Image-guided optical spectroscopy in diagnosis of osteoarthritis: a clinical study

Detecting inflammation in rheumatoid arthritis using Fourier transform analysis of dorsal optical transmission images from a pilot study

A clinical need exists for low-cost and noninvasive imaging tools capable of detecting inflammation in the joints of inflammatory arthritis patients. Previous studies have reported an optical contrast between inflamed and noninflamed joints resulting from distinct absorption and scattering properties. Accurate classification using nonocclusion-based continuous wave, transillumination imaging was limited to patient-specific changes during follow-up examination as opposed to single time-point examination, which was attributed to high intersubject variability. In distinction from previous work, optical images were acquired from the dorsal side with illumination on the palmar side and features about the spatial distribution of transmitted light along the joint were assessed using a normalized Fourier transform method. Results using this approach demonstrated an area under receiver operator curve of up to 0.888 for detecting inflammation in a pilot study involving single time-point examination of 144 joints from 21 rheumatology patients. This workflow may enable future development of clinically viable, low-cost devices for assessing inflammation in arthritis patients, without the need for cuff occlusion or comparison to baseline.

Multispectral, non-contact diffuse optical tomography of healthy human finger joints

Rheumatoid arthritis (RA) is an inflammatory joint disease often affecting the hands, which if untreated causes disability. Diffuse optical tomography (DOT) provides information about the underlying functional properties of biological tissue. To detect pathophysiological changes in inflamed RA joints, a good understanding of the baseline values for healthy subjects is first required. Finger joints from healthy subjects were imaged using a non-contact, multispectral, continuous wave DOT system, recovering physiological parameters of oxygen saturation, total haemoglobin, water concentration and scatter amplitude. Reconstructed values across the cohort demonstrated good consistency between finger joints from the same participant, with greater variation seen between subjects.

Optical mapping of prefrontal activity in pathological gamblers

Functional near-infrared spectroscopy (fNIRS) has emerged as a highly promising brain mapping technique that enables continuously and noninvasively monitoring the hemodynamic responses in the human brain. In this study, fNIRS was utilized to identify the different brain activation patterns between pathological gamblers (PGs) and healthy controls (HCs). Specifically, we examined the hemodynamic changes in the prefrontal cortex using fNIRS recordings during the completion of executive function and decision-making tasks for both PGs and HCs. Our mapping results revealed that PGs and HCs exhibited notable differences in the hemodynamic responses and brain activation patterns across the prefrontal region.

Two schemes for quantitative photoacoustic tomography based on Monte Carlo simulation

PURPOSE

The aim of this study was to develop novel methods for photoacoustically determining the optical absorption coefficient of biological tissues using Monte Carlo (MC) simulation.

METHODS

In this study, the authors propose two quantitative photoacoustic tomography (PAT) methods for mapping the optical absorption coefficient. The reconstruction methods combine conventional PAT with MC simulation in a novel way to determine the optical absorption coefficient of biological tissues or organs. Specifically, the authors' two schemes were theoretically and experimentally examined using simulations, tissue-mimicking phantoms, ex vivo, and in vivo tests. In particular, the authors explored these methods using several objects with different absorption contrasts embedded in turbid media and by using high-absorption media when the diffusion approximation was not effective at describing the photon transport.

RESULTS

The simulations and experimental tests showed that the reconstructions were quantitatively accurate in terms of the locations, sizes, and optical properties of the targets. The positions of the recovered targets were accessed by the property profiles, where the authors discovered that the off center error was less than 0.1 mm for the circular target. Meanwhile, the sizes and quantitative optical properties of the targets were quantified by estimating the full width half maximum of the optical absorption property. Interestingly, for the reconstructed sizes, the authors discovered that the errors ranged from 0 for relatively small-size targets to 26% for relatively large-size targets whereas for the recovered optical properties, the errors ranged from 0% to 12.5% for different cases.

CONCLUSIONS

The authors found that their methods can quantitatively reconstruct absorbing objects of different sizes and optical contrasts even when the diffusion approximation is unable to accurately describe the photon propagation in biological tissues. In particular, their methods are able to resolve the intrinsic difficulties that occur when quantitative PAT is conducted by combining conventional PAT with the diffusion approximation or with radiation transport modeling.

Joint blood flow is more sensitive to inflammatory arthritis than oxyhemoglobin, deoxyhemoglobin, and oxygen saturation

Joint hypoxia plays a central role in the progression and perpetuation of rheumatoid arthritis (RA). Thus, optical techniques that can measure surrogate markers of hypoxia such as blood flow, oxyhemoglobin, deoxyhemoglobin, and oxygen saturation are being developed to monitor RA. The purpose of the current study was to compare the sensitivity of these physiological parameters to arthritis. Experiments were conducted in a rabbit model of RA and the results revealed that joint blood flow was the most sensitive to arthritis and could detect a statistically significant difference (p<0.05, power = 0.8) between inflamed and healthy joints with a sample size of only four subjects. Considering that this a quantitative technique, the high sensitivity to arthritis suggests that joint perfusion has the potential to become a potent tool for monitoring disease progression and treatment response in RA.

Dual-Modality Imaging of the Human Finger Joint Systems by Using Combined Multispectral Photoacoustic Computed Tomography and Ultrasound Computed Tomography

We developed a homemade dual-modality imaging system that combines multispectral photoacoustic computed tomography and ultrasound computed tomography for reconstructing the structural and functional information of human finger joint systems. The fused multispectral photoacoustic-ultrasound computed tomography (MPAUCT) system was examined by the phantom and in vivo experimental tests. The imaging results indicate that the hard tissues such as the bones and the soft tissues including the blood vessels, the tendon, the skins, and the subcutaneous tissues in the finger joints systems can be effectively recovered by using our multimodality MPAUCT system. The developed MPAUCT system is able to provide us with more comprehensive information of the human finger joints, which shows its potential for characterization and diagnosis of bone or joint diseases.

A systematic investigation of reflectance diffuse optical tomography using nonlinear reconstruction methods and continuous wave measurements

We conducted a systematic investigation of the reflectance diffuse optical tomography using continuous wave (CW) measurements and nonlinear reconstruction algorithms. We illustrated and suggested how to fine-tune the nonlinear reconstruction methods in order to optimize target localization with depth-adaptive regularizations, reduce boundary noises in the reconstructed images using a logarithm based objective function, improve reconstruction quantification using transport models, and resolve crosstalk problems between absorption and scattering contrasts with the CW reflectance measurements. The upgraded nonlinear reconstruction algorithms were evaluated with a series of numerical and experimental tests, which show the potentials of the proposed approaches for imaging both absorption and scattering contrasts in the deep targets with enhanced image quality.

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

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.

Limited-view photoacoustic imaging based on an iterative adaptive weighted filtered backprojection approach

An iterative adaptive weighted filtered backprojection (FBP) approach was applied to our photoacoustic imaging (PAI) of the optical absorption in biological tissues from limited-view data. By using an image-based adaptive weighted PAI reconstruction, we can modify the defect of the artifacts degrading the quality of the image. Results of numerical simulations demonstrated that the proposed algorithm was superior to FBP in terms of both accuracy and robustness to noise. Reconstructed images of biological tissues agreed well with the structures of the samples. The resolution of the PAI system with the proposed method was experimentally demonstrated to be better than 0.14 mm. By using the proposed method, the imaging quality of the PAI system can be improved.

Combining independent component analysis and Granger causality to investigate brain network dynamics with fNIRS measurements

In this study a new strategy that combines Granger causality mapping (GCM) and independent component analysis (ICA) is proposed to reveal complex neural network dynamics underlying cognitive processes using functional near infrared spectroscopy (fNIRS) measurements. The GCM-ICA algorithm implements the following two procedures: (i) extraction of the region of interests (ROIs) of cortical activations by ICA, and (ii) estimation of the direct causal influences in local brain networks using Granger causality among voxels of ROIs. Our results show that the use of GCM in conjunction with ICA is able to effectively identify the directional brain network dynamics in time-frequency domain based on fNIRS recordings.