High‐resolution x‐ray guided three‐dimensional diffuse optical tomography of joint tissues in hand osteoarthritis: Morphological and functional assessments

Yuan, Zhen; Zhang, Qizhi; Sobel, Eric S.; Jiang, Huabei

doi:10.1118/1.3467755

Cited by 20 publications

(16 citation statements)

References 27 publications

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“…Functional near infrared spectroscopy (fNIRS) offers unsurpassed high temporal resolution and provides quantitative hemodynamic information for both oxyhemoglobin ( HbO 2 ) and deoxyhemoglobin ( HbR ), which plays an important role in the in vivo study of cognitive processing in the human brain (Jobsis, 1977; Cope and Delpy, 1988; Hoshi, 2003; Singh et al, 2005; Huppert et al, 2009; Ye et al, 2009; Yuan et al, 2010a,b; Brunno et al, 2011; Egetemeir et al, 2011; Gagnon et al, 2012; Yuan, in press). Similar to its fNIRS counterpart, functional magnetic resonance imaging (fMRI) is also a non-invasive imaging method that measures the hemodynamic responses to even-related neural activity with excellent spatial resolution and low temporal resolution.…”

Section: Introductionmentioning

confidence: 99%

Fusion of fNIRS and fMRI data: identifying when and where hemodynamic signals are changing in human brains

Yuan¹,

2013

Front. Hum. Neurosci.

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In this study we implemented a new imaging method to fuse functional near infrared spectroscopy (fNIRS) measurements and functional magnetic resonance imaging (fMRI) data to reveal the spatiotemporal dynamics of the hemodynamic responses with high spatiotemporal resolution across the brain. We evaluated this method using multimodal data acquired from human right finger tapping tasks. And we found the proposed method is able to clearly identify from the linked components of fMRI and fNIRS where and when the hemodynamic signals are changing. In particular, the estimated associations between fNIRS and fMRI will be displayed as time varying spatial fMRI maps along with the fNIRS time courses. In addition, the joint components between fMRI and fNIRS are combined together to generate full spatiotemporal “snapshots” and movies, which provides an excellent way to examine the dynamic interplay between hemodynamic fNIRS and fMRI measurements.

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Section: Introductionmentioning

confidence: 99%

Fusion of fNIRS and fMRI data: identifying when and where hemodynamic signals are changing in human brains

Yuan¹,

2013

Front. Hum. Neurosci.

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“…This procedure allows performing tomographic reconstructions without having to probe the medium with multiple sources at different boundaries positions or with multiple frequencies. Moreover, it avoids combining prior knowledge provided by another imaging modalities such as MRI or x ray by exclusively exploiting the qualitative indication obtained by our reconstruction algorithm.…”

Section: Resultsmentioning

confidence: 99%

Three‐dimensional frequency‐domain optical anisotropy imaging of biological tissues with near‐infrared light

2019

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Purpose Near‐infrared optical imaging aims to reconstruct the absorption μa and scattering μs coefficients in order to detect tumors at early stage. However, the reconstructions have only been limited to μa and μs due to theoretical and computational limitations. The authors propose an efficient method of the reconstruction, in three‐dimensional geometries, of the anisotropy factor g of the Henyey–Greenstein phase function as a new optical imaging biomarker. Methods The light propagation in biological tissues is accurately modeled by the radiative transfer equation (RTE) in the frequency‐domain. The reconstruction algorithm is based on a gradient‐based updating scheme. The adjoint method is used to efficiently compute the gradient of the objective function which represents the discrepancy between simulated and measured boundary data. A parallel implementation is carried out to reduce the computational time. Results We show that by illuminating only one surface of a tissue‐like phantom, the algorithm is able to accurately reconstruct optical values and different shapes (spherical and cylindrical) that characterize small tumor‐like inclusions. Numerical simulations show the robustness of the algorithm to reconstruct the anisotropy factor with different contrast levels, inclusion depths, initial guesses, heterogeneous background, noise levels, and two‐layered medium. The crosstalk problem when reconstructing simultaneously μs and g has been reported and achieved with a reasonable quality. Conclusions The proposed RTE‐based reconstruction algorithm is robust to spatially retrieve and localize small tumoral inclusions. Heterogeneities in g‐factor have been accurately reconstructed which makes the new algorithm a candidate of choice to image this factor as new intrinsic contrast biomarker for optical imaging.

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“…4a,b). The 3D finger phantom from the 3D scan of actual human finger is selected here since we are interested in applying FD-DOT to the imaging of finger joints [17-22]. In total, 11 distinct point sources (Fig.…”

Section: Numerical Phantomsmentioning

confidence: 99%

“…This limits the applications for which the DE can be used. For example, some groups (including our team) have recently shown that DOT appears to be capable of accurately diagnosing rheumatoid arthritis (RA) [17, 18, 19] and osteoarthritis (OA) [20, 21, 22] in finger joints. Yet because fingers contain void-like regions, occupy a relatively small volume, and, in the case of RA, may contain inflamed regions that are highly absorbing, the DE is of limited accuracy.…”

Section: Introductionmentioning

confidence: 99%

Frequency-domain optical tomographic image reconstruction algorithm with the simplified spherical harmonics (SP3) light propagation model

Kim

Montejo

Jia

et al. 2017

International Journal of Thermal Sciences

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We introduce here the finite volume formulation of the frequency-domain simplified spherical harmonics model with n-th order absorption coefficients (FD-SPN) that approximates the frequency-domain equation of radiative transfer (FD-ERT). We then present the FD-SPN based reconstruction algorithm that recovers absorption and scattering coefficients in biological tissue. The FD-SPN model with 3rd order absorption coefficient (i.e., FD-SP3) is used as a forward model to solve the inverse problem. The FD-SP3 is discretized with a node-centered finite volume scheme and solved with a restarted generalized minimum residual (GMRES) algorithm. The absorption and scattering coefficients are retrieved using a limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) algorithm. Finally, the forward and inverse algorithms are evaluated using numerical phantoms with optical properties and size that mimic small-volume tissue such as finger joints and small animals. The forward results show that the FD-SP3 model approximates the FD-ERT (S12) solution within relatively high accuracy; the average error in the phase (<3.7%) and the amplitude (<7.1%) of the partial current at the boundary are reported. From the inverse results we find that the absorption and scattering coefficient maps are more accurately reconstructed with the SP3 model than those with the SP1 model. Therefore, this work shows that the FD-SP3 is an efficient model for optical tomographic imaging of small-volume media with non-diffuse properties both in terms of computational time and accuracy as it requires significantly lower CPU time than the FD-ERT (S12) and also it is more accurate than the FD-SP1.

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High‐resolution x‐ray guided three‐dimensional diffuse optical tomography of joint tissues in hand osteoarthritis: Morphological and functional assessments

Cited by 20 publications

References 27 publications

Fusion of fNIRS and fMRI data: identifying when and where hemodynamic signals are changing in human brains

Fusion of fNIRS and fMRI data: identifying when and where hemodynamic signals are changing in human brains

Three‐dimensional frequency‐domain optical anisotropy imaging of biological tissues with near‐infrared light

Frequency-domain optical tomographic image reconstruction algorithm with the simplified spherical harmonics (SP3) light propagation model

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