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Automatic "pipeline" analysis of 3-D MRI data for clinical trials: application to multiple sclerosis
Abstract
The quantitative analysis of magnetic resonance imaging (MRI) data has become increasingly important in both research and clinical studies aiming at human brain development, function, and pathology. Inevitably, the role of quantitative image analysis in the evaluation of drug therapy will increase, driven in part by requirements imposed by regulatory agencies. However, the prohibitive length of time involved and the significant intraand inter-rater variability of the measurements obtained from manual analysis of large MRI databases represent major obstacles to the wider application of quantitative MRI analysis. We have developed a fully automatic "pipeline" image analysis framework and have successfully applied it to a number of large-scale, multicenter studies (more than 1,000 MRI scans). This pipeline system is based on robust image processing algorithms, executed in a parallel, distributed fashion. This paper describes the application of this system to the automatic quantification of multiple sclerosis lesion load in MRI, in the context of a phase III clinical trial. The pipeline results were evaluated through an extensive validation study, revealing that the obtained lesion measurements are statistically indistinguishable from those obtained by trained human observers. Given that intra- and inter-rater measurement variability is eliminated by automatic analysis, this system enhances the ability to detect small treatment effects not readily detectable through conventional analysis techniques. While useful for clinical trial analysis in multiple sclerosis, this system holds widespread potential for applications in other neurological disorders, as well as for the study of neurobiology in general.
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Citations
Cites
Measuring nominal scale agreement among many raters.
Fleiss, J. L. (1971) · Psychological Bulletin · doi:10.1037/h0031619 · Cited by 8,733
A nonparametric method for automatic correction of intensity nonuniformity in MRI data
Sled, J. G., Zijdenbos, A. P., & Evans, A. C. (1998) · IEEE Transactions on Medical Imaging · doi:10.1109/42.668698 · Cited by 4,731
Self-citationAutomatic 3D intersubject registration of MR volumetric data in standardized Talairach space
Collins, D. L., Neelin, P., Peters, T. M., & Evans, A. C. (1994) · Journal of Computer Assisted Tomography · doi:10.1097/00004728-199403000-00005 · Cited by 3,431 · cited 3×
“The stereotaxic target used at our institute is an average -weighted scan of 305 normal volunteers [6], [17], [43].”
BackgroundMethodSelf-citationStructural maturation of neural pathways in children and adolescents: in vivo study
Paus, T., Zijdenbos, A., Worsley, K., Collins, D. L., Blumenthal, J., Giedd, J. N., Rapoport, J. L., & Evans, A. C. (1999) · Science · doi:10.1126/science.283.5409.1908 · Cited by 1,322
Self-citationAge and gender predict volume decline in the anterior and posterior hippocampus in early adulthood
Pruessner, J. C., Collins, D. L., Pruessner, M., & Evans, A. C. (2001) · The Journal of Neuroscience · doi:10.1523/jneurosci.21-01-00194.2001 · Cited by 292
Self-citation
Cited by
Ashburner, J., & Friston, K. J. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2005.02.018 · Cited by 7,507
Attention-deficit/hyperactivity disorder is characterized by a delay in cortical maturation
Shaw, P., Eckstrand, K., Sharp, W., Blumenthal, J., Lerch, J. P., Greenstein, D., Clasen, L., Evans, A., Giedd, J., & Rapoport, J. L. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0707741104 · Cited by 1,819
Self-citationNeurodevelopmental Trajectories of the Human Cerebral Cortex
Shaw, P., Kabani, N. J., Lerch, J. P., Eckstrand, K., Lenroot, R., Gogtay, N., Greenstein, D., Clasen, L., Evans, A., Rapoport, J. L., et al. (2008) · The Journal of Neuroscience · doi:10.1523/jneurosci.5309-07.2008 · Cited by 1,644
Self-citationIntellectual ability and cortical development in children and adolescents
Shaw, P., Greenstein, D., Lerch, J., Clasen, L., Lenroot, R., Gogtay, N., Evans, A., Rapoport, J., & Giedd, J. (2006) · Nature · doi:10.1038/nature04513 · Cited by 1,543
Self-citationMapping brain maturation and cognitive development during adolescence
Paus, T. (2005) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2004.12.008 · Cited by 1,348
Sexual dimorphism of brain developmental trajectories during childhood and adolescence
Lenroot, R. K., Gogtay, N., Greenstein, D. K., Wells, E. M., Wallace, G. L., Clasen, L. S., Blumenthal, J. D., Lerch, J., Zijdenbos, A. P., Evans, A. C., et al. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.03.053 · Cited by 1,309
Self-citationHe, Y., Chen, Z., & Evans, A. (2008) · The Journal of Neuroscience · doi:10.1523/jneurosci.0141-08.2008 · Cited by 965
Self-citationShaw, P., Lerch, J., Greenstein, D., Sharp, W., Clasen, L., Evans, A., Giedd, J., Castellanos, F. X., & Rapoport, J. (2006) · Archives of General Psychiatry · doi:10.1001/archpsyc.63.5.540 · Cited by 703
Self-citationEffective treatment of chronic low back pain in humans reverses abnormal brain anatomy and function
Seminowicz, D. A., Wideman, T. H., Naso, L., Hatami-Khoroushahi, Z., Fallatah, S., Ware, M. A., Jarzem, P., Bushnell, M. C., Shir, Y., Ouellet, J. A., et al. (2011) · The Journal of Neuroscience · doi:10.1523/jneurosci.5280-10.2011 · Cited by 622
Cortical thickness and pain sensitivity in zen meditators.
Grant, J. A., Courtemanche, J., Duerden, E. G., Duncan, G. H., & Rainville, P. (2010) · Emotion · doi:10.1037/a0018334 · Cited by 395
Spatial patterns of cortical thinning in mild cognitive impairment and Alzheimer’s disease
Singh, V., Chertkow, H., Lerch, J. P., Evans, A. C., Dorr, A. E., & Kabani, N. J. (2006) · Brain · doi:10.1093/brain/awl256 · Cited by 386
Self-citationDevelopment of Cortical Surface Area and Gyrification in Attention-Deficit/Hyperactivity Disorder
Shaw, P., Malek, M., Watson, B., Sharp, W., Evans, A., & Greenstein, D. (2012) · Biological Psychiatry · doi:10.1016/j.biopsych.2012.01.031 · Cited by 357
Self-citationGray matter differences correlate with spontaneous strategies in a human virtual navigation task
Bohbot, V. D., Lerch, J., Thorndycraft, B., Iaria, G., & Zijdenbos, A. P. (2007) · The Journal of Neuroscience · doi:10.1523/jneurosci.1763-07.2007 · Cited by 347
Self-citationDucharme, S., Albaugh, M. D., Nguyen, T.-V., Hudziak, J. J., Mateos-Pérez, J. M., Labbe, A., Evans, A. C., & Karama, S. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2015.10.010 · Cited by 304
Self-citationLenroot, R. K., Schmitt, J. E., Ordaz, S. J., Wallace, G. L., Neale, M. C., Lerch, J. P., Kendler, K. S., Evans, A. C., & Giedd, J. N. (2009) · Human Brain Mapping · doi:10.1002/hbm.20494 · Cited by 320
Self-citationCerebellar development and clinical outcome in attention deficit hyperactivity disorder
Mackie, S., Shaw, P., Lenroot, R., Pierson, R., Greenstein, D. K., Nugent, T. F., Sharp, W. S., Giedd, J. N., & Rapoport, J. L. (2007) · American Journal of Psychiatry · doi:10.1176/appi.ajp.164.4.647 · Cited by 333
Decreased Cortical Representation of Genital Somatosensory Field After Childhood Sexual Abuse
Heim, C. M., Mayberg, H. S., Mletzko, T., Nemeroff, C. B., & Pruessner, J. C. (2013) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2013.12070950 · Cited by 318
Shaw, P., Malek, M., Watson, B., Greenstein, D., de Rossi, P., & Sharp, W. (2013) · Biological Psychiatry · doi:10.1016/j.biopsych.2013.04.007 · Cited by 303
Maze training in mice induces MRI-detectable brain shape changes specific to the type of learning
Lerch, J. P., Yiu, A. P., Martinez-Canabal, A., Pekar, T., Bohbot, V. D., Frankland, P. W., Henkelman, R. M., Josselyn, S. A., & Sled, J. G. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2010.09.086 · Cited by 300
Raznahan, A., Lee, Y., Stidd, R., Long, R., Greenstein, D., Clasen, L., Addington, A., Gogtay, N., Rapoport, J. L., & Giedd, J. N. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1006025107 · Cited by 278
Psychostimulant treatment and the developing cortex in attention deficit hyperactivity disorder
Shaw, P., Sharp, W. S., Morrison, M., Eckstrand, K., Greenstein, D. K., Clasen, L. S., Evans, A. C., & Rapoport, J. L. (2009) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2008.08050781 · Cited by 261
Self-citationShaw, P., Lerch, J. P., Pruessner, J. C., Taylor, K. N., Rose, A. B., Greenstein, D., Clasen, L., Evans, A., Rapoport, J. L., & Giedd, J. N. (2007) · The Lancet Neurology · doi:10.1016/s1474-4422(07)70106-0 · Cited by 257
Self-citationShaw, P., Lalonde, F., Lepage, C., Rabin, C., Eckstrand, K., Sharp, W., Greenstein, D., Evans, A., Giedd, J. N., & Rapoport, J. (2009) · Archives of General Psychiatry · doi:10.1001/archgenpsychiatry.2009.103 · Cited by 249
Self-citationShaw, P., Gornick, M., Lerch, J., Addington, A., Seal, J., Greenstein, D., Sharp, W., Evans, A., Giedd, J. N., Castellanos, F. X., et al. (2007) · Archives of General Psychiatry · doi:10.1001/archpsyc.64.8.921 · Cited by 242
Self-citationDevelopmental Changes in Organization of Structural Brain Networks
Khundrakpam, B. S., Reid, A., Brauer, J., Carbonell, F., Lewis, J., Ameis, S., Karama, S., Lee, J., Chen, Z., Das, S., et al. (2013) · Cerebral Cortex · doi:10.1093/cercor/bhs187 · Cited by 234
Self-citationGhafoorian, M., Karssemeijer, N., Heskes, T., van Uden, I. W. M., Sanchez, C. I., Litjens, G., de Leeuw, F.-E., van Ginneken, B., Marchiori, E., & Platel, B. (2017) · Scientific Reports · doi:10.1038/s41598-017-05300-5 · Cited by 236
Proal, E. (2011) · Archives of General Psychiatry · doi:10.1001/archgenpsychiatry.2011.117 · Cited by 207
Sex differences in the growth of white matter during adolescence
Perrin, J. S., Leonard, G., Perron, M., Pike, G. B., Pitiot, A., Richer, L., Veillette, S., Pausova, Z., & Paus, T. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.01.023 · Cited by 197
Herting, M. M., Johnson, C., Mills, K. L., Vijayakumar, N., Dennison, M., Liu, C., Goddings, A.-L., Dahl, R. E., Sowell, E. R., Whittle, S., et al. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.01.020 · Cited by 185
Cerebellar volume and cognitive functioning in children who experienced early deprivation
Bauer, P. M., Hanson, J. L., Pierson, R. K., Davidson, R. J., & Pollak, S. D. (2009) · Biological Psychiatry · doi:10.1016/j.biopsych.2009.06.014 · Cited by 167
Stefansdottir, H., Arnar, D. O., Aspelund, T., Sigurdsson, S., Jonsdottir, M. K., Hjaltason, H., Launer, L. J., & Gudnason, V. (2013) · Stroke · doi:10.1161/strokeaha.12.679381 · Cited by 166
Insular cortex mediates increased pain tolerance in yoga practitioners
Villemure, C., eko, M., Cotton, V. A., & Bushnell, M. C. (2014) · Cerebral Cortex · doi:10.1093/cercor/bht124 · Cited by 163
Pruessner, M., Pruessner, J. C., Hellhammer, D. H., Bruce Pike, G., & Lupien, S. J. (2007) · Psychiatry Research Neuroimaging · doi:10.1016/j.pscychresns.2006.12.007 · Cited by 150
Coronary Artery Calcium, Brain Function and Structure: The AGES-Reykjavik Study
Vidal, J.-S., Sigurdsson, S., Jonsdottir, M. K., Eiriksdottir, G., Thorgeirsson, G., Kjartansson, O., Garcia, M. E., van Buchem, M. A., Harris, T. B., Gudnason, V., et al. (2010) · Stroke · doi:10.1161/strokeaha.110.579581 · Cited by 139
Structural brain development: A review of methodological approaches and best practices
(2017) · doi:10.1016/j.dcn.2017.11.008 · Cited by 124
Identifying incipient dementia individuals using machine learning and amyloid imaging
Mathotaarachchi, S., Pascoal, T. A., Shin, M., Benedet, A. L., Kang, M. S., Beaudry, T., Fonov, V. S., Gauthier, S., & Rosa-Neto, P. (2017) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2017.06.027 · Cited by 118
Network inefficiencies in autism spectrum disorder at 24 months.
Lewis, J. D., Evans, A. C., Pruett, J. R., Botteron, K., Zwaigenbaum, L., Estes, A., Gerig, G., Collins, L., Kostopoulos, P., McKinstry, R., et al. (2014) · Translational Psychiatry · doi:10.1038/tp.2014.24 · Cited by 110
Self-citationINTREPAD: A randomized trial of naproxen to slow progress of presymptomatic Alzheimer disease
Meyer, P.-F., Tremblay-Mercier, J., Leoutsakos, J., Madjar, C., Lafaille-Maignan, M.-É., Savard, M., Rosa-Neto, P., Poirier, J., Etienne, P., Breitner, J., et al. (2019) · Neurology · doi:10.1212/wnl.0000000000007232 · Cited by 113
Fahim, C., Yoon, U., Das, S., Lyttelton, O., Chen, J., Arnaoutelis, R., Rouleau, G., Sandor, P., Frey, K., Brandner, C., et al. (2010) · Cortex · doi:10.1016/j.cortex.2009.06.008 · Cited by 107
Self-citationThe dynamic role of genetics on cortical patterning during childhood and adolescence
Schmitt, J. E., Neale, M. C., Fassassi, B., Perez, J., Lenroot, R. K., Wells, E. M., & Giedd, J. N. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1311630111 · Cited by 103
Fotros, A., Casey, K. F., Larcher, K., Verhaeghe, J. A., Cox, S. M., Gravel, P., Reader, A. J., Dagher, A., Benkelfat, C., & Leyton, M. (2013) · Neuropsychopharmacology · doi:10.1038/npp.2013.77 · Cited by 89
Mapping cortical laminar structure in the 3D BigBrain
Wagstyl, K., Lepage, C., Bludau, S., Zilles, K., Fletcher, P. C., Amunts, K., & Evans, A. C. (2018) · Cerebral Cortex · doi:10.1093/cercor/bhy074 · Cited by 85
Self-citationStructural brain magnetic resonance imaging of pediatric twins
Giedd, J. N., Schmitt, J. E., & Neale, M. C. (2007) · Human Brain Mapping · doi:10.1002/hbm.20403 · Cited by 72
Duerden, E. G., Card, D., Roberts, S. W., Mak-Fan, K. M., Chakravarty, M. M., Lerch, J. P., & Taylor, M. J. (2014) · Brain Structure and Function · doi:10.1007/s00429-013-0562-2 · Cited by 65
White and Gray Matter Abnormalities After Cranial Radiation in Children and Mice
Nieman, B. J., de Guzman, A. E., Gazdzinski, L. M., Lerch, J. P., Chakravarty, M. M., Pipitone, J., Strother, D., Fryer, C., Bouffet, E., Laughlin, S., et al. (2015) · International Journal of Radiation Oncology*Biology*Physics · doi:10.1016/j.ijrobp.2015.07.2293 · Cited by 62
Koh, S.-H., Choi, S. H., Jeong, J. H., Jang, J.-W., Park, K. W., Kim, E.-J., Kim, H. J., Hong, J. Y., Yoon, S. J., Yoon, B., et al. (2020) · Aging · doi:10.18632/aging.102893 · Cited by 51
Identifying schizophrenia subgroups using clustering and supervised learning
Talpalaru, A., Bhagwat, N., Devenyi, G. A., Lepage, M., & Chakravarty, M. M. (2019) · Schizophrenia Research · doi:10.1016/j.schres.2019.05.044 · Cited by 53
Faridi, N., Karama, S., Burgaleta, M., White, M. T., Evans, A. C., Fonov, V., Collins, D. L., & Waber, D. P. (2015) · Neuropsychology · doi:10.1037/neu0000079 · Cited by 42
Self-citationSex-Based Differences in Cortical and Subcortical Development in 436 Individuals Aged 4–54 Years
Duerden, E. G., Chakravarty, M. M., Lerch, J. P., & Taylor, M. J. (2020) · Cerebral Cortex · doi:10.1093/cercor/bhz279 · Cited by 28
Lee, N. R., Wallace, G. L., Raznahan, A., Clasen, L. S., & Giedd, J. N. (2014) · Frontiers in Psychology · doi:10.3389/fpsyg.2014.00496 · Cited by 30
“Tissue was classified into gray or white matter, spinal fluid, or background with a neural net classifier (Zijdenbos et al., 2002).”
BackgroundMethod
Metadata
- Authors
- Zijdenbos, A. P., Forghani, R., & Evans, A. C.
- Venue
- IEEE Transactions on Medical Imaging
- Published
- 2002-10
- Volume
- 21
- Issue
- 10
- Pages
- 1280-1291
- ISSN
- 0278-0062 (ISSN-L)
- OpenAlex
- W2161913873
- Cited by
- 761
- References
- 5
- FWCI
- 8.61
- Type
- journal article
- Language
- en
- Open access
- closed
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