Image reconstruction for magnetic resonance spectroscopic imaging (MRSI) requires specialized spatial and spectral data processing methods and benefits from the use of several sources of prior information that are not commonly available, including MRI-derived tissue segmentation, morphological analysis and spectral characteristics of the observed metabolites. In addition, incorporating information obtained from MRI data can enhance the display of low-resolution metabolite images and multiparametric and regional statistical analysis methods can improve detection of altered metabolite distributions. As a result, full MRSI processing and analysis can involve multiple processing steps and several different data types. In this paper, a processing environment is described that integrates and automates these data processing and analysis functions for imaging of proton metabolite distributions in the normal human brain. The capabilities include normalization of metabolite signal intensities and transformation into a common spatial reference frame, thereby allowing the formation of a database of MR-measured human metabolite values as a function of acquisition, spatial and subject parameters. This development is carried out under the MIDAS project (Metabolite Imaging and Data Analysis System), which provides an integrated set of MRI and MRSI processing functions. It is anticipated that further development and distribution of these capabilities will facilitate more widespread use of MRSI for diagnostic imaging, encourage the development of standardized MRSI acquisition, processing and analysis methods and enable improved mapping of metabolite distributions in the human brain.

Susceptibility weighted imaging (SWI) is a new MRI technique that can identify calcification by using phase images. We present a single case with a partially calcified oligodendroglioma, multiple calcified cysticercosis lesions, and multiple physiologic calcifications in the same patient. SWI phase images and computed tomography (CT) images are compared. SWI phase images showed the same calcified lesions as shown on CT and sometimes some new calcifications. Our conclusion is that SWI filtered phase images can identify calcifications as well as CT in this case.

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Purpose:To evaluate the efficacy of susceptibility weighted imaging (SWI) in comparison to standard T1 weighted postgadolinium contrast (T1-Gd) MRI in patients with SturgeWeber Syndrome (SWS). Materials and Methods:Twelve children (mean age, 5.6 years) with the diagnosis of SWS and unilateral hemispheric involvement were recruited prospectively and examined with high resolution three dimensional SWI and conventional T1-Gd. Both SWI and T1-Gd images were evaluated using a four-grade scoring system according to six types of imaging findings (enlargement of transmedullary veins, periventricular veins, and choroid plexus, as well as leptomeningeal abnormality, cortical gyriform abnormality, and gray matter/white matter junctional abnormality). The scores of SWI versus T1-Gd images were then compared for each type of abnormality.Results: SWI was superior to T1-Gd in identifying the enlarged transmedullary veins (P ϭ 0.0020), abnormal periventricular veins (P ϭ 0.0078), cortical gyriform abnormalities (P ϭ 0.0020), and gray matter/white matter junction abnormalities (P ϭ 0.0078). Conversely, T1-Gd was better than SWI in identifying enlarged choroid plexus (P ϭ 0.0050) and leptomeningeal abnormalities (P ϭ 0.0050). Conclusion:SWI can provide useful and unique information complementary to conventional contrast enhanced T1 weighted MRI for characterizing SWS. Therefore, SWI should be integrated into routine clinical MRI protocols for suspected SWS.

The high sensitivity but low specificity of breast MRI has prompted exploration of breast 1 H MRS for breast cancer detection. However, several obstacles still prevent the routine application of in vivo breast 1 H MRS, including poor spatial resolution, long acquisition time associated with conventional multi-voxel MRS imaging (MRSI) techniques, and the difficulty of "extra" lipid suppression in a magnetic field with relatively poor achievable homogeneity compared to the brain. Using a combination of a recently developed echo-filter (EF) suppression technique and an elliptical sampling scheme, we demonstrate the feasibility of overcoming these difficulties. It is robust (the suppression technique is insensitive to magnetic field inhomogeneity), fast (acquisition time of about 12 min) and offers high spatial resolution (up to 0.6 cm 3 per voxel at 1.5 T with a TE of only 60 ms). This approach should be even better at 3 T with higher resolution and/or shorter TE.

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The implementation of Magnetic Resonance Spectroscopic Imaging (MRSI) for diagnostic imaging benefits from close integration of the lower-spatial resolution MRSI information with information from high-resolution structural MRI. Since patients can commonly move between acquisitions, it is necessary to account for possible mis-registration between the datasets arising from differences in patient positioning. In this paper we evaluate the use of 4 common multi-modality registration criteria to recover alignment between high resolution structural MRI and 3D MRSI data of the brain with sub-voxel accuracy. We explore the use of alternative MRSI water reference images to provide different types of structural information for the alignment process. The alignment accuracy was evaluated using both synthetically created MRSI and MRI data and a set of carefully collected subject image data with known ground truth spatial transformation between image volumes. The final accuracy and precision of estimates were assessed using multiple random starts of the registration algorithm. Sub voxel accuracy was found by all four similarity criteria with normalized mutual information providing the lowest target registration error for the 7 subject images. This effort supports the ongoing development of a database of brain metabolite distributions in normal subjects, which will be used in the evaluation of metabolic changes in neurological diseases.

A new approach to tumor discrimination using magnetic resonance imaging is reported. The susceptibility difference between venous blood and the surrounding tissue is used to generate contrast. This approach is able to exquisitely reveal small veins even those which are smaller than a voxel. Using this method, it is possible to visualize the primary draining veins within tumors better than contrast enhanced magnetic resonance imaging methods that require a contrast agent or even conventional angiography. The ability to highlight deoxygenated blood may lead to the possibility of differentiating benign from malignant tumors noninvasively.