Framework for integrated MRI average of the spinal cord white and gray matter: The MNI-Poly-AMU template

NeuroImage

Volumn 102, Issue P2, 2014, Pages 817-827

  Fonov, V S ^a   Le Troter, A ^d   Taso, M ^d   De Leener, B ^b   Leveque G ^b   Benhamou, M ^b   Sdika, M ^e   Benali, H ^f   Pradat, P F ^f,g   Collins, D L ^a   Callot, V ^d   Cohen Adad, J ^b,c  

^a MCGILL UNIVERSITY   (Canada)

^b ÉCOLE POLYTECHNIQUE DE MONTRÉAL   (Canada)

^c UNIVERSITÉ DE MONTRÉAL   (Canada)

^d University of Aix Marseille   (France)

^e UNIVERSITÉ DE LYON   (France)

^f SORBONNE UNIVERSITÉ   (France)

^g PITIÉ SALPÊTRIÈRE HOSPITAL   (France)

Author keywords

Group analysis; MRI; Registration; Spinal cord; Template

Indexed keywords

ADULT; ARTICLE; AUTOMATION; CONCEPTUAL FRAMEWORK; CONTROLLED STUDY; DIFFUSION WEIGHTED IMAGING; EQUIPMENT DESIGN; FEMALE; GRAY MATTER; HUMAN; HUMAN EXPERIMENT; IMAGE ANALYSIS; IMAGE PROCESSING; IMAGE RECONSTRUCTION; IMAGING SYSTEM; MALE; MATHEMATICAL COMPUTING; MATHEMATICAL MODEL; NEUROANATOMY; NEUROIMAGING; NORMAL HUMAN; NUCLEAR MAGNETIC RESONANCE IMAGING; NUCLEAR MAGNETIC RESONANCE SCANNER; OPTICAL RESOLUTION; PARAMETRIC TEST; PROBABILITY; PROCESS DESIGN; PROCESS DEVELOPMENT; PROCESS MODEL; PROCESS TECHNOLOGY; SIGNAL PROCESSING; SPINAL CORD; SPINE; SYSTEM ANALYSIS; THREE DIMENSIONAL IMAGING; VALIDATION PROCESS; VOXEL BASED MORPHOMETRY; WHITE MATTER; ANATOMY AND HISTOLOGY;

ADULT; FEMALE; GRAY MATTER; HUMANS; MAGNETIC RESONANCE IMAGING; MALE; SPINAL CORD; WHITE MATTER;

EID: 84907462771     PISSN: 10538119     EISSN: 10959572     Source Type: Journal    
DOI: 10.1016/j.neuroimage.2014.08.057     Document Type: Article

References (51)

1. Asman A.J., Smith S.A., Reich D.S., Landman B.A. Robust GM/WM segmentation of the spinal cord with iterative non-local statistical fusion. Med. Image Comput. Comput. Assist. Interv. 2013, 16:759-767.
2. Asman A.J., Bryan F.W., Smith S.A., Reich D.S., Landman B.A. Groupwise multi-atlas segmentation of the spinal cord's internal structure. Med. Image Anal. 2014, 18:460-471.
3. Avants B.B., Epstein C.L., Grossman M., Gee J.C. Symmetric diffeomorphic image registration with cross-correlation: evaluating automated labeling of elderly and neurodegenerative brain. Med. Image Anal. 2008, 12:26-41.
4. Boykov Y., Funka-Lea G. Graph cuts and efficient N-D image segmentation. Int. J. Comput. Vis. 2006, 70:109-131.
5. Brooks J.C., Beckmann C.F., Miller K.L., Wise R.G., Porro C.A., Tracey I., Jenkinson M. Physiological noise modelling for spinal functional magnetic resonance imaging studies. NeuroImage 2008, 39:680-692.
6. Cadotte D.W., Cadotte A., Cohen-Adad J., Fleet D., Livne M., Mikulis D., Fehlings M.G. Resolving the anatomic variability of the human cervical spinal cord: a solution to facilitate advanced neural imaging. Proceedings of the 22nd Annual Meeting of ISMRM, Milan, Italy 2014, 1719.
7. Chen M., Carass A., Oh J., Nair G., Pham D.L., Reich D.S., Prince J.L. Automatic magnetic resonance spinal cord segmentation with topology constraints for variable fields of view. NeuroImage 2013, 83:1051-1062.
8. Cohen-Adad J., El Mendili M.-M., Lehéricy S., Pradat P.-F., Blancho S., Rossignol S., Benali H. Demyelination and degeneration in the injured human spinal cord detected with diffusion and magnetization transfer MRI. NeuroImage 2011, 55:1024-1033.
9. Cohen-Adad J., Mareyam A., Keil B., Polimeni J.R., Wald L.L. 32-channel RF coil optimized for brain and cervical spinal cord at 3T. Magn. Reson. Med. 2011, 66:1198-1208.
10. Cohen-Adad J., El Mendili M.M., Morizot-Koutlidis R., Lehericy S., Meininger V., Blancho S., Rossignol S., Benali H., Pradat P.F. Involvement of spinal sensory pathway in ALS and specificity of cord atrophy to lower motor neuron degeneration. Amyotroph. Lateral Scler. Frontotemporal Degener. 2013, 14:30-38.
11. Cohen-Adad J., De Leener B., Benhamou M., Cadotte D., Fleet D., Cadotte A., Fehlings M.G., Pelletier Paquette J.P., Thong W., Taso M., Collins D.L., Callot V., Fonov V. Spinal Cord Toolbox: an open-source framework for processing spinal cord MRI data. Proceedings of the 20th Annual Meeting of OHBM, Hamburg, Germany 2014, 3633.
12. Cohen-Adad J., Samson R.S., Schneider T., Smith A.K., Benhamou M., Leveque G., Smith S.A., Wheeler-Kingshott C.A.M. Multisite DTI of the spinal cord with integrated template and white matter atlas processing pipeline. Proceedings of the 22nd Annual Meeting of ISMRM, Milan, Italy 2014, 1727.
13. Collins D.L., Neelin P., Peters T.M., Evans A.C. Automatic 3D intersubject registration of MR volumetric data in standardized Talairach space. J. Comput. Assist. Tomogr. 1994, 18:192-205.
14. Collins D.L., Holmes C.J., Peters T.M., Evans A.C. Automatic 3-D model-based neuroanatomical segmentation. Hum. Brain Mapp. 1995, 3:190-208.
15. De Leener B., Kadoury S., Cohen-Adad J. Robust, accurate and fast automatic segmentation of the spinal cord. NeuroImage 2014, 98:528-536.
16. Dice L.R. Measures of the amount of ecologic associations between species. J. Ecol. 1945, 26:297-302.
17. Dowell N.G., Jenkins T.M., Ciccarelli O., Miller D.H., Wheeler-Kingshott C.A. Contiguous-slice zonally oblique multislice (CO-ZOOM) diffusion tensor imaging: examples of in vivo spinal cord and optic nerve applications. J. Magn. Reson. Imaging 2009, 29:454-460.
18. Eippert F., Finsterbusch J., Bingel U., Büchel C. Direct evidence for spinal cord involvement in placebo analgesia. Science 2009, 326:404.
19. El Mendili M.M., Chen R., Tiret B., Pelegrini-Issac M., Cohen-Adad J., Lehericy S., Pradat P.F., Benali H. Validation of a semiautomated spinal cord segmentation method. J. Magn. Reson. Imaging 2014, 10.1002/jmri.24571.
20. Ellingson B.M., Ulmer J.L., Schmit B.D. Gray and white matter delineation in the human spinal cord using diffusion tensor imaging and fuzzy logic. Acad. Radiol. 2007, 14:847-858.
21. Ellingson B.M., Ulmer J.L., Kurpad S.N., Schmit B.D. Diffusion tensor MR imaging of the neurologically intact human spinal cord. AJNR Am. J. Neuroradiol. 2008, 29:1279-1284.
22. Finsterbusch J. High-resolution diffusion tensor imaging with inner field-of-view EPI. J. Magn. Reson. Imaging 2009, 29:987-993.
23. Finsterbusch J., Eippert F., Buchel C. Single, slice-specific z-shim gradient pulses improve T2*-weighted imaging of the spinal cord. NeuroImage 2012, 59:2307-2315.
24. Fonov V., Evans A.C., Botteron K., Almli C.R., McKinstry R.C., Collins D.L. Unbiased average age-appropriate atlases for pediatric studies. NeuroImage 2011, 54:313-327.
25. Fradet L., Arnoux P.J., Ranjeva J.P., Petit Y., Callot V. Morphometrics of the entire human spinal cord and spinal canal measured from in vivo high-resolution anatomical magnetic resonance imaging. Spine (Phila Pa 1976) 2014, 39:E262-E269.
26. Fujimoto K., Polimeni J.R., van der Kouwe A.J., Reuter M., Kober T., Benner T., Fischl B., Wald L.L. Quantitative comparison of cortical surface reconstructions from MP2RAGE and multi-echo MPRAGE data at 3 and 7T. NeuroImage 2014, 90:60-73.
27. Haegelen C., Coupe P., Fonov V., Guizard N., Jannin P., Morandi X., Collins D.L. Automated segmentation of basal ganglia and deep brain structures in MRI of Parkinson's disease. Int. J. Comput. Assist. Radiol. Surg. 2013, 8:99-110.
28. Horsfield M.A., Sala S., Neema M., Absinta M., Bakshi A., Sormani M.P., Rocca M.A., Bakshi R., Filippi M. Rapid semi-automatic segmentation of the spinal cord from magnetic resonance images: application in multiple sclerosis. NeuroImage 2010, 50:446-455.
29. Huber P., Ronchetti E. Robust Statistics 2009, Wiley. 2nd edition.
30. Jenkinson M., Bannister P., Brady M., Smith S. Improved optimization for the robust and accurate linear registration and motion correction of brain images. NeuroImage 2002, 17:825-841.
31. Kato F., Yukawa Y., Suda K., Yamagata M., Ueta T. Normal morphology, age-related changes and abnormal findings of the cervical spine. Part II: magnetic resonance imaging of over 1,200 asymptomatic subjects. Eur. Spine J. 2012, 21:1499-1507.
32. Kearney H., Yiannakas M.C., Abdel-Aziz K., Wheeler-Kingshott C.A., Altmann D.R., Ciccarelli O., Miller D.H. Improved MRI quantification of spinal cord atrophy in multiple sclerosis. J. Magn. Reson. Imaging 2014, 39:617-623.
33. Klein A., Andersson J., Ardekani B.A., Ashburner J., Avants B., Chiang M.C., Christensen G.E., Collins D.L., Gee J., Hellier P., Song J.H., Jenkinson M., Lepage C., Rueckert D., Thompson P., Vercauteren T., Woods R.P., Mann J.J., Parsey R.V. Evaluation of 14 nonlinear deformation algorithms applied to human brain MRI registration. NeuroImage 2009, 46:786-802.
34. Klein J.P., Arora A., Neema M., Healy B.C., Tauhid S., Goldberg-Zimring D., Chavarro-Nieto C., Stankiewicz J.M., Cohen A.B., Buckle G.J., Houtchens M.K., Ceccarelli A., Dell'Oglio E., Guttmann C.R., Alsop D.C., Hackney D.B., Bakshi R. A 3T MR imaging investigation of the topography of whole spinal cord atrophy in multiple sclerosis. AJNR Am. J. Neuroradiol. 2011, 32:1138-1142.
35. Lang J. Clinical Anatomy of the Cervical Spine 1993, Thieme Medical Publishers, New York.
36. Losseff N.A., Webb S.L., O'Riordan J.I., Page R., Wang L., Barker G.J., Tofts P.S., McDonald W.I., Miller D.H., Thompson A.J. Spinal cord atrophy and disability in multiple sclerosis. A new reproducible and sensitive MRI method with potential to monitor disease progression. Brain 1996, 119(Pt 3):701-708.
37. Manjon J.V., Coupe P., Marti-Bonmati L., Collins D.L., Robles M. Adaptive non-local means denoising of MR images with spatially varying noise levels. J. Magn. Reson. Imaging 2010, 31:192-203.
38. Mulcahey M.J., Samdani A., Gaughan J., Barakat N., Faro S., Betz R.R., Finsterbusch J., Mohamed F.B. Diffusion tensor imaging in pediatric spinal cord injury: preliminary examination of reliability and clinical correlation. Spine (Phila Pa 1976) 2012, 37:E797-E803.
39. Sigmund E.E., Suero G.A., Hu C., McGorty K., Sodickson D.K., Wiggins G.C., Helpern J.A. High-resolution human cervical spinal cord imaging at 7T. NMR Biomed. 2012, 25:891-899.
40. Smith S.A., Jones C.K., Gifford A., Belegu V., Chodkowski B., Farrell J.A.D., Landman B.A., Reich D.S., Calabresi P.A., McDonald J.W., Van Zijl P.C.M. Reproducibility of tract-specific magnetization transfer and diffusion tensor imaging in the cervical spinal cord at 3Tesla. NMR Biomed. 2010, 23:207-217.
41. Stroman P.W., Figley C.R., Cahill C.M. Spatial normalization, bulk motion correction and coregistration for functional magnetic resonance imaging of the human cervical spinal cord and brainstem. Magn. Reson. Imaging 2008, 26:809-814.
42. Stroman P.W., Bosma R.L., Tsyben A. Somatotopic arrangement of thermal sensory regions in the healthy human spinal cord determined by means of spinal cord functional MRI. Magn. Reson. Med. 2012, 68:923-931.
43. Stroman P.W., Wheeler-Kingshott C., Bacon M., Schwab J.M., Bosma R., Brooks J., Cadotte D., Carlstedt T., Ciccarelli O., Cohen-Adad J., Curt A., Evangelou N., Fehlings M.G., Filippi M., Kelley B.J., Kollias S., Mackay A., Porro C.A., Smith S., Strittmatter S.M., Summers P., Tracey I. The current state-of-the-art of spinal cord imaging: methods. NeuroImage 2014, 84:1070-1081.
44. Taso M., Le Troter A., Sdika M., Ranjeva J.P., Guye M., Bernard M., Callot V. Construction of an in vivo human spinal cord atlas based on high-resolution MR images at cervical and thoracic levels: preliminary results. MAGMA 2014, 27:257-267.
45. Taso M., Le Troter A., Sdika M., Fonov V.S., Cohen-Adad J., Guye M., Ranjeva J.P., Callot V. Validation of a 2D spinal cord probabilistic atlas. Application to FA measurement and VBM study of the GM atrophy occurring with age. Proceedings of the 22nd Annual Meeting of ISMRM, Milan, Italy 2014, 1710.
46. Tozer D., Yiannakas M.C., Kearney H., Wheeler-Kingshott C.A.M. Cervical spinal cord template of healthy controls using high-resolution axial gradient echo imaging. Proceedings of the 20th Annual Meeting of ISMRM, Melbourne, Australia 2012, 1043.
47. Tustison N.J., Avants B.B., Cook P.A., Zheng Y., Egan A., Yushkevich P.A., Gee J.C. N4ITK: improved N3 bias correction. IEEE Trans. Med. Imaging 2010, 29:1310-1320.
48. Valsasina P., Horsfield M.A., Rocca M.A., Absinta M., Comi G., Filippi M. Spatial normalization and regional assessment of cord atrophy: voxel-based analysis of cervical cord 3D T1-weighted images. Am. J. Neuroradiol. 2012, 33:2195-2200.
49. Weier K., Fonov V., Lavoie K., Doyon J., Collins D.L. Rapid automatic segmentation of the human cerebellum and its lobules (RASCAL)-implementation and application of the patch-based label-fusion technique with a template library to segment the human cerebellum. Hum. Brain Mapp. 2014, 10.1002/hbm.22529.
50. Wheeler-Kingshott C.A., Stroman P.W., Schwab J.M., Bacon M., Bosma R., Brooks J., Cadotte D.W., Carlstedt T., Ciccarelli O., Cohen-Adad J., Curt A., Evangelou N., Fehlings M.G., Filippi M., Kelley B.J., Kollias S., Mackay A., Porro C.A., Smith S., Strittmatter S.M., Summers P., Thompson A.J., Tracey I. The current state-of-the-art of spinal cord imaging: applications. NeuroImage 2014, 84:1082-1093.
51. Yiannakas M.C., Kearney H., Samson R.S., Chard D.T., Ciccarelli O., Miller D.H., Wheeler-Kingshott C.A.M. Feasibility of grey matter and white matter segmentation of the upper cervical cord in vivo: a pilot study with application to magnetisation transfer measurements. NeuroImage 2012, 63:1054-1059.