Evidence map›Paper›PMID 39068299›Full record

ArticleScientific reports2024

Spectral characterization of intraoperative renal perfusion using hyperspectral imaging and artificial intelligence.

A Studier-Fischer, M Bressan, A Bin Qasim, B Özdemir, J Sellner, S Seidlitz, C M Haney, L Egen, M Michel, M Dietrich and 8 more

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
–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

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  5. Review
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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

18 authors.

A Studier-FischerDepartment of General, Visceral, and Transplantation Surgery, Heidelberg University Hospital, Heidelberg, Germany. alexander@studier-fischer.com.
M BressanDepartment of General, Visceral, and Transplantation Surgery, Heidelberg University Hospital, Heidelberg, Germany.
A Bin QasimDivision of Intelligent Medical Systems, German Cancer Research Center (DKFZ) Heidelberg, Heidelberg, Germany.
B ÖzdemirDepartment of General, Visceral, and Transplantation Surgery, Heidelberg University Hospital, Heidelberg, Germany.
J SellnerDivision of Intelligent Medical Systems, German Cancer Research Center (DKFZ) Heidelberg, Heidelberg, Germany.
S SeidlitzDivision of Intelligent Medical Systems, German Cancer Research Center (DKFZ) Heidelberg, Heidelberg, Germany.
C M HaneyDepartment of Urology and Urosurgery, Medical Faculty of the University of Heidelberg, University Medical Center Mannheim, Mannheim, Germany.
L EgenDepartment of Urology and Urosurgery, Medical Faculty of the University of Heidelberg, University Medical Center Mannheim, Mannheim, Germany.
M MichelDepartment of Urology and Urosurgery, Medical Faculty of the University of Heidelberg, University Medical Center Mannheim, Mannheim, Germany.
M DietrichDepartment of Anesthesiology, Heidelberg University Hospital, Heidelberg, Germany.
G A SalgDepartment of General, Visceral, and Transplantation Surgery, Heidelberg University Hospital, Heidelberg, Germany.
F BillmannDepartment of General, Visceral, and Transplantation Surgery, Heidelberg University Hospital, Heidelberg, Germany.
H NienhüserDepartment of General, Visceral, and Transplantation Surgery, Heidelberg University Hospital, Heidelberg, Germany.
T HackertDepartment of General, Visceral, and Thoracic Surgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
B P MüllerDepartment of Digestive Surgery, University Digestive Healthcare Center, Basel, Switzerland.
L Maier-HeinDivision of Intelligent Medical Systems, German Cancer Research Center (DKFZ) Heidelberg, Heidelberg, Germany.
F Nickel *Department of General, Visceral, and Transplantation Surgery, Heidelberg University Hospital, Heidelberg, Germany.
K F Kowalewski *Department of Urology and Urosurgery, Medical Faculty of the University of Heidelberg, University Medical Center Mannheim, Mannheim, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accurate intraoperative assessment of organ perfusion is a pivotal determinant in preserving organ function e.g. during kidney surgery including partial nephrectomy or kidney transplantation. Hyperspectral imaging (HSI) has great potential to objectively describe and quantify this perfusion as opposed to conventional surrogate techniques such as ultrasound flowmeter, indocyanine green or the subjective eye of the surgeon. An established live porcine model under general anesthesia received median laparotomy and renal mobilization. Different scenarios that were measured using HSI were (1) complete, (2) gradual and (3) partial malperfusion. The differences in spectral reflectance as well as HSI oxygenation (StO

Indexed as

Hyperspectral ImagingKidneyAnimalsArtificial IntelligenceHumansNephrectomyPerfusionSwineHyperspectral imagingMachine learningPorcine modelRenal malperfusionRenal perfusionSurgerySurgical data scienceTranslational research

Identifiers

PMID39068299
PMCPMC11283474

What OpenQuestion 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 OpenQuestion graph.