PMID- 33570495 OWN - NLM STAT- In-Data-Review VI - 10 TI - Constructing and optimizing 3D atlases from 2D data with application to the developing mouse brain. CI - © 2021, Young et al. LA - eng PT - Journal Article PL - England TA - Elife JT - eLife JID - 101579614 IS - 2050-084X (Electronic) LID - 10.7554/eLife.61408 [doi] LID - e61408 [pii] FAU - Young, David M AU - Young DM AUID- ORCID: https://orcid.org/0000-0003-3303-2001 AD - Department of Psychiatry and Behavioral Sciences, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, United States. AD - Institute of Molecular and Cell Biology, Agency for Science, Technology and Research, Singapore, Singapore. FAU - Fazel Darbandi, Siavash AU - Fazel Darbandi S AD - Department of Psychiatry and Behavioral Sciences, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, United States. FAU - Schwartz, Grace AU - Schwartz G AD - Department of Psychiatry and Behavioral Sciences, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, United States. FAU - Bonzell, Zachary AU - Bonzell Z AD - Department of Psychiatry and Behavioral Sciences, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, United States. FAU - Yuruk, Deniz AU - Yuruk D AD - Department of Psychiatry and Behavioral Sciences, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, United States. FAU - Nojima, Mai AU - Nojima M AD - Department of Psychiatry and Behavioral Sciences, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, United States. FAU - Gole, Laurent C AU - Gole LC AD - Institute of Molecular and Cell Biology, Agency for Science, Technology and Research, Singapore, Singapore. FAU - Rubenstein, John Lr AU - Rubenstein JL AUID- ORCID: http://orcid.org/0000-0002-4414-7667 AD - Department of Psychiatry and Behavioral Sciences, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, United States. FAU - Yu, Weimiao AU - Yu W AD - Institute of Molecular and Cell Biology, Agency for Science, Technology and Research, Singapore, Singapore. FAU - Sanders, Stephan J AU - Sanders SJ AUID- ORCID: https://orcid.org/0000-0001-9112-5148 AD - Department of Psychiatry and Behavioral Sciences, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, United States. IS - 2050-084X (Linking) SB - IM OTO - NOTNLM OT - 3D atlas OT - computational biology OT - developmental biology OT - image processing OT - mouse OT - mouse development OT - neuroanatomy OT - neurodevelopment OT - systems biology OT - tissue clearing PMC - PMC7994002 LR - 20210408 DP - 2021 Feb 11 DEP - 20210211 AB - 3D imaging data necessitate 3D reference atlases for accurate quantitative interpretation. Existing computational methods to generate 3D atlases from 2D-derived atlases result in extensive artifacts, while manual curation approaches are labor-intensive. We present a computational approach for 3D atlas construction that substantially reduces artifacts by identifying anatomical boundaries in the underlying imaging data and using these to guide 3D transformation. Anatomical boundaries also allow extension of atlases to complete edge regions. Applying these methods to the eight developmental stages in the Allen Developing Mouse Brain Atlas (ADMBA) led to more comprehensive and accurate atlases. We generated imaging data from 15 whole mouse brains to validate atlas performance and observed qualitative and quantitative improvement (37% greater alignment between atlas and anatomical boundaries). We provide the pipeline as the MagellanMapper software and the eight 3D reconstructed ADMBA atlases. These resources facilitate whole-organ quantitative analysis between samples and across development. OAB - The research community needs precise, reliable 3D atlases of organs to pinpoint where biological structures and processes are located. For instance, these maps are essential to understand where specific genes are turned on or off, or the spatial organization of various groups of cells over time. For centuries, atlases have been built by thinly ‘slicing up’ an organ, and then precisely representing each 2D layer. Yet this approach is imperfect: each layer may be accurate on its own, but inevitable mismatches appear between the slices when viewed in 3D or from another angle. Advances in microscopy now allow entire organs to be imaged in 3D. Comparing these images with atlases could help to detect subtle differences that indicate or underlie disease. However, this is only possible if 3D maps are accurate and do not feature mismatches between layers. To create an atlas without such artifacts, one approach consists in starting from scratch and manually redrawing the maps in 3D, a labor-intensive method that discards a large body of well-established atlases. Instead, Young et al. set out to create an automated method which could help to refine existing ‘layer-based’ atlases, releasing software that anyone can use to improve current maps. The package was created by harnessing eight atlases in the Allen Developing Mouse Brain Atlas, and then using the underlying anatomical images to resolve discrepancies between layers or fill out any missing areas. Known as MagellanMapper, the software was extensively tested to demonstrate the accuracy of the maps it creates, including comparison to whole-brain imaging data from 15 mouse brains. Armed with this new software, researchers can improve the accuracy of their atlases, helping them to understand the structure of organs at the level of the cell and giving them insight into a broad range of human disorders.