Quantifying White Matter Hyperintensity and Brain Volumes in Heterogeneous Clinical and Low-Field Portable MRI

Pablo Laso; Stefano Cerri; Annabel Sorby-Adams; Jennifer Guo; Farrah Mateen; Philipp Goebl; Jiaming Wu; Peirong Liu; Hongwei Bran Li; Sean I. Young; Benjamin Billot; Oula Puonti; Gordon Sze; Sam Payabavash; Adam DeHavenon; Kevin N. Sheth; Matthew S. Rosen; John Kirsch; Nicola Strisciuglio; Jelmer M. Wolterink; Arman Eshaghi; Frederik Barkhof; W. Taylor Kimberly; Juan Eugenio Iglesias

doi:10.1109/ISBI56570.2024.10635502

Quantifying White Matter Hyperintensity and Brain Volumes in Heterogeneous Clinical and Low-Field Portable MRI

Pablo Laso, Stefano Cerri, Annabel Sorby-Adams, Jennifer Guo, Farrah Mateen, Philipp Goebl, Jiaming Wu, Peirong Liu, Hongwei Bran Li, Sean I. Young, Benjamin Billot, Oula Puonti, Gordon Sze, Sam Payabavash, Adam DeHavenon, Kevin N. Sheth, Matthew S. Rosen, John Kirsch, Nicola Strisciuglio, Jelmer M. WolterinkArman Eshaghi, Frederik Barkhof, W. Taylor Kimberly, Juan Eugenio Iglesias

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

4 Citations (Scopus)

17 Downloads (Pure)

Abstract

Brain atrophy and white matter hyperintensity (WMH) are critical neuroimaging features for ascertaining brain injury in cerebrovascular disease and multiple sclerosis. Automated segmentation and quantification is desirable but existing methods require high-resolution MRI with good signal-to-noise ratio (SNR). This precludes application to clinical and low-field portable MRI (pMRI) scans, thus hampering large-scale tracking of atrophy and WMH progression, especially in underserved areas where pMRI has huge potential. Here we present a method that segments white matter hyperintensity and 36 brain regions from scans of any resolution and contrast (including pMRI) without retraining. We show results on eight public datasets and on a private dataset with paired high- and low-field scans (3T and 64mT), where we attain strong correlation between the WMH (ρ=.85) and hippocampal volumes (ρ=.89) estimated at both fields. Our method is publicly available as part of FreeSurfer, at: http://surfer.nmr.mgh.harvard.edu/fswiki/WMH-SynthSeg.

Original language	English
Title of host publication	2024 IEEE International Symposium on Biomedical Imaging (ISBI)
Subtitle of host publication	27-30 May, 2024 - Athens, Greece, Megaron Athens International Conference Centre
Publisher	IEEE
Pages	1-5
Number of pages	5
ISBN (Electronic)	979-8-3503-1333-8
ISBN (Print)	979-8-3503-1334-5
DOIs	https://doi.org/10.1109/ISBI56570.2024.10635502
Publication status	Published - 22 Aug 2024
Event	21st IEEE International Symposium on Biomedical Imaging, ISBI 2024 - Athens, Greece Duration: 27 May 2024 → 30 May 2024 Conference number: 21

Conference

Conference	21st IEEE International Symposium on Biomedical Imaging, ISBI 2024
Abbreviated title	ISBI 2024
Country/Territory	Greece
City	Athens
Period	27/05/24 → 30/05/24

Keywords

2024 OA procedure
Neuroimaging
Image segmentation
Multiple sclerosis
Image resolution
Magnetic resonance imaging
White matter
Atrophy

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1109/ISBI56570.2024.10635502

Quantifying_White_Matter_Hyperintensity_and_Brain_Volumes_in_Heterogeneous_Clinical_and_Low-Field_Portable_MRIFinal published version, 3.04 MBLicence: Taverne

Cite this

Laso, P., Cerri, S., Sorby-Adams, A., Guo, J., Mateen, F., Goebl, P., Wu, J., Liu, P., Li, H. B., Young, S. I., Billot, B., Puonti, O., Sze, G., Payabavash, S., DeHavenon, A., Sheth, K. N., Rosen, M. S., Kirsch, J., Strisciuglio, N., ... Iglesias, J. E. (2024). Quantifying White Matter Hyperintensity and Brain Volumes in Heterogeneous Clinical and Low-Field Portable MRI. In 2024 IEEE International Symposium on Biomedical Imaging (ISBI): 27-30 May, 2024 - Athens, Greece, Megaron Athens International Conference Centre (pp. 1-5). Article 10635502 IEEE. https://doi.org/10.1109/ISBI56570.2024.10635502

@inproceedings{4459cb5b03ce4c948d9c5291872ccfcb,

title = "Quantifying White Matter Hyperintensity and Brain Volumes in Heterogeneous Clinical and Low-Field Portable MRI",

abstract = "Brain atrophy and white matter hyperintensity (WMH) are critical neuroimaging features for ascertaining brain injury in cerebrovascular disease and multiple sclerosis. Automated segmentation and quantification is desirable but existing methods require high-resolution MRI with good signal-to-noise ratio (SNR). This precludes application to clinical and low-field portable MRI (pMRI) scans, thus hampering large-scale tracking of atrophy and WMH progression, especially in underserved areas where pMRI has huge potential. Here we present a method that segments white matter hyperintensity and 36 brain regions from scans of any resolution and contrast (including pMRI) without retraining. We show results on eight public datasets and on a private dataset with paired high- and low-field scans (3T and 64mT), where we attain strong correlation between the WMH (ρ=.85) and hippocampal volumes (ρ=.89) estimated at both fields. Our method is publicly available as part of FreeSurfer, at: http://surfer.nmr.mgh.harvard.edu/fswiki/WMH-SynthSeg.",

keywords = "2024 OA procedure, Neuroimaging, Image segmentation, Multiple sclerosis, Image resolution, Magnetic resonance imaging, White matter, Atrophy",

author = "Pablo Laso and Stefano Cerri and Annabel Sorby-Adams and Jennifer Guo and Farrah Mateen and Philipp Goebl and Jiaming Wu and Peirong Liu and Li, {Hongwei Bran} and Young, {Sean I.} and Benjamin Billot and Oula Puonti and Gordon Sze and Sam Payabavash and Adam DeHavenon and Sheth, {Kevin N.} and Rosen, {Matthew S.} and John Kirsch and Nicola Strisciuglio and Wolterink, {Jelmer M.} and Arman Eshaghi and Frederik Barkhof and Kimberly, {W. Taylor} and Iglesias, {Juan Eugenio}",

note = "Publisher Copyright: {\textcopyright} 2024 IEEE.; 21st IEEE International Symposium on Biomedical Imaging, ISBI 2024, ISBI 2024 ; Conference date: 27-05-2024 Through 30-05-2024",

year = "2024",

month = aug,

day = "22",

doi = "10.1109/ISBI56570.2024.10635502",

language = "English",

isbn = "979-8-3503-1334-5",

pages = "1--5",

booktitle = "2024 IEEE International Symposium on Biomedical Imaging (ISBI)",

publisher = "IEEE",

address = "United States",

}

Laso, P, Cerri, S, Sorby-Adams, A, Guo, J, Mateen, F, Goebl, P, Wu, J, Liu, P, Li, HB, Young, SI, Billot, B, Puonti, O, Sze, G, Payabavash, S, DeHavenon, A, Sheth, KN, Rosen, MS, Kirsch, J, Strisciuglio, N , Wolterink, JM, Eshaghi, A, Barkhof, F, Kimberly, WT & Iglesias, JE 2024, Quantifying White Matter Hyperintensity and Brain Volumes in Heterogeneous Clinical and Low-Field Portable MRI. in 2024 IEEE International Symposium on Biomedical Imaging (ISBI): 27-30 May, 2024 - Athens, Greece, Megaron Athens International Conference Centre., 10635502, IEEE, pp. 1-5, 21st IEEE International Symposium on Biomedical Imaging, ISBI 2024, Athens, Greece, 27/05/24. https://doi.org/10.1109/ISBI56570.2024.10635502

Quantifying White Matter Hyperintensity and Brain Volumes in Heterogeneous Clinical and Low-Field Portable MRI. / Laso, Pablo; Cerri, Stefano; Sorby-Adams, Annabel et al.
2024 IEEE International Symposium on Biomedical Imaging (ISBI): 27-30 May, 2024 - Athens, Greece, Megaron Athens International Conference Centre. IEEE, 2024. p. 1-5 10635502.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Quantifying White Matter Hyperintensity and Brain Volumes in Heterogeneous Clinical and Low-Field Portable MRI

AU - Laso, Pablo

AU - Cerri, Stefano

AU - Sorby-Adams, Annabel

AU - Guo, Jennifer

AU - Mateen, Farrah

AU - Goebl, Philipp

AU - Wu, Jiaming

AU - Liu, Peirong

AU - Li, Hongwei Bran

AU - Young, Sean I.

AU - Billot, Benjamin

AU - Puonti, Oula

AU - Sze, Gordon

AU - Payabavash, Sam

AU - DeHavenon, Adam

AU - Sheth, Kevin N.

AU - Rosen, Matthew S.

AU - Kirsch, John

AU - Strisciuglio, Nicola

AU - Wolterink, Jelmer M.

AU - Eshaghi, Arman

AU - Barkhof, Frederik

AU - Kimberly, W. Taylor

AU - Iglesias, Juan Eugenio

N1 - Conference code: 21

PY - 2024/8/22

Y1 - 2024/8/22

N2 - Brain atrophy and white matter hyperintensity (WMH) are critical neuroimaging features for ascertaining brain injury in cerebrovascular disease and multiple sclerosis. Automated segmentation and quantification is desirable but existing methods require high-resolution MRI with good signal-to-noise ratio (SNR). This precludes application to clinical and low-field portable MRI (pMRI) scans, thus hampering large-scale tracking of atrophy and WMH progression, especially in underserved areas where pMRI has huge potential. Here we present a method that segments white matter hyperintensity and 36 brain regions from scans of any resolution and contrast (including pMRI) without retraining. We show results on eight public datasets and on a private dataset with paired high- and low-field scans (3T and 64mT), where we attain strong correlation between the WMH (ρ=.85) and hippocampal volumes (ρ=.89) estimated at both fields. Our method is publicly available as part of FreeSurfer, at: http://surfer.nmr.mgh.harvard.edu/fswiki/WMH-SynthSeg.

AB - Brain atrophy and white matter hyperintensity (WMH) are critical neuroimaging features for ascertaining brain injury in cerebrovascular disease and multiple sclerosis. Automated segmentation and quantification is desirable but existing methods require high-resolution MRI with good signal-to-noise ratio (SNR). This precludes application to clinical and low-field portable MRI (pMRI) scans, thus hampering large-scale tracking of atrophy and WMH progression, especially in underserved areas where pMRI has huge potential. Here we present a method that segments white matter hyperintensity and 36 brain regions from scans of any resolution and contrast (including pMRI) without retraining. We show results on eight public datasets and on a private dataset with paired high- and low-field scans (3T and 64mT), where we attain strong correlation between the WMH (ρ=.85) and hippocampal volumes (ρ=.89) estimated at both fields. Our method is publicly available as part of FreeSurfer, at: http://surfer.nmr.mgh.harvard.edu/fswiki/WMH-SynthSeg.

KW - 2024 OA procedure

KW - Neuroimaging

KW - Image segmentation

KW - Multiple sclerosis

KW - Image resolution

KW - Magnetic resonance imaging

KW - White matter

KW - Atrophy

UR - http://www.scopus.com/inward/record.url?scp=85203333196&partnerID=8YFLogxK

U2 - 10.1109/ISBI56570.2024.10635502

DO - 10.1109/ISBI56570.2024.10635502

M3 - Conference contribution

SN - 979-8-3503-1334-5

SP - 1

EP - 5

BT - 2024 IEEE International Symposium on Biomedical Imaging (ISBI)

PB - IEEE

T2 - 21st IEEE International Symposium on Biomedical Imaging, ISBI 2024

Y2 - 27 May 2024 through 30 May 2024

ER -

Laso P, Cerri S, Sorby-Adams A, Guo J, Mateen F, Goebl P et al. Quantifying White Matter Hyperintensity and Brain Volumes in Heterogeneous Clinical and Low-Field Portable MRI. In 2024 IEEE International Symposium on Biomedical Imaging (ISBI): 27-30 May, 2024 - Athens, Greece, Megaron Athens International Conference Centre. IEEE. 2024. p. 1-5. 10635502 doi: 10.1109/ISBI56570.2024.10635502

Quantifying White Matter Hyperintensity and Brain Volumes in Heterogeneous Clinical and Low-Field Portable MRI

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Keywords

UN SDGs

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