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Photoacoustic imaging radiomics in patient-derived xenografts: a study on feature sensitivity and model discrimination.

Published version
Peer-reviewed

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Authors

Escudero Sanchez, Lorena 
Brown, Emma 
Rundo, Leonardo 
Ursprung, Stephan 
Sala, Evis 

Abstract

Photoacoustic imaging is an increasingly popular method of exploring the tumour microenvironment, which can provide insight into tumour oxygenation status and potentially treatment response assessment. Currently, the measurements most commonly performed on such images are the mean and median of the pixel values of the tumour volumes of interest. We investigated expanding the set of measurements that can be extracted from these images by adding radiomic features. In particular, we found that Skewness was sensitive to differences between basal and luminal patient derived xenograft cancer models with an [Formula: see text] of 0.86, and that it was robust to variations in confounding factors such as reconstruction type and wavelength. We also built discriminant models with radiomic features that were correlated with the underlying tumour model and were independent from each other. We then ranked features by their importance in the model. Skewness was again found to be an important feature, as were 10th Percentile, Root Mean Squared, and several other texture-based features. In summary, this paper proposes a methodology to select radiomic features extracted from photoacoustic images that are robust to changes in acquisition and reconstruction parameters, and discusses features found to have discriminating power between the underlying tumour models in a pre-clinical dataset.

Description

Funder: Mark Foundation For Cancer Research; doi: http://dx.doi.org/10.13039/100014599


Funder: Cambridge Commonwealth, European and International Trust

Keywords

Animals, Diagnostic Imaging, Disease Models, Animal, Heterografts, Humans, Neoplasms, Photoacoustic Techniques, Tumor Microenvironment

Journal Title

Sci Rep

Conference Name

Journal ISSN

2045-2322
2045-2322

Volume Title

Publisher

Springer Science and Business Media LLC
Sponsorship
Wellcome Trust (215733/Z/19/Z)
National Institute for Health and Care Research (IS-BRC-1215-20014)