Suchergebnisse

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 such imaging 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 submicron structural changes associated with carcinoma which may inform the origins of the disease, its progression and improve diagnosis. ; This project received funding from Irish Research Council (IRC), under Government of Ireland postdoctoral fellowship with project ID: GOIPD/2017/837. Nandan Das acknowledge National University of Ireland Galway (NUIG) for research facilities. Also, this project has received funding from the European Union's Horizon 2020 research and innovation program under grant agreements no. 761214 and no. 779960. The materials presented and views expressed here are the responsibility of the author(s) only. The EU Commission takes no responsibility for any use made of the information set out. This work was supported by NUI Galway, Galway University Foundation, the University of Limerick Foundation, the National Biophotonics Imaging Platform (NBIP) Ireland funded under the Higher Education Authority PRTLI Cycle 4 and co-funded by the Irish Government and the European Union. ; peer-reviewed

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. ; Funding agencies: Irish Research Council (IRC), under Government of IrelandIrish Research Council for Science, Engineering and ...

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. ; This project received funding from Irish Research Council (IRC), under Government of Ireland postdoctoral fellowship with project ID: GOIPD/2017/837. Nandan Das acknowledge National University of Ireland Galway (NUIG) for research facilities. He would also like to acknowledge the Knut and Alice Wallenberg Foundation support through the Wallenberg Centre for Molecular Medicine (WCMM) at Linköping University (LiU), Sweden. Also, this project has received funding from the European Union's Horizon 2020 research and innovation program under Grant Agreement Nos. 761214 and 779960. The materials presented and views expressed here are the responsibility of the author(s) only. The EU Commission takes no responsibility for any use made of the information set out. ; peer-reviewed