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. 2021 Feb 4;11:3106. doi: 10.1038/s41598-021-82665-8

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© The Author(s) 2021

Open Access This 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/.

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Longitudinal analysis of parametric MR images from 381 VS patients. Regardless of the state of the tumor (progressed, pseudo-progressed, or regressed), there were negligible differences between the predictions of the proposed AI model and clinical measurements obtained by expert radiologists. The median differences are presented here at each follow-up time point: + 1.74%, − 0.31%, − 0.44%, − 0.19%, − 0.01%, and + 0.26 (Mean: average, Std: standard deviation, MIN: minimum, IQ1: 25th interquartile, IQ3: 75th interquartile, MED: median, MAX: maximum).