The primary research goal of the Muftuler laboratory is to address engineering challenges in diagnostic imaging to achieve higher sensitivity and specificity to the pathophysiology of various diseases. In order to accomplish these goals, we have developed novel hardware and imaging protocols (pulse sequences) for MRI systems and utilized these new technologies in various neuroimaging, musculoskeletal imaging and cancer imaging research studies.
Our objective is to establish a strong research program in MRI technology and build productive collaborations with researchers from diverse backgrounds, which is essential to address increasingly complex issues in the field of healthcare.
More information about Dr. Muftuler can be found on his neurosurgery page.
Research Area: Diffusion Kurtosis Imaging
Diffusion MRI, in general, helps estimate the bulk behavior of water molecules' random displacements inside tissues. A series of images were acquired from the brain with different diffusion weightings obtained by varying MRI gradient fields. Analysis of this series of brain images helps probe tissue microstructure noninvasively. The conventional approach called Diffusion Tensor Imaging (DTI) assumes a Gaussian distribution of water molecule displacements. However, in complex tissue structures, Gaussian distribution provides a crude estimate. This shortcoming is addressed by Diffusion Kurtosis Imaging (DKI), which estimates the distribution of water molecule displacements as a sum of a Gaussian component and a non-Gaussian component (Kurtosis). This requires an additional set of images acquired with a different set of diffusion weightings called “b-values”. So, conventional DTI acquires a series of diffusion weighted images with a single b-value, while DKI requires a series of diffusion weighted images with two different b-values. Then the post-processing software fits the Gaussian + Kurtosis model to estimate bulk behavior of water molecules more accurately. The output of this software provides both the conventional DTI parameters such as Fractional Anisotropy (FA) and Mean Diffusivity (MD) and also additional Kurtosis metrics depicting the complexity of tissues in better detail. Therefore, DKI is a clinically feasible extension of DTI. It examines the additional non-Gaussian diffusion effects that occur in the brain tissues, thereby overcoming the limitations of DTI.
Research Area: Multi-parametric MR Imaging of Spinal Disc Degeneration
We have recently initiated a new research project to study intervertebral disc degeneration using perfusion MRI, DTI, Ultra-short TE and T1rho imaging techniques that utilizes the multi-nuclear RF coils and imaging protocols that we developed (European Spine Journal, 2014). The goal is to explore the pathophysiology of spinal disc degeneration and the mechanisms that lead to this ailment. Our preliminary findings show that the blood perfusion deficiencies in disc endplates are closely associated with degeneration.
Research Area: Highly accelerated projection imaging (HAPI) with coil sensitivity encoding for rapid MRI
Rapid MRI acquisition is typically achieved by acquiring all or most lines of k-space after one RF excitation. Parallel imaging techniques can further accelerate data acquisition by acquiring fewer phase-encoded lines and utilizing the spatial sensitivity information of the RF coil arrays. The goal of this study was to develop a new MRI data acquisition and reconstruction technique that is capable of reconstructing a 2D image using highly undersampled k-space data without any special hardware. Such a technique would be very efficient, as it would significantly reduce the time wasted during multiple RF excitations or phase encoding and gradient switching periods.
The essence of this new technique is to densely sample a small number of projections, which should be acquired at an angle other than 0 degrees or multiples of 45 degrees (Ersoz A et al., Med Phys., 2013). This results in multiple rays passing through a voxel and provides new and independent measurements for each voxel. Then the images are reconstructed using the unique information coming from these projections combined with RF coil sensitivity profiles. The feasibility of this new technique was investigated with realistic simulations and experimental studies using a phantom and compared with conventional nonuniform fast Fourier transform technique. Eigenvalue analysis and error calculations were conducted to find optimal projection angles and minimum requirements for dense sampling.
Research Area: Novel Radio Frequency (RF) coil developments for MRI
We have developed a new inverse-solution approach to design RF coils optimized for parallel imaging techniques in MRI. Parallel imaging improves the speed of image acquisition. However, it introduces spatially varying degradation in signal to noise ratio (SNR) in images when conventional RF coils are used. In order to address this problem, we derived an inverse problem in which SNR was formulated as a function of coil geometry. This expression is calculated by a Least Squares approach to find the RF coil geometry that maximized the SNR of images. We hold a patent for this approach (Patent no: 7362101) and received the 1st place award in Engineering Category in the 2006 scientific meeting of the International Society of Magnetic Resonance in Medicine (ISMRM) (abstract # 26).
We have also developed various new RF coil designs to achieve better sensitivity for multinuclear MRI. One of those RF coils can be tuned automatically inside the MRI using LabVIEW to achieve the best performance for variations in the loads (Muftuler LT et al., J Magn Reson, 2002). We also developed a PIN diode controlled multinuclear RF coil that improved the SNR by more than two-fold compared to conventional coil designs (Ha S et al., Phys Med Biol, 2010). These RF coils are essential to study anatomy and metabolism simultaneously. For instance, changes in sodium concentration were implicated in tumors. Similarly, localized sodium deficits were reported in the brain in several cognitive disorders. Thus, one can obtain information about the disease metabolism from the sodium images while hydrogen images provide high-resolution structural information.
Research Area: Studies of brain development
We have studied age-associated changes in the cortex, subcortical structures and brain white matter tracts using high resolution T1 weighted images (Muftuler LT et al., Brain Res, 2011) and Diffusion Tensor Images (DTI) (Muftuler LT et al., Brain Res, 2012). The results revealed maps of brain development in preadolescent ages at very high spatial and temporal detail.
Research Area: Studies of Aging and Dementia
Investigating subtle changes in tissue structure and metabolism is critical to diagnose diseases at early stages. Therefore, we have studied techniques to improve image resolution and contrast in various neuroimaging studies. For instance, we have recently obtained a very high resolution DTI of the perforant path in the hippocampus, a very thin and curved axonal fiber tract (Yassa MA et al., Proc Natl Acad Sci U S A, 2010). Apart from the small size, it resides in a region that is prone to severe distortions and signal loss due to variations in tissue magnetic susceptibility. This fiber tract is implicated in early stages of Alzheimer’s disease.
Research Area: MR based Electrical Impedance Tomography (MREIT)
This is a new imaging technique that provides image contrast based on electrical properties of tissues. We successfully applied this technique to study conductivity changes in animal models of breast cancer (Muftuler LT et al., Technol Cancer Res Treat, 2006).
Tissue conductivity becomes a critical factor in the efficiency of RF coils as the MRI operating frequency increases. Therefore, this technique can also be an important tool in developing improved radiofrequency coil designs and could aid in optimized B1 shimming for ultra-high field MRI (7T and higher).
Center for Imaging Research | Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226 | (414) 955-4663