Ozlem Birgul

In vivo water state measurements in breast cancer using broadband diffuse optical spectroscopy

Structural changes in water molecules are related to physiological, anatomical and pathological properties of tissues. Near infrared (NIR) optical absorption methods are sensitive to water; however, detailed characterization of water in thick tissues is difficult to achieve because subtle spectral shifts can be obscured by multiple light scattering. In the NIR, a water absorption peak is observed around 975 nm. The precise NIR peaks shape and position are highly sensitive to water molecular disposition. We introduce a bound water index (BWI) that quantifies shifts observed in tissue water absorption spectra measured by broadband diffuse optical spectroscopy (DOS). DOS quantitatively measures light absorption and scattering spectra and therefore reveals bound water spectral shifts. BWI as a water state index was validated by comparing broadband DOS to magnetic resonance spectroscopy, diffusion-weighted MRI and conductivity in bound water tissue phantoms. Non-invasive DOS measurements of malignant and normal breast tissues performed in 18 subjects showed a significantly higher fraction of free water in malignant tissues (p < 0.0001) compared to normal tissues. BWI of breast cancer tissues inversely correlated with Nottingham-Bloom-Richardson histopathology scores. These results highlight broadband DOS sensitivity to molecular disposition of water and demonstrate the potential of BWI as a non-invasive in vivo index that correlates with tissue pathology.

Current constrained voltage scaled reconstruction (CCVSR) algorithm for MR-EIT and its performance with different probing current patterns.

Conventional injected-current electrical impedance tomography (EIT) and magnetic resonance imaging (MRI) techniques can be combined to reconstruct high resolution true conductivity images. The magnetic flux density distribution generated by the internal current density distribution is extracted from MR phase images. This information is used to form a fine detailed conductivity image using an Ohms law based update equation. The reconstructed conductivity image is assumed to differ from the true image by a scale factor. EIT surface potential measurements are then used to scale the reconstructed image in order to find the true conductivity values. This process is iterated until a stopping criterion is met. Several simulations are carried out for opposite and cosine current injection patterns to select the best current injection pattern for a 2D thorax model. The contrast resolution and accuracy of the proposed algorithm are also studied. In all simulation studies, realistic noise models for voltage and magnetic flux density measurements are used. It is shown that, in contrast to the conventional EIT techniques, the proposed method has the capability of reconstructing conductivity images with uniform and high spatial resolution. The spatial resolution is limited by the larger element size of the finite element mesh and twice the magnetic resonance image pixel size.

Experimental results for 2D magnetic resonance electrical impedance tomography (MR-EIT) using magnetic flux density in one direction

Magnetic resonance electrical impedance tomography (MR-EIT) is an emerging imaging technique that reconstructs conductivity images using magnetic flux density measurements acquired employing MRI together with conventional EIT measurements. In this study, experimental MR-EIT images from phantoms with conducting and insulator objects are presented. The technique is implemented using the 0.15 T Middle East Technical University MRI system. The dc current method used in magnetic resonance current density imaging is adopted. A reconstruction algorithm based on the sensitivity matrix relation between conductivity and only one component of magnetic flux distribution is used. Therefore, the requirement for object rotation is eliminated. Once the relative conductivity distribution is found, it is scaled using the peripheral voltage measurements to obtain the absolute conductivity distribution. Images of several insulator and conductor objects in saline filled phantoms are reconstructed. The L2 norm of relative error in conductivity values is found to be 13%, 17% and 14% for three different conductivity distributions.

Resolution and contrast in magnetic resonance electrical impedance tomography (MREIT) and its application to cancer imaging.

It has been reported that the electrical impedance of malignancies could be 20–40 times lower than healthy tissues and benign formations. Therefore, in vivo impedance imaging of suspicious lesions may prove to be helpful in improving the sensitivity and specificity of detecting malignant tumors. Several systems have been developed to map the conductivity distribution inside a volume of tissue, however they suffer from poor spatial resolution because the measurements are taken only from surface electrodes. MRI based impedance imaging (MREIT) is a novel method, in which weak electrical currents are injected into the tissue and the resulting perturbations in the magnetic field are measured using MRI. This method has been shown to provide better resolution compared to previous techniques of impedance imaging because the measurements are taken from inside the object on a uniform grid. Thus, it has the potential to be a useful modality that may detect malignancies earlier. Several phantom imaging experiments were performed to investigate the spatial resolution and dynamic range of contrast of this technique. The method was also applied to a live rat bearing a R3230 AC tumor. Tumor location was identified by contrast enhanced imaging.

Combined Diffuse Optical Tomography (DOT) and MRI System for Cancer Imaging in Small Animals

Recently, there has been a great amount of interest in developing multi-modality imaging techniques for oncologic research and clinical studies with the aim of obtaining complementary information and, thus, improving the detection and characterization of tumors. In this present work, the details of a combined MR-diffuse optical imaging system for dual-modality imaging of small animals are given. As a part of this effort, a multi-spectral frequency domain diffuse optical tomography system is integrated with an MRI system. Here, a network analyzer provides the rf modulation signal for the laser diodes and measures the amplitude and the phase of the detected signals. Photomultiplier tubes are utilized to measure low-level signals. The integration of this optical imaging system with the 4T MRI system is realized by incorporating a fiber adaptive interface inside the MR magnet. Coregistration is achieved by a special probe design utilizing fiducial markers. A finite element algorithm is used to solve the diffusion equation and an inverse solver based on this forward solver is implemented to calculate the absorption and scattering maps from the acquired data. The MR a priori information is used to guide the optical reconstruction algorithm. Phantom studies show that the absorption coefficient of a 7 mm inclusion in an irregular object located in 64 mm phantom is recovered with 11% error when MR a priori information is used. ENU induced tumor model is used to test the performance of the system in vivo.

Design and implementation of a multifrequency near-infrared diffuse optical tomography system

The design and implementation of a multifrequency and multispectral diffuse optical tomography system is described. Four wavelengths are utilized: 665, 785, 808, and 830 nm. The system is based on a network analyzer, which provides rf modulation signals for the laser diodes, as well as measures the amplitude and the phase of the detected signals. Six different modulation frequencies ranging from 110 to 280 MHz are used. The details of instrumentation, calibration, data acquisition, and performance of the system are given. A finite element algorithm is used to solve the diffusion equation, and an inverse solver based on this forward solver is implemented to calculate the absorption and scattering maps from the acquired data. Data acquisition for one wavelength is completed in less than 2.5 min for a single modulation frequency. The measurement repeatability is 0.5% in ac intensity and 0.2 deg in phase. The performance of the system is evaluated with phantom studies. A multifrequency reconstruction algorithm is used, in which a single absorption and scattering image pair is obtained using the whole dataset obtained at different modulation frequencies. It is shown that the multifrequency reconstruction approach provides superior image quality compared to the single frequency counterpart.

Measurement of ion diffusion using magnetic resonance electrical impedance tomography

In magnetic resonance electrical impedance tomography (MREIT), currents are applied to an object, the resulting magnetic flux density measured using MRI and the conductivity distribution reconstructed using these MRI data. In this study, we assess the ability of MREIT to monitor changes in the conductivity distribution of an agarose gel phantom, using injected current pulses of 900 microA. The phantom initially contained a distinct region of high sodium chloride concentration which diffused into the background over time. MREIT data were collected over a 12 h span, and conductivity images were reconstructed using the iterative sensitivity matrix method with Tikhonov regularization. The results indicate that MREIT was able to monitor the changing conductivity and concentration distributions resulting from the diffusion of ions within the agarose gel phantom.

Contrast and spatial resolution in MREIT using low amplitude current

Magnetic resonance-electrical impedance tomography employs low amplitude currents injected or induced inside an object. The additional magnetic field due to these currents results in a phase in the MR images. In this study, a modified fast spin-echo sequence was used to measure this magnetic field, which is obtained by scaling the MR phase image. A finite element method with first order triangular elements was used for the solution of the forward problem. An iterated sensitivity matrix-based algorithm was developed for the inverse problem. The resulting ill-conditioned matrix equation was regularized using the Tikhonov method and solved using a conjugate gradient solver. The spatial and contrast resolution of the technique was tested using agarose gel phantoms. A circular phantom with 7 cm diameter and 1 cm thickness is used in the phantom experiments. The amplitude of the injected current was 1 mA. 3, 5 and 8 mm diameter insulators and high conductor objects are used for the spatial resolution study and an average full-width half-maximum value of 4.7 mm is achieved for the 3 mm insulator case. For the contrast analysis, the conductivity of a 15 mm object is varied between 44% and 500% with respect to the background and results are compared to the ideal reconstruction.

Diffuse optical tomographic reconstruction using multifrequency data

We investigated the use of multifrequency diffuse optical tomography (MF-DOT) data for the reconstruction of the optical parameters. The experiments were performed in a 63 mm diameter cylindrical phantom containing a 15 mm diameter cylindrical object. Modulation frequencies ranging from 110 MHz to 280 MHz were used in the phantom experiments changing the contrast in absorption of the object with respect to the phantom while keeping the scattering value the same. The diffusion equation was solved using the finite element method. The sensitivity information from each frequency was combined to form a single Jacobian. The inverse problem was solved iteratively by minimizing the difference between the measurements and forward problem using single and multiple modulation frequency data. A multiparameter Tikhonov scheme was used for regularization. The phantom results show that the peak absorption coefficient in a region of interest was obtained with an error less then 5% using two-frequency reconstruction for absorption contrast values up to 2.2 times higher than background and 10% for the absorption contrast values larger than 2.2. The use of two-frequency data is sufficient to improve the quantitative accuracy compared with the single frequency reconstruction with appropriate selection of these frequencies.

New technique for high-resolution absolute conductivity imaging using magnetic-resonance electrical impedance tomography (MR-EIT)

A novel MR-EIT imaging modality has been developed to reconstruct high-resolution conductivity images with true conductivity value. In this new technique, electrical impedance tomography (EIT) and magnetic resonance imaging (MRI) techniques are simultaneously used. Peripheral voltages are measured using EIT and magnetic flux density measurements are determined using MRI. The image reconstruction algorithm used is an iterative one, based on minimizing the difference between two current density distributions calculated from voltage and magnetic flux density measurements separately. The performance of the proposed method and the suggested reconstruction algorithm are tested on simulated data. A finite element model with 1089 nodes and 2048 triangular elements is used to generate the simulated potential and magnetic field measurements. A 16 electrode opposite drive EIT strategy is adopted. The spatial resolution is space independent and limited by either the finite element size or half the MR resolution. The worst of the two defines the spatial resolution. The rms error in reconstructed conductivity for a concentric inhomogeneity is calculated as 5.35% and this error increases to 13.22% when 10% uniformly distributed random noise is added to potential and magnetic flux density measurements. The performance of the algorithm for more complex models will also be presented.