A handheld imaging system uses deep-ultraviolet (DUV) light to visualize molecular features in biological samples without chemical stains, with potential relevance for diagnostic laboratories. The system – described in a study published in eLight and known as the deep-ultraviolet ptychographic pocket-scope (DART) – combines lens-free imaging with spectroscopic analysis to detect nucleic acids and proteins in unstained specimens.
Pathology workflows typically rely on staining to provide contrast, but staining adds time and can alter samples. Label-free imaging approaches offer an alternative but often lack molecular specificity or sufficient field of view. DART operates in the DUV range, where biomolecules naturally absorb light at specific wavelengths, allowing intrinsic molecular contrast without labels.
The system uses two DUV wavelengths, 266 nm and 280 nm, which preferentially highlight nucleic acids and proteins. Images are reconstructed using ptychography, a computational method that builds high-resolution images from diffraction patterns rather than lenses. According to the authors, DART can image centimeter-scale areas with submicron resolution and millimeter-scale depth of field, enabling examination of large or uneven samples without mechanical refocusing.
To address optical artifacts associated with DUV imaging, the researchers implemented a computational correction method that separates true specimen information from system-related errors. This approach improved image quality across multiple unstained sample types, including fine-needle aspiration smears, blood smears, tissue sections, and cultured cells.
The study outlines several diagnostic-relevant demonstrations. In unstained lung fine-needle aspiration smears, DART revealed nuclear and cytoplasmic features that were not visible with standard brightfield microscopy. In blood samples, the system enabled label-free visualization of leukocytes and quantitative separation of mononuclear and polymorphonuclear cells based on morphology and nuclear-to-cytoplasmic ratios, parameters commonly used in hematologic assessment.
DART also supports “virtual staining” by converting quantitative measurements of nucleic acid and protein content into images resembling hematoxylin and eosin staining. This process is based on measured molecular absorption rather than machine learning, maintaining a direct link between image contrast and molecular composition.
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