The Poudel Lab develops advanced tissue processing workflows, high-resolution 3D imaging platforms and computational tools — including machine learning and artificial intelligence — to advance the emerging field of 3D digital pathology. Using these innovative tools, our mission is to enhance the understanding, diagnosis and treatment of disease with the goal of improving human health.

We are deeply committed to collaborative science, working closely with clinical researchers, pathologists and bioengineers to ensure our discoveries are both scientifically robust and translationally meaningful. By bridging basic research with clinical application, we strive to accelerate the development of next-generation diagnostic tools and therapeutic strategies that improve patient outcomes.

Our current projects are focused on the following themes:

(i) 3D spatial atlases of kidney diseases

Our lab is building detailed 3D reference maps of the kidney using advanced imaging modalities such as open-top light-sheet (OTLS) and two-photon microscopy to achieve subcellular resolution across large tissue volumes. To handle the vast and complex datasets generated by 3D microscopy, we have developed custom AI-driven image analysis pipelines, including tailored deep learning models for automated segmentation and tubule tracking. These tools allow us to map the spatial organization of key kidney structures within intact tissue volumes.

Funded by NIDDK- Innovative Science Accelerator Program (ISAC).

(ii) 3D digital pathology of human kidney biopsies

Our lab aims to advance 3D digital pathology of human kidney biopsies by combining fluorescent analogs of classical histology stains with high-resolution 3D imaging. This approach enables visualization of entire core needle biopsies and nephrectomy samples in their intact, unsectioned state. Using AI-based analysis tools, we will assess tissue architecture and pathology in full volumetric context, preserving the native 3D relationships between structures such as tubules, vasculature and interstitial compartments.

We aim to demonstrate that 3D digital pathology provides significant advantages over current 2D slide-based histopathology, including:

• Increased tissue sampling through full-volume imaging.

• True 3D visualization of complex anatomical structures.

• Reversible, non-destructive workflows that preserve tissue for downstream assays.

This direction represents a paradigm shift in renal pathology, offering greater diagnostic depth while maintaining the integrity of precious clinical samples.