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Spectroscopic optical coherence tomography (SOCT) allows for the targeted analysis of cell nuclei due to their spectrally distinct scattering properties. SOCT has been explored for optical biopsy based on its ability to extract structural and spectroscopic properties of a sample without the need for labels. Using the dual-window method for SOCT, spatial correlations can be computed throughout volumetric scans and analyzed to determine the size of cell nuclei. Such analysis could enable quantitative visualization of tissue boundaries that appear homogenous in structural OCT images. Here, we present spectroscopic correlation tomography (SpCT), a technique for mapping spatial correlation measurements to a hue-saturation-value (HSV) color space to help visualize relative changes in spatial correlation throughout volumetric OCT samples. SpCT B-Scans and volumes of polystyrene bead samples with diameters 5.1 μm to 11.3 μm were acquired and scatterer sizes were quantified using a Gaussian mixture model, achieving size estimates within half-wavelength accuracy. 3T3 fibroblasts were imaged and analyzed via connected component analysis, producing strong agreement with scatterer size measured via confocal microscopy, thus validating our approach. Histology versus SpCT B-Scan comparisons were performed for human colon organoids, cardiac organoids, and human lung airway explant to demonstrate this technique’s ability to identify varying degrees of nuclear morphology in different regions. SpCT volumes were used to objectively discriminate between control and APC -mutated human colon organoids based on a connected component analysis, identifying regions of long spatial correlation and computing the coefficient of variation of the region volumes, which points to a potential clinical use of this technique.
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O'Kane et al. (2026) studied this question.
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