A non-invasive means to determine lesion depth (I.e. Breslow Thickness) and an indirect, lesion-specific assessment of cellular morphology could substantially improve the efficacy of melanoma screening. Such applications would be of great benefit in aiding diagnosis, reducing the number of unnecessary biopsies, and improving treatment options for patients. Using Spatial Frequency Domain Imaging (SFDI), we have developed a spectral method to isolate depth-specific scattering properties and hence, differentiate pigmented lesion volumes from underlying tissue by its structural morphology. This method was evaluated on solid phantoms that emulate the optical properties of suspect pigmented lesions over multiple thicknesses.

Detection of hemoglobin (tHb), water (tH2O), and microvascular perfusion dynamics is of great importance as these indicate early signs of tissue physiological changes related to diseases. We have developed a physiological model based on tissue absorption and scattering properties measured by a customized spatial frequency domain imaging (SFDI) system. We performed an in-vivo investigation to evaluate the imager’s ability to characterize dermal response under a noxious heating protocol. In this initial study, we found that noxious heating induced changes in extravascular water content, hemoglobin, and tissue morphology that can be interpreted as vascular perfusion and dilation, inflammation, and edema.

Significance: Assessment of disease using optical coherence tomography is an actively investigated problem, owing to many unresolved challenges in early disease detection, diagnosis, and treatment response monitoring. The early manifestation of disease or precancer is typically associated with subtle alterations in the tissue dielectric and ultrastructural morphology. In addition, biological tissue is known to have ultrastructural multifractality.

Aim: Detection and characterization of nanosensitive structural morphology and multifractality in the tissue submicron structure. Quantification of nanosensitive multifractality and its alteration in progression of tumor.

Approach: We have developed a label free nanosensitive multifractal detrended fluctuation analysis(nsMFDFA) technique in combination with multifractal analysis and nanosensitive optical coherence tomography (nsOCT). The proposed method deployed for extraction and quantification of nanosensitive multifractal parameters in mammary fat pad (MFP).

Results: Initially, the nsOCT approach is numerically validated on synthetic submicron axial structures. The nsOCT technique was applied to pathologically characterized MFP of murine breast tissue to extract depth-resolved nanosensitive submicron structures. Subsequently, two-dimensional MFDFA were deployed on submicron structural en face images to extract nanosensitive tissue multifractality. We found that nanosensitive multifractality increases in transition from healthy to tumor.

Conclusions: This method for extraction of nanosensitive tissue multifractality promises to provide a noninvasive diagnostic tool for early disease detection and monitoring treatment response. The novel ability to delineate the dominant submicron scale nanosensitive multifractal properties may also prove useful for characterizing a wide variety of complex scattering media of non-biological origin.

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Detection of scattering and absorption properties in both visible and near-infrared regions are crucial to quantify multiple functional responses in tissue. We developed a compact, clinical spatial frequency domain imaging (SFDI) system around a custom, nine wavelength, compound-eye camera, spanning ~450-1000nm. In addition to the characterization and validation of this device, we performed a preliminary in-vivo investigation to evaluate the imager’s ability to characterize dermal response under a noxious heating protocol. Increases in hemoglobin and water concentration are detected as well as slight alterations in the reduced scattering spectrum that maybe correlated with cellular and extra-cellular reactivity.

Assessment of disease using OCT is an actively investigated problem, owing to many unresolved challenges in early disease detection, diagnosis and treatment response monitoring. The spatial scale to which the information can be obtained from the scattered light is limited by the diffraction limit (~λ/2; λ = wavelength of light is typically in the micron level) and the axial resolution of OCT systems is limited by the inverse of spectral bandwidth. Yet, onset or progression of disease /precancer is typically associated with subtle alterations in the tissue dielectric and its ultra-structural morphology. On the other hand, biological tissue is known to have ultra-structural multifractality. For both the fundamental study of biological processes and early diagnosis of pathological processes, information on the nanoscale in the tissue sub-micron structural morphology is crucial. Therefore, we have developed a novel spectroscopic and label-free 3D OCT system with nanoscale sensitivity in combination of multifractal analysis for extraction and quantification of tissue ultra-structural multifractal parameters. This present approach demonstrated its capability to measure nano-sensitive tissue ultra-structural multifractality. In an initial study, we found that nano-sensitive sub-micron structural multifractality changes in transition from healthy to tumor in pathologically characterized fresh tissue samples. This novel method for extraction of nanosensitive tissue multifractality promises to develop a non-invasive diagnosis tool for early cancer detection.

Approximately 90% of cancers originate in epithelial tissues leading to epithelial thickening, but the ultrastructural changes and underlying architecture are less well known. Depth resolved label free visualization of nanoscale tissue morphology is required to reveal the extent and distribution of ultrastructural changes in underlying tissue, but is difficult to achieve with existing imaging modalities. We developed a nanosensitive optical coherence tomography (nsOCT) approach to provide suchimaging based on dominant axial structure with a few nanometre detection accuracy. nsOCT maps the distribution of axial structural sizes an order of magnitude smaller than the axial resolution of the system. We validated nsOCT methodology by detecting synthetic axial structure via numerical simulations. Subsequently, we validated the nsOCT technique experimentally by detecting known structures from a commercially fabricated sample. nsOCT reveals scaling with different depth of dominant submicronstructural changes associated with carcinoma which may inform the origins of the disease, its progression and improve diagnosis.