Subdiffusion reflectance spectroscopy to measure tissue ultrastructure and microvasculature: model and inverse algorithm

Radosevich, Andrew J.; Eshein, Adam; Nguyen, The-Quyen; Backman, Vadim

doi:10.1117/1.jbo.20.9.097002

Cited by 20 publications

(36 citation statements)

References 42 publications

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“…The fraction of hemoglobin saturated with oxygen was extracted from the diffuse backscattering spectrum using methods described in other publications. 26,27 Measurements acquired manually have a lower percentage of oxygen-saturated hemoglobin, and despite the manual measurements in Fig. 9(a) appearing very similar, the interpatient variance is significantly higher (P < 0.05) indicating a level of inconsistency from patient-to-patient.…”

Section: Automated In Vivo Signal Acquisitionmentioning

confidence: 85%

“…Many optical spectroscopy techniques require processing (e.g., subtraction) of spectra, measured from different channels or detectors, 5,18,23,24 or fitting wavelength-dependent features in the spectrum. 23,[25][26][27][28] If the wavelength calibration on the detectors is not accurate or has shifted with time since initial factory calibration, then small features in the spectra can become large artifacts in the resulting processed spectra. This process is shown in Fig.…”

Section: Wavelength Calibration Featurementioning

confidence: 99%

See 1 more Smart Citation

Fully automated fiber-based optical spectroscopy system for use in a clinical setting

Eshein¹,

Radosevich²,

Gould³

et al. 2018

J. Biomed. Opt.

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While there are a plethora of in vivo fiber-optic spectroscopic techniques that have demonstrated the ability to detect a number of diseases in research trials with highly trained personnel familiar with the operation of experimental optical technologies, very few techniques show the same level of success in large multicenter trials. To meet the stringent requirements for a viable optical spectroscopy system to be used in a clinical setting, we developed components including an automated calibration tool, optical contact sensor for signal acquisition, and a methodology for real-time in vivo probe calibration correction. The end result is a state-of-the-art medical device that can be realistically used by a physician with spectroscopic fiber-optic probes. We show how the features of this system allow it to have excellent stability measuring two scattering phantoms in a clinical setting by clinical staff with ∼0.5 % standard deviation over 25 unique measurements on different days. In addition, we show the systems' ability to overcome many technical obstacles that spectroscopy applications often face such as speckle noise and user variability. While this system has been designed and optimized for our specific application, the system and design concepts are applicable to most in vivo fiber-optic-based spectroscopic techniques.

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Section: Automated In Vivo Signal Acquisitionmentioning

confidence: 85%

Section: Wavelength Calibration Featurementioning

confidence: 99%

Fully automated fiber-based optical spectroscopy system for use in a clinical setting

Eshein¹,

Radosevich²,

Gould³

et al. 2018

J. Biomed. Opt.

Self Cite

View full text Add to dashboard Cite

show abstract

“…A first-order approximation to conceptualizing γ is the ratio of relative contributions of large to small scatters [27]. Previous work has reported γ values in tissue in the range of [1.3–2.2] [−] [12,14,26,31], with smaller values representative of scatterers that are smaller than the wavelength of scattered light and larger values representative of scatterers approaching the same length scale as the wavelength of light. While γ has been shown to be linearly proportional to the fractal dimension of scatterers in a turbid medium, a deterministic link between the two parameters is complicated by other physical parameters that influence the exact form of the scattering phase function [27]; therefore, a concise description of γ may best be as a metric proportional to the length scale of biological scattering features.…”

Section: Methodsmentioning

confidence: 99%

Wide-field quantitative imaging of tissue microstructure using sub-diffuse spatial frequency domain imaging

McClatchy¹,

Rizzo²,

Wells³

et al. 2016

Optica

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Localized measurements of scattering in biological tissue provide sensitivity to microstructural morphology but have limited utility to wide-field applications, such as surgical guidance. This study introduces sub-diffusive spatial frequency domain imaging (sd-SFDI), which uses high spatial frequency illumination to achieve wide-field sampling of localized reflectances. Model-based inversion recovers macroscopic variations in the reduced scattering coefficient (μs′) and the phase function backscatter parameter (γ). Measurements in optical phantoms show quantitative imaging of user-tuned phase-function-based contrast with accurate decoupling of parameters that define both the density and the size-scale distribution of scatterers. Measurements of fresh ex vivo breast tissue samples revealed, for the first time, unique clustering of sub-diffusive scattering properties for different tissue types. The results support that sd-SFDI provides maps of microscopic structural biomarkers that cannot be obtained with diffuse wide-field imaging and characterizes spatial variations not resolved by point-based optical sampling.

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“…While the contrast at low spatial frequencies is dictated by absorption features (presence of blood, fat) and diffuse scattering (density of tissue), the contrast of sub-diffusive high spatial frequency images is dictated by both scattering intensity and the angular distribution of scattering events, or phase function, as photon propagation is constrained to superficial volumes with minimal volumetric averaging over tortuous photon path-lengths (Krishnaswamy et al 2014, Bodenschatz et al 2014). The phase function arises from the underlying physical properties of tissue ultrastructure (Bartek et al 2006, Rogers et al 2009, Radosevich et al 2015). Recent studies have used sub-diffusive structured light imaging to quantify angular scattering distributions through the phase function parameter γ , which is related to the size-scale distribution of scattering features (Kanick et al 2014, Bodenschatz et al 2015).…”

Section: Introductionmentioning

confidence: 99%

Calibration and analysis of a multimodal micro-CT and structured light imaging system for the evaluation of excised breast tissue

et al. 2017

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A multimodal micro-computed tomography (CT) and multi-spectral structured light imaging (SLI) system is introduced and systematically analyzed to test its feasibility to aid in margin delineation during breast conserving surgery (BCS). Phantom analysis of the micro-CT yielded a signal-to-noise ratio (SNR) of 34, a contrast of 1.64, and a minimum detectable resolution of 240 µm for a 1.2 min scan. The SLI system, spanning wavelengths 490 nm to 800 nm and spatial frequencies up to 1.37 mm−1, was evaluated with aqueous tissue simulating phantoms having variations in particle size distribution, scatter density, and blood volume fraction. The reduced scattering coefficient, μs′ and phase function parameter, γ, were accurately recovered over all wavelengths independent of blood volume fractions from 0% to 4%, assuming a flat sample geometry perpendicular to the imaging plane. The resolution of the optical system was tested with a step phantom, from which the modulation transfer function (MTF) was calculated yielding a maximum resolution of 3.78 cycles per mm. The three dimensional (3D) spatial co-registration between the CT and optical imaging space was tested and shown to be accurate within 0.7 mm. A freshly resected breast specimen, with lobular carcinoma, fibrocystic disease, and adipose, was imaged with the system. The micro-CT provided visualization of the tumor mass and its spiculations, and SLI yielded superficial quantification of light scattering parameters for the malignant and benign tissue types. These results appear to be the first demonstration of SLI combined with standard medical tomography for imaging excised tumor specimens. While further investigations are needed to determine and test the spectral, spatial, and CT features required to classify tissue, this study demonstrates the ability of multimodal CT/SLI to quantify, visualize, and spatially navigate breast tumor specimens, which could potentially aid in the assessment of tumor margin status during BCS.

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Subdiffusion reflectance spectroscopy to measure tissue ultrastructure and microvasculature: model and inverse algorithm

Cited by 20 publications

References 42 publications

Fully automated fiber-based optical spectroscopy system for use in a clinical setting

Fully automated fiber-based optical spectroscopy system for use in a clinical setting

Wide-field quantitative imaging of tissue microstructure using sub-diffuse spatial frequency domain imaging

Calibration and analysis of a multimodal micro-CT and structured light imaging system for the evaluation of excised breast tissue

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