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

Abstract

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.

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

“…2, have been outlined previously. 8 In brief, patients placed their hands on the platform of the system, which collected optical transmission images of the finger using an air-cooled, charged couple device camera, while a broadband, point source was injected into the opposing side of the joint. Images were collected at 14 source positions in a straight line along the sagittal direction of the finger, with this acquisition repeated at five wavelengths (650, 710, 730, 830, and 930 nm) by spectral decoupling using a filter wheel preceding the camera objective lens.…”

“…Intrinsic optical contrast in DOI results from changes in the predominant absorbing chromophores: oxyhaemoglobin, deoxyhaemoglobin, water, and lipids, or changes in scattering properties. Two modes of data acquisition have been investigated for joint imaging: continuous wave (CW), [8][9][10] in which only the amplitude of transmitted intensity was considered, or frequency domain (FD), 11,12 in which the mean phase shift for a modulated source is also measured providing information about the photon pathlength.…”

“…Longitudinal studies using this device involving a total of 136 proximal interphalangeal (PIP) joints from 22 RA patients and 8 healthy controls, reported up to 80% sensitivity (S E ) and 89% specificity (S P ) for correctly classifying changes in the inflammatory status over time when comparing baseline and follow-up examinations, by using advanced classification tools such as, a generalized linear model, Gaussian process regression, Gaussian process classification, or support vector machines. [8][9][10] Despite these promising results for monitoring disease progression, the authors describe an inability to accurately determine the inflammatory status using this dataset from a single examination alone without reference baseline, as attributed to a "high interindividual variability of joint structure and optical characteristics." 9 This has been supported by evidence of a significantly greater variation observed between fingers from different subjects than when comparing fingers from the same subject in pathophysiological parameters recovered using tomographic, multispectral CW data.…”

“…9 This has been supported by evidence of a significantly greater variation observed between fingers from different subjects than when comparing fingers from the same subject in pathophysiological parameters recovered using tomographic, multispectral CW data. 8 The use of cuff occlusion to partially diminish the impact of intersubject variability, in which haemodynamic changes were induced in the joint during wide-field, CW trans-illumination measurement, enabled inflammation in PIP joints to be classified with 83% S E and 64% S P from single time-point assessment; 18 however, occlusion can potentially introduce additional discomfort in patients already experiencing a degree of pain. State-of-the-art techniques, involving tomographic reconstruction of 3-D maps of absorption and scattering coefficients using single wavelength FD data reported S E and S P of up to 91% and 86%, respectively, using basic statistical features such as the maximum, minimum, and variance.…”

“…A noncontact, multispectral DOI system has been previously reported. 8 Motivated by previous demonstrations of improvement in classification accuracy through the use of FFT analysis of absorption and scattering maps in diffuse optical tomography, 32 a normalized FFT methodology is presented in this work to extract features about the spatial profile of transmitted flux along the sagittal direction of the joint. The impact of an asymmetrical distribution of inflammation in the coronal direction on these features is investigated in simulation studies and finally the performance of this methodology for classifying the inflammatory status of joints in patients with inflammatory arthritis is assessed in a pilot study.…”