Volumetric navigators for prospective motion correction and selective reacquisition in neuroanatomical MRI
We introduce a novel method of prospectively compensating for subject motion in neuroanatomical imaging. Short three‐dimensional echo‐planar imaging volumetric navigators are embedded in a long three‐dimensional sequence, and the resulting image volumes are registered to provide an estimate of the s...
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| Published in | Magnetic resonance in medicine Vol. 68; no. 2; pp. 389 - 399 |
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| Main Authors | , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Hoboken
Wiley Subscription Services, Inc., A Wiley Company
01.08.2012
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| Subjects | |
| Online Access | Get full text |
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| Abstract | We introduce a novel method of prospectively compensating for subject motion in neuroanatomical imaging. Short three‐dimensional echo‐planar imaging volumetric navigators are embedded in a long three‐dimensional sequence, and the resulting image volumes are registered to provide an estimate of the subject's location in the scanner at a cost of less than 500 ms, ∼ 1% change in contrast, and ∼3% change in intensity. This time fits well into the existing gaps in sequences routinely used for neuroimaging, thus giving a motion‐corrected sequence with no extra time required. We also demonstrate motion‐driven selective reacquisition of k‐space to further compensate for subject motion. We perform multiple validation experiments to evaluate accuracy, navigator impact on tissue intensity/contrast, and the improvement in final output. The complete system operates without adding additional hardware to the scanner and requires no external calibration, making it suitable for high‐throughput environments. Magn Reson Med, 2012. © 2011 Wiley Periodicals, Inc. |
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| AbstractList | We introduce a novel method of prospectively compensating for subject motion in neuroanatomical imaging. Short three‐dimensional echo‐planar imaging volumetric navigators are embedded in a long three‐dimensional sequence, and the resulting image volumes are registered to provide an estimate of the subject's location in the scanner at a cost of less than 500 ms, ∼ 1% change in contrast, and ∼3% change in intensity. This time fits well into the existing gaps in sequences routinely used for neuroimaging, thus giving a motion‐corrected sequence with no extra time required. We also demonstrate motion‐driven selective reacquisition of
k
‐space to further compensate for subject motion. We perform multiple validation experiments to evaluate accuracy, navigator impact on tissue intensity/contrast, and the improvement in final output. The complete system operates without adding additional hardware to the scanner and requires no external calibration, making it suitable for high‐throughput environments. Magn Reson Med, 2012. © 2011 Wiley Periodicals, Inc. We introduce a novel method of prospectively compensating for subject motion in neuroanatomical imaging. Short three‐dimensional echo‐planar imaging volumetric navigators are embedded in a long three‐dimensional sequence, and the resulting image volumes are registered to provide an estimate of the subject's location in the scanner at a cost of less than 500 ms, ∼ 1% change in contrast, and ∼3% change in intensity. This time fits well into the existing gaps in sequences routinely used for neuroimaging, thus giving a motion‐corrected sequence with no extra time required. We also demonstrate motion‐driven selective reacquisition of k‐space to further compensate for subject motion. We perform multiple validation experiments to evaluate accuracy, navigator impact on tissue intensity/contrast, and the improvement in final output. The complete system operates without adding additional hardware to the scanner and requires no external calibration, making it suitable for high‐throughput environments. Magn Reson Med, 2012. © 2011 Wiley Periodicals, Inc. We introduce a novel method of prospectively compensating for subject motion in neuroanatomical imaging. Short three-dimensional echo-planar imaging volumetric navigators are embedded in a long three-dimensional sequence, and the resulting image volumes are registered to provide an estimate of the subject's location in the scanner at a cost of less than 500 ms, ~ 1% change in contrast, and ~3% change in intensity. This time fits well into the existing gaps in sequences routinely used for neuroimaging, thus giving a motion-corrected sequence with no extra time required. We also demonstrate motion-driven selective reacquisition of k-space to further compensate for subject motion. We perform multiple validation experiments to evaluate accuracy, navigator impact on tissue intensity/contrast, and the improvement in final output. The complete system operates without adding additional hardware to the scanner and requires no external calibration, making it suitable for high-throughput environments.We introduce a novel method of prospectively compensating for subject motion in neuroanatomical imaging. Short three-dimensional echo-planar imaging volumetric navigators are embedded in a long three-dimensional sequence, and the resulting image volumes are registered to provide an estimate of the subject's location in the scanner at a cost of less than 500 ms, ~ 1% change in contrast, and ~3% change in intensity. This time fits well into the existing gaps in sequences routinely used for neuroimaging, thus giving a motion-corrected sequence with no extra time required. We also demonstrate motion-driven selective reacquisition of k-space to further compensate for subject motion. We perform multiple validation experiments to evaluate accuracy, navigator impact on tissue intensity/contrast, and the improvement in final output. The complete system operates without adding additional hardware to the scanner and requires no external calibration, making it suitable for high-throughput environments. We introduce a novel method of prospectively compensating for subject motion in neuroanatomical imaging. Short 3D EPI volumetric navigators (vNavs) are embedded in a long 3D sequence, and the resulting image volumes registered to provide an estimate of the subject’s location in the scanner at a cost of less than 500 ms, ~ 1% change in contrast, and ~ 3% change in intensity. This time fits well into the existing gaps in sequences routinely used for neuroimaging, thus giving a motion-corrected sequence with no extra time required. We also demonstrate motion-driven selective reacquisition of k-space to further compensate for subject motion. We perform multiple validation experiments to evaluate accuracy, navigator impact on tissue intensity/contrast, and the improvement in final output. The complete system operates without adding additional hardware to the scanner and requires no external calibration, making it suitable for high-throughput environments. We introduce a novel method of prospectively compensating for subject motion in neuroanatomical imaging. Short three-dimensional echo-planar imaging volumetric navigators are embedded in a long three-dimensional sequence, and the resulting image volumes are registered to provide an estimate of the subject's location in the scanner at a cost of less than 500 ms, ~ 1% change in contrast, and ~3% change in intensity. This time fits well into the existing gaps in sequences routinely used for neuroimaging, thus giving a motion-corrected sequence with no extra time required. We also demonstrate motion-driven selective reacquisition of k-space to further compensate for subject motion. We perform multiple validation experiments to evaluate accuracy, navigator impact on tissue intensity/contrast, and the improvement in final output. The complete system operates without adding additional hardware to the scanner and requires no external calibration, making it suitable for high-throughput environments. |
| Author | Fischl, Bruce van der Kouwe, André J. W. Hess, Aaron T. Reuter, Martin Tisdall, M. Dylan Meintjes, Ernesta M. |
| AuthorAffiliation | 4 Medical Research Council/University of Cape Town Medical Imaging Research Unit, South Africa 6 Neurology, Harvard Medical School, Brookline, MA, USA 5 Neurology, Massachusetts General Hospital, Charlestown, MA, USA 2 Radiology, Harvard Medical School, Brookline, MA, USA 1 Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA 3 Department of Human Biology, University of Cape Town, South Africa 7 Computer Science and AI Lab, Massachusetts Institute of Technology, Cambridge, MA, USA |
| AuthorAffiliation_xml | – name: 7 Computer Science and AI Lab, Massachusetts Institute of Technology, Cambridge, MA, USA – name: 6 Neurology, Harvard Medical School, Brookline, MA, USA – name: 1 Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA – name: 5 Neurology, Massachusetts General Hospital, Charlestown, MA, USA – name: 2 Radiology, Harvard Medical School, Brookline, MA, USA – name: 3 Department of Human Biology, University of Cape Town, South Africa – name: 4 Medical Research Council/University of Cape Town Medical Imaging Research Unit, South Africa |
| Author_xml | – sequence: 1 givenname: M. Dylan surname: Tisdall fullname: Tisdall, M. Dylan email: tisdall@nmr.mgh.harvard.edu organization: Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA – sequence: 2 givenname: Aaron T. surname: Hess fullname: Hess, Aaron T. organization: Department of Human Biology, MRC/UCT Medical Imaging Research Unit, University of Cape Town, South Africa – sequence: 3 givenname: Martin surname: Reuter fullname: Reuter, Martin organization: Department Neurology, Massachusetts General Hospital, Charlestown, Massachusetts, USA – sequence: 4 givenname: Ernesta M. surname: Meintjes fullname: Meintjes, Ernesta M. organization: Department of Human Biology, MRC/UCT Medical Imaging Research Unit, University of Cape Town, South Africa – sequence: 5 givenname: Bruce surname: Fischl fullname: Fischl, Bruce organization: Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA – sequence: 6 givenname: André J. W. surname: van der Kouwe fullname: van der Kouwe, André J. W. organization: Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/22213578$$D View this record in MEDLINE/PubMed |
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| References | Fischl B, Dale AM. Measuring the thickness of the human cerebral cortex from magnetic resonance images. Proc Nat Acad Sci USA 2000; 97: 11050-11055. Jovicich J, Czanner S, Greve D, Haley E, van der Kouwe A, Gollub R, Kennedy D, Schmitt F, Brown G, MacFall J, Fischl B, Dale A. Reliability in multi-site structural MRI studies: effects of gradient nonlinearity correction on phantom and human data. Neuroimage 2006; 30: 436-443. Welch EB, Manduca A, Grimm RC, Ward HA, Jack CR. Spherical navigator echoes for full 3d rigid body motion measurement in MRI. Magn Reson Med 2002; 47: 32-41. Brown TT, Kuperman JM, Erhart M, White NS, Roddey JC, Shankaranarayanan A, Han ET, Rettmann D, Dale AM. Prospective motion correction of high-resolution magnetic resonance imaging data in children. Neuroimage 2010; 53: 139-145. Dale A, Fischl B, Sereno MI. Cortical surface-based analysis. i. Segmentation and surface reconstruction. Neuroimage 1999; 9: 179-194. Pipe JG. Motion correction with propeller MRI: application to head motion and free-breathing cardiac imaging. Magn Reson Med 1999; 42: 963-969. Hess AT, Tisdall MD, Andronesi OC, Meintjes EM, van der Kouwe AJW. Real-time motion and b0 corrected single voxel spectroscopy using volumetric navigators. Magn Reson Med 2011; 66: 314-323. Segonne F, Dale AM, Busa E, Glessner M, Salat D, Hahn HK, Fischl B. A hybrid approach to the skull stripping problem in MRI. Neuroimage 2004; 22: 1060-1075. Thesen S, Heid O, Mueller E, Schad LR. Prospective acquisition correction for head motion with image-based tracking for real-time fMRI. Magn Reson Med 2000; 44: 457-465. Bydder M, Larkman DJ, Hajnal JV. Detection and elimination of motion artifacts by regeneration of k-space. Magn Reson Med 2002; 47: 677-686. Ooi MB, Krueger S, Thomas WJ, Swaminathan SV, Brown TR. Prospective real-time correction for arbitrary head motion using active markers. Magn Reson Med 2009; 62: 943-954. Fischl B, Liu A, Dale AM. Automated manifold surgery: constructing geometrically accurate and topologically correct models of the human cerebral cortex. IEEE Med Imaging 2001; 20: 70-80. Greve DN, Fischl B. Accurate and robust brain image alignment using boundary-based registration. Neuroimage 2009; 48: 63-72. Reuter M, Fischl B. Avoiding asymmetry-induced bias in longitudinal image processing. Neuroimage 2011; 57: 19-21. Liu J, Drangova M. Rapid six-degree-of-freedom motion detection using prerotated baseline spherical navigator echoes. Magn Reson Med 2010; 65: 506-514. Fischl B, Salat DH, van der Kouwe AJ, Makris N, Ségonne F, Quinn BT, Dale AM. Sequence-independent segmentation of magnetic resonance images. Neuroimage 2004; 23( Suppl 1): S69-S84. Fischl B, Sereno MI, Tootell RB, Dale AM. High-resolution intersubject averaging and a coordinate system for the cortical surface. Hum Brain Mapp 1999; 8: 272-284. Jiang A, Kennedy DN, Baker JR, Weisskoff RM, Tootell RBH, Woods RP, Benson RR, Kwong KK, Brady TJ, Rosen BR, Belliveau JW. Motion detection and correction in functional MR imaging. Hum Brain Mapp 1995; 3: 224-235. Fischl B, Sereno MI, Dale A. Cortical surface-based analysis. II: inflation, flattening, and a surface-based coordinate system. Neuroimage 1999; 9: 195-207. Atkinson D, Hill D, Stoyle P, Summers P, Keevil S. Automatic correction of motion artifacts in magnetic resonance images using an entropy focus criterion. IEEE Trans Med Imaging 1997; 16: 903-910. Qin L, van Gelderen P, Derbyshire JA, Jin F, Lee J, de Zwart JA, Tao Y, Duyn JH. Prospective head-movement correction for high-resolution MRI using an in-bore optical tracking system. Magn Reson Med 2009; 62: 924-934. van der Kouwe AJW, Benner T, Dale AM. Real-time rigid body motion correction and shimming using cloverleaf navigators. Magn Reson Med 2006; 56: 1019-1032. Friston KJ, Frith CD, Frackowiak RS, Turner R. Characterizing dynamic brain responses with fmri: a multivariate approach. Neuroimage 1995; 2: 166-172. Maclaren J, Lee KJ, Luengviriya C, Speck O, Zaitsev M. Combined prospective and retrospective motion correction to relax navigator requirements. Magn Reson Med 2011; 65: 1724-1732. van der Kouwe AJW, Benner T, Salat DH, Fischl B. Brain morphometry with multiecho mprage. Neuroimage 2008; 40: 559-569. 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. Keating B, Deng W, Roddey JC, White N, Dale A, Stenger VA, Ernst T. Prospective motion correction for single-voxel 1 h MR spectroscopy. Magn Reson Med 2010; 64: 672-679. White N, Roddey C, Shankaranarayanan A, Han E, Rettmann D, Santos J, Kuperman J, Dale A. Promo: real-time prospective motion correction in MRI using image-based tracking. Magn Reson Med 2010; 63: 91-105. Fischl B, van der Kouwe A, Destrieux C, Halgren E, Ségonne F, Salat DH, Busa E, Seidman LJ, Goldstein J, Kennedy D, Caviness V, Makris N, Rosen B, Dale AM. Automatically parcellating the human cerebral cortex. Cereb Cortex 2004; 14: 11-22. Liu C, Bammer R, Kim D-H, Moseley ME. Self-navigated interleaved spiral (snails): application to high-resolution diffusion tensor imaging. Magn Reson Med 2004; 52: 1388-1396. Crum W, Camara O, Hill D. Generalized overlap measures for evaluation and validation in medical image analysis. IEEE Trans Med Imaging 2006; 25: 1451-1461. Fischl B, Salat DH, Busa E, Albert M, Dieterich M, Haselgrove C, van der Kouwe A, Killiany R, Kennedy D, Klaveness S, Montillo A, Makris N, Rosen B, Dale AM. Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain. Neuron 2002; 33: 341-355. Han X, Jovicich J, Salat D, van der Kouwe A, Quinn B, Czanner S, Busa E, Pacheco J, Albert M, Killiany R, Maguire P, Rosas D, Makris N, Dale A, Dickerson B, Fischl B. Reliability of MRI-derived measurements of human cerebral cortical thickness: The effects of field strength, scanner upgrade, and manufacturer. Neuroimage 2006; 32: 180-194. Reuter M, Rosas HD, Fischl B. Highly accurate inverse consistent registration: a robust approach. Neuroimage 2010; 53: 1181-1196. Ward HA, Riederer SJ, Grimm RC, Ehman RL, Felmlee JP, Jack CR. Prospective multiaxial motion correction for fMRI. Magn Reson Med 2000; 43: 459-469. 2002; 17 2004; 22 2010; 53 2006; 30 2009; 62 2006; 56 2006; 32 2000; 43 2000; 44 2004; 23 2002; 33 1999; 42 2011; 57 1995; 2 1999; 8 1995; 3 2010; 63 2009; 48 2001; 20 1999; 9 2002; 47 2004; 52 2010; 65 2010; 64 2004; 14 2006; 25 2000; 97 2011; 66 1997; 16 2011; 65 2008; 40 e_1_2_7_5_2 e_1_2_7_4_2 e_1_2_7_3_2 e_1_2_7_2_2 e_1_2_7_9_2 e_1_2_7_8_2 e_1_2_7_7_2 e_1_2_7_6_2 e_1_2_7_19_2 e_1_2_7_18_2 e_1_2_7_17_2 e_1_2_7_16_2 e_1_2_7_15_2 e_1_2_7_14_2 e_1_2_7_13_2 e_1_2_7_12_2 e_1_2_7_11_2 e_1_2_7_10_2 e_1_2_7_26_2 e_1_2_7_27_2 e_1_2_7_28_2 e_1_2_7_29_2 e_1_2_7_25_2 e_1_2_7_24_2 e_1_2_7_30_2 e_1_2_7_23_2 e_1_2_7_31_2 e_1_2_7_22_2 e_1_2_7_32_2 e_1_2_7_21_2 e_1_2_7_33_2 e_1_2_7_20_2 e_1_2_7_34_2 e_1_2_7_35_2 e_1_2_7_36_2 |
| References_xml | – reference: Reuter M, Fischl B. Avoiding asymmetry-induced bias in longitudinal image processing. Neuroimage 2011; 57: 19-21. – reference: Maclaren J, Lee KJ, Luengviriya C, Speck O, Zaitsev M. Combined prospective and retrospective motion correction to relax navigator requirements. Magn Reson Med 2011; 65: 1724-1732. – reference: Qin L, van Gelderen P, Derbyshire JA, Jin F, Lee J, de Zwart JA, Tao Y, Duyn JH. Prospective head-movement correction for high-resolution MRI using an in-bore optical tracking system. Magn Reson Med 2009; 62: 924-934. – reference: 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. – reference: Segonne F, Dale AM, Busa E, Glessner M, Salat D, Hahn HK, Fischl B. A hybrid approach to the skull stripping problem in MRI. Neuroimage 2004; 22: 1060-1075. – reference: van der Kouwe AJW, Benner T, Dale AM. Real-time rigid body motion correction and shimming using cloverleaf navigators. Magn Reson Med 2006; 56: 1019-1032. – reference: Hess AT, Tisdall MD, Andronesi OC, Meintjes EM, van der Kouwe AJW. Real-time motion and b0 corrected single voxel spectroscopy using volumetric navigators. Magn Reson Med 2011; 66: 314-323. – reference: Liu C, Bammer R, Kim D-H, Moseley ME. Self-navigated interleaved spiral (snails): application to high-resolution diffusion tensor imaging. Magn Reson Med 2004; 52: 1388-1396. – reference: Greve DN, Fischl B. Accurate and robust brain image alignment using boundary-based registration. Neuroimage 2009; 48: 63-72. – reference: Thesen S, Heid O, Mueller E, Schad LR. Prospective acquisition correction for head motion with image-based tracking for real-time fMRI. Magn Reson Med 2000; 44: 457-465. – reference: Bydder M, Larkman DJ, Hajnal JV. Detection and elimination of motion artifacts by regeneration of k-space. Magn Reson Med 2002; 47: 677-686. – reference: Reuter M, Rosas HD, Fischl B. Highly accurate inverse consistent registration: a robust approach. Neuroimage 2010; 53: 1181-1196. – reference: Fischl B, Liu A, Dale AM. Automated manifold surgery: constructing geometrically accurate and topologically correct models of the human cerebral cortex. IEEE Med Imaging 2001; 20: 70-80. – reference: van der Kouwe AJW, Benner T, Salat DH, Fischl B. Brain morphometry with multiecho mprage. Neuroimage 2008; 40: 559-569. – reference: White N, Roddey C, Shankaranarayanan A, Han E, Rettmann D, Santos J, Kuperman J, Dale A. Promo: real-time prospective motion correction in MRI using image-based tracking. Magn Reson Med 2010; 63: 91-105. – reference: Fischl B, Sereno MI, Tootell RB, Dale AM. High-resolution intersubject averaging and a coordinate system for the cortical surface. Hum Brain Mapp 1999; 8: 272-284. – reference: Fischl B, Salat DH, van der Kouwe AJ, Makris N, Ségonne F, Quinn BT, Dale AM. Sequence-independent segmentation of magnetic resonance images. Neuroimage 2004; 23( Suppl 1): S69-S84. – reference: Jovicich J, Czanner S, Greve D, Haley E, van der Kouwe A, Gollub R, Kennedy D, Schmitt F, Brown G, MacFall J, Fischl B, Dale A. Reliability in multi-site structural MRI studies: effects of gradient nonlinearity correction on phantom and human data. Neuroimage 2006; 30: 436-443. – reference: Jiang A, Kennedy DN, Baker JR, Weisskoff RM, Tootell RBH, Woods RP, Benson RR, Kwong KK, Brady TJ, Rosen BR, Belliveau JW. Motion detection and correction in functional MR imaging. Hum Brain Mapp 1995; 3: 224-235. – reference: Liu J, Drangova M. Rapid six-degree-of-freedom motion detection using prerotated baseline spherical navigator echoes. Magn Reson Med 2010; 65: 506-514. – reference: Han X, Jovicich J, Salat D, van der Kouwe A, Quinn B, Czanner S, Busa E, Pacheco J, Albert M, Killiany R, Maguire P, Rosas D, Makris N, Dale A, Dickerson B, Fischl B. Reliability of MRI-derived measurements of human cerebral cortical thickness: The effects of field strength, scanner upgrade, and manufacturer. Neuroimage 2006; 32: 180-194. – reference: Welch EB, Manduca A, Grimm RC, Ward HA, Jack CR. Spherical navigator echoes for full 3d rigid body motion measurement in MRI. Magn Reson Med 2002; 47: 32-41. – reference: Ooi MB, Krueger S, Thomas WJ, Swaminathan SV, Brown TR. Prospective real-time correction for arbitrary head motion using active markers. Magn Reson Med 2009; 62: 943-954. – reference: Fischl B, Salat DH, Busa E, Albert M, Dieterich M, Haselgrove C, van der Kouwe A, Killiany R, Kennedy D, Klaveness S, Montillo A, Makris N, Rosen B, Dale AM. Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain. Neuron 2002; 33: 341-355. – reference: Brown TT, Kuperman JM, Erhart M, White NS, Roddey JC, Shankaranarayanan A, Han ET, Rettmann D, Dale AM. 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| Snippet | We introduce a novel method of prospectively compensating for subject motion in neuroanatomical imaging. Short three‐dimensional echo‐planar imaging volumetric... We introduce a novel method of prospectively compensating for subject motion in neuroanatomical imaging. Short three-dimensional echo-planar imaging volumetric... We introduce a novel method of prospectively compensating for subject motion in neuroanatomical imaging. Short 3D EPI volumetric navigators (vNavs) are... |
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| SubjectTerms | Algorithms Brain - anatomy & histology brain morphometry Humans Image Enhancement - methods Image Interpretation, Computer-Assisted - methods Imaging, Three-Dimensional - methods Magnetic Resonance Imaging - methods Motion navigator Neuroradiography - methods Pattern Recognition, Automated - methods prospective motion correction Reproducibility of Results Sensitivity and Specificity validation |
| Title | Volumetric navigators for prospective motion correction and selective reacquisition in neuroanatomical MRI |
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