Joseph R Guy1, Pascal Sati2, Emily Leibovitch3, Steven Jacobson4, Afonso C Silva5, Daniel S Reich6. 1. Division of Neuroimmunology and Neurovirology, National Institute of Neurologic Disorders and Stroke, 10 Center Drive MSC 1400, Building 10 Room 5C103, Bethesda, MD 20892, United States. Electronic address: joseph.guy@nih.gov. 2. Division of Neuroimmunology and Neurovirology, National Institute of Neurologic Disorders and Stroke, 10 Center Drive MSC 1400, Building 10 Room 5C103, Bethesda, MD 20892, United States. Electronic address: pascal.sati@nih.gov. 3. Division of Neuroimmunology and Neurovirology, National Institute of Neurologic Disorders and Stroke, 10 Center Drive MSC 1400, Building 10 Room 5C103, Bethesda, MD 20892, United States. Electronic address: leibovitchel@ninds.nih.gov. 4. Division of Neuroimmunology and Neurovirology, National Institute of Neurologic Disorders and Stroke, 10 Center Drive MSC 1400, Building 10 Room 5C103, Bethesda, MD 20892, United States. Electronic address: JacobsonS@ninds.nih.gov. 5. Laboratory of Functional and Molecular Imaging, National Institute of Neurologic Disorders and Stroke, 49 Convent Drive MSC 1065 Building 49 Room 3A72, Bethesda, MD 20892, United States. Electronic address: SilvaA@ninds.nih.gov. 6. Division of Neuroimmunology and Neurovirology, National Institute of Neurologic Disorders and Stroke, 10 Center Drive MSC 1400, Building 10 Room 5C103, Bethesda, MD 20892, United States. Electronic address: reichds@ninds.nih.gov.
Abstract
BACKGROUND: MRI has the advantage of sampling large areas of tissue and locating areas of interest in 3D space in both living and ex vivo systems, whereas histology has the ability to examine thin slices of ex vivo tissue with high detail and specificity. Although both are valuable tools, it is currently difficult to make high-precision comparisons between MRI and histology due to large differences inherent to the techniques. A method combining the advantages would be an asset to understanding the pathological correlates of MRI. NEW METHOD: 3D-printed brain holders were used to maintain marmoset brains in the same orientation during acquisition of ex vivo MRI and pathologic cutting of the tissue. RESULTS: The results of maintaining this same orientation show that sub-millimeter, discrete neuropathological features in marmoset brain consistently share size, shape, and location between histology and ex vivo MRI, which facilitates comparison with serial imaging acquired in vivo. COMPARISON WITH EXISTING METHODS: Existing methods use computational approaches sensitive to data input in order to warp histologic images to match large-scale features on MRI, but the new method requires no warping of images, due to a preregistration accomplished in the technique, and is insensitive to data formatting and artifacts in both MRI and histology. CONCLUSIONS: The simple method of using 3D-printed brain holders to match brain orientation during pathologic sectioning and MRI acquisition enables rapid and precise comparison of small features seen on MRI to their underlying histology. Published by Elsevier B.V.
BACKGROUND: MRI has the advantage of sampling large areas of tissue and locating areas of interest in 3D space in both living and ex vivo systems, whereas histology has the ability to examine thin slices of ex vivo tissue with high detail and specificity. Although both are valuable tools, it is currently difficult to make high-precision comparisons between MRI and histology due to large differences inherent to the techniques. A method combining the advantages would be an asset to understanding the pathological correlates of MRI. NEW METHOD: 3D-printed brain holders were used to maintain marmoset brains in the same orientation during acquisition of ex vivo MRI and pathologic cutting of the tissue. RESULTS: The results of maintaining this same orientation show that sub-millimeter, discrete neuropathological features in marmoset brain consistently share size, shape, and location between histology and ex vivo MRI, which facilitates comparison with serial imaging acquired in vivo. COMPARISON WITH EXISTING METHODS: Existing methods use computational approaches sensitive to data input in order to warp histologic images to match large-scale features on MRI, but the new method requires no warping of images, due to a preregistration accomplished in the technique, and is insensitive to data formatting and artifacts in both MRI and histology. CONCLUSIONS: The simple method of using 3D-printed brain holders to match brain orientation during pathologic sectioning and MRI acquisition enables rapid and precise comparison of small features seen on MRI to their underlying histology. Published by Elsevier B.V.
Entities:
Keywords:
3D printing; EAE; Ex vivo; Histology; MRI; Marmoset
Authors: Pascal Sati; Afonso C Silva; Peter van Gelderen; Maria I Gaitan; Jillian E Wohler; Steven Jacobson; Jeff H Duyn; Daniel S Reich Journal: Neuroimage Date: 2011-08-27 Impact factor: 6.556
Authors: B A Hart; J Bauer; H J Muller; B Melchers; K Nicolay; H Brok; R E Bontrop; H Lassmann; L Massacesi Journal: Am J Pathol Date: 1998-08 Impact factor: 4.307
Authors: Martina Absinta; Govind Nair; Massimo Filippi; Abhik Ray-Chaudhury; Maria I Reyes-Mantilla; Carlos A Pardo; Daniel S Reich Journal: J Neuropathol Exp Neurol Date: 2014-08 Impact factor: 3.685
Authors: Emily Leibovitch; Jillian E Wohler; Sheila M Cummings Macri; Kelsey Motanic; Erin Harberts; María I Gaitán; Pietro Maggi; Mary Ellis; Susan Westmoreland; Afonso Silva; Daniel S Reich; Steven Jacobson Journal: PLoS Pathog Date: 2013-01-31 Impact factor: 6.823
Authors: Martina Absinta; Govind Nair; Maria Chiara G Monaco; Dragan Maric; Nathanael J Lee; Seung-Kwon Ha; Nicholas J Luciano; Pascal Sati; Steven Jacobson; Daniel S Reich Journal: Ann Neurol Date: 2019-03-30 Impact factor: 10.422
Authors: Nathanael J Lee; Seung-Kwon Ha; Pascal Sati; Martina Absinta; Nicholas J Luciano; Jennifer A Lefeuvre; Matthew K Schindler; Emily C Leibovitch; Jae Kyu Ryu; Mark A Petersen; Afonso C Silva; Steven Jacobson; Katerina Akassoglou; Daniel S Reich Journal: Brain Date: 2018-06-01 Impact factor: 13.501
Authors: Nathanael J Lee; Seung-Kwon Ha; Pascal Sati; Martina Absinta; Govind Nair; Nicholas J Luciano; Emily C Leibovitch; Cecil C Yen; Tracey A Rouault; Afonso C Silva; Steven Jacobson; Daniel S Reich Journal: J Clin Invest Date: 2019-10-01 Impact factor: 14.808
Authors: Maxime Donadieu; Hannah Kelly; Diego Szczupak; Jing-Ping Lin; Yeajin Song; Cecil C C Yen; Frank Q Ye; Hadar Kolb; Joseph R Guy; Erin S Beck; Steven Jacobson; Afonso C Silva; Pascal Sati; Daniel S Reich Journal: Cereb Cortex Date: 2021-01-01 Impact factor: 5.357
Authors: Nicholas J Luciano; Pascal Sati; Govind Nair; Joseph R Guy; Seung-Kwon Ha; Martina Absinta; Wen-Yang Chiang; Emily C Leibovitch; Steven Jacobson; Afonso C Silva; Daniel S Reich Journal: J Vis Exp Date: 2016-12-06 Impact factor: 1.355
Authors: Piotr Majka; Tristan A Chaplin; Hsin-Hao Yu; Alexander Tolpygo; Partha P Mitra; Daniel K Wójcik; Marcello G P Rosa Journal: J Comp Neurol Date: 2016-08-01 Impact factor: 3.215
Authors: Martina Absinta; Seung-Kwon Ha; Govind Nair; Pascal Sati; Nicholas J Luciano; Maryknoll Palisoc; Antoine Louveau; Kareem A Zaghloul; Stefania Pittaluga; Jonathan Kipnis; Daniel S Reich Journal: Elife Date: 2017-10-03 Impact factor: 8.140
Authors: Darío R Quiñones; Jorge Ferragud-Agulló; Ricardo Pérez-Feito; Juan A García-Manrique; Santiago Canals; David Moratal Journal: Materials (Basel) Date: 2018-08-25 Impact factor: 3.623