In-vivo high-resolution \chi-separation at 7T
A recently introduced quantitative susceptibility mapping (QSM) technique, $\chi$-separation, offers the capability to separate paramagnetic ($\chi_{\text{para}}$) and diamagnetic ($\chi_{\text{dia}}$) susceptibility distribution within the brain. In-vivo high-resolution mapping of iron and myelin d...
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creator | Kim, Jiye Kim, Minjun Ji, Sooyeon Min, Kyeongseon Jeong, Hwihun Shin, Hyeong-Geol Oh, Chungseok Straub, Sina Kim, Seong-Gi Lee, Jongho |
description | A recently introduced quantitative susceptibility mapping (QSM) technique,
$\chi$-separation, offers the capability to separate paramagnetic
($\chi_{\text{para}}$) and diamagnetic ($\chi_{\text{dia}}$) susceptibility
distribution within the brain. In-vivo high-resolution mapping of iron and
myelin distribution, estimated by $\chi$-separation, could provide a deeper
understanding of brain substructures, assisting the investigation of their
functions and alterations. This can be achieved using 7T MRI, which benefits
from a high signal-to-noise ratio and susceptibility effects. However, applying
$\chi$-separation at 7T presents difficulties due to the requirement of an
$R_2$ map, coupled with issues such as high specific absorption rate (SAR),
large $B_1$ transmit field inhomogeneities, and prolonged scan time.
To address these challenges, we developed a novel deep neural network,
R2PRIMEnet7T, designed to convert a 7T $R_2^*$ map into a 3T $R_2'$ map.
Building on this development, we present a new pipeline for $\chi$-separation
at 7T, enabling us to generate high-resolution $\chi$-separation maps from
multi-echo gradient-echo data. The proposed method is compared with alternative
pipelines, such as an end-to-end network and linearly-scaled $R_2'$, and is
validated against $\chi$-separation maps at 3T, demonstrating its accuracy. The
7T $\chi$-separation maps generated by the proposed method exhibit similar
contrasts to those from 3T, while 7T high-resolution maps offer enhanced
clarity and detail. Quantitative analysis confirms that the proposed method
surpasses the alternative pipelines. The proposed method results well delineate
the detailed brain structures associated with iron and myelin. This new
pipeline holds promise for analyzing iron and myelin concentration changes in
various neurodegenerative diseases through precise structural examination. |
doi_str_mv | 10.48550/arxiv.2410.12239 |
format | Article |
fullrecord | <record><control><sourceid>arxiv_GOX</sourceid><recordid>TN_cdi_arxiv_primary_2410_12239</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2410_12239</sourcerecordid><originalsourceid>FETCH-arxiv_primary_2410_122393</originalsourceid><addsrcrecordid>eNpjYJA0NNAzsTA1NdBPLKrILNMzMgEKGBoZGVtyMuh65umWZZblK2RkpmfoFqUW5-eUlmTm5ynEJGdk6hanFiQWJYL5iSUK5iE8DKxpiTnFqbxQmptB3s01xNlDF2xwfEFRZm5iUWU8yIJ4sAXGhFUAAIRsL0U</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>In-vivo high-resolution \chi-separation at 7T</title><source>arXiv.org</source><creator>Kim, Jiye ; Kim, Minjun ; Ji, Sooyeon ; Min, Kyeongseon ; Jeong, Hwihun ; Shin, Hyeong-Geol ; Oh, Chungseok ; Straub, Sina ; Kim, Seong-Gi ; Lee, Jongho</creator><creatorcontrib>Kim, Jiye ; Kim, Minjun ; Ji, Sooyeon ; Min, Kyeongseon ; Jeong, Hwihun ; Shin, Hyeong-Geol ; Oh, Chungseok ; Straub, Sina ; Kim, Seong-Gi ; Lee, Jongho</creatorcontrib><description>A recently introduced quantitative susceptibility mapping (QSM) technique,
$\chi$-separation, offers the capability to separate paramagnetic
($\chi_{\text{para}}$) and diamagnetic ($\chi_{\text{dia}}$) susceptibility
distribution within the brain. In-vivo high-resolution mapping of iron and
myelin distribution, estimated by $\chi$-separation, could provide a deeper
understanding of brain substructures, assisting the investigation of their
functions and alterations. This can be achieved using 7T MRI, which benefits
from a high signal-to-noise ratio and susceptibility effects. However, applying
$\chi$-separation at 7T presents difficulties due to the requirement of an
$R_2$ map, coupled with issues such as high specific absorption rate (SAR),
large $B_1$ transmit field inhomogeneities, and prolonged scan time.
To address these challenges, we developed a novel deep neural network,
R2PRIMEnet7T, designed to convert a 7T $R_2^*$ map into a 3T $R_2'$ map.
Building on this development, we present a new pipeline for $\chi$-separation
at 7T, enabling us to generate high-resolution $\chi$-separation maps from
multi-echo gradient-echo data. The proposed method is compared with alternative
pipelines, such as an end-to-end network and linearly-scaled $R_2'$, and is
validated against $\chi$-separation maps at 3T, demonstrating its accuracy. The
7T $\chi$-separation maps generated by the proposed method exhibit similar
contrasts to those from 3T, while 7T high-resolution maps offer enhanced
clarity and detail. Quantitative analysis confirms that the proposed method
surpasses the alternative pipelines. The proposed method results well delineate
the detailed brain structures associated with iron and myelin. This new
pipeline holds promise for analyzing iron and myelin concentration changes in
various neurodegenerative diseases through precise structural examination.</description><identifier>DOI: 10.48550/arxiv.2410.12239</identifier><language>eng</language><subject>Physics - Medical Physics ; Quantitative Biology - Quantitative Methods</subject><creationdate>2024-10</creationdate><rights>http://arxiv.org/licenses/nonexclusive-distrib/1.0</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>228,230,780,885</link.rule.ids><linktorsrc>$$Uhttps://arxiv.org/abs/2410.12239$$EView_record_in_Cornell_University$$FView_record_in_$$GCornell_University$$Hfree_for_read</linktorsrc><backlink>$$Uhttps://doi.org/10.48550/arXiv.2410.12239$$DView paper in arXiv$$Hfree_for_read</backlink></links><search><creatorcontrib>Kim, Jiye</creatorcontrib><creatorcontrib>Kim, Minjun</creatorcontrib><creatorcontrib>Ji, Sooyeon</creatorcontrib><creatorcontrib>Min, Kyeongseon</creatorcontrib><creatorcontrib>Jeong, Hwihun</creatorcontrib><creatorcontrib>Shin, Hyeong-Geol</creatorcontrib><creatorcontrib>Oh, Chungseok</creatorcontrib><creatorcontrib>Straub, Sina</creatorcontrib><creatorcontrib>Kim, Seong-Gi</creatorcontrib><creatorcontrib>Lee, Jongho</creatorcontrib><title>In-vivo high-resolution \chi-separation at 7T</title><description>A recently introduced quantitative susceptibility mapping (QSM) technique,
$\chi$-separation, offers the capability to separate paramagnetic
($\chi_{\text{para}}$) and diamagnetic ($\chi_{\text{dia}}$) susceptibility
distribution within the brain. In-vivo high-resolution mapping of iron and
myelin distribution, estimated by $\chi$-separation, could provide a deeper
understanding of brain substructures, assisting the investigation of their
functions and alterations. This can be achieved using 7T MRI, which benefits
from a high signal-to-noise ratio and susceptibility effects. However, applying
$\chi$-separation at 7T presents difficulties due to the requirement of an
$R_2$ map, coupled with issues such as high specific absorption rate (SAR),
large $B_1$ transmit field inhomogeneities, and prolonged scan time.
To address these challenges, we developed a novel deep neural network,
R2PRIMEnet7T, designed to convert a 7T $R_2^*$ map into a 3T $R_2'$ map.
Building on this development, we present a new pipeline for $\chi$-separation
at 7T, enabling us to generate high-resolution $\chi$-separation maps from
multi-echo gradient-echo data. The proposed method is compared with alternative
pipelines, such as an end-to-end network and linearly-scaled $R_2'$, and is
validated against $\chi$-separation maps at 3T, demonstrating its accuracy. The
7T $\chi$-separation maps generated by the proposed method exhibit similar
contrasts to those from 3T, while 7T high-resolution maps offer enhanced
clarity and detail. Quantitative analysis confirms that the proposed method
surpasses the alternative pipelines. The proposed method results well delineate
the detailed brain structures associated with iron and myelin. This new
pipeline holds promise for analyzing iron and myelin concentration changes in
various neurodegenerative diseases through precise structural examination.</description><subject>Physics - Medical Physics</subject><subject>Quantitative Biology - Quantitative Methods</subject><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>GOX</sourceid><recordid>eNpjYJA0NNAzsTA1NdBPLKrILNMzMgEKGBoZGVtyMuh65umWZZblK2RkpmfoFqUW5-eUlmTm5ynEJGdk6hanFiQWJYL5iSUK5iE8DKxpiTnFqbxQmptB3s01xNlDF2xwfEFRZm5iUWU8yIJ4sAXGhFUAAIRsL0U</recordid><startdate>20241016</startdate><enddate>20241016</enddate><creator>Kim, Jiye</creator><creator>Kim, Minjun</creator><creator>Ji, Sooyeon</creator><creator>Min, Kyeongseon</creator><creator>Jeong, Hwihun</creator><creator>Shin, Hyeong-Geol</creator><creator>Oh, Chungseok</creator><creator>Straub, Sina</creator><creator>Kim, Seong-Gi</creator><creator>Lee, Jongho</creator><scope>ALC</scope><scope>GOX</scope></search><sort><creationdate>20241016</creationdate><title>In-vivo high-resolution \chi-separation at 7T</title><author>Kim, Jiye ; Kim, Minjun ; Ji, Sooyeon ; Min, Kyeongseon ; Jeong, Hwihun ; Shin, Hyeong-Geol ; Oh, Chungseok ; Straub, Sina ; Kim, Seong-Gi ; Lee, Jongho</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-arxiv_primary_2410_122393</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Physics - Medical Physics</topic><topic>Quantitative Biology - Quantitative Methods</topic><toplevel>online_resources</toplevel><creatorcontrib>Kim, Jiye</creatorcontrib><creatorcontrib>Kim, Minjun</creatorcontrib><creatorcontrib>Ji, Sooyeon</creatorcontrib><creatorcontrib>Min, Kyeongseon</creatorcontrib><creatorcontrib>Jeong, Hwihun</creatorcontrib><creatorcontrib>Shin, Hyeong-Geol</creatorcontrib><creatorcontrib>Oh, Chungseok</creatorcontrib><creatorcontrib>Straub, Sina</creatorcontrib><creatorcontrib>Kim, Seong-Gi</creatorcontrib><creatorcontrib>Lee, Jongho</creatorcontrib><collection>arXiv Quantitative Biology</collection><collection>arXiv.org</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Kim, Jiye</au><au>Kim, Minjun</au><au>Ji, Sooyeon</au><au>Min, Kyeongseon</au><au>Jeong, Hwihun</au><au>Shin, Hyeong-Geol</au><au>Oh, Chungseok</au><au>Straub, Sina</au><au>Kim, Seong-Gi</au><au>Lee, Jongho</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>In-vivo high-resolution \chi-separation at 7T</atitle><date>2024-10-16</date><risdate>2024</risdate><abstract>A recently introduced quantitative susceptibility mapping (QSM) technique,
$\chi$-separation, offers the capability to separate paramagnetic
($\chi_{\text{para}}$) and diamagnetic ($\chi_{\text{dia}}$) susceptibility
distribution within the brain. In-vivo high-resolution mapping of iron and
myelin distribution, estimated by $\chi$-separation, could provide a deeper
understanding of brain substructures, assisting the investigation of their
functions and alterations. This can be achieved using 7T MRI, which benefits
from a high signal-to-noise ratio and susceptibility effects. However, applying
$\chi$-separation at 7T presents difficulties due to the requirement of an
$R_2$ map, coupled with issues such as high specific absorption rate (SAR),
large $B_1$ transmit field inhomogeneities, and prolonged scan time.
To address these challenges, we developed a novel deep neural network,
R2PRIMEnet7T, designed to convert a 7T $R_2^*$ map into a 3T $R_2'$ map.
Building on this development, we present a new pipeline for $\chi$-separation
at 7T, enabling us to generate high-resolution $\chi$-separation maps from
multi-echo gradient-echo data. The proposed method is compared with alternative
pipelines, such as an end-to-end network and linearly-scaled $R_2'$, and is
validated against $\chi$-separation maps at 3T, demonstrating its accuracy. The
7T $\chi$-separation maps generated by the proposed method exhibit similar
contrasts to those from 3T, while 7T high-resolution maps offer enhanced
clarity and detail. Quantitative analysis confirms that the proposed method
surpasses the alternative pipelines. The proposed method results well delineate
the detailed brain structures associated with iron and myelin. This new
pipeline holds promise for analyzing iron and myelin concentration changes in
various neurodegenerative diseases through precise structural examination.</abstract><doi>10.48550/arxiv.2410.12239</doi><oa>free_for_read</oa></addata></record> |
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title | In-vivo high-resolution \chi-separation at 7T |
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