Biomedical subjects

Simon R Arridge

Publications and source records attributed to Simon R Arridge.

At least 19 recordsLinked to original sources

PubMed2006

Two-dimensional quantitative photoacoustic image reconstruction of absorption distributions in scattering media by use of a simple iterative method.

Photoacoustic imaging is a noninvasive biomedical imaging modality for visualizing the internal structure and function of soft tissues. Conventionally, an image proportional to the absorbed optical energy is reconstructed from measurements of light-induced acoustic emissions. We describe a simple iterative algorithm to recover the distribution of optical absorption coefficients from the image of the absorbed optical energy. The algorithm, which incorporates a diffusion-based finite-element model of light transport, converges quickly onto an accurate estimate of the distribution of absolute absorption coefficients. Two-dimensional examples with physiologically realistic optical properties are shown. The ability to recover optical properties (which directly reflect tissue physiology) could enhance photoacoustic imaging techniques, particularly methods based on spectroscopic analysis of chromophores.

Acoustics↗

PubMed2006

Diffuse photon propagation in multilayered geometries.

Diffuse optical tomography (DOT) is an emerging functional medical imaging modality which aims to recover the optical properties of biological tissue. The forward problem of the light propagation of DOT can be modelled in the frequency domain as a diffusion equation with Robin boundary conditions. In the case of multilayered geometries with piecewise constant parameters, the forward problem is equivalent to a set of coupled Helmholtz equations. In this paper, we present solutions for the multilayered diffuse light propagation for a three-layer concentric sphere model using a series expansion method and for a general layered geometry using the boundary element method (BEM). Results are presented comparing these solutions to an independent Monte Carlo model, and for an example three layered head model.

Algorithms↗

PubMed2006

Information content of data types in time-domain optical tomography.

The information content of data types in time-domain optical tomography is quantified by studying the detectability of signals in the attenuation and reduced scatter coefficients. Detection in both uniform and structured backgrounds is considered, and our results show a complex dependence of spatial detectability maps on the type of signal, data type, and background. In terms of the detectability of lesions, the mean time of arrival of photons and the total number of counts effectively summarize the information content of the full temporal waveform. A methodology for quantifying information content prior to reconstruction without assumptions of linearity is established, and the importance of signal and background characterization is highlighted.

Algorithms↗

PubMed2005

Dynamic physiological modeling for functional diffuse optical tomography.

Diffuse optical tomography (DOT) is a noninvasive imaging technology that is sensitive to local concentration changes in oxy- and deoxyhemoglobin. When applied to functional neuroimaging, DOT measures hemodynamics in the scalp and brain that reflect competing metabolic demands and cardiovascular dynamics. The diffuse nature of near-infrared photon migration in tissue and the multitude of physiological systems that affect hemodynamics motivate the use of anatomical and physiological models to improve estimates of the functional hemodynamic response. In this paper, we present a linear state-space model for DOT analysis that models the physiological fluctuations present in the data with either static or dynamic estimation. We demonstrate the approach by using auxiliary measurements of blood pressure variability and heart rate variability as inputs to model the background physiology in DOT data. We evaluate the improvements accorded by modeling this physiology on ten human subjects with simulated functional hemodynamic responses added to the baseline physiology. Adding physiological modeling with a static estimator significantly improved estimates of the simulated functional response, and further significant improvements were achieved with a dynamic Kalman filter estimator (paired t tests, n=10, P<0.05). These results suggest that physiological modeling can improve DOT analysis. The further improvement with the Kalman filter encourages continued research into dynamic linear modeling of the physiology present in DOT. Cardiovascular dynamics also affect the blood-oxygen-dependent (BOLD) signal in functional magnetic resonance imaging (fMRI). This state-space approach to DOT analysis could be extended to BOLD fMRI analysis, multimodal studies and real-time analysis.

Blood Pressure↗

PubMed2005

Coupled radiative transfer equation and diffusion approximation model for photon migration in turbid medium with low-scattering and non-scattering regions.

In this paper, a coupled radiative transfer equation and diffusion approximation model is extended for light propagation in turbid medium with low-scattering and non-scattering regions. The light propagation is modelled with the radiative transfer equation in sub-domains in which the assumptions of the diffusion approximation are not valid. The diffusion approximation is used elsewhere in the domain. The two equations are coupled through their boundary conditions and they are solved simultaneously using the finite element method. The streamline diffusion modification is used to avoid the ray-effect problem in the finite element solution of the radiative transfer equation. The proposed method is tested with simulations. The results of the coupled model are compared with the finite element solutions of the radiative transfer equation and the diffusion approximation and with results of Monte Carlo simulation. The results show that the coupled model can be used to describe photon migration in turbid medium with low-scattering and non-scattering regions more accurately than the conventional diffusion model.

Animals↗

PubMed2005

Linear and nonlinear reconstruction for optical tomography of phantoms with nonscattering regions.

Most research in optical imaging incorrectly assumes that light transport in nonscattering regions in the head may be modeled by use of the diffusion approximation. The effect of this assumption is examined in a series of experiments on tissue-equivalent phantoms. Images from cylindrical and head-shaped phantoms with and without clear regions [simulating the cerebrospinal fluid (CSF) filled ventricles] and a clear layer (simulating the CSF layer surrounding the brain) are reconstructed with linear and nonlinear reconstruction techniques. The results suggest that absorbing and scattering perturbations can be identified reliably with nonlinear reconstruction methods when the clear regions are also present in the reference data but that the quality of the image degrades considerably if the reference data does not contain these features. Linear reconstruction performs similarly to nonlinear reconstruction, provided the clear regions are present in the reference data, but otherwise linear reconstruction fails. This study supports the use of linear reconstruction for dynamic imaging but suggests that, in all cases, image quality is likely to improve if the clear regions are modeled correctly.

Algorithms↗

PubMed2005

Optical tomography of the breast using a multi-channel time-resolved imager.

A time-resolved optical tomography system has been used to generate cross-sectional images of the human breast. Images are reconstructed using an iterative, nonlinear algorithm and measurements of mean photon flight time relative to those acquired on a homogeneous reference phantom. Thirty-eight studies have been performed on three healthy volunteers and 21 patients with a variety of breast lesions including cancer. We have successfully detected 17 out of 19 lesions, and shown that optical images of the healthy breast of the same volunteer display a heterogeneity which is repeatable over a period of months. However, results also indicate that the lack of accurate quantitation of optical parameters and limited morphological information limits the ability to characterize different types of lesions and distinguish benign from malignant tissues. Drawbacks of our current methodology and plans for overcoming them are discussed.

Adult↗

PubMed2005

Gauss-Newton method for image reconstruction in diffuse optical tomography.

We present a regularized Gauss-Newton method for solving the inverse problem of parameter reconstruction from boundary data in frequency-domain diffuse optical tomography. To avoid the explicit formation and inversion of the Hessian which is often prohibitively expensive in terms of memory resources and runtime for large-scale problems, we propose to solve the normal equation at each Newton step by means of an iterative Krylov method, which accesses the Hessian only in the form of matrix-vector products. This allows us to represent the Hessian implicitly by the Jacobian and regularization term. Further we introduce transformation strategies for data and parameter space to improve the reconstruction performance. We present simultaneous reconstructions of absorption and scattering distributions using this method for a simulated test case and experimental phantom data.

Algorithms↗

PubMed2005

Diffuse optical tomography with spectral constraints and wavelength optimization.

We present an algorithm that explicitly utilizes the wavelength dependence of tissue optical properties for diffuse optical tomography. We have previously shown that the method gives superior separation of absorption and scattering. Here the technique is described and tested in detail, and optimum wavelength sets for a broad range of chromophore combinations are discovered and analyzed.

Algorithms↗

PubMed2005

Computational calibration method for optical tomography.

We propose a computational calibration method for optical tomography. The model of the calibration scheme is based on the rotation symmetry of source and detector positions in the measurement setup. The relative amplitude losses and phase shifts at the optic fibers are modeled by complex-valued coupling coefficients. The coupling coefficients can be estimated when optical tomography data from a homogeneous and isotropic object are given. Once these coupling coefficients have been estimated, any data measured with the same measurement setup can be corrected for the relative variation in the data due to source and detector losses. The final calibration of the data for the source and detector losses and the source calibration between the data and the forward model are obtained as part of the initial estimation for reconstruction. The calibration method was tested with simulations and measurements. The results show that the coupling coefficients of the sources and detectors can be estimated with good accuracy. Furthermore, the results show that the method can significantly improve the quality of reconstructed images.

Algorithms↗

PubMed2005

Monitoring recovery after laser surgery of the breast with optical tomography: a case study.

Results are presented of a study to monitor the changes in the optical properties of breast tissue over a 12-month period after interstitial laser photocoagulation treatment of a fibroadenoma. The study involved generating cross-sectional images of the breast with a multichannel time-resolved imaging system and a nonlinear image reconstruction algorithm. Images of the internal absorbing and scattering properties revealed the expected initial inflammatory response, followed by the development of low-scattering cysts consistent with corresponding ultrasound examinations. Although results indicate that purely qualitative images can potentially provide clinically valuable data, means of enhancing diagnostic information by overcoming present limitations of the approach are discussed.

Adult↗

PubMed2005

An inverse problem approach to the estimation of volume change.

We present a new technique for determining structure-by-structure volume changes, using an inverse problem approach. Given a pre-labelled brain and a series of images at different time-points, we generate finite element meshes from the image data, with volume change modelled by means of an unknown coefficient of expansion on a per-structure basis. We can then determine the volume change in each structure of interest using inverse problem optimization techniques. The proposed method has been tested with simulated and clinical data. Results suggest that the presented technique can be seen as an alternative for volume change estimation.

Algorithms↗

PubMed2005

Physiological system identification with the Kalman filter in diffuse optical tomography.

Algorithms↗

PubMed2005

Diffuse optical tomography of breast cancer during neoadjuvant chemotherapy: a case study with comparison to MRI.

We employ diffuse optical tomography (DOT) to track treatment progress in a female subject presenting with locally advanced invasive carcinoma of the breast during neoadjuvant chemotherapy. Three-dimensional images of total hemoglobin concentration and scattering identified the tumor. Our measurements reveal tumor shrinkage during the course of chemotherapy, in reasonable agreement with magnetic resonance images of the same subject. A decrease in total hemoglobin concentration contrast between tumor and normal tissue was also observed over time. The results demonstrate the potential of DOT for measuring physiological parameters of breast lesions during chemotherapy.

Adult↗

PubMed2004

Imaging changes in blood volume and oxygenation in the newborn infant brain using three-dimensional optical tomography.

Induced haemodynamic and blood oxygenation changes occurring within the brain of a ventilated newborn infant have been imaged in three dimensions using optical tomography. Noninvasive measurements of the flight times of transmitted light were acquired during illumination of the brain by laser pulses at wavelengths of 780 nm and 815 nm. The oxygen and carbon dioxide partial pressures were adjusted through alterations to the ventilator settings, resulting in changes to the cerebral blood volume and oxygenation. Three-dimensional images were generated using the physiologically associated differences in the measured data, obviating the need for data calibration using a separate reference measurement. The results exhibit large changes in absorption coefficient at both wavelengths. Images corresponding to differences in concentrations of oxy- and deoxyhaemoglobin are in qualitative agreement with known physiological data.

Blood Flow Velocity↗

PubMed2003

Uniqueness and wavelength optimization in continuous-wave multispectral diffuse optical tomography.

We derive conditions for the unique and simultaneous recovery of chromophore concentrations and scattering coefficients in multispectral continuous-wave diffuse optical tomography. These conditions depend strongly on measurement wavelengths. We introduce and demonstrate a general methodology for choosing those wavelengths, which yields superior separation of scattering from absorption and superior separation of one chromophore from another. Application of these concepts should significantly improve the fidelity of continuous-wave diffuse near-infrared optical tomography in tissues.

Computer Simulation↗

PubMed2003

Time-series estimation of biological factors in optical diffusion tomography.

We apply state space estimation techniques to the time-varying reconstruction problem in optical tomography. We develop a stochastic model for describing the evolution of quasi-sinusoidal medical signals such as the heartbeat, assuming these are represented as a known frequency with randomly varying amplitude and phase. We use the extended Kalman filter in combination with spatial regularization techniques to reconstruct images from highly under-determined time-series data. This system also naturally segments activity belonging to different biological processes. We present reconstructions of simulated data and of real data recorded from the human motor cortex (Franceschini et al 2000 Optics Express 6 49-57). It is argued that the application of these time-series techniques improves both the fidelity and temporal resolution of reconstruction in optical tomography.

Algorithms↗

PubMed2003

Optical tomography of a realistic neonatal head phantom.

We have begun clinical trials of optical tomography of the neonatal brain. To validate this research, we have built and imaged an anatomically realistic, tissue-equivalent neonatal head phantom that is hollow, allowing contrasting objects to be placed inside it. Images were reconstructed by use of two finite-element meshes, one generated from a computed tomography image of the phantom and the other spherical. The phantom was filled with a liquid of the same optical properties as the outer region, and two perturbations were placed inside. These were successfully imaged with good separation between the absorption and scatter coefficients. The phantom was then refilled with a liquid of increased absorption compared with the background to simulate the brain, and the absolute properties of the two regions were found. These were used as a priori information for the complete reconstruction. Both perturbations were visible, superimposed on the increased absorption of the central region. The head-shaped mesh performed slightly better than the spherical mesh, particularly when the absorption of the central region of the phantom was increased.

Head↗