Biomedical subjects

Ozlem Birgul

Publications and source records attributed to Ozlem Birgul.

7 recordsLinked to original sources

PubMed2006

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.

Algorithms↗

PubMed2006

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.

Algorithms↗

PubMed2006

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.

Algorithms↗

PubMed2006

In vivo MRI electrical impedance tomography (MREIT) of tumors.

A significant increase in electrical conductivity of neoplasticities compared to healthy tissues and benign formations has been reported in several studies. We previously reported preliminary results with MR based Electrical Impedance Tomography (MREIT) on several phantoms and a single animal. In the presented study, we applied the technique on ten tumor-bearing rats and collected MREIT images to investigate the potential of MREIT for characterizing malignant tumors. Results show that the tumors had significantly higher mean conductivity compared to the mean of conductivity in the rest of the body. Although heterogeneity of conductivity was observed in the tumor, the mean was still higher than the background.

Algorithms↗

PubMed2004

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.

Animals↗

PubMedDate not supplied

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.

Equipment Design↗

PubMedDate not supplied

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.

Algorithms↗