Nature Nanotechnology · 2023 · 33 citations · 27 references
Natural SciencesBiomedical EngineeringPathologyBiomedical ImagingBiomedical OpticsMolecular PathologyCellular ImagingConfocal MicroscopyLight MicroscopySuper-resolution MicroscopyDiffraction-limited ImagingDiffraction-limited ResolutionFormalin-fixed Paraffin-embedded Tissue AnalysisMolecular Profiling From BiopsyResolution EnhancementResolution Enhancement TechniquesSuper-resolutionTissue Imaging
Abstract Expansion microscopy physically enlarges biological specimens to achieve nanoscale resolution using diffraction-limited microscopy systems 1 . However, optimal performance is usually reached using laser-based systems (for example, confocal microscopy), restricting its broad applicability in clinical pathology, as most centres have access only to light-emitting diode (LED)-based widefield systems. As a possible alternative, a computational method for image resolution enhancement, namely, super-resolution radial fluctuations (SRRF) 2,3 , has recently been developed. However, this method has not been explored in pathology specimens to date, because on its own, it does not achieve sufficient resolution for routine clinical use. Here, we report expansion-enhanced super-resolution radial fluctuations (ExSRRF), a simple, robust, scalable and accessible workflow that provides a resolution of up to 25 nm using LED-based widefield microscopy. ExSRRF enables molecular profiling of subcellular structures from archival formalin-fixed paraffin-embedded tissues in complex clinical and experimental specimens, including ischaemic, degenerative, neoplastic, genetic and immune-mediated disorders. Furthermore, as examples of its potential application to experimental and clinical pathology, we show that ExSRRF can be used to identify and quantify classical features of endoplasmic reticulum stress in the murine ischaemic kidney and diagnostic ultrastructural features in human kidney biopsies.
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scikit-image: image processing in Python
Stéfan van der Walt, Johannes L. Schönberger, Juan Nunez-Iglesias et al. · PeerJ · 2014 · 6.9K citations · Full text
Fay Wang, John J. Flanagan, Nan Su et al. · Journal of Molecular Diagnostics · 2011 · 2.7K citations · Full text