Validating atlas-guided DOT: A comparison of diffuse optical tomography informed by atlas and subject-specific anatomies
Introduction
Near-infrared spectroscopy (NIRS) provides functional information about the oxygenation status of tissue by measuring optical signals which reflect changes in the concentrations of oxygenated-hemoglobin (HbO) and deoxygenated-hemoglobin (HbR) (Jöbsis, 1977). Diffuse optical tomography (DOT) is a multichannel NIRS approach, whereby numerous near-infrared sources and detectors coupled to the skin enable depth-resolved images of the spatio-temporal variations in hemoglobin concentrations to be reconstructed (Bluestone et al., 2001, Culver et al., 2003, Gibson et al., 2005, Zeff et al., 2007). Both NIRS and DOT have been widely applied to investigate brain function over the last 15 years (Durduran et al., 2010, Gibson et al., 2005, Lloyd-Fox et al., 2010). Recently, DOT has been used to map the visual cortex and investigate functional connectivity and motor–visual coordination with millimeter-order spatial resolution (White et al., 2009, Zeff et al., 2007). Whole-head, three-dimensional image reconstruction of regional blood volume and oxygenation has also been demonstrated in healthy and neurologically damaged infants (Austin et al., 2006, Gibson et al., 2006).
Numerous approaches have been investigated for improving DOT image sensitivity, resolution and accuracy (Boas et al., 2004, Gibson et al., 2005, Zeff et al., 2007). Employing a large number of sources and detectors (optodes), densely packed so as to provide spatially overlapping measurements, is essential for accurate DOT image reconstruction (Culver et al., 2003, Durduran et al., 2010, Zeff et al., 2007). The importance of including source–detector pairs with a relatively short separation (of 10 mm or less) has also been confirmed for both NIRS (Gagnon et al., 2011) and DOT (Gregg et al., 2010). Short-separation channels are sensitive to superficial tissues only. Such measurements not only allow the confounding effects of scalp hemodynamics to be removed from standard-separation signals in NIRS studies, but also improve the separation of superficial and cortical signals inherent to depth-resolved DOT.
Despite these advances, the most significant drawback of traditional DOT approaches is the absence of corresponding images of brain structure. Knowledge of the specific brain anatomy not only allows registration of DOT images to the cerebral cortex, but can also significantly improve the images themselves by restraining the ill-posed DOT image reconstruction problem. This same approach has been investigated extensively for EEG and MEG techniques; registration to an anatomical MRI image can be used to restrain the source reconstruction problem and has been shown to be of significant benefit (Dale and Sereno, 1993, Huppertz et al., 1998). The same has been achieved for diffuse optical tomography using subject-specific MRI images (Barbour et al., 1995, Boas and Dale, 2005, Ntziachristos et al., 2002). However, the requirement to obtain a subject's MRI undermines one of the fundamental advantages of DOT systems: that they are portable and can be easily applied to vulnerable subjects. A promising alternative is therefore to use a registered 3D atlas head model in place of the subject's MRI, as described by Custo et al. (2010). This MRI-free approach to anatomically guided DOT image reconstruction and interpretation is based on registering a selected atlas to the subject's head surface and solving the photon migration forward problem in the registered atlas space. This approach requires measuring the positions of the optical sources and detectors and the cranial landmarks of the subject's head in 3D space, commonly using an electromagnetic tracking system. This allows the atlas to be transformed into the subject space (or ‘registered’) using an affine transformation computed using the corresponding cranial landmarks in the two spaces (Singh et al., 2005, Tsuzuki et al., 2007).
Atlas-guided DOT will clearly exhibit errors in the localization of cortical activations. The sources of this error will be: 1) imperfect registration between the subject and atlas spaces, 2) differences between the subject's true anatomy and the atlas anatomy and 3) the localization error associated with diffuse optical image reconstruction. These sources of error have previously been investigated, but not in combination. Studies have shown that by employing the subject-specific MRI, the error associated with DOT localization of simulated brain activation in the cortex is 5–10 mm (Boas and Dale, 2005). The error due to the registration process has also been explicitly investigated and found to be on the order of 4–7 mm (Singh et al., 2005, Tsuzuki et al., 2007). However, it is clearly necessary to explicitly test the entire atlas-based DOT process, and how errors in localization, registration and anatomy will affect the accuracy of the image reconstruction process.
In this paper we seek to validate the atlas-guided DOT methods described in Custo et al. (2010), and quantify the corresponding error in the localization of simulated cortical activations. Using an MRI library of 32 subjects, we simulate DOT measurements of brain activation in the subject space then reconstruct the corresponding DOT images using both an atlas registered to the subject and the subject's true anatomy. This allows us to directly compare the anatomical location of the images reconstructed in the atlas space with those reconstructed in the subject space.
Section snippets
MRI data, atlas and pre-processing
Anatomical MRI images with a voxel size of 0.94 × 0.94 × 1.5 mm were obtained using the multi-echo FLASH pulse sequence described in Fischl et al. (2004) for 32 adult subjects. The atlas MRI volume we employed was the high-resolution ‘Colin27’ digital brain phantom as described by Collins et al. (1998). The atlas MRI volume and all subject MRI volumes were automatically transformed into a single coordinate system in FreeSurfer, which ensures consistent orientation. Preprocessing of the 32 individual
Results
The optode positioning error was calculated for each of the 32 registered atlas heads, and the average for each optode position is depicted in Fig. 5. Note that the largest errors occur where the head surface is highly curved, particularly towards the occipital region. The average (and standard deviation) optode positioning error across all subjects and optodes was 2.8 (± 1.7) mm.
Fig. 6 shows seven simulated activations, but in addition shows the corresponding DOT images reconstructed using the
Discussion
With the application of DOT techniques becoming more common, across a variety of fields, there is a growing need to develop a method which extracts as much of the spatial information present in DOT as possible, while maintaining the advantages the technique has over other neuroimaging modalities; namely convenience, cost and portability. The atlas-guided DOT approach described here and by Custo et al. (2010) meets this requirement. As a prerequisite for its extended application we have
Acknowledgments
This work was supported by NIH P41-RR14075, P41-RR13218, and R01-EB006385 (to D.A.B.), NIH P41-RR-013218 and P41-EB-015902 (to W.W.), Comprehensive Research on Disability, Health and Welfare from Health and Labour Sciences Research Grants (to I.D.), and the Grants-in-Aid for Scientific Research from the Japan Society for Promotion of Science (23390354, and 23650217 to I.D.).
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These authors contributed equally to this paper.