Reimer, M. L.; Kauer, S. D.; Benson, C. A.; King, J. F.; Patwa, S.; Feng, S.; Estacion, M. A.; Bangalore, L.; Waxman, S.; Tan, A. M.

Neuroanatomy is fundamental to understanding the nervous system, particularly dendritic spines, which are vital for synaptic transmission and change in response to injury or disease. Advancements in imaging have allowed for detailed 3D visualization of these structures. However, existing tools for analyzing dendritic spine morphology are limited. To address this, we developed an open-source, virtual reality (VR) Structural Analysis Software Ecosystem (coined \'VR-SASE\') that offers a powerful, intuitive approach for analyzing dendritic spines. Our validation process confirmed the method\'s superior accuracy, outperforming recognized gold standard neural reconstruction techniques. Importantly, the VR-SASE workflow automatically calculates key morphological metrics such as dendritic spine length, volume, and surface area, and reliably replicates established datasets from published dendritic spine studies. By integrating the Neurodata Without Borders (NWB) data standard and DataJoint, VR-SASE also aligns with FAIR principles--guidelines aimed at improving the findability, accessibility, interoperability, and reusability of digital assets--enhancing data usability and longevity in neuroscience research.