Quantitative synthetic MRI reveals grey matter abnormalities in children with drug-naïve attention-deficit/hyperactivity disorder
To investigate the quantitative profiles of brain grey matter (GM) in pediatric drug-naïve ADHD patients using synthetic magnetic resonance imaging (SyMRI). A total of 37 drug-naïve pediatric ADHD and 27 age- and gender-matched healthy controls (HC) were enrolled in this study. Each subject underwen...
Saved in:
Published in | Brain imaging and behavior Vol. 16; no. 1; pp. 406 - 414 |
---|---|
Main Authors | , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
New York
Springer US
01.02.2022
Springer Nature B.V |
Subjects | |
Online Access | Get full text |
ISSN | 1931-7557 1931-7565 1931-7565 |
DOI | 10.1007/s11682-021-00514-8 |
Cover
Abstract | To investigate the quantitative profiles of brain grey matter (GM) in pediatric drug-naïve ADHD patients using synthetic magnetic resonance imaging (SyMRI). A total of 37 drug-naïve pediatric ADHD and 27 age- and gender-matched healthy controls (HC) were enrolled in this study. Each subject underwent both SyMRI and conventional 3D T1-FSPGR scans. Quantitative parameters, T1 and T2 maps, were extracted from the SyMRI data. Between-group quantitative maps were compared using a general linear model analysis. Pearson correlation analysis was conducted to assess the association between significantly altered MR indices and clinical measurements in ADHD. Compared with the HC group, altered T1 and T2 relaxometry times in the ADHD group were mainly distributed in GM regions of the cerebellum, attention and execution control network, default mode network, and limbic areas. Moreover, the T1 value of the right cerebellum 8 was negatively correlated with the attention concentration level in ADHD (R = 0.140,
P
= 0.0225). With regards to T2 map, the associations were observed between the attention level of ADHD patients and left fusiform gyrus (R = 0.251,
P
= 0.0016), and right cerebellum crus2 (R = 0.142,
P
= 0.0214). Altered T1, T2 values found in specific regions of GM, including cerebellum, attention and execution control network, default mode network, and limbic areas, may reveal widespread micromorphology changes, i.e., brain iron deficiency, low myelin content, and enlarged vascular interstitial space in ADHD patients. Thus, T1, T2 values might be promising imaging markers for future ADHD studies. |
---|---|
AbstractList | To investigate the quantitative profiles of brain grey matter (GM) in pediatric drug-naïve ADHD patients using synthetic magnetic resonance imaging (SyMRI). A total of 37 drug-naïve pediatric ADHD and 27 age- and gender-matched healthy controls (HC) were enrolled in this study. Each subject underwent both SyMRI and conventional 3D T1-FSPGR scans. Quantitative parameters, T1 and T2 maps, were extracted from the SyMRI data. Between-group quantitative maps were compared using a general linear model analysis. Pearson correlation analysis was conducted to assess the association between significantly altered MR indices and clinical measurements in ADHD. Compared with the HC group, altered T1 and T2 relaxometry times in the ADHD group were mainly distributed in GM regions of the cerebellum, attention and execution control network, default mode network, and limbic areas. Moreover, the T1 value of the right cerebellum 8 was negatively correlated with the attention concentration level in ADHD (R = 0.140, P = 0.0225). With regards to T2 map, the associations were observed between the attention level of ADHD patients and left fusiform gyrus (R = 0.251, P = 0.0016), and right cerebellum crus2 (R = 0.142, P = 0.0214). Altered T1, T2 values found in specific regions of GM, including cerebellum, attention and execution control network, default mode network, and limbic areas, may reveal widespread micromorphology changes, i.e., brain iron deficiency, low myelin content, and enlarged vascular interstitial space in ADHD patients. Thus, T1, T2 values might be promising imaging markers for future ADHD studies. To investigate the quantitative profiles of brain grey matter (GM) in pediatric drug-naïve ADHD patients using synthetic magnetic resonance imaging (SyMRI). A total of 37 drug-naïve pediatric ADHD and 27 age- and gender-matched healthy controls (HC) were enrolled in this study. Each subject underwent both SyMRI and conventional 3D T1-FSPGR scans. Quantitative parameters, T1 and T2 maps, were extracted from the SyMRI data. Between-group quantitative maps were compared using a general linear model analysis. Pearson correlation analysis was conducted to assess the association between significantly altered MR indices and clinical measurements in ADHD. Compared with the HC group, altered T1 and T2 relaxometry times in the ADHD group were mainly distributed in GM regions of the cerebellum, attention and execution control network, default mode network, and limbic areas. Moreover, the T1 value of the right cerebellum 8 was negatively correlated with the attention concentration level in ADHD (R = 0.140, P = 0.0225). With regards to T2 map, the associations were observed between the attention level of ADHD patients and left fusiform gyrus (R = 0.251, P = 0.0016), and right cerebellum crus2 (R = 0.142, P = 0.0214). Altered T1, T2 values found in specific regions of GM, including cerebellum, attention and execution control network, default mode network, and limbic areas, may reveal widespread micromorphology changes, i.e., brain iron deficiency, low myelin content, and enlarged vascular interstitial space in ADHD patients. Thus, T1, T2 values might be promising imaging markers for future ADHD studies.To investigate the quantitative profiles of brain grey matter (GM) in pediatric drug-naïve ADHD patients using synthetic magnetic resonance imaging (SyMRI). A total of 37 drug-naïve pediatric ADHD and 27 age- and gender-matched healthy controls (HC) were enrolled in this study. Each subject underwent both SyMRI and conventional 3D T1-FSPGR scans. Quantitative parameters, T1 and T2 maps, were extracted from the SyMRI data. Between-group quantitative maps were compared using a general linear model analysis. Pearson correlation analysis was conducted to assess the association between significantly altered MR indices and clinical measurements in ADHD. Compared with the HC group, altered T1 and T2 relaxometry times in the ADHD group were mainly distributed in GM regions of the cerebellum, attention and execution control network, default mode network, and limbic areas. Moreover, the T1 value of the right cerebellum 8 was negatively correlated with the attention concentration level in ADHD (R = 0.140, P = 0.0225). With regards to T2 map, the associations were observed between the attention level of ADHD patients and left fusiform gyrus (R = 0.251, P = 0.0016), and right cerebellum crus2 (R = 0.142, P = 0.0214). Altered T1, T2 values found in specific regions of GM, including cerebellum, attention and execution control network, default mode network, and limbic areas, may reveal widespread micromorphology changes, i.e., brain iron deficiency, low myelin content, and enlarged vascular interstitial space in ADHD patients. Thus, T1, T2 values might be promising imaging markers for future ADHD studies. To investigate the quantitative profiles of brain grey matter (GM) in pediatric drug-naïve ADHD patients using synthetic magnetic resonance imaging (SyMRI). A total of 37 drug-naïve pediatric ADHD and 27 age- and gender-matched healthy controls (HC) were enrolled in this study. Each subject underwent both SyMRI and conventional 3D T1-FSPGR scans. Quantitative parameters, T1 and T2 maps, were extracted from the SyMRI data. Between-group quantitative maps were compared using a general linear model analysis. Pearson correlation analysis was conducted to assess the association between significantly altered MR indices and clinical measurements in ADHD. Compared with the HC group, altered T1 and T2 relaxometry times in the ADHD group were mainly distributed in GM regions of the cerebellum, attention and execution control network, default mode network, and limbic areas. Moreover, the T1 value of the right cerebellum 8 was negatively correlated with the attention concentration level in ADHD (R = 0.140, P = 0.0225). With regards to T2 map, the associations were observed between the attention level of ADHD patients and left fusiform gyrus (R = 0.251, P = 0.0016), and right cerebellum crus2 (R = 0.142, P = 0.0214). Altered T1, T2 values found in specific regions of GM, including cerebellum, attention and execution control network, default mode network, and limbic areas, may reveal widespread micromorphology changes, i.e., brain iron deficiency, low myelin content, and enlarged vascular interstitial space in ADHD patients. Thus, T1, T2 values might be promising imaging markers for future ADHD studies. |
Author | Zhou, Qin Xiang, Xianhong Su, Shu Dai, Yan Lin, Liping Yang, Zhiyun Zou, Mengsha Liu, Meina Chen, Yingqian Zhang, Hongyu Qian, Long |
Author_xml | – sequence: 1 givenname: Shu surname: Su fullname: Su, Shu organization: Department of Radiology, First Affiliated Hospital, Sun Yat-Sen University – sequence: 2 givenname: Yingqian surname: Chen fullname: Chen, Yingqian organization: Department of Radiology, First Affiliated Hospital, Sun Yat-Sen University – sequence: 3 givenname: Yan surname: Dai fullname: Dai, Yan organization: Department of Radiology, First Affiliated Hospital, Sun Yat-Sen University – sequence: 4 givenname: Liping surname: Lin fullname: Lin, Liping organization: Department of Radiology, First Affiliated Hospital, Sun Yat-Sen University – sequence: 5 givenname: Long surname: Qian fullname: Qian, Long organization: MR Research, GE Healthcare – sequence: 6 givenname: Qin surname: Zhou fullname: Zhou, Qin organization: Department of Radiology, First Affiliated Hospital, Sun Yat-Sen University – sequence: 7 givenname: Mengsha surname: Zou fullname: Zou, Mengsha organization: Department of Radiology, First Affiliated Hospital, Sun Yat-Sen University – sequence: 8 givenname: Hongyu surname: Zhang fullname: Zhang, Hongyu organization: Department of Pediatric, First Affiliated Hospital, Sun Yat-Sen University – sequence: 9 givenname: Meina surname: Liu fullname: Liu, Meina organization: Department of Pediatric, First Affiliated Hospital, Sun Yat-Sen University – sequence: 10 givenname: Xianhong surname: Xiang fullname: Xiang, Xianhong email: xxianhong@mail.sysu.edu.cn organization: Department of Radiology, First Affiliated Hospital, Sun Yat-Sen University – sequence: 11 givenname: Zhiyun orcidid: 0000-0002-6139-9049 surname: Yang fullname: Yang, Zhiyun email: yzhyun@mail.sysu.edu.cn organization: Department of Radiology, First Affiliated Hospital, Sun Yat-Sen University |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/34491528$$D View this record in MEDLINE/PubMed |
BookMark | eNp9kctu1DAUhi3Uil7gBVggS2zYhPqaOEtUFajUCrUqa8uxT2ZcJc5gO0XZ8kI8BC-Gp9MWqYuu7MX3_efo_EdoL0wBEHpHySdKSHOSKK0VqwijFSGSikq9Qoe05bRqZC33nv6yOUBHKd0WSKiWvkYHXIiWSqYO0e-r2YTss8n-DnBaQl5D9hZfXp_jCHdghoRXERY8mpwhYtOFKY5m8NlDwj5gu_aDixDwL5_X2MV5VQXz908J2wolegqVg95bn0_WywaisWWUzwt2Pk3RQXyD9vsyBt4-vMfox5ezm9Nv1cX3r-enny8qyxuZK9WzhomOOsVaV3PumKAKXNOXI9iO1YYyK3pZW8OAO0FJp0zfSWJIKxvjOn6MPu5yN3H6OUPKevTJwjCYANOcNJMNoQXmoqAfnqG30xxD2U6zmtVCybrhhXr_QM3dCE5voh9NXPTjdQugdoCNU0oRem3vLz2FHI0fNCV6W6TeFalLkfq-SL1V2TP1Mf1Fie-kVOCwgvh_7Resf_ATsuM |
CitedBy_id | crossref_primary_10_1016_j_jad_2023_03_065 crossref_primary_10_1097_RCT_0000000000001507 crossref_primary_10_1515_dx_2024_0168 crossref_primary_10_1016_j_jpsychires_2024_03_035 crossref_primary_10_1007_s00431_023_05397_z crossref_primary_10_2463_mrms_tn_2022_0161 crossref_primary_10_1007_s11042_024_19460_w crossref_primary_10_1007_s00234_025_03547_8 crossref_primary_10_1017_S0033291722002598 |
Cites_doi | 10.3892/etm.2020.8645 10.1016/S2215-0366(17)30200-6 10.1016/j.nicl.2019.101851 10.1007/s00406-019-01032-x 10.1016/j.clinimag.2019.09.005 10.1007/s12035-014-8685-x 10.1093/cercor/bhx182 10.1016/B978-0-444-64196-0.00016-9 10.1503/jpn.140377 10.1002/hbm.23137 10.1016/j.neubiorev.2019.02.011 10.1016/j.nicl.2018.11.010 10.1016/j.euroneuro.2018.08.225 10.1016/S0140-6736(15)00238-X 10.1001/jamapsychiatry.2016.0383 10.1016/j.pscychresns.2011.07.001 10.1002/hbm.22418 10.1017/S0033291714001858 10.1093/cercor/bhz152 10.1007/s00415-018-9139-6 10.1002/mrm.21635 10.1016/j.neuroimage.2014.02.026 10.1542/peds.2014-3482 10.1038/s41582-020-0312-z 10.1111/dmcn.14050 10.1001/jamapsychiatry.2016.0700 10.1016/j.neuroimage.2017.12.087 10.1016/j.neurad.2019.02.005 10.1111/j.1600-0447.2011.01786.x 10.3174/ajnr.A4977 10.1016/j.neuroimage.2018.02.055 10.1007/s11065-014-9251-z |
ContentType | Journal Article |
Copyright | The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021. |
Copyright_xml | – notice: The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021 – notice: 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. – notice: The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021. |
DBID | AAYXX CITATION CGR CUY CVF ECM EIF NPM 3V. 7RV 7TK 7X7 7XB 88E 88G 8FE 8FG 8FH 8FI 8FJ 8FK ABUWG AFKRA ARAPS AZQEC BBNVY BENPR BGLVJ BHPHI CCPQU DWQXO FYUFA GHDGH GNUQQ HCIFZ K9. KB0 LK8 M0S M1P M2M M7P NAPCQ P5Z P62 PHGZM PHGZT PJZUB PKEHL PPXIY PQEST PQGLB PQQKQ PQUKI PRINS PSYQQ Q9U 7X8 |
DOI | 10.1007/s11682-021-00514-8 |
DatabaseName | CrossRef Medline MEDLINE MEDLINE (Ovid) MEDLINE MEDLINE PubMed ProQuest Central (Corporate) Nursing & Allied Health Database Neurosciences Abstracts Health & Medical Collection ProQuest Central (purchase pre-March 2016) Medical Database (Alumni Edition) Psychology Database (Alumni) ProQuest SciTech Collection ProQuest Technology Collection ProQuest Natural Science Journals Hospital Premium Collection Hospital Premium Collection (Alumni Edition) ProQuest Central (Alumni) (purchase pre-March 2016) ProQuest Central (Alumni) ProQuest Central UK/Ireland Advanced Technologies & Aerospace Collection ProQuest Central Essentials Biological Science Collection ProQuest Central Technology Collection Natural Science Collection ProQuest One Community College ProQuest Central Korea Health Research Premium Collection Health Research Premium Collection (Alumni) ProQuest Central Student SciTech Premium Collection ProQuest Health & Medical Complete (Alumni) Nursing & Allied Health Database (Alumni Edition) Biological Sciences ProQuest Health & Medical Collection Medical Database Psychology Database Biological Science Database Nursing & Allied Health Premium Advanced Technologies & Aerospace Database ProQuest Advanced Technologies & Aerospace Collection ProQuest Central Premium ProQuest One Academic (New) ProQuest Health & Medical Research Collection ProQuest One Academic Middle East (New) ProQuest One Health & Nursing ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Applied & Life Sciences ProQuest One Academic ProQuest One Academic UKI Edition ProQuest Central China ProQuest One Psychology ProQuest Central Basic MEDLINE - Academic |
DatabaseTitle | CrossRef MEDLINE Medline Complete MEDLINE with Full Text PubMed MEDLINE (Ovid) ProQuest One Psychology ProQuest Central Student Technology Collection ProQuest One Academic Middle East (New) ProQuest Advanced Technologies & Aerospace Collection ProQuest Central Essentials ProQuest Health & Medical Complete (Alumni) ProQuest Central (Alumni Edition) SciTech Premium Collection ProQuest One Community College ProQuest One Health & Nursing ProQuest Natural Science Collection ProQuest Central China ProQuest Central ProQuest One Applied & Life Sciences ProQuest Health & Medical Research Collection Health Research Premium Collection Health and Medicine Complete (Alumni Edition) Natural Science Collection ProQuest Central Korea Health & Medical Research Collection Biological Science Collection ProQuest Central (New) ProQuest Medical Library (Alumni) Advanced Technologies & Aerospace Collection ProQuest Biological Science Collection ProQuest Central Basic ProQuest One Academic Eastern Edition ProQuest Nursing & Allied Health Source ProQuest Hospital Collection ProQuest Technology Collection Health Research Premium Collection (Alumni) ProQuest Psychology Journals (Alumni) Biological Science Database ProQuest SciTech Collection Neurosciences Abstracts ProQuest Hospital Collection (Alumni) Advanced Technologies & Aerospace Database Nursing & Allied Health Premium ProQuest Health & Medical Complete ProQuest Medical Library ProQuest Psychology Journals ProQuest One Academic UKI Edition ProQuest Nursing & Allied Health Source (Alumni) ProQuest One Academic ProQuest One Academic (New) ProQuest Central (Alumni) MEDLINE - Academic |
DatabaseTitleList | MEDLINE MEDLINE - Academic ProQuest One Psychology |
Database_xml | – sequence: 1 dbid: NPM name: PubMed url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 2 dbid: EIF name: MEDLINE url: https://proxy.k.utb.cz/login?url=https://www.webofscience.com/wos/medline/basic-search sourceTypes: Index Database – sequence: 3 dbid: 8FG name: ProQuest Technology Collection url: https://search.proquest.com/technologycollection1 sourceTypes: Aggregation Database |
DeliveryMethod | fulltext_linktorsrc |
Discipline | Medicine |
EISSN | 1931-7565 |
EndPage | 414 |
ExternalDocumentID | 34491528 10_1007_s11682_021_00514_8 |
Genre | Journal Article |
GrantInformation_xml | – fundername: the Natural Science Fund Youth Science Fund Project of China grantid: 82001439 – fundername: the Medical Scientific Research Foundation of Guangdong Province grantid: A2020327 |
GroupedDBID | --- -55 -5G -BR -EM -Y2 -~C .86 .VR 04C 06D 0R~ 0VY 1N0 203 23N 29~ 2J2 2JN 2JY 2KG 2KM 2LR 2VQ 2~H 30V 3V. 4.4 406 408 409 40D 40E 53G 5GY 5VS 67Z 6J9 6NX 7RV 7X7 875 88E 8FE 8FG 8FH 8FI 8FJ 8TC 8UJ 95- 95. 95~ 96X AAAVM AABHQ AACDK AAHNG AAIAL AAJBT AAJKR AANXM AANZL AARHV AARTL AASML AATNV AATVU AAUYE AAWCG AAYIU AAYQN AAYTO AAYZH ABAKF ABBXA ABDZT ABECU ABFTV ABHLI ABHQN ABIVO ABJNI ABJOX ABKCH ABMNI ABMQK ABNWP ABPLI ABQBU ABSXP ABTEG ABTHY ABTKH ABTMW ABULA ABUWG ABWNU ABXPI ACAOD ACDTI ACGFS ACHSB ACHXU ACIWK ACKNC ACMDZ ACMLO ACOKC ACOMO ACPIV ACPRK ACREN ACSNA ACZOJ ADBBV ADHHG ADHIR ADINQ ADKNI ADKPE ADRFC ADTPH ADURQ ADYFF ADYOE ADZKW AEBTG AEFQL AEGAL AEGNC AEJHL AEJRE AEKMD AEMSY AENEX AEOHA AEPYU AESKC AETLH AEVLU AEXYK AFBBN AFGCZ AFKRA AFLOW AFQWF AFRAH AFWTZ AFYQB AFZKB AGAYW AGDGC AGJBK AGMZJ AGQEE AGQMX AGRTI AGWIL AGWZB AGYKE AHAVH AHBYD AHKAY AHMBA AHSBF AHYZX AIAKS AIGIU AIIXL AILAN AITGF AJBLW AJRNO AJZVZ AKMHD ALIPV ALMA_UNASSIGNED_HOLDINGS ALWAN AMKLP AMTXH AMXSW AMYLF AMYQR AOCGG ARAPS ARMRJ AXYYD AZQEC B-. BA0 BBNVY BDATZ BENPR BGLVJ BGNMA BHPHI BKEYQ BMSDO BPHCQ BSONS BVXVI CAG CCPQU COF CS3 CSCUP DDRTE DNIVK DPUIP DU5 DWQXO EBD EBLON EBS EIHBH EIOEI EJD EMOBN ESBYG EX3 F5P FERAY FFXSO FIGPU FINBP FNLPD FRRFC FSGXE FWDCC FYUFA GGCAI GGRSB GJIRD GNUQQ GNWQR GQ6 GQ7 GQ8 GXS H13 HCIFZ HF~ HG5 HG6 HLICF HMCUK HMJXF HQYDN HRMNR HZ~ IJ- IKXTQ IWAJR IXC IXD IXE IZIGR IZQ I~X I~Z J-C J0Z JBSCW JCJTX JZLTJ KDC KOV LK8 LLZTM M1P M2M M4Y M7P MA- NAPCQ NPVJJ NQJWS NU0 O9- O93 O9J OAM P62 P9L PF0 PQQKQ PROAC PSQYO PSYQQ PT4 QOR QOS R89 R9I ROL RPX RSV S16 S1Z S27 S3B SAP SBS SDH SHX SISQX SJYHP SNE SNPRN SNX SOHCF SOJ SPISZ SRMVM SSLCW SSXJD STPWE SV3 SZN T13 TSG TSK TSV TUC U2A U9L UG4 UKHRP UOJIU UTJUX UZXMN VC2 VFIZW W23 W48 WK8 WOW YLTOR Z45 Z82 Z83 ZMTXR ZOVNA ~A9 ~KM AAPKM AAYXX ABBRH ABDBE ABFSG ACMFV ACSTC AEZWR AFDZB AFHIU AFOHR AHPBZ AHWEU AIXLP ATHPR AYFIA CITATION PHGZM PHGZT CGR CUY CVF ECM EIF NPM 7TK 7XB 8FK ABRTQ K9. PJZUB PKEHL PPXIY PQEST PQGLB PQUKI PRINS PUEGO Q9U 7X8 |
ID | FETCH-LOGICAL-c375t-8f2724b1d829d633d2418ed7f168cb26a12c4f56ca2e3d410b8afb50a0957adb3 |
IEDL.DBID | AGYKE |
ISSN | 1931-7557 1931-7565 |
IngestDate | Fri Sep 05 03:59:55 EDT 2025 Sat Sep 06 23:10:33 EDT 2025 Wed Feb 19 02:27:31 EST 2025 Tue Jul 01 04:04:34 EDT 2025 Thu Apr 24 23:12:04 EDT 2025 Fri Feb 21 02:47:42 EST 2025 |
IsPeerReviewed | true |
IsScholarly | true |
Issue | 1 |
Keywords | Attention-deficit/hyperactivity disorder Quantitative MRI Grey matter |
Language | English |
License | 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. |
LinkModel | DirectLink |
MergedId | FETCHMERGED-LOGICAL-c375t-8f2724b1d829d633d2418ed7f168cb26a12c4f56ca2e3d410b8afb50a0957adb3 |
Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
ORCID | 0000-0002-6139-9049 |
PMID | 34491528 |
PQID | 2626485673 |
PQPubID | 1486349 |
PageCount | 9 |
ParticipantIDs | proquest_miscellaneous_2570109534 proquest_journals_2626485673 pubmed_primary_34491528 crossref_citationtrail_10_1007_s11682_021_00514_8 crossref_primary_10_1007_s11682_021_00514_8 springer_journals_10_1007_s11682_021_00514_8 |
ProviderPackageCode | CITATION AAYXX |
PublicationCentury | 2000 |
PublicationDate | 20220200 2022-02-00 2022-Feb 20220201 |
PublicationDateYYYYMMDD | 2022-02-01 |
PublicationDate_xml | – month: 2 year: 2022 text: 20220200 |
PublicationDecade | 2020 |
PublicationPlace | New York |
PublicationPlace_xml | – name: New York – name: United States – name: Indianapolis |
PublicationTitle | Brain imaging and behavior |
PublicationTitleAbbrev | Brain Imaging and Behavior |
PublicationTitleAlternate | Brain Imaging Behav |
PublicationYear | 2022 |
Publisher | Springer US Springer Nature B.V |
Publisher_xml | – name: Springer US – name: Springer Nature B.V |
References | Norman, L. J., Carlisi, C., Lukito, S., et al. (2016). Structural and functional brain abnormalities in attention-deficit/hyperactivity disorder and obsessive-compulsive disorder: A comparative meta-analysis. JAMA Psychiatry, 73(8), 815–825. Does, M. D. (2018). Inferring brain tissue composition and microstructure via MR relaxometry. NeuroImage, 182, 136–148. Kupeli, A., Kocak, M., Goktepeli, M., et al. (2020). Role of T1 mapping to evaluate brain aging in a healthy population. Clinical Imaging, 59(1), 56–60. Edwards, L. J., Kirilina, E., Mohammadi, S., et al. (2018). Microstructural imaging of human neocortex in vivo. NeuroImage, 182, 184–206. Megna, R., Alfano, B., Lanzillo, R., et al. (2019). Brain tissue volumes and relaxation rates in multiple sclerosis: Implications for cognitive impairment. Journal of Neurology, 266(2), 361–368. Deoni, S. C., Zinkstok, J. R., Daly, E., et al. (2015). White-matter relaxation time and myelin water fraction differences in young adults with autism. Psychological Medicine, 45(4), 795–805. Caye, A., Rocha, T. B., Anselmi, L., et al. (2016). Attention-deficit/hyperactivity disorder trajectories from childhood to young adulthood: Evidence from a birth cohort supporting a late-onset syndrome. JAMA Psychiatry, 73(7), 705–712. Cheng, Q. Q., Huang, J. X., Liang, J. Y., et al. (2020). Evaluation of abnormal iron distribution in specific regions in the brains of patients with Parkinson’s disease using quantitative susceptibility mapping and R2*mapping. Experimental and Therapeutic Medicine, 19(6), 3778–3786. Wang, Y., Sun, K., Liu, Z., et al. (2020a). Classification of unmedicated bipolar disorder using whole-brain functional activity and connectivity: A radiomics analysis. Cerebral Cortex, 30(3), 1117–1128. Albajara Saenz, A., Villemonteix, T., & Massat, I. (2019). Structural and functional neuroimaging in attention-deficit/hyperactivity disorder. Development Medicine and Child Neurology, 61(4), 399–405. Wu, Z. M., Llera, A., Hoogman, M., et al. (2019). Linked anatomical and functional brain alterations in children with attention-deficit/hyperactivity disorder. Neuroimage Clinical, 23, 101851. Hoogman, M., Bralten, J., Hibar, D. P., et al. (2017). Subcortical brain volume differences in participants with attention deficit hyperactivity disorder in children and adults: A cross-sectional mega-analysis. Lancet Psychiatry, 4(4), 310–319. Samea, F., Soluki, S., Nejati, V., et al. (2019). Brain alterations in children/adolescents with ADHD revisited: A neuroimaging meta-analysis of 96 structural and functional studies. Neuroscience and Biobehavioral Reviews, 100, 1–8. Bralten, J., Greven, C. U., Franke, B., et al. (2016). Voxel-based morphometry analysis reveals frontal brain differences in participants with ADHD and their unaffected siblings. Journal of Psychiatry & Neuroscience, 41(4), 272–279. Sun, L., Cao, Q., Long, X., et al. (2012). Abnormal functional connectivity between the anterior cingulate and the default mode network in drug-naïve boys with attention deficit hyperactivity disorder. Psychiatry Research, 201(2), 120–127. Wardlaw, J. M., Benveniste, H., Nedergaard, M., et al. (2020). Perivascular spaces in the brain: Anatomy, physiology and pathology. Nature Reviews Neurology, 16(3), 137–153. Stuber, C., Morawski, M., Schafer, A., et al. (2014). Myelin and iron concentration in the human brain: A quantitative study of MRI contrast. NeuroImage, 93(Pt 1), 95–106. Hagiwara, A., Hori, M., Yokoyama, K., et al. (2017). Utility of a multiparametric quantitative MRI Model that assesses myelin and edema for evaluating plaques, periplaque white matter, and normal-appearing white matter in patients with multiple sclerosis: A feasibility study. American Journal of Neuroradiology, 38(2), 237–242. Jiang, W. H., Duan, K. K., Chen, J. Y., et al. (2019). Structural brain alterations and their association with cognitive function and symptoms in attention-deficit/hyperactivity disorder families. European Neuropsychopharmacology, 29, 1189–1190. Ambrosino, S., de Zeeuw, P., Wierenga, L. M., et al. (2017). What can cortical development in attention-deficit/hyperactivity disorder teach us about the early developmental mechanisms involved? Cerebral Cortex, 27(9), 4624–4634. Frodl, T., & Skokauskas, N. (2012). Meta-analysis of structural MRI studies in children and adults with attention deficit hyperactivity disorder indicates treatment effects. Acta Psychiatrica Scandinavica, 125(2), 114–126. Cao, M., Shu, N., Cao, Q., et al. (2014). Imaging functional and structural brain connectomics in attention-deficit/hyperactivity disorder. Molecular Neurobiology, 50(3), 1111–1123. Andica, C., Hagiwara, A., Hori, M., et al. (2019). Review of synthetic MRI in pediatric brains: Basic principle of MR quantification, its features, clinical applications, and limitations. Journal of Neuroradiology 46(4), 268–275. Thapar, A., & Cooper, M. (2016). Attention deficit hyperactivity disorder. The Lancet, 387(10024), 1240–1250. Lorio, S., Kherif, F., Ruef, A., et al. (2016). Neurobiological origin of spurious brain morphological changes: A quantitative MRI study. Human Brain Mapping, 37(5), 1801–1815. Posner, J., Park, C., & Wang, Z. (2014). Connecting the dots: A review of resting connectivity MRI studies in attention-deficit/hyperactivity disorder. Neuropsychology Review, 24(1), 3–15. Vogt, B. A. (2019). Cingulate impairments in ADHD: Comorbidities, connections, and treatment. Handbook of Clinical Neurology, 166, 297–314. Warntjes, J. B., Leinhard, O. D., West, J., et al. (2008). Rapid magnetic resonance quantification on the brain: Optimization for clinical usage. Magnetic Resonance in Medicine, 60(2), 320–329. Thomas, R., Sanders, S., Doust, J., et al. (2015). Prevalence of attention-deficit/hyperactivity disorder: A systematic review and meta-analysis. Pediatrics, 135(4), e994–1001. Lei, X., Wang, Y., Yuan, H., et al. (2014). Neuronal oscillations and functional interactions between resting state networks. Human Brain Mapping, 35(7), 3517–3528. Qian, X., Castellanos, F. X., Uddin, L. Q., et al. (2019). Large-scale brain functional network topology disruptions underlie symptom heterogeneity in children with attention-deficit/hyperactivity disorder. Neuroimage Clinical, 21, 101600. Wang, L. J., Li, S. C., Kuo, H. C., et al. (2020b). Gray matter volume and microRNA levels in patients with attention-deficit/hyperactivity disorder. European Archives of Psychiatry and Clinical Neuroscience, 270(8), 1037–1045. 514_CR6 514_CR11 514_CR7 514_CR12 514_CR8 514_CR31 514_CR9 514_CR10 514_CR32 514_CR30 514_CR19 514_CR17 514_CR18 514_CR15 514_CR16 514_CR13 514_CR14 514_CR1 514_CR2 514_CR3 514_CR4 514_CR5 514_CR22 514_CR23 514_CR20 514_CR21 514_CR28 514_CR29 514_CR26 514_CR27 514_CR24 514_CR25 |
References_xml | – reference: Kupeli, A., Kocak, M., Goktepeli, M., et al. (2020). Role of T1 mapping to evaluate brain aging in a healthy population. Clinical Imaging, 59(1), 56–60. – reference: Thapar, A., & Cooper, M. (2016). Attention deficit hyperactivity disorder. The Lancet, 387(10024), 1240–1250. – reference: Norman, L. J., Carlisi, C., Lukito, S., et al. (2016). Structural and functional brain abnormalities in attention-deficit/hyperactivity disorder and obsessive-compulsive disorder: A comparative meta-analysis. JAMA Psychiatry, 73(8), 815–825. – reference: Thomas, R., Sanders, S., Doust, J., et al. (2015). Prevalence of attention-deficit/hyperactivity disorder: A systematic review and meta-analysis. Pediatrics, 135(4), e994–1001. – reference: Wang, Y., Sun, K., Liu, Z., et al. (2020a). Classification of unmedicated bipolar disorder using whole-brain functional activity and connectivity: A radiomics analysis. Cerebral Cortex, 30(3), 1117–1128. – reference: Wu, Z. M., Llera, A., Hoogman, M., et al. (2019). Linked anatomical and functional brain alterations in children with attention-deficit/hyperactivity disorder. Neuroimage Clinical, 23, 101851. – reference: Posner, J., Park, C., & Wang, Z. (2014). Connecting the dots: A review of resting connectivity MRI studies in attention-deficit/hyperactivity disorder. Neuropsychology Review, 24(1), 3–15. – reference: Wang, L. J., Li, S. C., Kuo, H. C., et al. (2020b). Gray matter volume and microRNA levels in patients with attention-deficit/hyperactivity disorder. European Archives of Psychiatry and Clinical Neuroscience, 270(8), 1037–1045. – reference: Cao, M., Shu, N., Cao, Q., et al. (2014). Imaging functional and structural brain connectomics in attention-deficit/hyperactivity disorder. Molecular Neurobiology, 50(3), 1111–1123. – reference: Edwards, L. J., Kirilina, E., Mohammadi, S., et al. (2018). Microstructural imaging of human neocortex in vivo. NeuroImage, 182, 184–206. – reference: Megna, R., Alfano, B., Lanzillo, R., et al. (2019). Brain tissue volumes and relaxation rates in multiple sclerosis: Implications for cognitive impairment. Journal of Neurology, 266(2), 361–368. – reference: Wardlaw, J. M., Benveniste, H., Nedergaard, M., et al. (2020). Perivascular spaces in the brain: Anatomy, physiology and pathology. Nature Reviews Neurology, 16(3), 137–153. – reference: Lei, X., Wang, Y., Yuan, H., et al. (2014). Neuronal oscillations and functional interactions between resting state networks. Human Brain Mapping, 35(7), 3517–3528. – reference: Samea, F., Soluki, S., Nejati, V., et al. (2019). Brain alterations in children/adolescents with ADHD revisited: A neuroimaging meta-analysis of 96 structural and functional studies. Neuroscience and Biobehavioral Reviews, 100, 1–8. – reference: Bralten, J., Greven, C. U., Franke, B., et al. (2016). Voxel-based morphometry analysis reveals frontal brain differences in participants with ADHD and their unaffected siblings. Journal of Psychiatry & Neuroscience, 41(4), 272–279. – reference: Hoogman, M., Bralten, J., Hibar, D. P., et al. (2017). Subcortical brain volume differences in participants with attention deficit hyperactivity disorder in children and adults: A cross-sectional mega-analysis. Lancet Psychiatry, 4(4), 310–319. – reference: Vogt, B. A. (2019). Cingulate impairments in ADHD: Comorbidities, connections, and treatment. Handbook of Clinical Neurology, 166, 297–314. – reference: Qian, X., Castellanos, F. X., Uddin, L. Q., et al. (2019). Large-scale brain functional network topology disruptions underlie symptom heterogeneity in children with attention-deficit/hyperactivity disorder. Neuroimage Clinical, 21, 101600. – reference: Ambrosino, S., de Zeeuw, P., Wierenga, L. M., et al. (2017). What can cortical development in attention-deficit/hyperactivity disorder teach us about the early developmental mechanisms involved? Cerebral Cortex, 27(9), 4624–4634. – reference: Hagiwara, A., Hori, M., Yokoyama, K., et al. (2017). Utility of a multiparametric quantitative MRI Model that assesses myelin and edema for evaluating plaques, periplaque white matter, and normal-appearing white matter in patients with multiple sclerosis: A feasibility study. American Journal of Neuroradiology, 38(2), 237–242. – reference: Warntjes, J. B., Leinhard, O. D., West, J., et al. (2008). Rapid magnetic resonance quantification on the brain: Optimization for clinical usage. Magnetic Resonance in Medicine, 60(2), 320–329. – reference: Does, M. D. (2018). Inferring brain tissue composition and microstructure via MR relaxometry. NeuroImage, 182, 136–148. – reference: Frodl, T., & Skokauskas, N. (2012). Meta-analysis of structural MRI studies in children and adults with attention deficit hyperactivity disorder indicates treatment effects. Acta Psychiatrica Scandinavica, 125(2), 114–126. – reference: Sun, L., Cao, Q., Long, X., et al. (2012). Abnormal functional connectivity between the anterior cingulate and the default mode network in drug-naïve boys with attention deficit hyperactivity disorder. Psychiatry Research, 201(2), 120–127. – reference: Cheng, Q. Q., Huang, J. X., Liang, J. Y., et al. (2020). Evaluation of abnormal iron distribution in specific regions in the brains of patients with Parkinson’s disease using quantitative susceptibility mapping and R2*mapping. Experimental and Therapeutic Medicine, 19(6), 3778–3786. – reference: Stuber, C., Morawski, M., Schafer, A., et al. (2014). Myelin and iron concentration in the human brain: A quantitative study of MRI contrast. NeuroImage, 93(Pt 1), 95–106. – reference: Andica, C., Hagiwara, A., Hori, M., et al. (2019). Review of synthetic MRI in pediatric brains: Basic principle of MR quantification, its features, clinical applications, and limitations. Journal of Neuroradiology 46(4), 268–275. – reference: Caye, A., Rocha, T. B., Anselmi, L., et al. (2016). Attention-deficit/hyperactivity disorder trajectories from childhood to young adulthood: Evidence from a birth cohort supporting a late-onset syndrome. JAMA Psychiatry, 73(7), 705–712. – reference: Deoni, S. C., Zinkstok, J. R., Daly, E., et al. (2015). White-matter relaxation time and myelin water fraction differences in young adults with autism. Psychological Medicine, 45(4), 795–805. – reference: Jiang, W. H., Duan, K. K., Chen, J. Y., et al. (2019). Structural brain alterations and their association with cognitive function and symptoms in attention-deficit/hyperactivity disorder families. European Neuropsychopharmacology, 29, 1189–1190. – reference: Albajara Saenz, A., Villemonteix, T., & Massat, I. (2019). Structural and functional neuroimaging in attention-deficit/hyperactivity disorder. Development Medicine and Child Neurology, 61(4), 399–405. – reference: Lorio, S., Kherif, F., Ruef, A., et al. (2016). Neurobiological origin of spurious brain morphological changes: A quantitative MRI study. Human Brain Mapping, 37(5), 1801–1815. – ident: 514_CR7 doi: 10.3892/etm.2020.8645 – ident: 514_CR13 doi: 10.1016/S2215-0366(17)30200-6 – ident: 514_CR32 doi: 10.1016/j.nicl.2019.101851 – ident: 514_CR28 doi: 10.1007/s00406-019-01032-x – ident: 514_CR15 doi: 10.1016/j.clinimag.2019.09.005 – ident: 514_CR5 doi: 10.1007/s12035-014-8685-x – ident: 514_CR2 doi: 10.1093/cercor/bhx182 – ident: 514_CR27 doi: 10.1016/B978-0-444-64196-0.00016-9 – ident: 514_CR4 doi: 10.1503/jpn.140377 – ident: 514_CR17 doi: 10.1002/hbm.23137 – ident: 514_CR22 doi: 10.1016/j.neubiorev.2019.02.011 – ident: 514_CR21 doi: 10.1016/j.nicl.2018.11.010 – ident: 514_CR14 doi: 10.1016/j.euroneuro.2018.08.225 – ident: 514_CR25 doi: 10.1016/S0140-6736(15)00238-X – ident: 514_CR6 doi: 10.1001/jamapsychiatry.2016.0383 – ident: 514_CR24 doi: 10.1016/j.pscychresns.2011.07.001 – ident: 514_CR16 doi: 10.1002/hbm.22418 – ident: 514_CR8 doi: 10.1017/S0033291714001858 – ident: 514_CR29 doi: 10.1093/cercor/bhz152 – ident: 514_CR18 doi: 10.1007/s00415-018-9139-6 – ident: 514_CR31 doi: 10.1002/mrm.21635 – ident: 514_CR23 doi: 10.1016/j.neuroimage.2014.02.026 – ident: 514_CR26 doi: 10.1542/peds.2014-3482 – ident: 514_CR30 doi: 10.1038/s41582-020-0312-z – ident: 514_CR1 doi: 10.1111/dmcn.14050 – ident: 514_CR19 doi: 10.1001/jamapsychiatry.2016.0700 – ident: 514_CR9 doi: 10.1016/j.neuroimage.2017.12.087 – ident: 514_CR3 doi: 10.1016/j.neurad.2019.02.005 – ident: 514_CR11 doi: 10.1111/j.1600-0447.2011.01786.x – ident: 514_CR12 doi: 10.3174/ajnr.A4977 – ident: 514_CR10 doi: 10.1016/j.neuroimage.2018.02.055 – ident: 514_CR20 doi: 10.1007/s11065-014-9251-z |
SSID | ssj0054891 |
Score | 2.3087687 |
Snippet | To investigate the quantitative profiles of brain grey matter (GM) in pediatric drug-naïve ADHD patients using synthetic magnetic resonance imaging (SyMRI). A... |
SourceID | proquest pubmed crossref springer |
SourceType | Aggregation Database Index Database Enrichment Source Publisher |
StartPage | 406 |
SubjectTerms | Abnormalities Attention Deficit Disorder with Hyperactivity - diagnostic imaging Attention deficit hyperactivity disorder Biomedical and Life Sciences Biomedicine Brain Brain - diagnostic imaging Brain Mapping Cerebellum Cerebral Cortex Child Correlation analysis Gray Matter - diagnostic imaging Humans Hyperactivity Iron deficiency Magnetic Resonance Imaging Medical imaging Myelin Neuroimaging Neuropsychology Neuroradiology Neurosciences Nutrient deficiency Original Research Patients Pediatrics Pharmaceutical Preparations Psychiatry Substantia grisea |
SummonAdditionalLinks | – databaseName: ProQuest Technology Collection dbid: 8FG link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfV1LTxsxELYoSKgX1FIeobQyUm9gkfVzc0KoagpIqVQEEreVvfYCEjhAkgNX_lB_RP8YM443EUJwXr_WY48_e2a-IeRHzcvCGN9jUqOZsW4Mc_huBZpQWROc8Q5jhwd_9NG5PLlQF_nBbZTdKludmBS1H9b4Rr7PNfpiKW3Ewd09w6xRaF3NKTQ-kKWCQ2cYKd7_3WpiAOMpYx5glIIZpUwOmpmGzhUasCU6KCQKcFa-PJheoc1XltJ0APU_kZWMHOnhVNSfyUKIq2R5kG3jX8jT34mNKWQMFBgdPUaAdlCUDk6PKfI0wTqjcLl-pLeJUpNaFxGv3iRKVXodaRvXTfFtlvqHySWL9v8_aAwrJK9I5gMyToz3r-D6muKrMPUE9ZnCc42c93-d_TxiOcMCq4VRY1Y23HDpCl_yntdCeDjPy-BNA5NTO65twWvZKF1bHoSXRdeVtnGqawGYGeudWCeLcRjDJqHBhyCUDkE3UvbKrrU9J71TttvIRgTTIUU7vVWd6ccxC8ZNNSdORpFUIJIqiaQqO2R3VuduSr7xbuntVmpV3oijar5sOmRn9hm2ENpFbAzDCZRRBg2ESsgO2ZhKe9adgJ8BiAON77Xinzf-9li23h_LV_KRYxhF8v7eJovjh0n4BuBm7L6nFfwM9233PA priority: 102 providerName: ProQuest |
Title | Quantitative synthetic MRI reveals grey matter abnormalities in children with drug-naïve attention-deficit/hyperactivity disorder |
URI | https://link.springer.com/article/10.1007/s11682-021-00514-8 https://www.ncbi.nlm.nih.gov/pubmed/34491528 https://www.proquest.com/docview/2626485673 https://www.proquest.com/docview/2570109534 |
Volume | 16 |
hasFullText | 1 |
inHoldings | 1 |
isFullTextHit | |
isPrint | |
link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3NbtQwELZoKyEu_EMX2spI3MBl4_89btFuC2grqFhpOUV27ABqcVE3OZQjL8RD8GIde51dlQJSL4mUjB3bGdufPTOfEXpeUV0o5QaEy2hmrGpFbNy3gpFQGOWtcjbGDk8O5cGUv52JWQ4Km3fe7p1JMo3Uq2C3QgIajC4FibSb6DW0IWCBAt1xY7j_6d2oG4EBhKeT8gCbFEQJoXKwzN9zuTwhXUGZVyykaeIZ30HTrsgLf5Pj3baxu9WPP9gcr1unu-h2RqJ4uFCde-iGD_fRzUm2tT9APz-0JqQQNBgQ8fw8AFQEUTw5eoMj7xPoLYbF-jn-lig6sbEh4t-TRNGKvwbcxYnjuNeL3Vn7mQTz-xdkFhMkL0vifGSwaF59geVwiteKR1lglylBH6LpePTx9QHJJzaQiinREF1TRbktnKYDJxlzgA-0d6qGalaWSlPQitdCVoZ65njRt9rUVvQNAD1lnGWP0Ho4DX4TYe-8Z0J6L2vOB7pvzMByZ4Xp17xmXvVQ0f22ssp05vFUjZNyRcQcG7eExi1T45a6h14s03xfkHn8V3qr04Yyd-x5SWV0CRRSsR56tnwNXTLaWUzwpy3ICBUNjoLxHnq80KLl5xhUBiATZP6y04hV5v8uy5PriT9Ft2gM00je5VtovTlr_TaAp8buoDU1U3DV4_2d3G_gvjc6fH8ET6d0eAFebRVg |
linkProvider | Springer Nature |
linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV3NbhMxEB6VIgEXxG8JFDASnMBq1r-bA0IIqBLaVAK1Um6LvfYCUtmUJhHKlQeCh-DFmPHuJkIVvfW83lmvZ2x_9sx8A_C0FHlmbRhwZcjNWFaWe7q3wpVQOxu9DZ5yh8cHZnik3k_0ZAN-dbkwFFbZrYlpoQ7Tku7Id4ShWCxtrHx18p1T1SjyrnYlNBqz2IvLH3hkm70cvUX9PhNi993hmyFvqwrwUlo953klrFA-C7kYBCNlwD0sj8FWmclLL4zLRKkqbUonogwq6_vcVV73HYIR64KXKPcSXFbkYsT5YyerAx6C_1ShDzFRxq3Wtk3SaVL1ULzgFBCRKMd5_u9GeAbdnvHMpg1v9wZcb5Eqe92Y1k3YiPUtuDJuffG34eeHhatTihoumGy2rBFKYlM2_jhixAuFds3wML9k3xKFJ3O-Jnx8nChc2deadXnkjO6CWThdfOa1-_MbhdELKQqTh0gMF_OdL3hcTvlcVOqChZYy9A4cXcjY34XNelrHe8BiiFFqE6OplBrkfecGXgWvXb9SlYy2B1k3vEXZ0p1T1Y3jYk3UTCopUCVFUkmR9-D56p2Thuzj3NbbndaKduLPirWZ9uDJ6jFOWfLDuDpOF9hGW3JIaql6sNVoe_U5iT-DkAqFv-jUvxb-_77cP78vj-Hq8HC8X-yPDvYewDVBKRwp8nwbNueni_gQgdXcP0rWzODTRU-fvzolNDU |
linkToPdf | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1LbxMxELZKK1VcEOWZ0oKR4ARWsn5uDhUC2qihJCoVlXrb2msvIJVN2yRCufKH-BHc-FXMON5EqKK3ntfrfYw9D8983xDyouR5ZozvMqkxzVhWhjk8twJNqKwJzniH2OHBUO8fyw8n6mSF_GmwMFhW2ejEqKj9qMQz8jbXWIultBHtKpVFHO723pxfMOwghZnWpp2GTW0W_E6kG0sgj4Mw-wHh3Hinvwuyf8l5b-_z-32WOg6wUhg1YXnFDZcu8znvei2EB_uWB2-qTOel49pmvJSV0qXlQXiZdVxuK6c6FhwVY70TMO8tsmbA6kMguPZub3h41NgFCA1i_z7wmDJmlDIJwjMH8sEDOMNyiUhIzvJ_zeQV3_dK3jaaw95dcif5sfTtfOFtkJVQ3yPrg5Spv09-fpraOgLYQJ3S8awGRxOG0sFRnyJrFKx6CqH-jH6PBJ_Uuhq957NI8Eq_1bRBmVM8Kab-cvqF1fb3L5gMb4g1mswH5L-YtL9CMB3RXtgIg_pEKPqAHN_I339IVutRHR4TGnwIQukQdCVlN-9Y23XSO2U7laxEMC2SNb-3KBMZOvbkOCuWNM4okgJEUkSRFHmLvFrccz6nArl29FYjtSKphXGxXMQt8nxxGTY0ZmlsHUZTGKMMpiuVkC3yaC7txeMEfAw4XDD560b8y8n__y6b17_LM7IOW6n42B8ePCG3OeI7Yln6FlmdXE7DNnhdE_c0LWdKTm96B_0F7VE_EA |
openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Quantitative+synthetic+MRI+reveals+grey+matter+abnormalities+in+children+with+drug-na%C3%AFve+attention-deficit%2Fhyperactivity+disorder&rft.jtitle=Brain+imaging+and+behavior&rft.au=Su%2C+Shu&rft.au=Chen%2C+Yingqian&rft.au=Dai%2C+Yan&rft.au=Lin%2C+Liping&rft.date=2022-02-01&rft.issn=1931-7557&rft.eissn=1931-7565&rft.volume=16&rft.issue=1&rft.spage=406&rft.epage=414&rft_id=info:doi/10.1007%2Fs11682-021-00514-8&rft.externalDBID=n%2Fa&rft.externalDocID=10_1007_s11682_021_00514_8 |
thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1931-7557&client=summon |
thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1931-7557&client=summon |
thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1931-7557&client=summon |