Prognostic imaging biomarkers for diabetic kidney disease (iBEAt): study protocol

dc.contributor.authorGooding KM
dc.contributor.authorLienczewski C
dc.contributor.authorPapale M
dc.contributor.authorKoivuviita N
dc.contributor.authorMaziarz M
dc.contributor.authorAndersson AMD
dc.contributor.authorSharma K
dc.contributor.authorPontrelli P
dc.contributor.authorHernandez AG
dc.contributor.authorBailey J
dc.contributor.authorTobin K
dc.contributor.authorSaunavaara V
dc.contributor.authorZetterqvist A
dc.contributor.authorShelley D
dc.contributor.authorTeh I
dc.contributor.authorBall C
dc.contributor.authorPuppala S
dc.contributor.authorIbberson M
dc.contributor.authorKarihaloo A
dc.contributor.authorMetsarinne K
dc.contributor.authorBanks RE
dc.contributor.authorGilmour PS
dc.contributor.authorMansfield M
dc.contributor.authorGilchrist M
dc.contributor.authorde Zeeuw D
dc.contributor.authorHeerspink HJL
dc.contributor.authorNuutila P
dc.contributor.authorKretzler M
dc.contributor.authorSmith MW
dc.contributor.authorGesualdo L
dc.contributor.authorAndress D
dc.contributor.authorGrenier N
dc.contributor.authorShore AC
dc.contributor.authorGomez MF
dc.contributor.authorSourbron S
dc.contributor.organizationfi=PET-keskus|en=Turku PET Centre|
dc.contributor.organizationfi=biolääketieteen laitos|en=Institute of Biomedicine|
dc.contributor.organizationfi=kliininen laitos|en=Department of Clinical Medicine|
dc.contributor.organizationfi=sisätautioppi|en=Internal Medicine|
dc.contributor.organizationfi=tyks, vsshp|en=tyks, varha|
dc.contributor.organization-code1.2.246.10.2458963.20.14646305228
dc.contributor.organization-code1.2.246.10.2458963.20.40502528769
dc.contributor.organization-code1.2.246.10.2458963.20.61334543354
dc.contributor.organization-code1.2.246.10.2458963.20.77952289591
dc.converis.publication-id49030645
dc.converis.urlhttps://research.utu.fi/converis/portal/Publication/49030645
dc.date.accessioned2022-10-28T12:32:01Z
dc.date.available2022-10-28T12:32:01Z
dc.description.abstract<b>Background:</b> Diabetic kidney disease (DKD) remains one of the leading causes of premature death in diabetes. DKD is classified on albuminuria and reduced kidney function (estimated glomerular filtration rate (eGFR)) but these have modest value for predicting future renal status. There is an unmet need for biomarkers that can be used in clinical settings which also improve prediction of renal decline on top of routinely available data, particularly in the early stages. The iBEAt study of the BEAt-DKD project aims to determine whether renal imaging biomarkers (magnetic resonance imaging (MRI) and ultrasound (US)) provide insight into the pathogenesis and heterogeneity of DKD (primary aim) and whether they have potential as prognostic biomarkers in DKD (secondary aim). <div><br /></div><div><b>Methods:</b> iBEAt is a prospective multi-centre observational cohort study recruiting 500 patients with type 2 diabetes (T2D) and eGFR >= 30 ml/min/1.73m(2). At baseline, blood and urine will be collected, clinical examinations will be performed, and medical history will be obtained. These assessments will be repeated annually for 3 years. At baseline each participant will also undergo quantitative renal MRI and US with central processing of MRI images. Biological samples will be stored in a central laboratory for biomarker and validation studies, and data in a central data depository. Data analysis will explore the potential associations between imaging biomarkers and renal function, and whether the imaging biomarkers improve the prediction of DKD progression. Ancillary substudies will: (1) validate imaging biomarkers against renal histopathology; (2) validate MRI based renal blood flow measurements against H<sub>2</sub>O<sup>15 </sup>positron-emission tomography (PET); (3) validate methods for (semi-)automated processing of renal MRI; (4) examine longitudinal changes in imaging biomarkers; (5) examine whether glycocalyx and microvascular measures are associated with imaging biomarkers and eGFR decline; (6) explore whether the findings in T2D can be extrapolated to type 1 diabetes. </div><div><b><br /></b></div><div><b>Discussion:</b> iBEAt is the largest DKD imaging study to date and will provide valuable insights into the progression and heterogeneity of DKD. The results may contribute to a more personalised approach to DKD management in patients with T2D.</div>
dc.identifier.eissn1471-2369
dc.identifier.jour-issn1471-2369
dc.identifier.olddbid177098
dc.identifier.oldhandle10024/160192
dc.identifier.urihttps://www.utupub.fi/handle/11111/32928
dc.identifier.urnURN:NBN:fi-fe2021042713291
dc.language.isoen
dc.okm.affiliatedauthorKoivuviita, Niina
dc.okm.affiliatedauthorSaunavaara, Virva
dc.okm.affiliatedauthorMetsärinne, Kaj
dc.okm.affiliatedauthorNuutila, Pirjo
dc.okm.affiliatedauthorDataimport, tyks, vsshp
dc.okm.discipline3121 Internal medicineen_GB
dc.okm.discipline3126 Surgery, anesthesiology, intensive care, radiologyen_GB
dc.okm.discipline3121 Sisätauditfi_FI
dc.okm.discipline3126 Kirurgia, anestesiologia, tehohoito, radiologiafi_FI
dc.okm.internationalcopublicationinternational co-publication
dc.okm.internationalityInternational publication
dc.okm.typeA1 ScientificArticle
dc.publisherBMC
dc.publisher.countryUnited Kingdomen_GB
dc.publisher.countryBritanniafi_FI
dc.publisher.country-codeGB
dc.relation.articlenumber242
dc.relation.doi10.1186/s12882-020-01901-x
dc.relation.ispartofjournalBMC Nephrology
dc.relation.issue1
dc.relation.volume21
dc.source.identifierhttps://www.utupub.fi/handle/10024/160192
dc.titlePrognostic imaging biomarkers for diabetic kidney disease (iBEAt): study protocol
dc.year.issued2020

Tiedostot

Näytetään 1 - 1 / 1
Ladataan...
Name:
s12882-020-01901-x.pdf
Size:
790.91 KB
Format:
Adobe Portable Document Format
Description:
Publishers's PDF