A multi-shell multi-tissue diffusion study of brain connectivity in early multiple sclerosis
The potential of multi-shell diffusion imaging to produce accurate brain connectivity metrics able to unravel key pathophysiological processes in multiple sclerosis (MS) has scarcely been investigated. To test, in patients with a clinically isolated syndrome (CIS), whether multi-shell imaging-derive...
Gespeichert in:
| Veröffentlicht in: | Multiple sclerosis Jg. 26; H. 7; S. 774 |
|---|---|
| Hauptverfasser: | , , , , , , , , , , , , , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
England
01.06.2020
|
| Schlagworte: | |
| ISSN: | 1477-0970, 1477-0970 |
| Online-Zugang: | Weitere Angaben |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| Abstract | The potential of multi-shell diffusion imaging to produce accurate brain connectivity metrics able to unravel key pathophysiological processes in multiple sclerosis (MS) has scarcely been investigated.
To test, in patients with a clinically isolated syndrome (CIS), whether multi-shell imaging-derived connectivity metrics can differentiate patients from controls, correlate with clinical measures, and perform better than metrics obtained with conventional single-shell protocols.
Nineteen patients within 3 months from the CIS and 12 healthy controls underwent anatomical and 53-direction multi-shell diffusion-weighted 3T images. Patients were cognitively assessed. Voxel-wise fibre orientation distribution functions were estimated and used to obtain network metrics. These were also calculated using a conventional single-shell diffusion protocol. Through linear regression, we obtained effect sizes and standardised regression coefficients.
Patients had lower mean nodal strength (
= 0.003) and greater network modularity than controls (
= 0.045). Greater modularity was associated with worse cognitive performance in patients, even after accounting for lesion load (
= 0.002). Multi-shell-derived metrics outperformed single-shell-derived ones.
Connectivity-based nodal strength and network modularity are abnormal in the CIS. Furthermore, the increased network modularity observed in patients, indicating microstructural damage, is clinically relevant. Connectivity analyses based on multi-shell imaging can detect potentially relevant network changes in early MS. |
|---|---|
| AbstractList | The potential of multi-shell diffusion imaging to produce accurate brain connectivity metrics able to unravel key pathophysiological processes in multiple sclerosis (MS) has scarcely been investigated.BACKGROUNDThe potential of multi-shell diffusion imaging to produce accurate brain connectivity metrics able to unravel key pathophysiological processes in multiple sclerosis (MS) has scarcely been investigated.To test, in patients with a clinically isolated syndrome (CIS), whether multi-shell imaging-derived connectivity metrics can differentiate patients from controls, correlate with clinical measures, and perform better than metrics obtained with conventional single-shell protocols.OBJECTIVETo test, in patients with a clinically isolated syndrome (CIS), whether multi-shell imaging-derived connectivity metrics can differentiate patients from controls, correlate with clinical measures, and perform better than metrics obtained with conventional single-shell protocols.Nineteen patients within 3 months from the CIS and 12 healthy controls underwent anatomical and 53-direction multi-shell diffusion-weighted 3T images. Patients were cognitively assessed. Voxel-wise fibre orientation distribution functions were estimated and used to obtain network metrics. These were also calculated using a conventional single-shell diffusion protocol. Through linear regression, we obtained effect sizes and standardised regression coefficients.METHODSNineteen patients within 3 months from the CIS and 12 healthy controls underwent anatomical and 53-direction multi-shell diffusion-weighted 3T images. Patients were cognitively assessed. Voxel-wise fibre orientation distribution functions were estimated and used to obtain network metrics. These were also calculated using a conventional single-shell diffusion protocol. Through linear regression, we obtained effect sizes and standardised regression coefficients.Patients had lower mean nodal strength (p = 0.003) and greater network modularity than controls (p = 0.045). Greater modularity was associated with worse cognitive performance in patients, even after accounting for lesion load (p = 0.002). Multi-shell-derived metrics outperformed single-shell-derived ones.RESULTSPatients had lower mean nodal strength (p = 0.003) and greater network modularity than controls (p = 0.045). Greater modularity was associated with worse cognitive performance in patients, even after accounting for lesion load (p = 0.002). Multi-shell-derived metrics outperformed single-shell-derived ones.Connectivity-based nodal strength and network modularity are abnormal in the CIS. Furthermore, the increased network modularity observed in patients, indicating microstructural damage, is clinically relevant. Connectivity analyses based on multi-shell imaging can detect potentially relevant network changes in early MS.CONCLUSIONConnectivity-based nodal strength and network modularity are abnormal in the CIS. Furthermore, the increased network modularity observed in patients, indicating microstructural damage, is clinically relevant. Connectivity analyses based on multi-shell imaging can detect potentially relevant network changes in early MS. The potential of multi-shell diffusion imaging to produce accurate brain connectivity metrics able to unravel key pathophysiological processes in multiple sclerosis (MS) has scarcely been investigated. To test, in patients with a clinically isolated syndrome (CIS), whether multi-shell imaging-derived connectivity metrics can differentiate patients from controls, correlate with clinical measures, and perform better than metrics obtained with conventional single-shell protocols. Nineteen patients within 3 months from the CIS and 12 healthy controls underwent anatomical and 53-direction multi-shell diffusion-weighted 3T images. Patients were cognitively assessed. Voxel-wise fibre orientation distribution functions were estimated and used to obtain network metrics. These were also calculated using a conventional single-shell diffusion protocol. Through linear regression, we obtained effect sizes and standardised regression coefficients. Patients had lower mean nodal strength ( = 0.003) and greater network modularity than controls ( = 0.045). Greater modularity was associated with worse cognitive performance in patients, even after accounting for lesion load ( = 0.002). Multi-shell-derived metrics outperformed single-shell-derived ones. Connectivity-based nodal strength and network modularity are abnormal in the CIS. Furthermore, the increased network modularity observed in patients, indicating microstructural damage, is clinically relevant. Connectivity analyses based on multi-shell imaging can detect potentially relevant network changes in early MS. |
| Author | Ciccarelli, Olga Kanber, Baris Ourselin, Sébastien Collorone, Sara Altmann, Daniel R Clayden, Jonathan D Charalambous, Thalis Grussu, Francesco Tur, Carmen Cawley, Niamh Barkhof, Frederik Wheeler-Kingshott, Claudia Am Gandini Prados, Ferran Toosy, Ahmed T |
| Author_xml | – sequence: 1 givenname: Carmen orcidid: 0000-0003-1849-3184 surname: Tur fullname: Tur, Carmen organization: Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, University College London (UCL), London, UK – sequence: 2 givenname: Francesco orcidid: 0000-0002-0945-3909 surname: Grussu fullname: Grussu, Francesco organization: Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, University College London (UCL), London, UK/Centre for Medical Image Computing, Department of Computer Science, University College London (UCL), London, UK – sequence: 3 givenname: Ferran surname: Prados fullname: Prados, Ferran organization: Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, University College London (UCL), London, UK/Translational Imaging Group, Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London (UCL), London, UK – sequence: 4 givenname: Thalis orcidid: 0000-0002-6919-4486 surname: Charalambous fullname: Charalambous, Thalis organization: Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, University College London (UCL), London, UK – sequence: 5 givenname: Sara orcidid: 0000-0003-1506-8983 surname: Collorone fullname: Collorone, Sara organization: Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, University College London (UCL), London, UK – sequence: 6 givenname: Baris surname: Kanber fullname: Kanber, Baris organization: Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, University College London (UCL), London, UK/Translational Imaging Group, Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London (UCL), London, UK – sequence: 7 givenname: Niamh surname: Cawley fullname: Cawley, Niamh organization: Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, University College London (UCL), London, UK – sequence: 8 givenname: Daniel R surname: Altmann fullname: Altmann, Daniel R organization: Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, University College London (UCL), London, UK/Department of Medical Statistics, London School of Hygiene and Tropical Medicine, University of London, London, UK – sequence: 9 givenname: Sébastien surname: Ourselin fullname: Ourselin, Sébastien organization: Translational Imaging Group, Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London (UCL), London, UK/School of Biomedical Engineering & Imaging Sciences, Faculty of Life Sciences and Medicine, King's College London, London, UK – sequence: 10 givenname: Frederik surname: Barkhof fullname: Barkhof, Frederik organization: Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, University College London (UCL), London, UK/Translational Imaging Group, Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London (UCL), London, UK/Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, The Netherlands/National Institute for Health Research University College London Hospitals Biomedical Research Centre, London, UK – sequence: 11 givenname: Jonathan D surname: Clayden fullname: Clayden, Jonathan D organization: UCL Great Ormond Street Institute of Child Health, University College London (UCL), London, UK – sequence: 12 givenname: Ahmed T surname: Toosy fullname: Toosy, Ahmed T organization: Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, University College London (UCL), London, UK – sequence: 13 givenname: Claudia Am Gandini surname: Wheeler-Kingshott fullname: Wheeler-Kingshott, Claudia Am Gandini organization: Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, University College London (UCL), London, UK/Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy; Brain MRI 3T Research Centre, IRCCS Mondino Foundation, Pavia, Italy – sequence: 14 givenname: Olga surname: Ciccarelli fullname: Ciccarelli, Olga organization: Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, University College London (UCL), London, UK/National Institute for Health Research University College London Hospitals Biomedical Research Centre, London, UK |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/31074686$$D View this record in MEDLINE/PubMed |
| BookMark | eNpNUEtLxDAYDKK4D717khy9VL88mrTHZfEFC170JpRs8gUjabo2rdB_78qu4GlmYGZgZkFOU5eQkCsGt4xpfcdEyWVZlayuZMmgPCFzJrUuoNZw-o_PyCLnTwDQWpTnZCYYaKkqNSfvK9qOcQhF_sAYj3wIOY9IXfB-zKFLNA-jm2jn6bY3IVHbpYR2CN9hmOheo-njdMjuItJsI_ZdDvmCnHkTM14ecUneHu5f10_F5uXxeb3aFFYqPhTGCMcsAEqotANdmdozxZAbrzhTwCuhvUdptYHaIQNvnENwTvGtQyH5ktwcend99zViHpo2ZLvfYxJ2Y244F6zeN9a_1uujddy26JpdH1rTT83fI_wHgNBmWg |
| CitedBy_id | crossref_primary_10_3389_fninf_2023_1060511 crossref_primary_10_1016_j_nicl_2021_102904 crossref_primary_10_3390_app14167001 crossref_primary_10_1002_jnr_25028 crossref_primary_10_1016_j_ijrobp_2025_03_019 crossref_primary_10_1016_j_nicl_2022_103108 crossref_primary_10_3389_fneur_2021_671894 crossref_primary_10_1162_netn_a_00276 crossref_primary_10_1177_13524585241247785 crossref_primary_10_1038_s41598_019_56806_z crossref_primary_10_1038_s41598_020_60611_4 crossref_primary_10_1177_15459683251318246 crossref_primary_10_1016_j_nic_2024_03_008 crossref_primary_10_1007_s00234_021_02732_9 crossref_primary_10_3389_fneur_2023_1172807 |
| ContentType | Journal Article |
| DBID | CGR CUY CVF ECM EIF NPM 7X8 |
| DOI | 10.1177/1352458519845105 |
| DatabaseName | Medline MEDLINE MEDLINE (Ovid) MEDLINE MEDLINE PubMed MEDLINE - Academic |
| DatabaseTitle | MEDLINE Medline Complete MEDLINE with Full Text PubMed MEDLINE (Ovid) MEDLINE - Academic |
| DatabaseTitleList | MEDLINE - Academic MEDLINE |
| Database_xml | – sequence: 1 dbid: NPM name: PubMed url: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 2 dbid: 7X8 name: MEDLINE - Academic url: https://search.proquest.com/medline sourceTypes: Aggregation Database |
| DeliveryMethod | no_fulltext_linktorsrc |
| Discipline | Medicine |
| EISSN | 1477-0970 |
| ExternalDocumentID | 31074686 |
| Genre | Research Support, Non-U.S. Gov't Journal Article |
| GrantInformation_xml | – fundername: Wellcome Trust grantid: 203148 – fundername: Medical Research Council grantid: MR/S026088/1 – fundername: Medical Research Council grantid: MR/J01107X/1 |
| GroupedDBID | --- -TM .2E .2F .2G .2J .2N 01A 0R~ 123 18M 1~K 29M 31R 31S 31U 31X 31Y 31Z 36B 39C 4.4 53G 54M 5VS 7X7 88E 8FI 8FJ 8R4 8R5 AABMB AABOD AACKU AACMV AACTG AADUE AAEJI AAEWN AAGGD AAGLT AAGMC AAJIQ AAJOX AAJPV AAKGS AANSI AAPEO AAPII AAQDB AAQXH AAQXI AARDL AARIX AATAA AATBZ AAUAS AAXOT AAYTG AAZBJ ABAFQ ABAWC ABAWP ABCCA ABCJG ABDWY ABEIX ABFWQ ABHFT ABHKI ABHQH ABIDT ABJIS ABJNI ABJZC ABKRH ABLUO ABNCE ABPGX ABPNF ABQKF ABQXT ABRHV ABUJY ABUWG ABVFX ABVVC ABYTW ACARO ACDSZ ACDXX ACFEJ ACFMA ACFYK ACGBL ACGFO ACGFS ACGZU ACJER ACJTF ACLFY ACLHI ACLZU ACNXM ACOFE ACOXC ACPRK ACROE ACRPL ACSIQ ACUAV ACUIR ACXKE ACXMB ADBBV ADDLC ADEBD ADEIA ADMPF ADNBR ADNMO ADNON ADRRZ ADSTG ADTBJ ADUCT ADUKL ADVBO ADYCS ADZYD ADZZY AECGH AECVZ AEDTQ AEKYL AENEX AEPTA AEQLS AERKM AESZF AEUHG AEWDL AEWHI AEXFG AEXNY AFEET AFKBI AFKRA AFKRG AFMOU AFQAA AFUIA AFVCE AFWMB AGHKR AGKLV AGNHF AGPXR AGQPQ AGWFA AGWNL AHDMH AHHFK AHMBA AIGRN AJABX AJEFB AJGYC AJMMQ AJSCY AJUZI AJVBE AJXAJ AJXGE ALIPV ALKWR ALMA_UNASSIGNED_HOLDINGS AMCVQ ANDLU ARTOV ASPBG AUTPY AVWKF AYAKG AZFZN AZQEC B3H B8M B8O B8R B8Z B93 B94 BBRGL BDDNI BENPR BKIIM BKNYI BKSCU BPACV BPHCQ BSEHC BVXVI BWJAD BYIEH CAG CBRKF CCPQU CDWPY CFDXU CGR COF CORYS CQQTX CS3 CUTAK CUY CVF DB0 DC- DC0 DD- DD0 DE- DF0 DO- DOPDO DU5 DV7 DV9 D~Y EBS ECM EIF EJD EMOBN F5P FD6 FEDTE FHBDP FYUFA GROUPED_SAGE_PREMIER_JOURNAL_COLLECTION H13 HF~ HMCUK HVGLF HZ~ J8X K.F K.J K9- M0R M1P N9A NPM O9- P.B P2P PHGZM PHGZT PJZUB PPXIY PQQKQ PROAC PSQYO Q1R Q2X Q7K Q7L Q7R Q7U Q7X Q82 Q83 ROL S01 SASJQ SAUOL SCNPE SDB SFB SFC SFK SFN SFT SGA SGO SGP SGR SGV SGX SGZ SHG SNB SPJ SPQ SPV SQCSI STM UKHRP XJT ZONMY ZPPRI ZRKOI ZSSAH 7X8 AJHME |
| ID | FETCH-LOGICAL-c462t-aa3d1c00e4087d078a9f161e2af621602837ffe4c7a09de10fadde0dd62bde342 |
| IEDL.DBID | 7X8 |
| ISICitedReferencesCount | 17 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000540055900007&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 1477-0970 |
| IngestDate | Thu Oct 02 11:36:18 EDT 2025 Mon Jul 21 06:02:47 EDT 2025 |
| IsDoiOpenAccess | false |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 7 |
| Keywords | Diffusion-weighted imaging multi-shell acquisitions tractography multi-shell multi-tissue constrained spherical deconvolution clinically isolated syndrome multiple sclerosis |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c462t-aa3d1c00e4087d078a9f161e2af621602837ffe4c7a09de10fadde0dd62bde342 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
| ORCID | 0000-0003-1849-3184 0000-0003-1506-8983 0000-0002-0945-3909 0000-0002-6919-4486 |
| OpenAccessLink | https://www.ncbi.nlm.nih.gov/pmc/articles/7611366 |
| PMID | 31074686 |
| PQID | 2231916194 |
| PQPubID | 23479 |
| ParticipantIDs | proquest_miscellaneous_2231916194 pubmed_primary_31074686 |
| PublicationCentury | 2000 |
| PublicationDate | 2020-06-01 |
| PublicationDateYYYYMMDD | 2020-06-01 |
| PublicationDate_xml | – month: 06 year: 2020 text: 2020-06-01 day: 01 |
| PublicationDecade | 2020 |
| PublicationPlace | England |
| PublicationPlace_xml | – name: England |
| PublicationTitle | Multiple sclerosis |
| PublicationTitleAlternate | Mult Scler |
| PublicationYear | 2020 |
| SSID | ssj0007735 |
| Score | 2.389672 |
| Snippet | The potential of multi-shell diffusion imaging to produce accurate brain connectivity metrics able to unravel key pathophysiological processes in multiple... |
| SourceID | proquest pubmed |
| SourceType | Aggregation Database Index Database |
| StartPage | 774 |
| SubjectTerms | Adult Cognitive Dysfunction - diagnostic imaging Cognitive Dysfunction - etiology Cognitive Dysfunction - pathology Diffusion Tensor Imaging - methods Female Gray Matter - diagnostic imaging Gray Matter - pathology Humans Male Middle Aged Multiple Sclerosis - complications Multiple Sclerosis - diagnostic imaging Multiple Sclerosis - pathology Nerve Net - diagnostic imaging Nerve Net - pathology Retrospective Studies White Matter - diagnostic imaging White Matter - pathology |
| Title | A multi-shell multi-tissue diffusion study of brain connectivity in early multiple sclerosis |
| URI | https://www.ncbi.nlm.nih.gov/pubmed/31074686 https://www.proquest.com/docview/2231916194 |
| Volume | 26 |
| WOSCitedRecordID | wos000540055900007&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV07a8MwEBZtU0qXvh_pCxW6ikiyIllTCaWhQxMytJChYBQ9oIud1El_f3WyQ6ZCoYuxB2P7dLr77uH7EHrg3NtcWkv6tu-J8NIQE3JKwDdIaeHnxTQy_1WNx_l0qidtwq1u2yrXNjEZaldZyJH3ohuLoQXE3I_zBQHWKKiuthQa26iTRSgDG1NNN9PClUoEm0woRahWdFOm7LEIPASUxHQuAGP8DjCToxke_vcVj9BBCzHxoNGJY7TlyxO0N2qL6KfoY4BTGyGpoQm0PV-mBcDAl7KCBBpOc2dxFfAMSCSwhYYY21BN4HjtYTAyXrcj4jo-Kfrbz_oMvQ-f355eSEuyQKyQfEmMyRyzlHpBc-UiYDA6xG_w3ATJmQT4oULwwipDtfOMBrCI1DnJZ85ngp-jnbIq_SXCOsx0zryOGEEJrYJ2NlN9Jp1mwQptuuh-LbciKjFUJkzpq1VdbCTXRReN8It5M22jyKBlVOby6g93X6N9DvFwypLcoE6IW9jfol37HaX4dZe0Ix7Hk9EPWAXE9Q |
| linkProvider | ProQuest |
| 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=A+multi-shell+multi-tissue+diffusion+study+of+brain+connectivity+in+early+multiple+sclerosis&rft.jtitle=Multiple+sclerosis&rft.au=Tur%2C+Carmen&rft.au=Grussu%2C+Francesco&rft.au=Prados%2C+Ferran&rft.au=Charalambous%2C+Thalis&rft.date=2020-06-01&rft.eissn=1477-0970&rft.volume=26&rft.issue=7&rft.spage=774&rft_id=info:doi/10.1177%2F1352458519845105&rft_id=info%3Apmid%2F31074686&rft_id=info%3Apmid%2F31074686&rft.externalDocID=31074686 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1477-0970&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1477-0970&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1477-0970&client=summon |