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Increased sensitivity and signal-to-noise ratio in diffusion-weighted MRI using multi-echo acquisitions
•Novel acquisition and reconstruction strategy to increase the signal to noise ratio (SNR) and contrast of diffusion MRI.•Statistical data modelling for image reconstruction with reduced noise bias.•Substantial SNR gain for only moderate increase in acquisition time. Post-mortem diffusion MRI (dMRI)...
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Published in: | NeuroImage (Orlando, Fla.) Fla.), 2020-11, Vol.221, p.117172-117172, Article 117172 |
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creator | Eichner, Cornelius Paquette, Michael Mildner, Toralf Schlumm, Torsten Pléh, Kamilla Samuni, Liran Crockford, Catherine Wittig, Roman M. Jäger, Carsten Möller, Harald E. Friederici, Angela D. Anwander, Alfred |
description | •Novel acquisition and reconstruction strategy to increase the signal to noise ratio (SNR) and contrast of diffusion MRI.•Statistical data modelling for image reconstruction with reduced noise bias.•Substantial SNR gain for only moderate increase in acquisition time.
Post-mortem diffusion MRI (dMRI) enables acquisitions of structural imaging data with otherwise unreachable resolutions - at the expense of longer scanning times. These data are typically acquired using highly segmented image acquisition strategies, thereby resulting in an incomplete signal decay before the MRI encoding continues. Especially in dMRI, with low signal intensities and lengthy contrast encoding, such temporal inefficiency translates into reduced image quality and longer scanning times. This study introduces Multi Echo (ME) acquisitions to dMRI on a human MRI system - a time-efficient approach, which increases SNR (Signal-to-Noise Ratio) and reduces noise bias for dMRI images. The benefit of the introduced ME-dMRI method was validated using numerical Monte Carlo simulations and showcased on a post-mortem brain of a wild chimpanzee. The proposed Maximum Likelihood Estimation echo combination results in an optimal SNR without detectable signal bias. The combined strategy comes at a small price in scanning time (here 30% additional) and leads to a substantial SNR increase (here white matter: ~ 1.6x, equivalent to 2.6 averages, grey matter: ~ 1.9x, equivalent to 3.6 averages) and a general reduction of the noise bias. |
doi_str_mv | 10.1016/j.neuroimage.2020.117172 |
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Post-mortem diffusion MRI (dMRI) enables acquisitions of structural imaging data with otherwise unreachable resolutions - at the expense of longer scanning times. These data are typically acquired using highly segmented image acquisition strategies, thereby resulting in an incomplete signal decay before the MRI encoding continues. Especially in dMRI, with low signal intensities and lengthy contrast encoding, such temporal inefficiency translates into reduced image quality and longer scanning times. This study introduces Multi Echo (ME) acquisitions to dMRI on a human MRI system - a time-efficient approach, which increases SNR (Signal-to-Noise Ratio) and reduces noise bias for dMRI images. The benefit of the introduced ME-dMRI method was validated using numerical Monte Carlo simulations and showcased on a post-mortem brain of a wild chimpanzee. The proposed Maximum Likelihood Estimation echo combination results in an optimal SNR without detectable signal bias. The combined strategy comes at a small price in scanning time (here 30% additional) and leads to a substantial SNR increase (here white matter: ~ 1.6x, equivalent to 2.6 averages, grey matter: ~ 1.9x, equivalent to 3.6 averages) and a general reduction of the noise bias.</description><identifier>ISSN: 1053-8119</identifier><identifier>EISSN: 1095-9572</identifier><identifier>DOI: 10.1016/j.neuroimage.2020.117172</identifier><identifier>PMID: 32682095</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Animals ; Autopsy ; Bias ; Bioengineering ; Chimpanzee ; Computer Simulation ; Diffusion ; Diffusion Magnetic Resonance Imaging - methods ; Diffusion Magnetic Resonance Imaging - standards ; dMRI ; Echo-Planar Imaging - methods ; Echo-Planar Imaging - standards ; Female ; Gray Matter - diagnostic imaging ; Humans ; Image Processing, Computer-Assisted - methods ; Image Processing, Computer-Assisted - standards ; Imaging ; Life Sciences ; Magnetic resonance imaging ; Monte Carlo Method ; MRI ; Multi-echo ; Neuroimaging ; Neuroimaging - methods ; Neuroimaging - standards ; Neurons and Cognition ; Neurosciences ; Noise ; Noise reduction ; Normal distribution ; Pan troglodytes ; Post-mortem ; Relaxometry ; Reproducibility of Results ; Scanning ; Segmented EPI ; Signal to noise ratio ; SNR ; Standard deviation ; Substantia alba ; Substantia grisea ; White Matter - diagnostic imaging</subject><ispartof>NeuroImage (Orlando, Fla.), 2020-11, Vol.221, p.117172-117172, Article 117172</ispartof><rights>2020</rights><rights>Copyright © 2020. Published by Elsevier Inc.</rights><rights>Copyright Elsevier Limited Nov 1, 2020</rights><rights>Distributed under a Creative Commons Attribution 4.0 International License</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c552t-e7f24d85c9d8c97151044385d425f23f0baf3ab84aa760919eab2e54d0dd571a3</citedby><cites>FETCH-LOGICAL-c552t-e7f24d85c9d8c97151044385d425f23f0baf3ab84aa760919eab2e54d0dd571a3</cites><orcidid>0000-0001-6597-5106 ; 0000-0002-5659-1925 ; 0000-0001-9163-1083 ; 0000-0002-4861-4808 ; 0000-0002-2528-5482 ; 0000-0001-6490-4031 ; 0000-0001-7957-6050 ; 0000-0002-8917-3391</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,780,784,885,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32682095$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink><backlink>$$Uhttps://hal.science/hal-03455941$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Eichner, Cornelius</creatorcontrib><creatorcontrib>Paquette, Michael</creatorcontrib><creatorcontrib>Mildner, Toralf</creatorcontrib><creatorcontrib>Schlumm, Torsten</creatorcontrib><creatorcontrib>Pléh, Kamilla</creatorcontrib><creatorcontrib>Samuni, Liran</creatorcontrib><creatorcontrib>Crockford, Catherine</creatorcontrib><creatorcontrib>Wittig, Roman M.</creatorcontrib><creatorcontrib>Jäger, Carsten</creatorcontrib><creatorcontrib>Möller, Harald E.</creatorcontrib><creatorcontrib>Friederici, Angela D.</creatorcontrib><creatorcontrib>Anwander, Alfred</creatorcontrib><title>Increased sensitivity and signal-to-noise ratio in diffusion-weighted MRI using multi-echo acquisitions</title><title>NeuroImage (Orlando, Fla.)</title><addtitle>Neuroimage</addtitle><description>•Novel acquisition and reconstruction strategy to increase the signal to noise ratio (SNR) and contrast of diffusion MRI.•Statistical data modelling for image reconstruction with reduced noise bias.•Substantial SNR gain for only moderate increase in acquisition time.
Post-mortem diffusion MRI (dMRI) enables acquisitions of structural imaging data with otherwise unreachable resolutions - at the expense of longer scanning times. These data are typically acquired using highly segmented image acquisition strategies, thereby resulting in an incomplete signal decay before the MRI encoding continues. Especially in dMRI, with low signal intensities and lengthy contrast encoding, such temporal inefficiency translates into reduced image quality and longer scanning times. This study introduces Multi Echo (ME) acquisitions to dMRI on a human MRI system - a time-efficient approach, which increases SNR (Signal-to-Noise Ratio) and reduces noise bias for dMRI images. The benefit of the introduced ME-dMRI method was validated using numerical Monte Carlo simulations and showcased on a post-mortem brain of a wild chimpanzee. The proposed Maximum Likelihood Estimation echo combination results in an optimal SNR without detectable signal bias. The combined strategy comes at a small price in scanning time (here 30% additional) and leads to a substantial SNR increase (here white matter: ~ 1.6x, equivalent to 2.6 averages, grey matter: ~ 1.9x, equivalent to 3.6 averages) and a general reduction of the noise bias.</description><subject>Animals</subject><subject>Autopsy</subject><subject>Bias</subject><subject>Bioengineering</subject><subject>Chimpanzee</subject><subject>Computer Simulation</subject><subject>Diffusion</subject><subject>Diffusion Magnetic Resonance Imaging - methods</subject><subject>Diffusion Magnetic Resonance Imaging - standards</subject><subject>dMRI</subject><subject>Echo-Planar Imaging - methods</subject><subject>Echo-Planar Imaging - standards</subject><subject>Female</subject><subject>Gray Matter - diagnostic imaging</subject><subject>Humans</subject><subject>Image Processing, Computer-Assisted - methods</subject><subject>Image Processing, Computer-Assisted - standards</subject><subject>Imaging</subject><subject>Life Sciences</subject><subject>Magnetic resonance imaging</subject><subject>Monte Carlo Method</subject><subject>MRI</subject><subject>Multi-echo</subject><subject>Neuroimaging</subject><subject>Neuroimaging - 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methods</topic><topic>Diffusion Magnetic Resonance Imaging - standards</topic><topic>dMRI</topic><topic>Echo-Planar Imaging - methods</topic><topic>Echo-Planar Imaging - standards</topic><topic>Female</topic><topic>Gray Matter - diagnostic imaging</topic><topic>Humans</topic><topic>Image Processing, Computer-Assisted - methods</topic><topic>Image Processing, Computer-Assisted - standards</topic><topic>Imaging</topic><topic>Life Sciences</topic><topic>Magnetic resonance imaging</topic><topic>Monte Carlo Method</topic><topic>MRI</topic><topic>Multi-echo</topic><topic>Neuroimaging</topic><topic>Neuroimaging - methods</topic><topic>Neuroimaging - standards</topic><topic>Neurons and Cognition</topic><topic>Neurosciences</topic><topic>Noise</topic><topic>Noise reduction</topic><topic>Normal distribution</topic><topic>Pan troglodytes</topic><topic>Post-mortem</topic><topic>Relaxometry</topic><topic>Reproducibility of Results</topic><topic>Scanning</topic><topic>Segmented EPI</topic><topic>Signal to noise ratio</topic><topic>SNR</topic><topic>Standard deviation</topic><topic>Substantia alba</topic><topic>Substantia grisea</topic><topic>White Matter - 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Post-mortem diffusion MRI (dMRI) enables acquisitions of structural imaging data with otherwise unreachable resolutions - at the expense of longer scanning times. These data are typically acquired using highly segmented image acquisition strategies, thereby resulting in an incomplete signal decay before the MRI encoding continues. Especially in dMRI, with low signal intensities and lengthy contrast encoding, such temporal inefficiency translates into reduced image quality and longer scanning times. This study introduces Multi Echo (ME) acquisitions to dMRI on a human MRI system - a time-efficient approach, which increases SNR (Signal-to-Noise Ratio) and reduces noise bias for dMRI images. The benefit of the introduced ME-dMRI method was validated using numerical Monte Carlo simulations and showcased on a post-mortem brain of a wild chimpanzee. The proposed Maximum Likelihood Estimation echo combination results in an optimal SNR without detectable signal bias. The combined strategy comes at a small price in scanning time (here 30% additional) and leads to a substantial SNR increase (here white matter: ~ 1.6x, equivalent to 2.6 averages, grey matter: ~ 1.9x, equivalent to 3.6 averages) and a general reduction of the noise bias.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>32682095</pmid><doi>10.1016/j.neuroimage.2020.117172</doi><tpages>1</tpages><orcidid>https://orcid.org/0000-0001-6597-5106</orcidid><orcidid>https://orcid.org/0000-0002-5659-1925</orcidid><orcidid>https://orcid.org/0000-0001-9163-1083</orcidid><orcidid>https://orcid.org/0000-0002-4861-4808</orcidid><orcidid>https://orcid.org/0000-0002-2528-5482</orcidid><orcidid>https://orcid.org/0000-0001-6490-4031</orcidid><orcidid>https://orcid.org/0000-0001-7957-6050</orcidid><orcidid>https://orcid.org/0000-0002-8917-3391</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Animals Autopsy Bias Bioengineering Chimpanzee Computer Simulation Diffusion Diffusion Magnetic Resonance Imaging - methods Diffusion Magnetic Resonance Imaging - standards dMRI Echo-Planar Imaging - methods Echo-Planar Imaging - standards Female Gray Matter - diagnostic imaging Humans Image Processing, Computer-Assisted - methods Image Processing, Computer-Assisted - standards Imaging Life Sciences Magnetic resonance imaging Monte Carlo Method MRI Multi-echo Neuroimaging Neuroimaging - methods Neuroimaging - standards Neurons and Cognition Neurosciences Noise Noise reduction Normal distribution Pan troglodytes Post-mortem Relaxometry Reproducibility of Results Scanning Segmented EPI Signal to noise ratio SNR Standard deviation Substantia alba Substantia grisea White Matter - diagnostic imaging |
title | Increased sensitivity and signal-to-noise ratio in diffusion-weighted MRI using multi-echo acquisitions |
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