Two-layer inverse model for improved longitudinal preclinical tumor imaging in the spatial frequency domain

Tabassum, Syeda; Pera, Vivian; Greening, Gage J.; Muldoon, Timothy J.; Roblyer, Darren

doi:10.1117/1.jbo.23.7.076011

Cited by 20 publications

(13 citation statements)

References 41 publications

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“…The current model assumes a homogeneous sample and reported optical properties and functional information are an averaged value for the underlying tissues. A two-layer model could improve measurements of tumor optical properties and hemodynamics (Tabassum et al, 2018). Given the diversity of anatomic locations common to sarcomas and body types, it is recommended to use a model where lipid layer thickness does not need to be known (Pifferi et al, 2001).…”

Section: Processing Modelmentioning

confidence: 99%

Clinical Feasibility of Diffuse Optical Spectroscopic Imaging for Sarcoma

Peterson

2016

Biomedical Optics 2016

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I have the best family and friends. You have created a support network that has allowed me to grow and overcome. I could not have done this without you. Darren, thank you for being my advisor. You have given me freedom to explore and discover. Bang, thank you for being my co-sponsor. You have coached me in the clinic and encouraged me with your unwavering enthusiasm for me and this project. I am grateful to my committee members, Cathie, Elise, and Ji, for guiding this project and me. I would like to acknowledge all members of the BOTLab, past and present, for their friendship and support, especially my fellow DOSI collaborators. Brannon, thank you for curiosity and patience while creating the phantom set. Professor Bigio, from my first year as an academic advisee to my final year as a Ph.D., you have been a steadfast mentor and an example of a student ally and advocate. I had a lot of help from my clinical collaborators. At Montefiore Medical Center and MD Anderson Cancer Center, I would like to acknowledge Drs. Bang Hoang, David Geller, Rui Yang, and Richard Gorlick. Thank you so much for your enthusiasm and support, you have been amazing collaborators. I also want to acknowledge Janet, Jeremy, and Damian, for coordinating measurements, consenting subjects, extracting patient data, documenting IRB amendments, and guiding me and this project. At Boston Medical Center, I would like to thank Liz, Salli, Jill, Meredith, Jen, Joanna, Malti, Debbie, and Nancy for all their help. Liz, I'll miss doing the DOSI-DO with you. For when everything falls apart, thank you Chris, Dan, and Eric at the Electronic Design Facility for helping me put it back together again. From measurements to data processing to repairs, I would also like to thank Anais, Amanda, and Tom for imparting all of their DOSI knowledge and wisdom. Within the Biomedical Engineerv ing Department, I'm so grateful for all the help, support, and laughs from Christen, Will, Allie, Stephanie, Nicole, and Tara.

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Section: Processing Modelmentioning

confidence: 99%

Clinical Feasibility of Diffuse Optical Spectroscopic Imaging for Sarcoma

Peterson

2016

Biomedical Optics 2016

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“…5 ). This effect can potentially be mitigated through the use of multi-layer inverse models or tomographic reconstructions that take different tissue regions (e.g., the skin layer) into consideration 64 . Similarly, the application of skin cream may also affect blood lipid results, and requires further investigation going forward.…”

Section: Discussionmentioning

confidence: 99%

Shortwave-infrared meso-patterned imaging enables label-free mapping of tissue water and lipid content

et al. 2020

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Water and lipids are key participants in many biological processes, but there are few non-invasive methods that provide quantification of these components in vivo, and none that can isolate and quantify lipids in the blood. Here we develop a new imaging modality termed shortwave infrared meso-patterned imaging (SWIR-MPI) to provide label-free, non-contact, spatial mapping of water and lipid concentrations in tissue. The method utilizes patterned hyperspectral illumination to target chromophore absorption bands in the 900–1,300 nm wavelength range. We use SWIR-MPI to monitor clinically important physiological processes including edema, inflammation, and tumor lipid heterogeneity in preclinical models. We also show that SWIR-MPI can spatially map blood-lipids in humans, representing an example of non-invasive and contact-free measurements of in vivo blood lipids. Together, these results highlight the potential of SWIR-MPI to enable new capabilities in fundamental studies and clinical monitoring of major conditions including obesity, cancer, and cardiovascular disease.

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“…Absorption ( μ a ( λ )) and reduced scattering (

μ_{s}^{'} ((), λ)

) were recovered using a two‐ f x inversion algorithm which indexed a lookup table (LUT) relating R d to optical properties for a given f x pair. LUTs were generated from Monte Carlo (MC) simulation results as described elsewhere . For in vivo measurements, HbO 2 (μM) and HHb concentrations (μM) were calculated by performing a least squares fit with Equation 1 using known extinction coefficients for HbO 2 and HHb, and measured μ a values at [659, 691, 731, 851] nm:

{\overset{false\to}{μ}}_{a} ((), λ) = {\overset{false\to}{ε}}_{Hb O_{2}} ((), λ) C_{Hb O_{2}} + {\overset{false\to}{ε}}_{HHb} ((), λ) C_{HHb} .

…”

Section: Methodsmentioning

confidence: 99%

Diffuse and nonlinear imaging of multiscale vascular parameters for in vivo monitoring of preclinical mammary tumors

Karrobi

Tank

Tabassum

et al. 2019

Journal of Biophotonics

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Diffuse optical imaging (DOI) techniques provide a wide‐field or macro assessment of the functional tumor state and have shown substantial promise for monitoring treatment efficacy in cancer. Conversely, intravital microscopy provides a high‐resolution view of the tumor state and has played a key role in characterizing treatment response in the preclinical setting. There has been little prior work in investigating how the macro and micro spatial scales can be combined to develop a more comprehensive and translational view of treatment response. To address this, a new multiscale preclinical imaging technique called diffuse and nonlinear imaging (DNI) was developed. DNI combines multiphoton microscopy with spatial frequency domain imaging (SFDI) to provide multiscale data sets of tumor microvascular architecture coregistered within wide‐field hemodynamic maps. A novel method was developed to match the imaging depths of both modalities by utilizing informed SFDI spatial frequency selection. An in vivo DNI study of murine mammary tumors revealed multiscale relationships between tumor oxygen saturation and microvessel diameter, and tumor oxygen saturation and microvessel length (|Pearson's ρ| ≥ 0.5, P < 0.05). Going forward, DNI will be uniquely enabling for the investigation of multiscale relationships in tumors during treatment.

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Two-layer inverse model for improved longitudinal preclinical tumor imaging in the spatial frequency domain

Cited by 20 publications

References 41 publications

Clinical Feasibility of Diffuse Optical Spectroscopic Imaging for Sarcoma

Clinical Feasibility of Diffuse Optical Spectroscopic Imaging for Sarcoma

Shortwave-infrared meso-patterned imaging enables label-free mapping of tissue water and lipid content

Diffuse and nonlinear imaging of multiscale vascular parameters for in vivo monitoring of preclinical mammary tumors

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