Improved segmentation of deep brain grey matter structures using magnetization transfer (MT) parameter maps

Gunther Helms, Bogdan Draganski, Richard Frackowiak, John Ashburner, Nikolaus Weiskopf, Gunther Helms, Bogdan Draganski, Richard Frackowiak, John Ashburner, Nikolaus Weiskopf

Abstract

Basal ganglia and brain stem nuclei are involved in the pathophysiology of various neurological and neuropsychiatric disorders. Currently available structural T1-weighted (T1w) magnetic resonance images do not provide sufficient contrast for reliable automated segmentation of various subcortical grey matter structures. We use a novel, semi-quantitative magnetization transfer (MT) imaging protocol that overcomes limitations in T1w images, which are mainly due to their sensitivity to the high iron content in subcortical grey matter. We demonstrate improved automated segmentation of putamen, pallidum, pulvinar and substantia nigra using MT images. A comparison with segmentation of high-quality T1w images was performed in 49 healthy subjects. Our results show that MT maps are highly suitable for automated segmentation, and so for multi-subject morphometric studies with a focus on subcortical structures.

Figures

Fig. 1
Fig. 1
Example of single subject T1w MDEFT (upper row) and MT map (bottom row) data in Montreal Neurological Institute (MNI) standard space. (a) transverse view of whole head; (b) putamen, (c) pallidum, (d) substantia nigra shown as a zoomed view. Consistent windowing was based on whole brain histograms (MDEFT: [35 a.u.–470 a.u.]; MT [0 p.u.–1.9 p.u.]).
Fig. 2
Fig. 2
Population average maps (n = 49) of gray matter probability in MNI standard space corresponding to the single subject images in Fig. 1: (a) full transverse view, (b) putamen, (c) pallidum, (d) substantia nigra. MT map (bottom row) showing improved segmentation of the basal ganglia compared to T1w MDEFT (upper row).
Fig. 3
Fig. 3
Statistical comparison between MDEFT- and MT-based population averaged GM probability maps in MNI standard space. t-test was performed on a subcortical ROI and voxels exceeding a threshold of p < 0.05 (FWE corrected) are displayed on a spatially normalised MT map of an individual. Columns a–c show increases in GM probability based on MT maps; column d decreases. The subregions of the thalamus were assigned to the lateral pulvinar (a,b top) and parts of the internal medullary lamina (d).

References

    1. Ashburner J. A fast diffeomorphic image registration algorithm. NeuroImage. 2007;38:95–113.
    1. Ashburner J., Friston K.J. Voxel-based morphometry — the methods. NeuroImage. 2000;11:805–821.
    1. Ashburner J., Friston K.J. Unified segmentation. NeuroImage. 2005;26:839–851.
    1. Ashburner J., Friston K. Computing average shaped tissue probability templates. NeuroImage. 2009;45:333–341.
    1. Ashburner J., Csernansky J.G., Davatzikos C., Fox N.C., Frisoni G.B., Thompson P.M. Computer-assisted imaging to assess brain structure in healthy and diseased brains. Lancet Neurol. 2003;2:79–88.
    1. Berg D., Youdim B. Role of iron in neurodegenerative disorders. Top. Magn. Reson. Imaging. 2006;17:5–17.
    1. Deichmann R., Schwarzbauer C., Turner R. Optimisation of the 3D MDEFT sequence for anatomical brain imaging: technical implications at 1.5 and 3 T. NeuroImage. 2004;21:757–767.
    1. Desikan R.S., Ségonne F., Fischl B., Quinn B.T., Dickerson B.C., Blacker D., Buckner R.L., Dale A.M., Maguire R.P., Hyman B.T., Albert M.S., Killiany R.J. An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. NeuroImage. 2006;31:968–980.
    1. Dousset V., Grossman R.I., Ramer K.N., Schnall M.D., Young L.H., Gonzalez-Scarano F., Lavi E., Cohen J.A. Experimental allergic encephalomyelitis and multiple sclerosis: lesion characterization with magnetization transfer imaging. Radiology. 1992;182:483–491.
    1. Graybiel A.M. The basal ganglia. Trends Neurosci. 1995;18:60–62.
    1. Haacke E., Cheng N., House M., Liu Q., Neelavalli J., Ogg R., Khan A., Ayaz M., Kirsch W., Obenaus A. Imaging iron stores in the brain using magnetic resonance imaging. Magn. Reson. Imaging. 2005;23:1–25.
    1. Haber S.N. The primate basal ganglia: parallel and integrative networks. J. Chem. Neuroanat. 2003;26:317–330.
    1. Helms G., Dechent P. Increased SNR and reduced distortions by averaging multiple gradient echo signals in 3D FLASH imaging of the human brain at 3T. J. Magn. Reson. Imaging. 2009;29:198–204.
    1. Helms G., Dathe H., Dechent P. Quantitative FLASH MRI at 3 Tesla using a rational approximation of the Ernst equation. Magn. Res. Med. 2008;59:667–672.
    1. Helms G., Dathe H., Kallenberg K., Dechent P. High-resolution maps of magnetisation transfer with inherent correction for RF inhomogeneity and T1 relaxation obtained from 3D FLASH MRI. Magn. Res. Med. 2008;60:1396–1407.
    1. Hirai T., Jones E.P. A new parcellation of the human thalamus on the basis of histochemical staining. Brain Res. Rev. 1989;14:1–34.
    1. Hoover J.E., Strick P.L. The organization of cerebellar and basal ganglia outputs to primary motor cortex as revealed by retrograde transneuronal transport of herpes simplex virus type 1. J. Neurosci. 1999;19:1446–1463.
    1. May A., Gaser C. Magnetic resonance-based morphometry: a window into structural plasticity of the brain. Curr. Opin. Neurol. 2006;19:407–411.
    1. McGuire P.K., Bench C.J., Frith C.D., Marks I.M., Frackowiak R.S., Dolan R.J. Functional anatomy of obsessive-compulsive phenomena. Br. J. Psychiatry. 1994;164:459–468.
    1. Meunier S., Lehericy S., Garnero L., Vidailhet M. Dystonia: lessons from brain mapping. Neuroscientist. 2003;9:76–81.
    1. Middleton F.A., Strick P.L. Anatomical evidence for cerebellar and basal ganglia involvement in higher cognitive function. Science. 1994;266:458–461.
    1. Middleton F.A., Strick P.L. New concepts about the organization of basal ganglia output. Adv. Neurol. 1997;74:57–68.
    1. Middleton F.A., Strick P.L. Basal ganglia output and cognition: evidence from anatomical, behavioral, and clinical studies. Brain Cogn. 2000;42:183–200.
    1. Middleton F.A., Strick P.L. Basal-ganglia ‘projections’ to the prefrontal cortex of the primate. Cereb. Cortex. 2002;12:926–935.
    1. Ogg R., Steen R. Age-related changes in brain T1 are correlated with iron concentration. Magn. Res. Med. 1998;40:749–753.
    1. Parent A., Hazrati L.N. Functional anatomy of the basal ganglia. I. The cortico-basal ganglia-thalamo-cortical loop. Brain Res. Brain Res. Rev. 1995;20:91–127.
    1. Parent A., Sato F., Wu Y., Gauthier J., Levesque M., Parent M. Organization of the basal ganglia: the importance of axonal collateralization. Trends Neurosci. 2000;23:S20–27.
    1. Percheron G., Francois C., Yelnik J., Fenelon G., Talbi B. Plenum Press; New York: 1994. The Basal Ganglia Related Systems of Primates: Definition, Description and Informational Analysis.
    1. Schenk J., Zimmerman E., Li Z., Adak S., Saha A., Tandon R., Fish K., Belden C., Gillen R., Barba A., Henderson D., Neil W., O'Keefe T. High-field magnetic resonance imaging of brain iron in Alzheimer disease. Top. Magn. Reson. Imaging. 2006;17:41–50.
    1. Utter A.A., Basso M.A. The basal ganglia: an overview of circuits and function. Neurosci. Biobehav. Rev. 2008;32:333–342.
    1. Vovk U., Pernus F., Likar B. A review of methods for correction of intensity inhomogeneity in MRI. IEEE Trans. Med. Imaging. 2007;26:405–421.
    1. Weiskopf N., Helms G. Multi-parameter mapping of the human brain at 1 mm resolution in less than 20 minutes. Proc. Intl. Soc. Magn. Reson. Med. 2008;16:2241. Toronto.
    1. Wonderlick J.S., Ziegler D.A., Hosseini-Varnamkhasti P., Locascio J.J., Bakkour A., van der Kouwe A., Triantafyllou C., Corkin S., Dickerson B.C. Reliability of MRI-derived cortical and subcortical morphometric measures: effects of pulse sequence, voxel geometry, and parallel imaging. NeuroImage. 2009;44:1324–1333.

Source: PubMed

スポンサーと協力者

医学的状態

薬物療法

3
購読する