Evidence map›Paper›PMID 35546207›Full record

ArticleSurgical endoscopy2022

Video: Clinical evaluation of a laparoscopic hyperspectral imaging system.

Annekatrin Pfahl, Hannes Köhler, Madeleine T Thomaßen, Marianne Maktabi, Albrecht M Bloße, Matthias Mehdorn, Orestis Lyros, Yusef Moulla, Stefan Niebisch, Boris Jansen-Winkeln and 2 more

Open access · hybridAbstract read
In one paragraph

Article in Surgical endoscopy, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
2.3field-weighted citation impact, top 12% 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

14 citing papers in PubMed, 17 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. Intraoperative Hyperspectral Imaging Predicts Early Allograft Dysfunction and Overall Survival in Liver Transplantation.Annals of surgery open : perspectives of surgical history, education, and clinical approaches · 2024
    Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. A High-Speed Hyperspectral Laparoscopic Imaging System.Proceedings of SPIE--the International Society for Optical Engineering · 2023
    Article
  12. Article
  13. Article
  14. 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

12 authors at 3 institutions in 1 country.

Annekatrin Pfahl *Innovation Center Computer Assisted Surgery (ICCAS), Faculty of Medicine, Leipzig University, Semmelweisstr. 14, 04103, Leipzig, Germany. annekatrin.pfahl@medizin.uni-leipzig.de.ORCID http://orcid.org/0000-0002-6285-1586
Hannes Köhler *Innovation Center Computer Assisted Surgery (ICCAS), Faculty of Medicine, Leipzig University, Semmelweisstr. 14, 04103, Leipzig, Germany.
Madeleine T ThomaßenDepartment of Visceral, Transplant, Thoracic, and Vascular Surgery, University Hospital of Leipzig, Leipzig, Germany.
Marianne MaktabiInnovation Center Computer Assisted Surgery (ICCAS), Faculty of Medicine, Leipzig University, Semmelweisstr. 14, 04103, Leipzig, Germany.
Albrecht M BloßeInnovation Center Computer Assisted Surgery (ICCAS), Faculty of Medicine, Leipzig University, Semmelweisstr. 14, 04103, Leipzig, Germany.
Matthias MehdornDepartment of Visceral, Transplant, Thoracic, and Vascular Surgery, University Hospital of Leipzig, Leipzig, Germany.
Orestis LyrosDepartment of Visceral, Transplant, Thoracic, and Vascular Surgery, University Hospital of Leipzig, Leipzig, Germany.
Yusef MoullaDepartment of Visceral, Transplant, Thoracic, and Vascular Surgery, University Hospital of Leipzig, Leipzig, Germany.
Stefan NiebischDepartment of Visceral, Transplant, Thoracic, and Vascular Surgery, University Hospital of Leipzig, Leipzig, Germany.
Boris Jansen-WinkelnDepartment of Visceral, Transplant, Thoracic, and Vascular Surgery, University Hospital of Leipzig, Leipzig, Germany.
Claire Chalopin *Innovation Center Computer Assisted Surgery (ICCAS), Faculty of Medicine, Leipzig University, Semmelweisstr. 14, 04103, Leipzig, Germany.
Ines Gockel *Department of Visceral, Transplant, Thoracic, and Vascular Surgery, University Hospital of Leipzig, Leipzig, Germany.
University Hospital Leipzig · DELeipzig University · DEKlinikum St. Georg · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHyperspectral imaging (HSI) during surgical procedures is a new method for perfusion quantification and tissue discrimination. Its use has been limited to open surgery due to large camera sizes, missing color video, or long acquisition times. A hand-held, laparoscopic hyperspectral camera has been developed now to overcome those disadvantages and evaluated clinically for the first time.

methodsIn a clinical evaluation study, gastrointestinal resectates of ten cancer patients were investigated using the laparoscopic hyperspectral camera. Reference data from corresponding anatomical regions were acquired with a clinically approved HSI system. An image registration process was executed that allowed for pixel-wise comparisons of spectral data and parameter images (StO

resultsThe obtained mean MAEs between the TIVITA® Tissue and the laparoscopic hyperspectral system resulted in StO

conclusionQualitatively, parameter images of the laparoscopic system corresponded to those of the system for open surgery. Quantitative deviations were attributed to technical differences rather than the study design. Limitations of the presented study are addressed in current large-scale in vivo trials.

Indexed as

Hyperspectral ImagingLaparoscopyGastrointestinal TractHemoglobinsHumansHemoglobinsClinical evaluation studyGastrointestinal surgeryHyperspectral imagingLaparoscopic surgeryMinimally invasive surgery

Identifiers

PMID35546207
PMCPMC9485189
OpenAlexW4280509874

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.