Evidence map›Paper›PMID 42511867›Full record

ArticleInternational journal of molecular sciences2026

Multimodal OCT Biomarkers of Fibrosis and Steatosis in the Regenerating Liver.

Svetlana Rodimova, Ekaterina Gubarkova, Nikolai Bobrov, Ilya Shchechkin, Vera Kozlova, Natalia Zolotova, Pavel Bureev, Anastasia Polozova, Maria Karabut, Grigory Gelikonov and 4 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in International journal of molecular sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Svetlana RodimovaInstitute of Experimental Oncology and Biomedical Technologies, Privolzhsky Research Medical University, 10/1 Minin and Pozharsky Sq., 603000 Nizhny Novgorod, Russia.ORCID 0000-0002-4454-2931
Ekaterina GubarkovaInstitute of Experimental Oncology and Biomedical Technologies, Privolzhsky Research Medical University, 10/1 Minin and Pozharsky Sq., 603000 Nizhny Novgorod, Russia.ORCID 0000-0001-5416-3241
Nikolai BobrovThe Volga District Medical Centre of Federal Medical and Biological Agency, 14 Ilinskaya St., 603000 Nizhny Novgorod, Russia.
Ilya ShchechkinInstitute of Experimental Oncology and Biomedical Technologies, Privolzhsky Research Medical University, 10/1 Minin and Pozharsky Sq., 603000 Nizhny Novgorod, Russia.ORCID 0009-0009-6071-8210
Vera KozlovaInstitute of Experimental Oncology and Biomedical Technologies, Privolzhsky Research Medical University, 10/1 Minin and Pozharsky Sq., 603000 Nizhny Novgorod, Russia.
Natalia ZolotovaInstitute of Experimental Oncology and Biomedical Technologies, Privolzhsky Research Medical University, 10/1 Minin and Pozharsky Sq., 603000 Nizhny Novgorod, Russia.
Pavel BureevInstitute of Experimental Oncology and Biomedical Technologies, Privolzhsky Research Medical University, 10/1 Minin and Pozharsky Sq., 603000 Nizhny Novgorod, Russia.
Anastasia PolozovaInstitute of Experimental Oncology and Biomedical Technologies, Privolzhsky Research Medical University, 10/1 Minin and Pozharsky Sq., 603000 Nizhny Novgorod, Russia.ORCID 0000-0003-1255-9760
Maria KarabutInstitute of Experimental Oncology and Biomedical Technologies, Privolzhsky Research Medical University, 10/1 Minin and Pozharsky Sq., 603000 Nizhny Novgorod, Russia.
Grigory GelikonovA.V. Gaponov-Grekhov Institute of Applied Physics of the Russian Academy of Sciences, 46 Ulyanova Street, 603950 Nizhny Novgorod, Russia.
Natalia D GladkovaInstitute of Experimental Oncology and Biomedical Technologies, Privolzhsky Research Medical University, 10/1 Minin and Pozharsky Sq., 603000 Nizhny Novgorod, Russia.
Vladimir ZagainovNizhny Novgorod Regional Clinical Oncologic Dispensary, Delovaya St., 11/1, 603126 Nizhny Novgorod, Russia.
Elena ZagaynovaInstitute of Experimental Oncology and Biomedical Technologies, Privolzhsky Research Medical University, 10/1 Minin and Pozharsky Sq., 603000 Nizhny Novgorod, Russia.
Daria KuznetsovaInstitute of Experimental Oncology and Biomedical Technologies, Privolzhsky Research Medical University, 10/1 Minin and Pozharsky Sq., 603000 Nizhny Novgorod, Russia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The liver's regenerative capacity is essential for resection and transplantation, but chronic liver diseases compromise this ability. Conventional preoperative tests poorly predict regeneration in diseased livers, necessitating new intraoperative tools. Optical coherence tomography (OCT) provides real-time high-resolution "optical biopsy" and functional tissue assessment, making it a promising method for evaluating liver regenerative potential. The aim of this study was to identify characteristic criteria derived from MM OCT that could be used intraoperatively to detect the presence and type of pathology, and to assess the reduction in liver regenerative potential in patients. In this study, we used intraoperative multimodal OCT (MM OCT)-combining attenuation mapping and elastography-for real-time, label-free assessment of changes in liver structure, and stiffness during regeneration. MM OCT also provides higher resolution and specificity than conventional clinical imaging. In a rat model, we induced steatosis by high-fat diet and fibrosis by CCl

Indexed as

BiomarkersFatty LiverLiverLiver CirrhosisLiver RegenerationTomography, Optical CoherenceAnimalsElasticity Imaging TechniquesHepatectomyMaleRatsBiomarkersattenuation coefficient of the OCT signalimage analysisliver fibrosisliver regenerationliver steatosisOCT elastographyoptical coherence tomographystiffness

Identifiers

PMID42511867
PMCPMC13411441

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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.