Evidence map›Paper›PMID 33262432›Full record

ArticleScientific reports2020

Kidney segmentation in neck-to-knee body MRI of 40,000 UK Biobank participants.

Taro Langner, Andreas Östling, Lukas Maldonis, Albin Karlsson, Daniel Olmo, Dag Lindgren, Andreas Wallin, Lowe Lundin, Robin Strand, Håkan Ahlström and 1 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
0.3field-weighted citation impact, top 37% 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.

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

19 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Association of Pancreas Volume With Adverse Clinical Outcomes.Journal of the American Heart Association · 2025
    Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. MRI of kidney size matters.Magma (New York, N.Y.) · 2024
    Review
  11. Multi-organ imaging-derived polygenic indexes for brain and body health.medRxiv : the preprint server for health sciences · 2024
    Article
  12. Observational
  13. Article
  14. Article
  15. Renal MRI: From Nephron to NMR Signal.Journal of magnetic resonance imaging : JMRI · 2023
    Review
  16. Article
  17. Article
  18. Article
  19. 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

11 authors at 2 institutions in 1 country.

Taro LangnerDepartment of Surgical Sciences, Uppsala University, 751 85, Uppsala, Sweden. taro.langner@surgsci.uu.se.
Andreas ÖstlingDepartment of Surgical Sciences, Uppsala University, 751 85, Uppsala, Sweden.
Lukas MaldonisAntaros Medical AB, BioVenture Hub, 431 53, Mölndal, Sweden.
Albin KarlssonDepartment of Surgical Sciences, Uppsala University, 751 85, Uppsala, Sweden.
Daniel OlmoDepartment of Surgical Sciences, Uppsala University, 751 85, Uppsala, Sweden.
Dag LindgrenAntaros Medical AB, BioVenture Hub, 431 53, Mölndal, Sweden.
Andreas WallinAntaros Medical AB, BioVenture Hub, 431 53, Mölndal, Sweden.
Lowe LundinAntaros Medical AB, BioVenture Hub, 431 53, Mölndal, Sweden.
Robin StrandDepartment of Surgical Sciences, Uppsala University, 751 85, Uppsala, Sweden.
Håkan AhlströmDepartment of Surgical Sciences, Uppsala University, 751 85, Uppsala, Sweden.
Joel KullbergDepartment of Surgical Sciences, Uppsala University, 751 85, Uppsala, Sweden.
Uppsala University · SEAntaros Medical (Sweden) · SE

Funding

Medical Research Council MC_PC_17228Medical Research Council MC_QA137853
6 · The paper itself

Abstract

The UK Biobank is collecting extensive data on health-related characteristics of over half a million volunteers. The biological samples of blood and urine can provide valuable insight on kidney function, with important links to cardiovascular and metabolic health. Further information on kidney anatomy could be obtained by medical imaging. In contrast to the brain, heart, liver, and pancreas, no dedicated Magnetic Resonance Imaging (MRI) is planned for the kidneys. An image-based assessment is nonetheless feasible in the neck-to-knee body MRI intended for abdominal body composition analysis, which also covers the kidneys. In this work, a pipeline for automated segmentation of parenchymal kidney volume in UK Biobank neck-to-knee body MRI is proposed. The underlying neural network reaches a relative error of 3.8%, with Dice score 0.956 in validation on 64 subjects, close to the 2.6% and Dice score 0.962 for repeated segmentation by one human operator. The released MRI of about 40,000 subjects can be processed within one day, yielding volume measurements of left and right kidney. Algorithmic quality ratings enabled the exclusion of outliers and potential failure cases. The resulting measurements can be studied and shared for large-scale investigation of associations and longitudinal changes in parenchymal kidney volume.

Indexed as

Biological Specimen BanksImage Interpretation, Computer-AssistedMagnetic Resonance ImagingAlgorithmsHumansKidneyKneeNeckNeural Networks, ComputerReproducibility of ResultsUnited Kingdom

Identifiers

PMID33262432
PMCPMC7708493
OpenAlexW3035386833

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.