Evidence map›Paper›PMID 39123437›Full record

ArticleCancers2024

Prospective Study of Non-Contrast, Abbreviated MRI for Hepatocellular Carcinoma Surveillance in Patients with Suboptimal Hepatic Visualisation on Ultrasound.

Mathew Vithayathil, Maria Qurashi, Pedro Rente Vicente, Ali Alsafi, Mitesh Naik, Alison Graham, Shahid Khan, Heather Lewis, Ameet Dhar, Belinda Smith and 7 more

Abstract read
In one paragraph

Article in Cancers, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Review
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

17 authors.

Mathew VithayathilDepartment of Surgery and Cancer, Imperial College London, London W12 0NN, UK.ORCID 0000-0002-1457-4385
Maria QurashiDepartment of Surgery and Cancer, Imperial College London, London W12 0NN, UK.ORCID 0000-0002-4821-4564
Pedro Rente VicenteDepartment of Brain Sciences, Imperial College London, London W12 0NN, UK.
Ali AlsafiDepartment of Interventional Radiology, Imperial College Healthcare NHS Trust, London W12 0HS, UK.
Mitesh NaikDepartment of Nuclear Medicine, Imperial College Healthcare NHS Trust, London W12 0HS, UK.ORCID 0000-0002-7257-7488
Alison GrahamDepartment of Interventional Radiology, Imperial College Healthcare NHS Trust, London W12 0HS, UK.
Shahid KhanDepartment of Hepatology, Imperial College Healthcare NHS Trust, London W12 0HS, UK.
Heather LewisDepartment of Hepatology, Imperial College Healthcare NHS Trust, London W12 0HS, UK.
Ameet DharDepartment of Hepatology, Imperial College Healthcare NHS Trust, London W12 0HS, UK.
Belinda SmithDepartment of Hepatology, Imperial College Healthcare NHS Trust, London W12 0HS, UK.
Nowlan SelvapattDepartment of Hepatology, Imperial College Healthcare NHS Trust, London W12 0HS, UK.
Pinelopi ManousouDepartment of Hepatology, Imperial College Healthcare NHS Trust, London W12 0HS, UK.
Lucia PossamaiDepartment of Hepatology, Imperial College Healthcare NHS Trust, London W12 0HS, UK.
Hooshang IzadiSchool of Engineering, Computing and Mathematics, Oxford Brookes University, Oxford OX3 0BP, UK.
Adrian LimDepartment of Radiology, Imperial College Healthcare NHS Trust, London W12 0HS, UK.ORCID 0000-0003-3904-2876
Paul TaitDepartment of Interventional Radiology, Imperial College Healthcare NHS Trust, London W12 0HS, UK.
Rohini SharmaDepartment of Surgery and Cancer, Imperial College London, London W12 0NN, UK.ORCID 0000-0003-2441-549X

Funding

Cancer Research UK Convergence Science Centre N/ANIHR Imperial Biomedical Research Centre N/ANorth West London Cancer Alliance N/A
6 · The paper itself

Abstract

backgroundBiannual ultrasound (US) is recommended for hepatocellular carcinoma (HCC) surveillance in patients with cirrhosis. However, US has limited sensitivity for early-stage HCC, particularly in overweight cohorts, where hepatic visualisation is often inadequate. Currently there are no robust imaging surveillance strategies in patients with inadequate US visualisation. We investigated the ability of non-contrast, abbreviated magnetic resonance imaging (aMRI) to adequately visualise the liver for HCC surveillance in patients with previously inadequate US.

methodsPatients undergoing US surveillance, where liver visualisation was inadequate (LI-RADS VIS-B and VIS-C), were prospectively recruited. Patients underwent non-contrast T2-weighted and diffusion-weighted aMRI. The images were reviewed and reported by an expert liver radiologist. Three independent, blinded radiologists assessed the aMRI visualisation quality using a binary score assessing five parameters (parenchymal definition, vascular definition, coverage of the liver, uniformity of liver appearance and signal-to-noise ratio).

resultsThirty patients completed the aMRI protocol. The majority (90%) had underlying cirrhosis and were overweight (93.3%), with 50% obese and 20% severely obese. A total of 93.3% of the aMRI scans were of satisfactory quality. Six patients (20%) had hepatic abnormalities detected with aMRI that were not seen on their US: one HCC, one haemangioma and three clinically insignificant lesions. For the aMRI visualisation quality assessment, the coverage of the liver, vascular definition and parenchymal definition were consistently rated to be of sufficient quality by all three radiologists.

conclusionsNon-contrast aMRI provided good visualisation of the liver and detection of abnormalities in patients with inadequate US. aMRI should be further explored in a larger, prospective study as an alternative surveillance strategy in patients with inadequate US.

Indexed as

hepatocellular carcinomamagnetic resonance imagingobesitysurveillance

Identifiers

PMID39123437
PMCPMC11312001

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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.