@misc{10481/78202,
year = {2022},
month = {11},
url = {https://hdl.handle.net/10481/78202},
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/m2, age = 22.0 ± 3.7 years) who underwent two cooling procedures, yielding four images per individual.
Regions of interest (ROIs) were delineated by two raters in the scBAT and deltoid areas on baseline images. The toolbox
enabled direct transfer of baseline ROIs to the registered follow-up images. For comparison, both raters also manually drew
ROIs in all follow-up images. Spatial ROI overlap between methods and raters was determined using the Dice coefficient.
Mean bias and 95% limits of agreement in mean skin temperature between methods and raters were assessed using Bland–
Altman analyses. ROI delineation time was four times faster with the IRT-toolbox (01:04 min) than with manual delineations
(04:12 min). In both anatomical areas, there was a large variability in ROI placement between methods. Yet, relatively
small skin temperature differences were found between methods (scBAT: 0.10 °C, 95%LoA[-0.13 to 0.33 °C] and deltoid:
0.05 °C, 95%LoA[-0.46 to 0.55 °C]). The variability in skin temperature between raters was comparable between methods.
The IRT-toolbox enables faster ROI delineations, while maintaining inter-user reliability compared to manual delineations.},
organization = {Netherlands Heart Foundation	2017T016	
CVON201402 ENERGISE	
CVON2017 GENIUS-2},
organization = {Alfonso Martin Escudero},
organization = {Maria Zambrano fellowship by the Ministerio de Universidades y la Union Europea -NextGeneration EU	RR_C_2021_04},
organization = {Dutch Society for Diabetes Research (NVDO)},
organization = {Dutch Diabetes Foundation	2015.81.1808},
organization = {Netherlands Cardiovascular Research Initiative},
organization = {LUMC profile area 'biomedical imaging'},
publisher = {Springer},
keywords = {Infrared thermography},
keywords = {Non-rigid image registration},
keywords = {Semi-automated analysis},
keywords = {BAT},
title = {The Infrared Thermography Toolbox: An Open‑access Semi‑automated Segmentation Tool for Extracting Skin Temperatures in the Thoracic Region including Supraclavicular Brown Adipose Tissue},
doi = {10.1007/s10916-022-01871-7},
author = {Sardjoe Mishre, Aashley S. D. and Méndez Gutiérrez, Andrea},
}