Hepatectomy risk assessment with functional magnetic resonance imaging (HEPARIM).

Functional MRI Future liver remnant Gadoxetate Indocyanine green Post hepatectomy liver failure Risk assessment

Journal

BMC cancer
ISSN: 1471-2407
Titre abrégé: BMC Cancer
Pays: England
ID NLM: 100967800

Informations de publication

Date de publication:
23 Oct 2021
Historique:
received: 28 02 2021
accepted: 04 10 2021
entrez: 24 10 2021
pubmed: 25 10 2021
medline: 12 2 2022
Statut: epublish

Résumé

Post hepatectomy liver failure (PHLF) remains a significant risk in patients undergoing curative liver resection for cancer, however currently available PHLF risk prediction investigations are not sufficiently accurate. The Hepatectomy risk assessment with functional magnetic resonance imaging trial (HEPARIM) aims to establish if quantitative MRI biomarkers of liver function & perfusion can be used to more accurately predict PHLF risk and FLR function, measured against indocyanine green (ICG) liver function test. HEPARIM is an observational cohort study recruiting patients undergoing liver resection of 2 segments or more, prior to surgery patients will have both Dynamic Gadoxetate-enhanced (DGE) liver MRI and ICG testing. Day one post op ICG testing is repeated and R15 compared to the Gadoxetate Clearance (GC) of the future liver remnant (FLR-GC) as measure by preoperative DGE- MRI which is the primary outcome, and preoperative ICG R15 compared to GC of whole liver (WL-GC) as a secondary outcome. Data will be collected from medical records, biochemistry, pathology and radiology reports and used in a multi-variate analysis to the value of functional MRI and derive multivariant prediction models for future validation. If successful, this test will potentially provide an efficient means to quantitatively assess FLR function and PHLF risk enabling surgeons to push boundaries of liver surgery further while maintaining safe practice and thereby offering chance of cure to patients who would previously been deemed inoperable. MRI has the added benefit of already being part of the routine diagnostic pathway and as such would have limited additional burden on patients time or cost to health care systems. (Hepatectomy Risk Assessment With Functional Magnetic Resonance Imaging - Full Text View - ClinicalTrials.gov , n.d.) TRIAL REGISTRATION: ClinicalTrials.gov, ClinicalTrials.gov NCT04705194 - Registered 12th January 2021 - Retrospectively registered.

Sections du résumé

BACKGROUND BACKGROUND
Post hepatectomy liver failure (PHLF) remains a significant risk in patients undergoing curative liver resection for cancer, however currently available PHLF risk prediction investigations are not sufficiently accurate. The Hepatectomy risk assessment with functional magnetic resonance imaging trial (HEPARIM) aims to establish if quantitative MRI biomarkers of liver function & perfusion can be used to more accurately predict PHLF risk and FLR function, measured against indocyanine green (ICG) liver function test.
METHODS METHODS
HEPARIM is an observational cohort study recruiting patients undergoing liver resection of 2 segments or more, prior to surgery patients will have both Dynamic Gadoxetate-enhanced (DGE) liver MRI and ICG testing. Day one post op ICG testing is repeated and R15 compared to the Gadoxetate Clearance (GC) of the future liver remnant (FLR-GC) as measure by preoperative DGE- MRI which is the primary outcome, and preoperative ICG R15 compared to GC of whole liver (WL-GC) as a secondary outcome. Data will be collected from medical records, biochemistry, pathology and radiology reports and used in a multi-variate analysis to the value of functional MRI and derive multivariant prediction models for future validation.
DISCUSSION CONCLUSIONS
If successful, this test will potentially provide an efficient means to quantitatively assess FLR function and PHLF risk enabling surgeons to push boundaries of liver surgery further while maintaining safe practice and thereby offering chance of cure to patients who would previously been deemed inoperable. MRI has the added benefit of already being part of the routine diagnostic pathway and as such would have limited additional burden on patients time or cost to health care systems. (Hepatectomy Risk Assessment With Functional Magnetic Resonance Imaging - Full Text View - ClinicalTrials.gov , n.d.) TRIAL REGISTRATION: ClinicalTrials.gov, ClinicalTrials.gov NCT04705194 - Registered 12th January 2021 - Retrospectively registered.

Identifiants

pubmed: 34688256
doi: 10.1186/s12885-021-08830-4
pii: 10.1186/s12885-021-08830-4
pmc: PMC8541801
doi:

Banques de données

ClinicalTrials.gov
['NCT04705194']

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

1139

Subventions

Organisme : Medical Research Council
ID : MR/P023398/1
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/P023398/2
Pays : United Kingdom
Organisme : Medical Research Council
ID : Grant Ref: MR/P023398/1
Pays : United Kingdom

Informations de copyright

© 2021. The Author(s).

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Auteurs

Mohamed Elsharif (M)

Leeds Teaching Hospitals NHS Trust, St James University teaching Hospital, Level 6, Bexley Wing. St James's Hospital, Beckett Street, Leeds, LS9 7TF, England. m.elsharif@nhs.net.

Matthew Roche (M)

Leeds Teaching Hospitals NHS Trust, St James University teaching Hospital, Level 6, Bexley Wing. St James's Hospital, Beckett Street, Leeds, LS9 7TF, England.

Daniel Wilson (D)

Leeds Teaching Hospitals NHS Trust, St James University teaching Hospital, Level 6, Bexley Wing. St James's Hospital, Beckett Street, Leeds, LS9 7TF, England.

Susmita Basak (S)

Biomedical Imaging Sciences Department, Leeds Institute of Cardiovascular and Metabolic Medicine LIGHT Laboratories, University of Leeds, Leeds, LS2 9JT, England.

Ian Rowe (I)

Leeds Teaching Hospitals NHS Trust, St James University teaching Hospital, Level 6, Bexley Wing. St James's Hospital, Beckett Street, Leeds, LS9 7TF, England.

Dhakshina Vijayanand (D)

Leeds Teaching Hospitals NHS Trust, St James University teaching Hospital, Level 6, Bexley Wing. St James's Hospital, Beckett Street, Leeds, LS9 7TF, England.

Richard Feltbower (R)

Leeds Institute for Data Analytics, School of Medicine, University of Leeds, Worsley Building, Clarendon Way, Leeds, LS2 9NL, England.

Darren Treanor (D)

Leeds Teaching Hospitals NHS Trust, St James University teaching Hospital, Level 6, Bexley Wing. St James's Hospital, Beckett Street, Leeds, LS9 7TF, England.
Department of Clinical Pathology, and Department of Clinical and Experimental Medicine, Linköping University, Linköping, Sweden.
Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden.
Level 4, Welcome Trust Brenner Building, St. James's University Hospital, Leeds, LS9 7TF, England.

Lee Roberts (L)

Cardiovascular and Diabetes Research, Leeds Institute of Cardiovascular and Metabolic Medicine LIGHT Laboratories, University of Leeds, LS2 9JT, Leeds, England.

Ashley Guthrie (A)

Leeds Teaching Hospitals NHS Trust, St James University teaching Hospital, Level 6, Bexley Wing. St James's Hospital, Beckett Street, Leeds, LS9 7TF, England.

Raj Prasad (R)

Leeds Teaching Hospitals NHS Trust, St James University teaching Hospital, Level 6, Bexley Wing. St James's Hospital, Beckett Street, Leeds, LS9 7TF, England.

Mark S Gilthorpe (MS)

Leeds Teaching Hospitals NHS Trust, St James University teaching Hospital, Level 6, Bexley Wing. St James's Hospital, Beckett Street, Leeds, LS9 7TF, England.

Magdy Attia (M)

Leeds Teaching Hospitals NHS Trust, St James University teaching Hospital, Level 6, Bexley Wing. St James's Hospital, Beckett Street, Leeds, LS9 7TF, England.

Steven Sourbron (S)

IICD - Sheffield, Sheffield, England.

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Classifications MeSH