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Field of View Normalization in Multi-Site Brain MRI

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Abstract

Multi-site brain MRI analysis is needed in big data neuroimaging studies, but challenging. The challenges lie in almost every analysis step including skull stripping. The diversities in multi-site brain MR images make it difficult to tune parameters specific to subjects or imaging protocols. Alternatively, using constant parameter settings often leads to inaccurate, inconsistent and even failed skull stripping results. One reason is that images scanned at different sites, under different scanners or protocols, and/or by different technicians often have very different fields of view (FOVs). Normalizing FOV is currently done manually or using ad hoc pre-processing steps, which do not always generalize well to multi-site diverse images. In this paper, we show that (a) a generic FOV normalization approach is possible in multi-site diverse images; we show experiments on images acquired from Philips, GE, Siemens scanners, from 1.0T, 1.5T, 3.0T field of strengths, and from subjects 0–90 years of ages; and (b) generic FOV normalization improves skull stripping accuracy and consistency for multiple skull stripping algorithms; we show this effect for 5 skull stripping algorithms including FSL’s BET, AFNI’s 3dSkullStrip, FreeSurfer’s HWA, BrainSuite’s BSE, and MASS. We have released our FOV normalization software at http://www.nitrc.org/projects/normalizefov.

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References

  • Acosta-Cabronero, J., Williams, G.B., Pereira, J.M., Pengas, G., Nestor, P.J. (2008). The impact of skull-stripping and radio-frequency bias correction on grey-matter segmentation for voxel-based morphometry. Neuroimage, 39(4), 1654–1665.

    Article  PubMed  Google Scholar 

  • Aljabar, P., Heckemann, R.A., Hammers, A., Hajnal, J.V., Rueckert, D. (2009). Multi-atlas based segmentation of brain images: atlas selection and its effect on accuracy. Neuroimage, 46(3), 726–738.

    Article  PubMed  CAS  Google Scholar 

  • Ardekani, B.A., & Bachman, A.H. (2009). Model-based automatic detection of the anterior and posterior commissures on MRI scans. Neuroimage, 46(3), 677–682.

    Article  PubMed  Google Scholar 

  • Bartsch, A.J., Homola, G., Biller, A., Smith, S.M., Weijers, H.-G., Wiesbeck, G.A., Jenkinson, M., De Stefano, N., Solymosi, L., Bendszus, M. (2007). Manifestations of early brain recovery associated with abstinence from alcoholism. Brain, 130(1), 36–47.

    Article  PubMed  Google Scholar 

  • Battaglini, M., Smith, S.M., Brogi, S., De Stefano, N. (2008). Enhanced brain extraction improves the accuracy of brain atrophy estimation. Neuroimage, 40(2), 583–589.

    Article  PubMed  Google Scholar 

  • Burton, P.R., Clayton, D.G., Cardon, L.R., Craddock, N., Deloukas, P., Duncanson, A., Kwiatkowski, D.P., McCarthy, M.I., Ouwehand, W.H., Samani, N.J. (2007). Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature, 447(7145), 661–678.

    Article  CAS  Google Scholar 

  • Caviness, V., Meyer, J., Makris, N., Kennedy, D. (1996). MRI-based topographic parcellation of human neocortex: an anatomically specified method with estimate of reliability. Journal of Cognitive Neuroscience, 8(6), 566–587.

    Article  PubMed  Google Scholar 

  • Cox, R.W. (1996). AFNI: software for analysis and visualization of functional magnetic resonance neuroimages. Computers and Biomedical research, 29(3), 162–173.

    Article  PubMed  CAS  Google Scholar 

  • 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. (2006). An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage, 31(3), 968–980.

    Article  PubMed  Google Scholar 

  • Doshi, J., Erus, G., Ou, Y., Gaonkar, B., Davatzikos, C. (2013). Multi- Atlas Skull-Stripping. Academic Radiology, 20(12), 1566–1576.

    Article  PubMed  Google Scholar 

  • Doshi, J., Erus, G., Ou, Y., Resnick, S.M., Gur, R.C., Gur, R.E., Satterthwaite, T.D., Furth, S., Davatzikos, C. (2016). A. N. Initiative, and others, MUSE: MUlti-atlas region segmentation utilizing ensembles of registration algorithms and parameters, and locally optimal atlas selection. NeuroImage.

  • Erus, G., Battapady, H., Satterthwaite, T.D., Hakonarson, H., Gur, R.E., Davatzikos, C., Gur, R.C. (2014). Imaging patterns of brain development and their relationship to cognition. Cerebral Cortex, p bht425.

  • Evans, A.C. (2006). The NIH MRI study of normal brain development. NeuroImage, 30, 184–202.

    Article  PubMed  Google Scholar 

  • Evans, A.C., Janke, A.L., Collins, D.L., Baillet, S. (2012). Brain templates and atlases. Neuroimage, 62(2), 911–922.

    Article  PubMed  Google Scholar 

  • Fennema-Notestine, C., Burak Ozyurt, I., Clark, C.P., Morris, S., Bischoff-Grethe, A., Bondi, M.W., Jernigan, T.L., Fischl, B., Segonne, F., Shattuck, D.W. (2006). Quantitative evaluation of automated skull-stripping methods applied to contemporary and legacy images: Effects of diagnosis, bias correction, and slice location. Human Brain Mapping, 27(2), 99–113.

    Article  PubMed  Google Scholar 

  • Fischl, B. (2012). FreeSurfer. Neuroimage, 62(2), 774–781.

    Article  PubMed  Google Scholar 

  • Fischl, B., van der Kouwe, A., Destrieux, C., Halgren, E., Ségonne, F., Salat, D.H., Busa, E., Seidman, L.J., Goldstein, J., Kennedy, D. (2004). Automatically parcellating the human cerebral cortex. Cerebral Cortex, 14(1), 11–22.

    Article  PubMed  Google Scholar 

  • Fonov, V., Evans, A.C., Botteron, K., Almli, C.R., McKinstry, R. C., Collins, D. L., Group, B.D.C. (2011). Unbiased average age- appropriate atlases for pediatric studies. NeuroImage, 54(1), 313–327.

    Article  PubMed  Google Scholar 

  • Galdames, F.J., Jaillet, F., Perez, C.A. (2012). An accurate skull stripping method based on simplex meshes and histogram analysis for magnetic resonance images. Journal of Neuroscience Methods, 206(2), 103–119.

    Article  PubMed  Google Scholar 

  • Glasser, M.F., Sotiropoulos, S.N., Wilson, J.A., Coalson, T.S., Fischl, B., Andersson, J.L., Xu, J., Jbabdi, S., Webster, M., Polimeni, J.R. (2013). The minimal preprocessing pipelines for the Human Connectome Project. Neuroimage, 80, 105–124.

    Article  PubMed  Google Scholar 

  • Gousias, I.S., Rueckert, D., Heckemann, R.A., Dyet, L.E., Boardman, J.P., Edwards, A.D., Hammers, A. (2008). Automatic segmentation of brain MRIs of 2-year-olds into 83 regions of interest. Neuroimage, 40(2), 672–684.

    Article  PubMed  Google Scholar 

  • Hartley, S., Scher, A., Korf, E., White, L., Launer, L. (2006). Analysis and validation of automated skull stripping tools: A validation study based on 296 MR images from the Honolulu Asia aging study. NeuroImage, 30, 1179–1186.

    Article  PubMed  CAS  Google Scholar 

  • Heckemann, R.A., Husson, R., Ledig, C., Rueckert, D., Hammers, A. (2013). Positional normalization as a first step in processing magnetic resonance brain images: work in progress. In Swedish symposium on image analysis for (pp. 1–3).

  • Hibar, D.P., Stein, J.L., Renteria, M.E., Arias-Vasquez, A., Desrivières, S., Jahanshad, N., Toro, R., Wittfeld, K., Abramovic, L., Andersson, M. (2015). Common genetic variants influence human subcortical brain structures. Nature, 520, 224–229.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Iglesias, J.E., Liu, C.-Y., Thompson, P. M., Tu, Z. (2011). Robust brain extraction across datasets and comparison with publicly available methods. IEEE Transactions on Medical Imaging, 30(9), 1617–1634.

    Article  PubMed  Google Scholar 

  • Jack, C.R., Bernstein, M.A., Fox, N.C., Thompson, P., Alexander, G., Harvey, D., Borowski, B., Britson, P.J., Whitwell, J.L, Ward, C. (2008). The Alzheimer’s disease neuroimaging initiative (ADNI): MRI methods. Journal of Magnetic Resonance Imaging, 27(4), 685–691.

    Article  PubMed  Google Scholar 

  • Jenkinson, M., Beckmann, C.F., Behrens, T.E., Woolrich, M.W., Smith, S.M. (2012). Fsl. Neuroimage, 62(2), 782–790.

    Article  PubMed  Google Scholar 

  • Jenkinson, M., Pechaud, M., Smith, S. (2005). BET2: MR-based estimation of brain, skull and scalp surfaces. In 11th annual meeting of the organization for human brain mapping (Vol. 17, p. 167). Toronto, ON.

  • Johansen-Berg, H., Behrens, T.E., Sillery, E., Ciccarelli, O., Thompson, A.J., Smith, S.M., Matthews, P.M. (2005). Functional-anatomical validation and individual variation of diffusion tractography-based segmentation of the human thalamus. Cerebral Cortex, 15(1), 31–39.

    Article  PubMed  Google Scholar 

  • Lancaster, J.L., Summerlin, J.L., Rainey, L., Freitas, C.S., Fox, P.T. (1997). The Talairach Daemon, a database server for Talairach atlas labels. Neuroimage, 5(4), S633.

    Google Scholar 

  • Lancaster, J.L., Woldorff, M.G., Parsons, L.M., Liotti, M., Freitas, C.S., Rainey, L., Kochunov, P.V., Nickerson, D., Mikiten, S.A., Fox, P.T. (2000). Automated Talairach atlas labels for functional brain mapping. Human Brain Mapping, 10(3), 120–131.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  • Lee, J.-M., Yoon, U., Nam, S.H., Kim, J.-H., Kim, I.-Y., Kim, S.I. (2003). Evaluation of automated and semi-automated skull-stripping algorithms using similarity index and segmentation error. Computers in Biology and Medicine, 33(6), 495–507.

    Article  PubMed  Google Scholar 

  • Leung, K.K., Barnes, J., Modat, M., Ridgway, G.R., Bartlett, J.W., Fox, N.C., Ourselin, S., Initiative, A.D.N. (2011). Brain MAPS: an automated, accurate and robust brain extraction technique using a template library. Neuroimage, 55(3), 1091–1108.

    Article  PubMed  Google Scholar 

  • Liao, M., Yang, W., Zhang, X., Lu, M., Dou, W. (2014). A preprocessing method for magnetic resonance images of head to improve the performance of brain extraction tools. In 2014 7th international conference on biomedical engineering and informatics (BMEI) (pp. 121–125). IEEE.

  • Lötjönen, J.M., Wolz, R., Koikkalainen, J.R., Thurfjell, L., Waldemar, G., Soininen, H., Rueckert, D., Initiative, A.D.N. (2010). Fast and robust multi-atlas segmentation of brain magnetic resonance images. Neuroimage, 49(3), 2352–2365.

    Article  PubMed  Google Scholar 

  • Marcus, D.S., Wang, T.H., Parker, J., Csernansky, J.G., Morris, J.C., Buckner, R.L. (2007). Open Access Series of Imaging Studies (OASIS): cross-sectional MRI data in young, middle aged, nondemented, and demented older adults. Journal of Cognitive Neuroscience, 19(9), 1498–1507.

    Article  PubMed  Google Scholar 

  • Mazziotta, J.C., Toga, A.W., Evans, A., Fox, P., Lancaster, J. (1995). A probabilistic atlas of the human brain: theory and rationale for its development the international consortium for brain mapping (ICBM). Neuroimage, 12(2PA), 89–101.

    Article  Google Scholar 

  • McLendon, R., Friedman, A., Bigner, D., Van Meir, E.G., Brat, D.J., Mastrogianakis, G.M., Olson, J.J., Mikkelsen, T., Lehman, N., Aldape, K. (2008). Comprehensive genomic characterization defines human glioblastoma genes and core pathways. Nature, 455(7216), 1061–1068.

    Article  CAS  Google Scholar 

  • Medland, S.E., Jahanshad, N., Neale, B.M., Thompson, P.M. (2014). Whole-genome analyses of whole-brain data: working within an expanded search space. Nature Neuroscience, 17(6), 791–800.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Ou, Y., Akbari, H., Bilello, M., Da, X., Davatzikos, C. (2014). Comparative evaluation of registration algorithms in different brain databases with varying difficulty: results and insights. IEEE Transactions on Medical Imaging, 33(10), 2039–2065.

    Article  PubMed  PubMed Central  Google Scholar 

  • Ou, Y., Gollub, R.L., Retzepi, K., Reynold, N.A., Pienaar, R., Murphy, S.N., Grant, P.E., Zöllei, L. (2015). Brain extraction in pediatric ADC maps, toward characterizing neuro-development in multi- platform and multi-institution clinical images. NeuroImage, 122, 246–261.

    Article  PubMed  Google Scholar 

  • Ou, Y., Sotiras, A., Paragios, N., Davatzikos, C. (2011). DRAMMS: Deformable registration via attribute matching and mutual-saliency weighting. Medical Image Analysis, 15(4), 622–639.

    Article  PubMed  Google Scholar 

  • Ou, Y., Zöllei, L., Retzepi, K., Castro, V., Bates, S.V., Pieper, S., Andriole, K.P., Murphy, S.N., Gollub, R.L., Grant, P.E. (2017). Using clinically acquired mri to construct age-specific ADC atlases: Quantifying spatiotemporal adc changes from birth to 6-year old. Human Brain Mapping, 38(6), 3052–3068.

    Article  PubMed  PubMed Central  Google Scholar 

  • Pacheco, J., Goh, J.O., Kraut, M.A., Ferrucci, L., Resnick, S.M. (2015). Greater cortical thinning in normal older adults predicts later cognitive impairment. Neurobiology of Aging, 36(2), 903–908.

    Article  PubMed  Google Scholar 

  • Penny, W.D., Friston, K.J., Ashburner, J.T., Kiebel, S.J., Nichols, T.E. (2011). Statistical parametric mapping: the analysis of functional brain images: the analysis of functional brain images. Cambridge: Academic Press.

    Google Scholar 

  • Popescu, V., Battaglini, M., Hoogstrate, W.S., Verfaillie, S.C.J., Sluimer, I.C., Van Schijndel, R.A., Van Dijk, B.W., Cover, K.S., Knol, D.L., Jenkinson, M. (2012). Optimizing parameter choice for FSL-Brain Extraction Tool (BET) on 3d T1 images in multiple sclerosis. Neuroimage, 61(4), 1484–1494.

    Article  PubMed  CAS  Google Scholar 

  • Rex, D.E., Ma, J.Q., Toga, A.W. (2003). The LONI pipeline processing environment. Neuroimage, 19(3), 1033–1048.

    Article  PubMed  Google Scholar 

  • Ridgway, G.R., Henley, S.M., Rohrer, J.D., Scahill, R.I., Warren, J.D., Fox, N.C. (2008). Ten simple rules for reporting voxel-based morphometry studies. Neuroimage, 40(4), 1429–1435.

    Article  PubMed  Google Scholar 

  • Rohlfing, T., Zahr, N.M., Sullivan, E.V., Pfefferbaum, A. (2010). The SRI24 multichannel atlas of normal adult human brain structure. Human Brain Mapping, 31(5), 798–819.

    Article  PubMed  Google Scholar 

  • Saad, Z.S., Glen, D.R., Chen, G., Beauchamp, M.S., Desai, R., Cox, R.W. (2009). A new method for improving functional-to-structural MRI alignment using local Pearson correlation. Neuroimage, 44(3), 839–848.

    Article  PubMed  Google Scholar 

  • Sadananthan, S.A., Zheng, W., Chee, M.W., Zagorodnov, V. (2010). Skull stripping using graph cuts. NeuroImage, 49(1), 225–239.

    Article  PubMed  Google Scholar 

  • Schmahmann, J.D., Doyon, J., McDonald, D., Holmes, C., Lavoie, K., Hurwitz, A.S., Kabani, N., Toga, A., Evans, A., Petrides, M. (1999). Three-dimensional MRI atlas of the human cerebellum in proportional stereotaxic space. Neuroimage, 10(3), 233–260.

    Article  PubMed  CAS  Google Scholar 

  • Schmahmann, J.D., Doyon, J., Petrides, M., Evans, A.C., Toga, A.W. (2000). MRI atlas of the human cerebellum. Cambridge: Academic Press.

    Google Scholar 

  • Segonne, F., Dale, A.M., Busa, E., Glessner, M., Salat, D., Hahn, H.K., Fischl, B. (2004). A hybrid approach to the skull stripping problem in MRI. Neuroimage, 22(3), 1060–1075.

    Article  PubMed  CAS  Google Scholar 

  • Seshadri, S., Wolf, P.A., Beiser, A., Au, R., McNulty, K., White, R., D’agostino, R.B. (1997). Lifetime risk of dementia and Alzheimer’s disease The impact of mortality on risk estimates in the Framingham Study. Neurology, 49(6), 1498–1504.

    Article  PubMed  CAS  Google Scholar 

  • Shams, R., Sadeghi, P., Kennedy, R., Hartley, R. (2010). A survey of medical image registration on multicore and the GPU. IEEE Signal Processing Magazine, 27(2), 50–60.

    Article  Google Scholar 

  • Shattuck, D.W., & Leahy, R.M. (2002). BrainSuite: an automated cortical surface identification tool. Medical Image Analysis, 6(2), 129–142.

    Article  PubMed  Google Scholar 

  • Shattuck, D.W., Mirza, M., Adisetiyo, V., Hojatkashani, C., Salamon, G., Narr, K.L., Poldrack, R.A., Bilder, R.M., Toga, A.W. (2008). Construction of a 3d probabilistic atlas of human cortical structures. Neuroimage, 39(3), 1064–1080.

    Article  PubMed  Google Scholar 

  • Shattuck, D.W., Prasad, G., Mirza, M., Narr, K.L., Toga, A.W. (2009). Online resource for validation of brain segmentation methods. NeuroImage, 45(2), 431–439.

    Article  PubMed  Google Scholar 

  • Shi, F., Fan, Y., Tang, S., Gilmore, J.H., Lin, W., Shen, D. (2010). Neonatal brain image segmentation in longitudinal MRI studies. Neuroimage, 49(1), 391–400.

    Article  PubMed  Google Scholar 

  • Shi, F., Wang, L., Dai, Y., Gilmore, J.H., Lin, W., Shen, D. (2012). LABEL: pediatric brain extraction using learning-based meta-algorithm. Neuroimage, 62(3), 1975–1986.

    Article  PubMed  Google Scholar 

  • Shi, F., Yap, P.-T., Wu, G., Jia, H., Gilmore, J.H., Lin, W., Shen, D. (2011). Infant brain atlases from neonates to 1-and 2-year-olds. PLoS One, 6(4), e18746.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Smith, S.M. (2002). Fast robust automated brain extraction. Human Brain Mapping, 17(3), 143–155.

    Article  PubMed  PubMed Central  Google Scholar 

  • Sowell, E.R., Thompson, P.M., Leonard, C.M., Welcome, S.E., Kan, E., Toga, A.W. (2004). Longitudinal mapping of cortical thickness and brain growth in normal children. The Journal of Neuroscience, 24 (38), 8223–8231.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  • Wang, Y., Nie, J., Yap, P.-T., Li, G., Shi, F., Geng, X., Guo, L., Shen, D. (2014). For the Alzheimer’s disease neuroimaging initiative knowledge-guided robust MRI brain extraction for diverse large-scale neuroimaging studies on humans and non-human primates. PLoS ONE, 9, e77810.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Warfield, S.K., Zou, K.H., Wells, W.M. (2004). Simultaneous truth and performance level estimation (STAPLE): an algorithm for the validation of image segmentation. IEEE Transactions on Medical Imaging, 23(7), 903–921.

    Article  PubMed  PubMed Central  Google Scholar 

  • Worth, A. (1996). The internet brain segmentation repository (ibsr).

  • Yang, W., Liao, M., Zhang, X., Dou, W., Zhang, M., Chen, H., Li, S., Wang, Y., Dai, J. (2014). An improvement method of brain extraction tools for magnetic resonance images. Journal of Medical Imaging and Health Informatics, 4(6), 895–900.

    Article  Google Scholar 

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Acknowledgements

The authors would like to acknowledge Instrumentation Grants 1S10RR023401, 1S10RR019307, and 1S10RR023043 for providing support of the high-performance batch computing environment, Thrasher Research Fund Early Career Award for support to YO, Boston Children’s Hospital and Harvard Medical School Faculty Development Fellowship to YO, NIH R01 EB014947 for support to YO, LZ, KR, PEG, SNM and RLG, NIH R00 HD061485 for support to LZ, NIH K23 CA169021 for support to ERG, and NIH U01 CA154601 and U24 CA180927 for support to YO, XD, ERG and JKC.

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    Authors and Affiliations

    1. Department of Pediatrics and Radiology, Boston Children’s Hospital, Harvard Medical School, Boston, MA, USA

      Yangming Ou & P. Ellen Grant

    2. Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA

      Yangming Ou, Lilla Zöllei, Kallirroi Retzepi, Bruce R. Rosen, Jayashree Kalpathy-Cramer & Randy L. Gollub

    3. Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA

      Yangming Ou & Randy L. Gollub

    4. Functional Neuroimaging Laboratory, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA

      Xiao Da

    5. Research Computing, Partners Healthcare, Boston, MA, USA

      Shawn N. Murphy

    6. Neuro-Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA

      Elizabeth R. Gerstner

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    Jayashree Kalpathy-Cramer and Randy L. Gollub contributed equally.

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    Ou, Y., Zöllei, L., Da, X. et al. Field of View Normalization in Multi-Site Brain MRI. Neuroinform 16, 431–444 (2018). https://doi.org/10.1007/s12021-018-9359-z

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