Effective reduction of CSF partial volume effect in DTI by acquiring additional DWIs with smaller β-value

Diffusion: ADC & DTI Methods - Poster presentationOne of the major limitations of DTI is its vulnerability to CSF contamination. To remove such effect, FLAIR preparation and the two-compartment tensor model have been proposed. However, they require substantially increased scan time (and lead to reduced brain tissue SNR in the former case). A simple and effective approach is proposed in the current study. Diffusion tensor (DT) was computed from diffusion-weighted images acquired with b-value=500 and 1000s/mm2. Experiments were performed in volunteers and rodents to compare this approach and conventional DTI, demonstrating effective reduction of CSF contamination.published_or_final_versionThe 17th Scientific Meeting & Exhibition of the International Society of Magnetic Resonance in Medicine (ISMRM), Honolulu, HI., 18-24 April 2009. In Proceedings of ISMRM 17th Scientific Meeting & Exhibition, 2009, p. 357

Kurtosis analysis of neural diffusion organization

A computational framework is presented for relating the kurtosis tensor for water diffusion in brain to tissue models of brain microstructure. The tissue models are assumed to be comprised of non-exchanging compartments that may be associated with various microstructural spaces separated by cell membranes. Within each compartment the water diffusion is regarded as Gaussian, although the diffusion for the full system would typically be non-Gaussian. The model parameters are determined so as to minimize the Frobenius norm of the difference between the measured kurtosis tensor and the model kurtosis tensor. This framework, referred to as kurtosis analysis of neural diffusion organization (KANDO), may be used to help provide a biophysical interpretation to the information provided by the kurtosis tensor. In addition, KANDO combined with diffusional kurtosis imaging can furnish a practical approach for developing candidate biomarkers for neuropathologies that involve alterations in tissue microstructure. KANDO is illustrated for simple tissue models of white and gray matter using data obtained from healthy human subjects.postprin

Observations Suggesting a Possible Link Between Gammacarboxyglutamic Acid and Porcine Bioprosthetic Valve Calcification

Observations that link gammacarboxyglutamic acid (Gla) peptides with ectopic calcification are accumulating in the literature and may be summarized as follows: 1) Gla peptides selectively bind calcium and hydroxyapatite. 2) The presence of detectable levels of Gla in calcified tissue is concurrent with the onset of mineralization. 3) In an animal model, osteocalcin (a Gla-containing protein) accounts for more than 90% of all the Gla found in the resulting subcutaneously implanted calcified leaflet. 4) Vitamin D stimulates osteocalcin synthesis in cultures of osteosarcoma cells, and in vitamin D deficient rats subcutaneously implanted valve leaflets are not calcified. 5) Gla content and the degree of calcification in degenerated porcine bioprosthetic valves removed from humans are positively correlated. 6) Porcine bioprosthetic valves implanted in children are calcified more rapidly than those of adults, and the normal GIa levels in the urine of children are more than twice those of normal adults

Diffusional Kurtosis and Diffusion Tensor Imaging Reveal Different Time-Sensitive Stroke-Induced Microstructural Changes

postprin

Epilepsy-related cytoarchitectonic abnormalities along white matter pathways

Objective Temporal lobe epilepsy (TLE) is one of the most common forms of epilepsy. Unfortunately, the clinical outcomes of TLE cannot be determined based only on current diagnostic modalities. A better understanding of white matter (WM) connectivity changes in TLE may aid the identification of network abnormalities associated with TLE and the phenotypic characterisation of the disease. Methods We implemented a novel approach for characterising microstructural changes along WM pathways using diffusional kurtosis imaging (DKI). Along-the-tract measures were compared for 32 subjects with left TLE and 36 age-matched and gender-matched controls along the left and right fimbria-fornix (FF), parahippocampal WM bundle (PWMB), arcuate fasciculus (AF), inferior longitudinal fasciculus (ILF), uncinate fasciculus (UF) and cingulum bundle (CB). Limbic pathways were investigated in relation to seizure burden and control with antiepileptic drugs. Results By evaluating measures along each tract, it was possible to identify abnormalities localised to specific tract subregions. Compared with healthy controls, subjects with TLE demonstrated pathological changes in circumscribed regions of the FF, PWMB, UF, AF and ILF. Several of these abnormalities were detected only by kurtosis-based and not by diffusivity-based measures. Structural WM changes correlated with seizure burden in the bilateral PWMB and cingulum. Conclusions DKI improves the characterisation of network abnormalities associated with TLE by revealing connectivity abnormalities that are not disclosed by other modalities. Since TLE is a neuronal network disorder, DKI may be well suited to fully assess structural network abnormalities related to epilepsy and thus serve as a tool for phenotypic characterisation of epilepsy

A Better Characterization of Spinal Cord Damage in Multiple Sclerosis: A Diffusional Kurtosis Imaging Study

BACKGROUND AND PURPOSE: The spinal cord is a site of predilection for MS lesions. While diffusion tensor imaging is useful for the study of anisotropic systems such as WM tracts, it is of more limited utility in tissues with more isotropic microstructures (on the length scales studied with diffusion MR imaging) such as gray matter. In contrast, diffusional kurtosis imaging, which measures both Gaussian and non-Gaussian properties of water diffusion, provides more biomarkers of both anisotropic and isotropic structural changes. The aim of this study was to investigate the cervical spinal cord of patients with MS and to characterize lesional and normal-appearing gray matter and WM damage by using diffusional kurtosis imaging. MATERIALS AND METHODS: Nineteen patients (13 women, mean age = 41.1 ± 10.7 years) and 16 controls (7 women, mean age = 35.6 ± 11.2-years) underwent MR imaging of the cervical spinal cord on a 3T scanner (T2 TSE, T1 magnetization-prepared rapid acquisition of gradient echo, diffusional kurtosis imaging, T2 fast low-angle shot). Fractional anisotropy, mean diffusivity, and mean kurtosis were measured on the whole cord and in normal-appearing gray matter and WM. RESULTS: Spinal cord T2-hyperintense lesions were identified in 18 patients. Whole spinal cord fractional anisotropy and mean kurtosis ( P = .0009, P = .003), WM fractional anisotropy ( P = .01), and gray matter mean kurtosis ( P = .006) were significantly decreased, and whole spinal cord mean diffusivity ( P = .009) was increased in patients compared with controls. Mean spinal cord area was significantly lower in patients ( P = .04). CONCLUSIONS: Diffusional kurtosis imaging of the spinal cord can provide a more comprehensive characterization of lesions and normal-appearing WM and gray matter damage in patients with MS. Diffusional kurtosis imaging can provide additional and complementary information to DTI on spinal cord pathology

Tensor estimation for double-pulsed diffusional kurtosis imaging

Double-pulsed diffusional kurtosis imaging (DP-DKI) represents the double diffusion encoding (DDE) MRI signal in terms of six-dimensional (6D) diffusion and kurtosis tensors. Here a method for estimating these tensors from experimental data is described. A standard numerical algorithm for tensor estimation from conventional (i.e. single diffusion encoding) diffusional kurtosis imaging (DKI) data is generalized to DP-DKI. This algorithm is based on a weighted least squares (WLS) fit of the signal model to the data combined with constraints designed to minimize unphysical parameter estimates. The numerical algorithm then takes the form of a quadratic programming problem. The principal change required to adapt the conventional DKI fitting algorithm to DP-DKI is replacing the three-dimensional diffusion and kurtosis tensors with the 6D tensors needed for DP-DKI. In this way, the 6D diffusion and kurtosis tensors for DP-DKI can be conveniently estimated from DDE data by using constrained WLS, providing a practical means for condensing DDE measurements into well-defined mathematical constructs that may be useful for interpreting and applying DDE MRI. Data from healthy volunteers for brain are used to demonstrate the DP-DKI tensor estimation algorithm. In particular, representative parametric maps of selected tensor-derived rotational invariants are presented.postprin

Functional deficits induced by cortical microinfarcts

published_or_final_versio