Evidence map›Paper›PMID 36319877›Full record

Trial reportJournal of medical systems2022

The Infrared Thermography Toolbox: An Open-access Semi-automated Segmentation Tool for Extracting Skin Temperatures in the Thoracic Region including Supraclavicular Brown Adipose Tissue.

Aashley S D Sardjoe Mishre, Maaike E Straat, Borja Martinez-Tellez, Andrea Mendez Gutierrez, Sander Kooijman, Mariëtte R Boon, Oleh Dzyubachyk, Andrew Webb, Patrick C N Rensen, Hermien E Kan

Abstract readClinical Trial
PubMed Full text at PMC Publisher
In one paragraph

Trial report in Journal of medical systems, 2022. 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

10 authors.

Aashley S D Sardjoe MishreDepartment of Medicine, Division of Endocrinology, Leiden University Medical Center, Leiden, the Netherlands.
Maaike E StraatDepartment of Medicine, Division of Endocrinology, Leiden University Medical Center, Leiden, the Netherlands.
Borja Martinez-TellezDepartment of Medicine, Division of Endocrinology, Leiden University Medical Center, Leiden, the Netherlands.
Andrea Mendez GutierrezDepartment of Biochemistry and Molecular Biology II, "José Mataix Verdú" Institute of Nutrition and Food Technology (INYTA), Biomedical Research Centre (CIBM), University of Granada, 18016, Granada, Spain.
Sander KooijmanDepartment of Medicine, Division of Endocrinology, Leiden University Medical Center, Leiden, the Netherlands.
Mariëtte R BoonDepartment of Medicine, Division of Endocrinology, Leiden University Medical Center, Leiden, the Netherlands.
Oleh DzyubachykDepartment of Radiology, Division of Image Processing (LKEB), Leiden University Medical Center, Leiden, The Netherlands.
Andrew WebbDepartment of Radiology, C.J. Gorter Center for High Field MRI, Leiden University Medical Center, Leiden, the Netherlands.
Patrick C N RensenDepartment of Medicine, Division of Endocrinology, Leiden University Medical Center, Leiden, the Netherlands.
Hermien E KanDepartment of Radiology, C.J. Gorter Center for High Field MRI, Leiden University Medical Center, Leiden, the Netherlands. H.E.Kan@lumc.nl.

Funding

Dutch Diabetes Foundation 2015.81.1808Dutch Heart Foundation 2017T016Dutch Society for Diabetes Research NVDO; Prof. dr. J. Terpstra AwardMinisterio de Universidades y la Unión Europea -NextGeneration EU RR_C_2021_04The Netherlands Cardiovascular Research Initiative CVON2014-02 ENERGISE
6 · The paper itself

Abstract

Infrared thermography (IRT) is widely used to assess skin temperature in response to physiological changes. Yet, it remains challenging to standardize skin temperature measurements over repeated datasets. We developed an open-access semi-automated segmentation tool (the IRT-toolbox) for measuring skin temperatures in the thoracic area to estimate supraclavicular brown adipose tissue (scBAT) activity, and compared it to manual segmentations. The IRT-toolbox, designed in Python, consisted of image pre-alignment and non-rigid image registration. The toolbox was tested using datasets of 10 individuals (BMI = 22.1 ± 2.1 kg/m

Indexed as

Adipose Tissue, BrownSkin TemperatureAdolescentAdultHumansReproducibility of ResultsThermographyThoraxYoung AdultBATInfrared thermographyNon-rigid image registrationSemi-automated analysis

Identifiers

PMID36319877
PMCPMC9626432

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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.