_version_ 1866913574136315904
author Schilling, Kurt G
Howard, Amy FD
Grussu, Francesco
Ianus, Andrada
Hansen, Brian
Barrett, Rachel L C
Aggarwal, Manisha
Michielse, Stijn
Nasrallah, Fatima
Syeda, Warda
Wang, Nian
Veraart, Jelle
Roebroeck, Alard
Bagdasarian, Andrew F
Eichner, Cornelius
Sepehrband, Farshid
Zimmermann, Jan
Soustelle, Lucas
Bowman, Christien
Tendler, Benjamin C
Hertanu, Andreea
Jeurissen, Ben
Verhoye, Marleen
Frydman, Lucio
van de Looij, Yohan
Hike, David
Dunn, Jeff F
Miller, Karla
Landman, Bennett A
Shemesh, Noam
Anderson, Adam
McKinnon, Emilie
Farquharson, Shawna
Acqua, Flavio Dell'
Pierpaoli, Carlo
Drobnjak, Ivana
Leemans, Alexander
Harkins, Kevin D
Descoteaux, Maxime
Xu, Duan
Huang, Hao
Santin, Mathieu D
Grant, Samuel C.
Obenaus, Andre
Kim, Gene S
Wu, Dan
Bihan, Denis Le
Blackband, Stephen J
Ciobanu, Luisa
Fieremans, Els
Bai, Ruiliang
Leergaard, Trygve B
Zhang, Jiangyang
Dyrby, Tim B
Johnson, G Allan
Cohen-Adad, Julien
Budde, Matthew D
Jelescu, Ileana O
author_facet Schilling, Kurt G
Howard, Amy FD
Grussu, Francesco
Ianus, Andrada
Hansen, Brian
Barrett, Rachel L C
Aggarwal, Manisha
Michielse, Stijn
Nasrallah, Fatima
Syeda, Warda
Wang, Nian
Veraart, Jelle
Roebroeck, Alard
Bagdasarian, Andrew F
Eichner, Cornelius
Sepehrband, Farshid
Zimmermann, Jan
Soustelle, Lucas
Bowman, Christien
Tendler, Benjamin C
Hertanu, Andreea
Jeurissen, Ben
Verhoye, Marleen
Frydman, Lucio
van de Looij, Yohan
Hike, David
Dunn, Jeff F
Miller, Karla
Landman, Bennett A
Shemesh, Noam
Anderson, Adam
McKinnon, Emilie
Farquharson, Shawna
Acqua, Flavio Dell'
Pierpaoli, Carlo
Drobnjak, Ivana
Leemans, Alexander
Harkins, Kevin D
Descoteaux, Maxime
Xu, Duan
Huang, Hao
Santin, Mathieu D
Grant, Samuel C.
Obenaus, Andre
Kim, Gene S
Wu, Dan
Bihan, Denis Le
Blackband, Stephen J
Ciobanu, Luisa
Fieremans, Els
Bai, Ruiliang
Leergaard, Trygve B
Zhang, Jiangyang
Dyrby, Tim B
Johnson, G Allan
Cohen-Adad, Julien
Budde, Matthew D
Jelescu, Ileana O
contents Preclinical diffusion MRI (dMRI) has proven value in methods development and validation, characterizing the biological basis of diffusion phenomena, and comparative anatomy. While dMRI enables in vivo non-invasive characterization of tissue, ex vivo dMRI is increasingly being used to probe tissue microstructure and brain connectivity. Ex vivo dMRI has several experimental advantages that facilitate high spatial resolution and high signal-to-noise ratio (SNR) images, cutting-edge diffusion contrasts, and direct comparison with histological data as a methodological validation. However, there are a number of considerations that must be made when performing ex vivo experiments. The steps from tissue preparation, image acquisition and processing, and interpretation of results are complex, with many decisions that not only differ dramatically from in vivo imaging of small animals, but ultimately affect what questions can be answered using the data. This work concludes a 3-part series of recommendations and considerations for preclinical dMRI. Herein, we describe best practices for dMRI of ex vivo tissue, with a focus on image pre-processing, data processing and model fitting, and tractography. In each section, we attempt to provide guidelines and recommendations, but also highlight areas for which no guidelines exist (and why), and where future work should lie. We end by providing guidelines on code sharing and data sharing, and point towards open-source software and databases specific to small animal and ex vivo imaging.
format Preprint
id arxiv_https___arxiv_org_abs_2411_05021
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Considerations and recommendations from the ISMRM Diffusion Study Group for preclinical diffusion MRI: Part 3 -- Ex vivo imaging: data processing, comparisons with microscopy, and tractography
Schilling, Kurt G
Howard, Amy FD
Grussu, Francesco
Ianus, Andrada
Hansen, Brian
Barrett, Rachel L C
Aggarwal, Manisha
Michielse, Stijn
Nasrallah, Fatima
Syeda, Warda
Wang, Nian
Veraart, Jelle
Roebroeck, Alard
Bagdasarian, Andrew F
Eichner, Cornelius
Sepehrband, Farshid
Zimmermann, Jan
Soustelle, Lucas
Bowman, Christien
Tendler, Benjamin C
Hertanu, Andreea
Jeurissen, Ben
Verhoye, Marleen
Frydman, Lucio
van de Looij, Yohan
Hike, David
Dunn, Jeff F
Miller, Karla
Landman, Bennett A
Shemesh, Noam
Anderson, Adam
McKinnon, Emilie
Farquharson, Shawna
Acqua, Flavio Dell'
Pierpaoli, Carlo
Drobnjak, Ivana
Leemans, Alexander
Harkins, Kevin D
Descoteaux, Maxime
Xu, Duan
Huang, Hao
Santin, Mathieu D
Grant, Samuel C.
Obenaus, Andre
Kim, Gene S
Wu, Dan
Bihan, Denis Le
Blackband, Stephen J
Ciobanu, Luisa
Fieremans, Els
Bai, Ruiliang
Leergaard, Trygve B
Zhang, Jiangyang
Dyrby, Tim B
Johnson, G Allan
Cohen-Adad, Julien
Budde, Matthew D
Jelescu, Ileana O
Medical Physics
Preclinical diffusion MRI (dMRI) has proven value in methods development and validation, characterizing the biological basis of diffusion phenomena, and comparative anatomy. While dMRI enables in vivo non-invasive characterization of tissue, ex vivo dMRI is increasingly being used to probe tissue microstructure and brain connectivity. Ex vivo dMRI has several experimental advantages that facilitate high spatial resolution and high signal-to-noise ratio (SNR) images, cutting-edge diffusion contrasts, and direct comparison with histological data as a methodological validation. However, there are a number of considerations that must be made when performing ex vivo experiments. The steps from tissue preparation, image acquisition and processing, and interpretation of results are complex, with many decisions that not only differ dramatically from in vivo imaging of small animals, but ultimately affect what questions can be answered using the data. This work concludes a 3-part series of recommendations and considerations for preclinical dMRI. Herein, we describe best practices for dMRI of ex vivo tissue, with a focus on image pre-processing, data processing and model fitting, and tractography. In each section, we attempt to provide guidelines and recommendations, but also highlight areas for which no guidelines exist (and why), and where future work should lie. We end by providing guidelines on code sharing and data sharing, and point towards open-source software and databases specific to small animal and ex vivo imaging.
title Considerations and recommendations from the ISMRM Diffusion Study Group for preclinical diffusion MRI: Part 3 -- Ex vivo imaging: data processing, comparisons with microscopy, and tractography
topic Medical Physics
url https://arxiv.org/abs/2411.05021