ArticleScientific reports2022
Prostate cancer histopathology using label-free multispectral deep-UV microscopy quantifies phenotypes of tumor aggressiveness and enables multiple diagnostic virtual stains.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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25 citing papers in PubMed.
- Quantitative comparison of different mounting media for transmissive DUV imaging of label-free biological specimens.Biomedical optics express · 2026Article
- MS-GATOR: multi-scale graph attention with topological reasoning for segmentation and classification of prostate cancer based on Gleason scores using histopathology images.Scientific reports · 2026Article
- Article
- Nondestructive, High-Resolution T Cell Characterization and Subtyping via Deep-UV Microscopy.BME frontiers · 2026Article
- Polarization resolved deep ultraviolet microscopy for label free imaging with enhanced nuclei and fiber contrast.Optics and lasers in engineering · 2026Article
- Deep Learning-Enabled Virtual Multiplexed Immunostaining of Label-Free Tissue for Vascular Invasion Assessment.BME frontiers · 2026Article
- A robust and scalable framework for hallucination detection in virtual tissue staining and digital pathology.Nature biomedical engineering · 2025Article
- Label-free deep UV microscopy in oral cytology: a step towards stain-free diagnostics.Biomedical optics express · 2025Article
- Label-free surface sectioning deep ultraviolet tissue imaging in multimodalities.Biomedical optics express · 2025Article
- Rapid, Point-of-Care Bone Marrow Aspirate Adequacy Assessment Via Deep Ultraviolet Microscopy.Laboratory investigation; a journal of technical methods and pathology · 2025Article
- Quantifying UV-induced photodamage for longitudinal live-cell imaging applications of deep-UV microscopy.Biomedical optics express · 2025Article
- Metabolic light absorption, scattering, and emission (MetaLASE) microscopy.Science advances · 2024Article
- Distinguishing of Histopathological Staging Features of H-E Stained Human cSCC by Microscopical Multispectral Imaging.Biosensors · 2024Article
- Deep-ultraviolet Fourier ptychography (DUV-FP) for label-free biochemical imaging via feature-domain optimization.APL photonics · 2024Article
- Deep learning-assisted low-cost autofluorescence microscopy for rapid slide-free imaging with virtual histological staining.Biomedical optics express · 2024Article
- Virtual histological staining of unlabeled autopsy tissue.Nature communications · 2024Article
- Deep learning-enabled realistic virtual histology with ultraviolet photoacoustic remote sensing microscopy.Nature communications · 2023Article
- Accelerating Cancer Histopathology Workflows with Chemical Imaging and Machine Learning.Cancer research communications · 2023Article
- Clinical analysis of EV-Fingerprint to predict grade group 3 and above prostate cancer and avoid prostate biopsy.Cancer medicine · 2023Article
- Deep learning-enabled virtual histological staining of biological samples.Light, science & applications · 2023Review
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8 authors.
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Abstract
Identifying prostate cancer patients that are harboring aggressive forms of prostate cancer remains a significant clinical challenge. Here we develop an approach based on multispectral deep-ultraviolet (UV) microscopy that provides novel quantitative insight into the aggressiveness and grade of this disease, thus providing a new tool to help address this important challenge. We find that UV spectral signatures from endogenous molecules give rise to a phenotypical continuum that provides unique structural insight (i.e., molecular maps or "optical stains") of thin tissue sections with subcellular (nanoscale) resolution. We show that this phenotypical continuum can also be applied as a surrogate biomarker of prostate cancer malignancy, where patients with the most aggressive tumors show a ubiquitous glandular phenotypical shift. In addition to providing several novel "optical stains" with contrast for disease, we also adapt a two-part Cycle-consistent Generative Adversarial Network to translate the label-free deep-UV images into virtual hematoxylin and eosin (H&E) stained images, thus providing multiple stains (including the gold-standard H&E) from the same unlabeled specimen. Agreement between the virtual H&E images and the H&E-stained tissue sections is evaluated by a panel of pathologists who find that the two modalities are in excellent agreement. This work has significant implications towards improving our ability to objectively quantify prostate cancer grade and aggressiveness, thus improving the management and clinical outcomes of prostate cancer patients. This same approach can also be applied broadly in other tumor types to achieve low-cost, stain-free, quantitative histopathological analysis.
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