkey
Neuron
On the effects of gating in diffusion imaging of the brain using single shot EPI
Magn. Reson. Imaging
Direct estimation of the fibre orientation density function from diffusion-weighted MRI data using spherical deconvolution
NeuroImage
Multiple-fibre reconstruction algorithms for diffusion MRI
Ann. N. Y. Acad. Sci.
Parallel organization of functionally segregated circuits linking basal ganglia and cortex
Annu. Rev. Neurosci.
Basal ganglia–thalamocortical circuits: parallel substrates for motor, oculomotor, “prefrontal” and “limbic” functions
Prog. Brain Res.
Detection and modeling of non-Gaussian apparent diffusion coefficient profiles in human brain data
Magn. Reson. Med.
New modeling and experimental framework to characterize hindered and restricted water diffusion in brain white matter
Magn. Reson. Med.
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