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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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Case demonstration: (A) 46 y/o female VS patient who underwent GKRS and sequential MRI follow-up (follow-up MR images revealed positive response to radiation and ongoing tumor regression); (B) 53 y/o male VS patient who underwent GKRS and sequential MRI follow-up (follow-up MR images also showed positive response to radiation treatment with loss of MR imaging signal in center of tumor but transient enlargement of tumor); (C) 43-year-old female VS patient who underwent GKRS and sequential MRI follow-up (follow-up MR images obtained at 6 months after GKRS showed poor response to radiation treatment). A loss of central enhancement was observed in the early stage after GKRS; however, the tumor continued growing. At most follow-up time points, the differences between the predictions of AI models and clinical measurements were less than 10%. The trends of the tumor progression or regression predicted by the proposed AI model were remarkably accurate.