Significance: Diffuse optical spectroscopic imaging (DOSI) is a versatile technology sensitive to changes in tissue composition and hemodynamics and has been used for a wide variety of clinical applications. Specific applications have prompted the development of versions of the DOSI technology to fit specific clinical needs. This work describes the development and characterization of a multi-modal DOSI (MM-DOSI) system that can acquire metabolic, compositional, and pulsatile information at multiple penetration depths in a single hardware platform. Additionally, a 3D tracking system is integrated with MM-DOSI, which enables registration of the acquired data to the physical imaging area.
Aim: We demonstrate imaging, layered compositional analysis, and metabolism tracking capabilities using a single MM-DOSI system on optical phantoms as well as in vivo human tissue.
Approach: We characterize system performance with a silicone phantom containing an embedded object. To demonstrate multi-layer sensitivity, we imaged human calf tissue with a 4.8-mm skin-adipose thickness. Human thenar tissue was also measured using a combined broadband DOSI and continuous-wave near-infrared spectroscopy method (∼15 Hz acquisition rate).
Results: High-resolution optical property maps of absorption (μa) and reduced scattering (μs ′ ) were recovered on the phantom by capturing over 1000 measurement points in under 5 minutes. On human calf tissue, we show two probing depth layers have significantly different (p < 0.001) total-hemo/myoglobin and μs ′ composition. On thenar tissue, we calculate tissue arterial oxygen saturation, venous oxygen saturation, and tissue metabolic rate of oxygen consumption during baseline and after release of an arterial occlusion.
Conclusions: The MM-DOSI can switch between collection of broadband spectra, high-resolution images, or multi-depth hemodynamics without any hardware reconfiguration. We conclude that MM-DOSI enables acquisition of high resolution, multi-modal data consolidated in a single platform, which can provide a more comprehensive understanding of tissue hemodynamics and composition for a wide range of clinical applications.
Diffuse optical spectroscopic imaging (DOSI) and diffuse correlation spectroscopy (DCS) are model-based near-infrared (NIR) methods that measure tissue optical properties (broadband absorption, μa, and reduced scattering, μs′) and blood flow (blood flow index, BFI), respectively. DOSI-derived μa values are used to determine composition by calculating the tissue concentration of oxy- and deoxyhemoglobin (HbO2, HbR), water, and lipid. We developed and evaluated a combined, coregistered DOSI/DCS handheld probe for mapping and imaging these parameters. We show that uncertainties of 0.3 mm−1 (37%) in μs′ and 0.003 mm−1 (33%) in μa lead to ∼53% and 9% errors in BFI, respectively. DOSI/DCS imaging of a solid tissue-simulating flow phantom and a breast cancer patient reveals well-defined spatial distributions of BFI and composition that clearly delineates both the flow channel and the tumor. BFI reconstructed with DOSI-corrected μa and μs′ values had a tumor/normal contrast of 2.7, 50% higher than the contrast using commonly assumed fixed optical properties. In conclusion, spatially coregistered imaging of DOSI and DCS enhances intrinsic tumor contrast and information content. This is particularly important for imaging diseased tissues where there are significant spatial variations in μa and μs′ as well as potential uncoupling between flow and metabolism.
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