Quantitative Susceptibility Mapping (QSM) Reconstruction from MRI Phase Data

Quantitative susceptibility mapping (QSM) is a powerful technique that reveals changes in the underlying tissue susceptibility distribution. It can be used to measure the concentrations of iron and calcium in the brain both of which are linked with numerous neurodegenerative diseases. However, reconstructing the QSM image from the MRI phase data is an ill-posed inverse problem. Different methods have been proposed to overcome this difficulty. Still, the reconstructed QSM images suffer from streaking artifacts and underestimate the measured susceptibility of deep gray matter, veins, and other high susceptibility regions. This thesis proposes a structurally constrained Susceptibility Weighted Imaging and Mapping (scSWIM) method to reconstruct QSM for multi-echo, multi-flip angle data collected using strategically acquired gradient echo (STAGE) imaging. scSWIM performs a single step regularization-based reconstruction technique that takes advantage of the unique contrast of the STAGE T1 weighted enhanced (T1WE) image to extract reliable geometry constraints to protect the basal ganglia from over-smoothing. Furthermore, the multi-echo, multi-flip angle data from STAGE can all be used to improve the contrast-to-noise ratio in QSM through a weighted averaging scheme. scSWIM was tested on both simulated and in vivo data. Results show that the unique contrast and tissue boundaries from T1WE and an earlier approach called iterative SWIM enable the accurate definition of the edges of high susceptibility regions. scSWIM achieved the best overall root mean squared error and structural similarity index metrics as well as the lowest deviation from the expected susceptibility in deep gray matter compared to other published methods. Finally, susceptibility measurements of the basal ganglia extracted from the scSWIM data for a cohort of Parkinson’s disease patients and healthy control subjects were in agreement with the literature

A Semi-Automated Computer Program for Assessment of Skeletal Maturity in Children

In pediatric patients, skeletal maturity is an important tool for detection of hormonal, growth or genetic disorders. The Fels method is a well-known visual assessment method in which the skeletal age is estimated by grading 98 skeletal indicators in the hand-wrist radiographic (x-ray) image. These indicators are features that reflect the three-dimensional shape of the bones and change during the maturation process. Generally, the Fels indicators could be categorized into three main groups of the status of ossification, the ratios of bone widths, and epiphysealdiaphyseal fusion

Super-Resolution Reconstruction of MRI

Magnetic Resonance Imaging (MRI) is a non-invasive technique that is used in clinical applications such as diseases diagnosis and monitoring and treatment progress. Although, MRI scans typically have high in-plane resolution but they have very poor resolution in slice direction. Furthermore, in some applications with limited acquisition time or where the subject is moving, increased slice thickness or inter-slice space (slice gaps) may be used which results in poor resolution MRI. In this research, we propose a novel Super Resolution (SR) technique for reconstructing High-Resolution (HR) MRI using a sequence of orthogonal Low-Resolution (LR) MRI scans. The resolution of this reconstructed SR MRI is improved in all directions and its information is increased comparing to the initial scans

A Semi-Automated Computer Program for Assessment of Skeletal Maturity in Children

In pediatric patients, skeletal maturity is an important tool for detection of hormonal, growth or genetic disorders. The Fels method is a well-known visual assessment method in which the skeletal age is estimated by grading 98 skeletal indicators in the hand-wrist radiographic (x-ray) image. These indicators are features that reflect the three-dimensional shape of the bones and change during the maturation process. Generally, the Fels indicators could be categorized into three main groups of the status of ossification, the ratios of bone widths, and epiphysealdiaphyseal fusion

Super-Resolution Reconstruction of MRI

Magnetic Resonance Imaging (MRI) is a non-invasive technique that is used in clinical applications such as diseases diagnosis and monitoring and treatment progress. Although, MRI scans typically have high in-plane resolution but they have very poor resolution in slice direction. Furthermore, in some applications with limited acquisition time or where the subject is moving, increased slice thickness or inter-slice space (slice gaps) may be used which results in poor resolution MRI. In this research, we propose a novel Super Resolution (SR) technique for reconstructing High-Resolution (HR) MRI using a sequence of orthogonal Low-Resolution (LR) MRI scans. The resolution of this reconstructed SR MRI is improved in all directions and its information is increased comparing to the initial scans

Super-Resolution Reconstruction of MRI

Magnetic Resonance Imaging (MRI) is a non-invasive technique that is used in clinical applications such as diseases diagnosis and monitoring and treatment progress. Although, MRI scans typically have high in-plane resolution but they have very poor resolution in slice direction. Furthermore, in some applications with limited acquisition time or where the subject is moving, increased slice thickness or inter-slice space (slice gaps) may be used which results in poor resolution MRI. In this research, we propose a novel Super Resolution (SR) technique for reconstructing High-Resolution (HR) MRI using a sequence of orthogonal Low-Resolution (LR) MRI scans. The resolution of this reconstructed SR MRI is improved in all directions and its information is increased comparing to the initial scans

Multi-Echo Quantitative Susceptibility Mapping for Strategically Acquired Gradient Echo (STAGE) Imaging

Purpose: To develop a method to reconstruct quantitative susceptibility mapping (QSM) from multi-echo, multi-flip angle data collected using strategically acquired gradient echo (STAGE) imaging. Methods: The proposed QSM reconstruction algorithm, referred to as “structurally constrained Susceptibility Weighted Imaging and Mapping” scSWIM, performs an ℓ1 and ℓ2 regularization-based reconstruction in a single step. The unique contrast of the T1 weighted enhanced (T1WE) image derived from STAGE imaging was used to extract reliable geometry constraints to protect the basal ganglia from over-smoothing. The multi-echo multi-flip angle data were used for improving the contrast-to-noise ratio in QSM through a weighted averaging scheme. The measured susceptibility values from scSWIM for both simulated and in vivo data were compared to the: original susceptibility model (for simulated data only), the multi orientation COSMOS (for in vivo data only), truncated k-space division (TKD), iterative susceptibility weighted imaging and mapping (iSWIM), and morphology enabled dipole inversion (MEDI) algorithms. Goodness of fit was quantified by measuring the root mean squared error (RMSE) and structural similarity index (SSIM). Additionally, scSWIM was assessed in ten healthy subjects. Results: The unique contrast and tissue boundaries from T1WE and iSWIM enable the accurate definition of edges of high susceptibility regions. For the simulated brain model without the addition of microbleeds and calcium, the RMSE was best at 5.21ppb for scSWIM and 8.74ppb for MEDI thanks to the reduced streaking artifacts. However, by adding the microbleeds and calcium, MEDI’s performance dropped to 47.53ppb while scSWIM performance remained the same. The SSIM was highest for scSWIM (0.90) and then MEDI (0.80). The deviation from the expected susceptibility in deep gray matter structures for simulated data relative to the model (and for the in vivo data relative to COSMOS) as measured by the slope was lowest for scSWIM + 1%(−1%); MEDI + 2%(−11%) and then iSWIM −5%(−10%). Finally, scSWIM measurements in the basal ganglia of healthy subjects were in agreement with literature. Conclusion: This study shows that using a data fidelity term and structural constraints results in reduced noise and streaking artifacts while preserving structural details. Furthermore, the use of STAGE imaging with multi-echo and multi-flip data helps to improve the signal-to-noise ratio in QSM data and yields less artifacts

Structurally Constrained Quantitative Susceptibility Mapping

In this study, a structurally constrained susceptibility reconstruction method, SCSWIM, is proposed. This method employs the unique contrast of STAGE imaging and segmented basal ganglia and vessels. It is tested on both simulated and in vivo human brain data. Evaluations show the improved reliability of the geometry information, reduced streaking artifacts, and increased accuracy of the susceptibilities of both basal ganglia and veins in the SCSWIM compared to other methods

Structurally Constrained Quantitative Susceptibility Mapping

In this study, a structurally constrained susceptibility reconstruction method, SCSWIM, is proposed. This method employs the unique contrast of STAGE imaging and segmented basal ganglia and vessels. It is tested on both simulated and in vivo human brain data. Evaluations show the improved reliability of the geometry information, reduced streaking artifacts, and increased accuracy of the susceptibilities of both basal ganglia and veins in the SCSWIM compared to other methods

Structurally Constrained Quantitative Susceptibility Mapping

In this study, a structurally constrained susceptibility reconstruction method, SCSWIM, is proposed. This method employs the unique contrast of STAGE imaging and segmented basal ganglia and vessels. It is tested on both simulated and in vivo human brain data. Evaluations show the improved reliability of the geometry information, reduced streaking artifacts, and increased accuracy of the susceptibilities of both basal ganglia and veins in the SCSWIM compared to other methods