3D implementation of bias-corrected phase-based CR-MREPT

Abstract

Electrical property imaging has been a point of interest for decades as it has promising applications such as anatomical imaging, tumor detection, stroke detection and classification, early diagnosis of Alzheimer disease and dementia, RF safety and SAR calculations, and therapy planning and monitoring. Among different electrical property imaging methods, MREPT has the advantage of using a standard MRI device so that its non-invasive, does not use external coils or electrodes, and does not rely on ionizing radiation. Many MREPT methods are proposed, but most of them suffer from similar limitations such as internal boundary artifacts, transceive phase approximation, concave bias, and long imaging times caused by high SNR requirements. These problems significantly limit the clinical feasibility of MREPT. cr-MREPT, especially in phase-based form, overcomes internal boundary artifacts without using the transceive phase approximation but still suffers from concave bias and high SNR requirements. Moreover, even tough implementation in 3D is straightforward, phase-based cr-MREPT is not previously employed in 3D since hardware requirements and reconstruction times make the method impractical for clinical applications. In this thesis, we aim to develop an MREPT method that overcomes all the mentioned limitations and is feasible to use in clinical applications. To achieve this, a novel bias correction method is proposed to overcome the concave bias. The proposed method is evaluated on the basis of simulation and experimental phantoms, and the conductivity distributions are successfully reconstructed in each case. Later on, the bias corrected phase-based cr-MREPT method is implemented in 3D and a new, practical reconstruction method is proposed to improve feasibility of the method applying on conductivity reconstructions of large objects. The method divides the object into smaller volumes so that the reconstruction of each volume is more manageable and can be parallelized to accelerate the solution process. Small region sizes are determined by performing sensitivity analysis on phase-based cr-MREPT, and the performance of the proposed method is proven on various noiseless and noise-added simulation data. Last but not least, a cr- MREPT library is developed to improve the availability of 2D/3D bias corrected cr-MREPT for researchers, increase collaboration between different groups and provide better comparative evaluation of different methods.