Dr. Soheil Soltani Profile

Dr. Soheil Soltani

at Ellison Institute LLC

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Publications (13)

SPIE Journal Paper | 14 July 2021 Open Access

Label-free detection of brain tumors in a 9L gliosarcoma rat model using stimulated Raman scattering-spectroscopic optical coherence tomography

Soheil Soltani, Zhe Guang, Zhaobin Zhang, Jeffrey Olson, Francisco Robles

JBO, Vol. 26, Issue 07, 076004, (July 2021) https://doi.org/10.1117/12.10.1117/1.JBO.26.7.076004

KEYWORDS: Tumors, Brain, Optical coherence tomography, Tissues, Raman spectroscopy, Proteins, Signal attenuation, Neuroimaging, Signal detection, Nonlinear optics

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Significance: In neurosurgery, it is essential to differentiate between tumor and healthy brain regions to maximize tumor resection while minimizing damage to vital healthy brain tissue. However, conventional intraoperative imaging tools used to guide neurosurgery are often unable to distinguish tumor margins, particularly in infiltrative tumor regions and low-grade gliomas. Aim: The aim of this work is to assess the feasibility of a label-free molecular imaging tool called stimulated Raman scattering-spectroscopic optical coherence tomography (SRS-SOCT) to differentiate between healthy brain tissue and tumor based on (1) structural biomarkers derived from the decay rate of signals as a function of depth and (2) molecular biomarkers based on relative differences in lipid and protein composition extracted from the SRS signals. Approach: SRS-SOCT combines the molecular sensitivity of SRS (based on vibrational spectroscopy) with the spatial and spectral multiplexing capabilities of SOCT to enable fast, spatially and spectrally resolved molecular imaging. SRS-SOCT is applied to image a 9L gliosarcoma rat tumor model, a well-characterized model that recapitulates human high-grade gliomas, including high proliferative capability, high vascularization, and infiltration at the margin. Structural and biochemical signatures acquired from SRS-SOCT are extracted to identify healthy and tumor tissues. Results: Data show that SRS-SOCT provides light-scattering-based signatures that correlate with the presence of tumors, similar to conventional OCT. Further, nonlinear phase changes from the SRS interaction, as measured with SRS-SOCT, provide an additional measure to clearly separate tumor tissue from healthy brain regions. We also show that the nonlinear phase signals in SRS-SOCT provide a signal-to-noise advantage over the nonlinear amplitude signals for identifying tumors. Conclusions: SRS-SOCT can distinguish both spatial and spectral features that identify tumor regions in the 9L gliosarcoma rat model. This tool provides fast, label-free, nondestructive, and spatially resolved molecular information that, with future development, can potentially assist in identifying tumor margins in neurosurgery.

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Proceedings Article | 5 March 2021 Presentation + Paper

Label-free multi-spectral deep UV imaging of prostate cancer tissue

Soheil Soltani, Ashkan Ojaghi, Adeboye Osunkoya, Francisco Robles

Proceedings Volume 11655, 116550H (2021) https://doi.org/10.1117/12.2579891

KEYWORDS: Tissues, Prostate cancer, Deep ultraviolet, Cancer, Visualization, Spatial resolution, Quantitative analysis, Proteins, Principal component analysis, Pathology

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Prostate cancer is the most common non-cutaneous cancer in men. Moreover, identifying the most effective treatment strategy for an individual with prostate cancer strongly depends on the Gleason score (Grade group) of the disease. However, this task continues to be a significant clinical challenge in a subset of patients. Currently, the gold standard for grading prostate cancer is the Pathologist’s visual assessment of hematoxylin-and-eosin-stained histological sections, and designation of a Gleason score (Grade group) based on the top two most common Gleason grades. However, this process is subjective and thus prone to error and high variability, especially amongst non-Urologic Pathologists or those who are not aware of recent modifications to the grading system. In addition, variations in protocols for staining, could make quantitative analysis of stained tissues challenging in some cases. Therefore, there is a significant clinical need to develop additional complementary quantitative methods that can provide robust, objective, reproducible, and accurate information of the aggressiveness and grade of prostate cancer. Here we address this issue by imaging unstained tissue sections using multi-spectral deep-UV microscopy. This method enables us to obtain valuable quantitative insight into the aggressiveness and grade of the disease due to its subcellular spatial resolution and high sensitivity to many endogenous biomolecules, including nucleic acid and proteins. The approach uses a simple, fast and cost effective wide-field imaging configuration that is well-suited for pathology applications. Spectral signatures form wavelengths ranging from 220 nm to 450 nm are analyzed using a geometrical representation of principal component analysis. Our results reveal distinct morphological and molecular alterations in tissue as they progress from benign to cancerous, and as they become more aggressive (higher grade). In this research project, we delineated the design of the multispectral, deep UV microscope and described our quantitative and qualitative image analysis. Our results show that multispectral deep UV microscopy provides a quantitative measure to differentiate between prostate cancer patients with varying grades of cancer.

Proceedings Article | 17 February 2020 Presentation + Paper

Deep UV microscopy of prostate cancer tissue

Soheil Soltani, Ashkan Ojaghi, Atsutse Kludze, Francisco Robles

Proceedings Volume 11243, 1124317 (2020) https://doi.org/10.1117/12.2546200

KEYWORDS: Prostate cancer, Tissues, Deep ultraviolet, Microscopy, Ultraviolet radiation, Cancer, Spherical lenses, Spatial resolution, Proteins, Principal component analysis

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Proceedings Article | 4 March 2019 Presentation + Paper

Characterization of the thermo-optic coefficient of silicon oxynitride using whispering gallery mode optical microcavities

Andre Kovach, Dongyu Chen, Soheil Soltani, Sumiko Poust, Vincent Gambin, Andrea Armani

Proceedings Volume 10904, 109041A (2019) https://doi.org/10.1117/12.2507561

KEYWORDS: Silicon, Refractive index, Thermal optics, Integrated optics, Silica, Resonators, Temperature metrology, Gas lasers, Optical microcavities, Integrated photonics

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Proceedings Article | 16 February 2018 Paper

Nonlinear behavior in hybrid microcavities

Andrea Armani, Dongyu Chen, Andre Kovach, Xiaoqin Shen, Hyungwoo Choi, Soheil Soltani

Proceedings Volume 10518, 1051804 (2018) https://doi.org/10.1117/12.2289093

KEYWORDS: Microresonators, Optical microcavities, Raman spectroscopy, Silica, Molecules, Nonlinear optics, Optical resonators, Machine learning, RF photonics, Quantum optics

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Proceedings Article | 21 April 2017 Presentation

Kerr frequency combs generated by hybrid microcavities (Conference Presentation)

Rigoberto Castro, Vinh Diep, Eda Gungor, Soheil Soltani, Andrea Armani

Proceedings Volume 10090, 100900K (2017) https://doi.org/10.1117/12.2253321

KEYWORDS: Frequency combs, Nanoparticles, Silica, Nanomaterials, Optical microcavities, Silicon, Microresonators, Gold, Physical phenomena, Optical resonators

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Proceedings Article | 21 April 2017 Presentation

Nanomaterial-enhanced frequency combs (Conference Presentation)

Andrea Armani, Rigoberto Castro-Beltran, Vinh Diep, Eda Gungor, Xiaoqin Shen, Soheil Soltani

Proceedings Volume 10090, 100900B (2017) https://doi.org/10.1117/12.2249698

KEYWORDS: Frequency combs, Nanomaterials, Optical microcavities, Resonators, Optical resonators, Optical amplifiers, Nonlinear dynamics, Frequency conversion, Four wave mixing, Silica

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Proceedings Article | 27 February 2017 Presentation + Paper

Integrated asymmetric whispering gallery mode resonator microcavity optomechanics

Soheil Soltani, Alexa Hudnut, Andrea Armani

Proceedings Volume 10090, 1009012 (2017) https://doi.org/10.1117/12.2251505

KEYWORDS: Optical resonators, Optomechanical design, Resonators, Optical microcavities, Physical phenomena, Photons, Oscillators, 3D modeling, Control systems, Instrument modeling

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Proceedings Article | 27 September 2016 Paper

Portable, low-power diagnostics based on integrated photonics and responsive materials

Andrea Armani, Daniel Amchin, Vinh Diep, Lea Fang, Eda Gungor, Alexa Hudnut, Brock Hudnut, Michele Lee, Sam McBirney, Soheil Soltani

Proceedings Volume 9930, 99300P (2016) https://doi.org/10.1117/12.2238709

KEYWORDS: Ultraviolet radiation, Diagnostics, Integrated photonics, Polymers, Polarimetry, Elastography, Sensors, Tissues, Atomic force microscopy, Smart materials

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Proceedings Article | 22 April 2016 Paper

High-Q GRIN resonators

A. Armani, S. Soltani, H. Choi, V. Diep, A. Kovach, K. Kuo

Proceedings Volume 9727, 972707 (2016) https://doi.org/10.1117/12.2214409

KEYWORDS: Silica, Sol-gels, Resonators, Coating, Refractive index, GRIN lenses, Optical resonators, Geometrical optics, Silicon, Temperature metrology

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Proceedings Article | 3 March 2015 Paper

Role of geometry in optothermal response of toroidal ultra-high-Q cavities

Soheil Soltani, Andrea Armani

Proceedings Volume 9343, 93431T (2015) https://doi.org/10.1117/12.2076480

KEYWORDS: Resonators, Absorption, Thermal optics, Oxides, Refractive index, Thermal modeling, Instrument modeling, Optical components, Optical resonators, Distortion

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Proceedings Article | 7 March 2014 Paper

High bandwidth, low loss suspended silica splitters

Soheil Soltani, Andrea Armani

Proceedings Volume 8980, 898005 (2014) https://doi.org/10.1117/12.2035309

KEYWORDS: Waveguides, Polarization, 3D modeling, Silica, Finite-difference time-domain method, Instrument modeling, Silicon, Optical simulations, Light wave propagation, Lithography

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Proceedings Article | 4 March 2014 Paper

Optically pumped gold nanorod plasmonic microlaser

Ce Shi, Soheil Soltani, Andrea Armani

Proceedings Volume 8960, 89600S (2014) https://doi.org/10.1117/12.2036015

KEYWORDS: Gold, Plasmonics, Polymers, Nanoparticles, Photorefractive polymers, Refractive index, 3D modeling, Polymethylmethacrylate, Silica, Nanorods

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Showing 5 of 13 publications

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