Evidence map›Paper›PMID 34688256›Full record

ArticleBMC cancer2021

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

Mohamed Elsharif, Matthew Roche, Daniel Wilson, Susmita Basak, Ian Rowe, Dhakshina Vijayanand, Richard Feltbower, Darren Treanor, Lee Roberts, Ashley Guthrie and 4 more

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in BMC cancer, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04705194 (Hepatectomy Risk Assessment With Functional Magnetic Resonance Imaging), which is not on this map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.6field-weighted citation impact, top 32% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT04705194 unknown statusnot on this map

Hepatectomy Risk Assessment With Functional Magnetic Resonance Imaging

TypeobservationalSponsorUniversity of LeedsRan2019 to 2022Enrolled134ConditionsHepatectomy, Liver Failure, Liver Cancer, Liver MetastasesArmsHepatectomy, PVE or ALPPS
3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 5 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors at 3 institutions in 3 countries.

Mohamed ElsharifLeeds 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.ORCID http://orcid.org/0000-0002-8413-1862
Matthew RocheLeeds Teaching Hospitals NHS Trust, St James University teaching Hospital, Level 6, Bexley Wing. St James's Hospital, Beckett Street, Leeds, LS9 7TF, England.
Daniel WilsonLeeds Teaching Hospitals NHS Trust, St James University teaching Hospital, Level 6, Bexley Wing. St James's Hospital, Beckett Street, Leeds, LS9 7TF, England.
Susmita BasakBiomedical Imaging Sciences Department, Leeds Institute of Cardiovascular and Metabolic Medicine LIGHT Laboratories, University of Leeds, Leeds, LS2 9JT, England.
Ian RoweLeeds Teaching Hospitals NHS Trust, St James University teaching Hospital, Level 6, Bexley Wing. St James's Hospital, Beckett Street, Leeds, LS9 7TF, England.
Dhakshina VijayanandLeeds Teaching Hospitals NHS Trust, St James University teaching Hospital, Level 6, Bexley Wing. St James's Hospital, Beckett Street, Leeds, LS9 7TF, England.
Richard FeltbowerLeeds Institute for Data Analytics, School of Medicine, University of Leeds, Worsley Building, Clarendon Way, Leeds, LS2 9NL, England.
Darren TreanorLeeds Teaching Hospitals NHS Trust, St James University teaching Hospital, Level 6, Bexley Wing. St James's Hospital, Beckett Street, Leeds, LS9 7TF, England.
Lee RobertsCardiovascular and Diabetes Research, Leeds Institute of Cardiovascular and Metabolic Medicine LIGHT Laboratories, University of Leeds, LS2 9JT, Leeds, England.
Ashley GuthrieLeeds Teaching Hospitals NHS Trust, St James University teaching Hospital, Level 6, Bexley Wing. St James's Hospital, Beckett Street, Leeds, LS9 7TF, England.
Raj PrasadLeeds 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 GilthorpeLeeds Teaching Hospitals NHS Trust, St James University teaching Hospital, Level 6, Bexley Wing. St James's Hospital, Beckett Street, Leeds, LS9 7TF, England.
Magdy AttiaLeeds Teaching Hospitals NHS Trust, St James University teaching Hospital, Level 6, Bexley Wing. St James's Hospital, Beckett Street, Leeds, LS9 7TF, England.
Steven SourbronIICD - Sheffield, Sheffield, England.
Leeds Teaching Hospitals NHS Trust · GBUniversity of Leeds · GBLinköping University · SE

Funding

Medical Research Council Grant Ref: MR/P023398/1Medical Research Council MR/P023398/1Medical Research Council MR/P023398/2
6 · The paper itself

Abstract

backgroundPost 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.

methodsHEPARIM 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: 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 registrationClinicalTrials.gov, ClinicalTrials.gov NCT04705194 - Registered 12th January 2021 - Retrospectively registered.

Indexed as

HepatectomyHumansLiver NeoplasmsMagnetic Resonance ImagingRisk AssessmentFunctional MRIFuture liver remnantGadoxetateIndocyanine greenPost hepatectomy liver failureRisk assessment

Identifiers

PMID34688256
PMCPMC8541801
OpenAlexW3210929471

What OpenQuestion holds

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LicenceCC BY
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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.