Evidence mapPaperPMID 40770504Full record

ArticleNature biomedical engineering2026

Tethered optoacoustic and optical coherence tomography capsule endoscopy for label-free assessment of Barrett's oesophageal neoplasia.

Qian Li, Zakiullah Ali, Christian Zakian, Massimiliano di Pietro, Judith Honing, Maria O'Donovan, Krzysztof Flisikowski, Vassilis Sarantos, Guillaume Pierre, Jerome Gloriod and 2 more

Abstract read
In one paragraph

Article in Nature biomedical engineering, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
  5. 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

12 authors.

Qian Li *Center for Medical Physics and Biomedical Engineering, Medical University Vienna, Vienna, Austria.ORCID http://orcid.org/0000-0003-4264-9222
Zakiullah Ali *Chair of Biological Imaging, Central Institute for Translational Cancer Research (TranslaTUM), School of Medicine and Health & School of Computation, Information and Technology, Technical University of Munich, Munich, Germany.
Christian Zakian *Chair of Biological Imaging, Central Institute for Translational Cancer Research (TranslaTUM), School of Medicine and Health & School of Computation, Information and Technology, Technical University of Munich, Munich, Germany.
Massimiliano di PietroEarly Cancer Institute, University of Cambridge, Cambridge, UK.
Judith HoningEarly Cancer Institute, University of Cambridge, Cambridge, UK.ORCID http://orcid.org/0000-0002-1595-3838
Maria O'DonovanDepartment of Histopathology, Cambridge University Hospital, Cambridge, UK.
Krzysztof FlisikowskiChair of Livestock Biotechnology, School of Life Sciences, Technical University of Munich, Munich, Germany.
Vassilis SarantosRayFos: Scientific Software, Basingstoke, UK.ORCID http://orcid.org/0000-0003-1476-6616
Guillaume PierreSONAXIS S.A., Besançon, France.
Jerome GloriodStatice, Besançon, France.
Wolfgang DrexlerCenter for Medical Physics and Biomedical Engineering, Medical University Vienna, Vienna, Austria.
Vasilis NtziachristosChair of Biological Imaging, Central Institute for Translational Cancer Research (TranslaTUM), School of Medicine and Health & School of Computation, Information and Technology, Technical University of Munich, Munich, Germany. bioimaging.translatum@tum.de.ORCID http://orcid.org/0000-0002-9988-0233

Funding

EC | Horizon 2020 Framework Programme (EU Framework Programme for Research and Innovation H2020) No 721766 (FBI)EC | Horizon 2020 Framework Programme (EU Framework Programme for Research and Innovation H2020) No 732720 (ESOTRAC)
6 · The paper itself

Abstract

Endoscopic detection of oesophageal cancer (EC) often occurs late in disease development, leading to high mortality rates. Improved technologies are urgently needed for earlier EC detection. Here we research an endoscopic ultra-broadband acoustic detection scheme and introduce a 360-degree hybrid optoacoustic and optical coherence endoscopy to enable interrogation of surface and subsurface precancerous and cancerous features at a three-dimensional micrometre scale. In the following pilot tissue investigation, the dual-modal imaging features are assessed for classifying different mucosal types in Barrett's oesophagus (BE)-a precursor of EC. We find that human lesions of different grades, such as metaplastic, dysplastic and cancerous mucosa, exhibit distinctly different imaging features that are unique to the hybrid modality. Based on these features, a classification system is developed and evaluated for identifying BE neoplasia. The results show accurate BE neoplasia detection due to the complementarity of the two imaging modalities. Therefore, this study highlights the ability of the new dual-modality feature set to improve the detection performance of any of the two modalities operating in stand-alone mode and enhance diagnostic accuracy.

Indexed as

Barrett EsophagusCapsule EndoscopyEsophageal NeoplasmsPhotoacoustic TechniquesTomography, Optical CoherenceHumans

Identifiers

PMID40770504
PMCPMC12920095

What Socratic holds

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Registered trials

None linked

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 Socratic graph.