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. 2021 May 27;48(7):2295–2305. doi: 10.1007/s00259-021-05401-4

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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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Fig. 3 — Distribution of SUVR values for [¹⁸F]flortaucipir, [¹⁸F]RO948, and [¹⁸F]MK6240 across data-driven ROIs. The notch in the box-and-whisker plots indicates the 95% confidence interval for the median. (A) The regions that best separated AD dementia from CU individuals (parahippocampus and inferior temporal cortex) and those diagnosed with non-AD neurodegenerative disorders (entorhinal cortex, amygdala, parahippocampus, and inferior temporal cortex) using [¹⁸F]flortaucipir PET. (B) The regions that best separated AD dementia from CU individuals (entorhinal cortex and amygdala) and those diagnosed with non-AD neurodegenerative disorders (entorhinal cortex, amygdala, parahippocampus, fusiform gyrus, and inferior temporal cortex) using [¹⁸F]RO948. (C) The regions that best separated AD dementia from CU individuals (fusiform gyrus, inferior temporal cortex, middle temporal gyrus) and those diagnosed with non-AD neurodegenerative disorders (entorhinal cortex, amygdala, the inferior temporal cortex, the banks of the superior temporal sulcus, and the fusiform gyrus) using [¹⁸F]MK6240