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. 2022 May 17;24:34. doi: 10.1186/s13058-022-01529-9

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© The Author(s) 2022

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

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Fig. 2 — Pearson-based associations between KEGG pathways and image measures. a Plot showing pathways significantly associated with each imaging measure. The associated pathways are shaded by their normalised enrichment scores (NES) and GLYC-GLUC and immune-related pathways highlighted by green and orange arrows. b Numbers of pathways associated with model flux-constants and SUV and TBR measures. c Cumulative distribution function (CDF) showing numbers of pathways (false positives) associated with permuted SUV_max values in 100 synthetic datasets