High-Resolution Mapping of the Human Olfactory Bulb Using X-Ray Phase Contrast Tomography and Virtual Surface Unfolding

The human olfactory bulb (OB) is a complex neural structure critical for odor processing and one of the earliest sites of pathology in a number of neurodegenerative diseases. We used X-ray phase-contrast tomography (XPCT) to obtain high-quality 3D images of OB tissue from postmortem patients, allowing detailed visualization of soft tissue microarchitecture, including the olfactory glomeruli. To improve spatial analysis, we developed a computational unfolding method that transforms the curved surface of the OB into a 2D map. This transformation preserves anatomical relationships, allowing accurate quantification of glomeruli by number, size, shape, and distribution. The unfolded representations of OB image support in-depth statistical analysis and are compatible with machine learning tools for automated detection and classification of OB morphological structures. This method provides a powerful framework for studying olfactory function and identifying early structural changes in diseases such as Parkinson's disease, Alzheimer's disease, and COVID-19-associated anosmia. By integrating XPCT with virtual unfolding, we offer a new approach to mapping OB morphological features with increased clarity and diagnostic accuracy.