Magnetic Resonance Spectroscopic Imaging Voxel Research Articles

Tensor-Based Method for Residual Water Suppression in 1H Magnetic Resonance Spectroscopic Imaging.

Magnetic resonance spectroscopic imaging (MRSI) signals are often corrupted by residual water and artifacts. Residual water suppression plays an important role in accurate and efficient quantification of metabolites from MRSI. A tensor-based method for suppressing residual water is proposed. A third-order tensor is constructed by stacking the Löwner matrices corresponding to each MRSI voxel spectrum along the third mode. A canonical polyadic decomposition is applied on the tensor to extract the water component and to, subsequently, remove it from the original MRSI signals. The proposed method applied on both simulated and in-vivo MRSI signals showed good water suppression performance. The tensor-based Löwner method has better performance in suppressing residual water in MRSI signals as compared to the widely used subspace-based Hankel singular value decomposition method. A tensor method suppresses residual water simultaneously from all the voxels in the MRSI grid and helps in preventing the failure of the water suppression in single voxels.

Contribution of Histopathologic Tissue Composition to Quantitative MR Spectroscopy and Diffusion-weighted Imaging of the Prostate.

To determine associations of metabolite levels derived from magnetic resonance (MR) spectroscopic imaging (ie, hydrogen 1 [(1)H] MR spectroscopic imaging) and apparent diffusion coefficients (ADCs) from diffusion-weighted imaging with prostate tissue composition assessed by digital image analysis of histologic sections. Institutional ethical review board approved this retrospective study and waived informed consent. Fifty-seven prostate cancer patients underwent an MR examination followed by prostatectomy. One hematoxylin and eosin-stained section of the resected prostate per patient was digitized and computationally segmented into nuclei, lumen, and combination of epithelial cytoplasm and stroma. On each stained section, regions of interest (ROIs) were chosen and matched to the corresponding ADC map and (1)H MR spectroscopic imaging voxels. ADC and two metabolite ratios (citrate [Cit], spermine [Spm], and creatine [Cr] to choline [Cho] and Cho to Cr plus Spm) were correlated with percentage areas of nuclei, lumen, and cytoplasm and stroma for peripheral zone (PZ), transition zone (TZ), and tumor tissue in both zones of the prostate by using a linear mixed-effect model and Spearman correlation coefficient (ρ). ADC and (Cit + Spm + Cr)/Cho ratio showed positive correlation with percentage area of lumen (ρ = 0.43 and 0.50, respectively) and negative correlation with percentage area of nuclei (ρ = -0.29 and -0.26, respectively). The Cho/(Cr + Spm) ratio showed negative association with percentage area of lumen (ρ = -0.40) and positive association with area of nuclei (ρ = 0.26). Percentage areas of lumen and nuclei, (Cit + Spm + Cr)/Cho ratio, and ADC were significantly different (P < .001) between benign PZ (23.7 and 7.7, 8.83, and 1.58 × 10(-3) mm(2)/sec, respectively) and tumor PZ tissue (11.4 and 12.5, 5.13, and 1.20 × 10(-3) mm(2)/sec, respectively). These parameters were also significantly different between benign TZ (20.0 and 8.2, 6.50, and 1.26 × 10(-3) mm(2)/sec, respectively) and tumor TZ tissue (9.8 and 11.2, 4.36, and 1.03 × 10(-3) mm(2)/sec, respectively). The observed correlation of (Cit + Spm + Cr)/Cho ratio and ADC of the prostate with its tissue composition indicates that components of this composition, such as percentage luminal area, contribute to the value of these MR parameters.

NI-46 * THE IMPACT OF INTEGRATING VOLUMETRIC MR SPECTROSCOPIC IMAGING IN RADIATION TREATMENT PLANNING FOR GLIOBLASTOMA

BACKGROUND: Magnetic resonance spectroscopic imaging (MRSI) has emerged as a molecular imaging modality which may better define active tumor compared to conventional anatomic magnetic resonance imaging (MRI). To date, using MRSI for radiation treatment (RT) planning has been challenging due to processing and resolution limitations. Here, we evaluate the feasibility of integrating 3-dimensional (3D) high-resolution full-brain MRSI into the RT planning process for glioblastoma, and determine the degree to which MRSI can modify RT targets and predict progression. METHODS: Six patients with newly-diagnosed glioblastoma participated in our institutional study in which a pre-RT MRSI was obtained. 3D MRSI was acquired using a volumetric spin-echo EPSI sequence and parallel imaging (GRAPPA), with a 32-channel head coil on a 3T (Siemens TRIO/TIM) system, and processed to give full-brain metabolite maps with 0.108 cm3 resolution. Each MRSI voxel map, representing relative choline (Cho) to N-acetylaspartate (NAA) ratios, was registered to a corresponding T1-weighted post-contrast MRI (T1c). An MRSI-defined 60 Gray planning target volume (mrsiPTV60) was created independently by two radiation oncologists based on spatial quantitative assessment of elevated Cho/NAA ratios, and analytically compared to the RT target defined by conventional T1c abnormalities (convPTV60). RESULTS: Using MRSI to aid target definition increased the convPTV60 by a median of 78% (range: 22%-1149%). The median dice similarity coefficient between conPTV60 and mrsiPTV60 was 0.72 (range: 0.15-0.91), indicating decreased spatial overlap. Expanded targets in two of six cases encompassed regions of tumor recurrence, which were not originally covered by the convPTV60. CONCLUSIONS: Integration of 3D high-resolution full-brain MRSI into RT planning is feasible, resulted in considerably modified RT target volumes, and predicted post-RT recurrences. Thus, MRSI may serve as an additional treatment planning tool for improving RT target definition for the benefit of glioblastoma patients.

Phosphorus Magnetic Resonance Spectroscopic Imaging at 7 T in Patients With Prostate Cancer

The aim of this study was to identify characteristics of phosphorus (P) spectra of the human prostate and to investigate changes of individual phospholipid metabolites in prostate cancer through in vivo P magnetic resonance spectroscopic imaging (MRSI) at 7 T. In this institutional review board-approved study, 15 patients with biopsy-proven prostate cancer underwent T2-weighted magnetic resonance imaging and 3-dimensional P MRSI at 7 T. Voxels were selected at the tumor location, in normal-appearing peripheral zone tissue, normal-appearing transition zone tissue, and in the base of the prostate close to the seminal vesicles. Phosphorus metabolite ratios were determined and compared between tissue types. Signals of phosphoethanolamine (PE) and phosphocholine (PC) were present and well resolved in most P spectra in the prostate. Glycerophosphocholine signals were observable in 43% of the voxels in malignant tissue, but in only 10% of the voxels in normal-appearing tissue away from the seminal vesicles. In many spectra, independent of tissue type, 2 peaks resonated in the chemical shift range of inorganic phosphate, possibly representing 2 separate pH compartments. The PC/PE ratio in the seminal vesicles was highly elevated compared with the prostate in 5 patients. A considerable overlap of P metabolite ratios was found between prostate cancer and normal-appearing prostate tissue, preventing direct discrimination of these tissues. The only 2 patients with high Gleason scores tumors (≥4+5) presented with high PC and glycerophosphocholine levels in their cancer lesions. Phosphorus MRSI at 7 T shows distinct features of phospholipid metabolites in the prostate gland and its surrounding structures. In this exploratory study, no differences in P metabolite ratios were observed between prostate cancer and normal-appearing prostate tissue possibly because of the partial volume effects of small tumor foci in large MRSI voxels.

Discriminating Cancer From Noncancer Tissue in the Prostate by 3-Dimensional Proton Magnetic Resonance Spectroscopic Imaging

A prospective multicenter validation of the ability of 1H magnetic resonance spectroscopic imaging (MRSI) to distinguish cancer from noncancer tissues throughout the prostate with histopathology of the resected organ as the standard of reference. Institutional review board approval was obtained for all centers and all participating patients and volunteers provided written informed consent. Ninety-nine patients and 10 age-matched volunteers from 8 participating centers underwent magnetic resonance imaging and 3-dimensional MRSI with an endorectal coil at 1.5 T. Selected MRSI voxels were assigned to the peripheral zone (PZ), the central gland (CG), the periurethral area, and cancer tissue. Signal ratios of choline + creatine to citrate (CC/C) in spectra of these voxels were automatically calculated. Receiver operating characteristic curves were constructed to assess the accuracy by which this ratio can discriminate cancer from noncancer tissue. A total of 70% of voxels in noncancer tissue and 90% of voxels in cancer tissue passed the quality check of the automatically fitted spectra. The median CC/C was significantly different between any noncancer and cancer tissue (P < 0.0001), but not between the different contributing centers. CC/C increased with cancer focus size (P =0.0008) and certainty of voxel mapping to histopathologic cancer site (P 0.0001). The area under the receiver operating characteristic curve for discriminating voxels of cancer tissue from noncancer tissue was 0.88 (confidence interval: 0.84-0.92) in the PZ and 0.76 (confidence interval: 0.71- 0.81) in the CG.

An Exploratory Study of Endorectal Magnetic Resonance Imaging and Spectroscopy of the Prostate as Preoperative Predictive Biomarkers of Biochemical Relapse After Radical Prostatectomy

Radical prostatectomy has significant side effects. Preoperative information predicting its long-term outcome would be valuable to patients and physicians. We determined whether pretreatment endorectal magnetic resonance imaging/magnetic resonance spectroscopic imaging predicts biochemical recurrence after radical prostatectomy. Of 202 patients who underwent endorectal magnetic resonance imaging/magnetic resonance spectroscopic imaging from January 2000 to December 2002 before radical prostatectomy 130 satisfied study inclusion criteria and were included in analysis. We compared imaging factors with potential predictive capability to biochemical recurrence data, including magnetic resonance imaging risk score based on local disease extent and magnetic resonance spectroscopic imaging index lesion characteristics, such as the number of voxels and degree of metabolic abnormality (magnetic resonance spectroscopic imaging grade). We evaluated associations of these imaging variables with time to biochemical recurrence by Cox proportional hazards regression adjusted for known predictors of biochemical recurrence, such as stage, grade and prostate specific antigen. At a median 68-month followup there were 26 biochemical failures. Risk score, lesion volume and high grade voxels each correlated with time to biochemical recurrence. In a model combining clinical parameters risk score, lesion volume and at least 1 high grade voxel the magnetic resonance spectroscopic imaging variables remained significant but the magnetic resonance imaging score dropped out. Index lesion volume on magnetic resonance spectroscopic imaging and high grade magnetic resonance spectroscopic imaging voxels correlate with time to biochemical recurrence after radical prostatectomy even when adjusted for clinical data. Results suggest the preoperative predictive usefulness of endorectal magnetic resonance imaging/magnetic resonance spectroscopic imaging in patients considering radical prostatectomy.

Quantitative magnetic resonance spectroscopic imaging in Parkinson’s disease, progressive supranuclear palsy and multiple system atrophy

Magnetic resonance spectroscopy (MRS) allows the measurement of a number of brain tissue metabolites in vivo, including N-acetylaspartate (NAA), a putative marker of neuronal integrity. Unlike single voxel MRS, magnetic resonance spectroscopic imaging (MRSI) enables quantification of these metabolites simultaneously from multiple anatomically localized voxels. Both single voxel MRS and MRSI allow the absolute quantification of these metabolites and, when combined with tissue segmentation, can give accurate metabolite concentrations even in the presence of partial volume effects from nearby cerebrospinal fluid. Using MRSI with cubic voxels with a nominal volume of 1.0 cm(3), we tested the hypothesis that concentrations of NAA in the basal ganglia in multiple system atrophy (MSA) and progressive supranuclear palsy (PSP) would show differences compared to Parkinson's disease (IPD). NAA values (in mM) from MRSI voxels centred to the putamen, pallidum and thalamus were obtained from 11 patients with IPD, 11 with MSA-P, six with MSA-C, 13 with PSP and 18 controls. The mean concentrations of NAA and its bulk grey and white matter values were also estimated over the whole brain slab. N-acetylaspartate concentrations in the pallidum, putamen and lentiform nucleus were significantly lower in patients with MSA-P and PSP compared to IPD and controls. The putaminal values were also significantly reduced in PSP compared to MSA-P. There were no significant differences between groups in the thalamus and over the whole brain slab. Our findings support the notion that MRSI can potentially quantify basal ganglia cellular pathology in MSA and PSP.

Application of volumetric MR spectroscopic imaging for localization of neocortical epilepsy

The aim of this study was to evaluate volumetric proton magnetic resonance spectroscopic imaging (MRSI) for localization of epileptogenic foci in neocortical epilepsy. Twenty-five subjects reporting seizures considered to be of neocortical origin were recruited to take part in a 3-T MR study that included high-resolution structural MRI and a whole-brain MRSI acquisition. Using a fully automated MRSI processing protocol, maps for signal intensity normalized N-acetylaspartate (NAA), creatine, and choline were created, together with the relative volume fraction of grey-matter, white-matter, and CSF within each MRSI voxel. Analyses were performed using visual observation of the metabolite and metabolite ratio maps; voxel-based calculation of differences in these metabolite maps relative to normal controls; comparison of average grey-matter and white-matter metabolite values over each lobar volume; and examination of relative left-right asymmetry factors by brain region. Data from 14 subjects were suitable for inclusion in the analysis. Eight subjects had MRI-visible pathologies that were associated with decreases in NAA/creatine, which extended beyond the volume indicated by the MRI. Five subjects demonstrated no significant metabolic alterations using any of the analysis methods, and one subject had no findings on MRI or MRSI. This proof of principle study supports previous evidence that alterations of MR-detected brain metabolites can be detected in tissue areas affected by neocortical seizure activity, while additionally demonstrating advantages of the volumetric MRSI approach.

MO‐EE‐A4‐02: Metabolic Changes in Malignant Brain Tumors During Mid‐Course Radiation Therapy: Initial Findings of 3Tesla Volumetric Magnetic Resonance Spectroscopic Imaging

Purpose: Metabolic activity of tumors obtained non‐invasively by magnetic resonance spectroscopic imaging (MRSI) during mid‐course of radiation therapy (RT) can be useful in the evaluating tumor response as well as to design effective boost RT plans. The purpose of this work is to assess the changes in metabolic status of malignant brain tumors using 3Tesla volumetric proton MRSI at three weeks of radiation therapy. Method and Materials: The MRSI data from 11 patients with malignant brain tumors acquired during pre‐ and at 3rd week of RT were analyzed retrospectively. The 3D MRSI was performed on a Siemens 3T TRIO TIM scanner using PRESS (point resolved spectroscopy) sequence with TE/TR: 135/1510 ms, 16×16×8 matrix, FOV: 16×16×8 resulting in MRSI voxel size of 10×10×10 mm3. Linear combination (LC) model was used to analyze the acquired spectra. Tumor activity was determined from the values of metabolites ratio “Choline to N‐Acetyl‐Aspartate” (Cho/NAA). MRSI voxels segmented from metabolically active tumor regions were compared for further analysis. Results: The mean Cho/NAA values at 3rd week of RT compared to their pre‐RT values were found to decrease 26% to 79% in 7 out of 11 patients and increase73% in one case. Three patients had minimal changes (−6% to +17%). Voxels with higher tumor activity (i.e., larger Cho/NAA value) at pre‐RT were observed to show large decrease at 3 weeks of RT. The spatial patterns of metabolic abnormality considerably altered during 3 weeks of RT compared to that of pre‐RT. Conclusion: MRSI derived metabolic status of malignant brain tumors in patients undergoing RT obtained during mid‐course of treatment provides valuable functional tumor information that is not available from other conventional anatomical imaging methods and it could help to devise patient‐specific effective treatment interventions.

Image‐fusion of MR spectroscopic images for treatment planning of gliomas

1H magnetic resonance spectroscopic imaging (MRSI) can improve the accuracy of target delineation for gliomas, but it lacks the anatomic resolution needed for image fusion. This paper presents a simple protocol for fusing simulation computer tomography (CT) and MRSI images for glioma intensity-modulated radiotherapy (IMRT), including a retrospective study of 12 patients. Each patient first underwent whole-brain axial fluid-attenuated-inversion-recovery (FLAIR) MRI (3 mm slice thickness, no spacing), followed by three-dimensional (3D) MRSI measurements (TE/TR: 144/1000 ms) of a user-specified volume encompassing the extent of the tumor. The nominal voxel size of MRSI ranged from 8 x 8 x 10 mm3 to 12 x 12 x 10 mm3. A system was developed to grade the tumor using the choline-to-creatine (Cho/Cr) ratios from each MRSI voxel. The merged MRSI images were then generated by replacing the Cho/Cr value of each MRSI voxel with intensities according to the Cho/Cr grades, and resampling the poorer-resolution Cho/Cr map into the higher-resolution FLAIR image space. The FUNCTOOL processing software was also used to create the screen-dumped MRSI images in which these data were overlaid with each FLAIR MRI image. The screen-dumped MRSI images were manually translated and fused with the FLAIR MRI images. Since the merged MRSI images were intrinsically fused with the FLAIR MRI images, they were also registered with the screen-dumped MRSI images. The position of the MRSI volume on the merged MRSI images was compared with that of the screen-dumped MRSI images and was shifted until agreement was within a predetermined tolerance. Three clinical target volumes (CTVs) were then contoured on the FLAIR MRI images corresponding to the Cho/Cr grades. Finally, the FLAIR MRI images were fused with the simulation CT images using a mutual-information algorithm, yielding an IMRT plan that simultaneously delivers three different dose levels to the three CTVs. The image-fusion protocol was tested on 12 (six high-grade and six low-grade) glioma patients. The average agreement of the MRSI volume position on the screen-dumped MRSI images and the merged MRSI images was 0.29 mm with a standard deviation of 0.07 mm. Of all the voxels with Cho/Cr grade one or above, the distribution of Cho/Cr grade was found to correlate with the glioma grade from pathologic finding and is consistent with literature results indicating Cho/Cr elevation as a marker for malignancy. In conclusion, an image-fusion protocol was developed that successfully incorporates MRSI information into the IMRT treatment plan for glioma.

Fast method for brain image segmentation: Application to proton magnetic resonance spectroscopic imaging

The interpretation of brain metabolite concentrations measured by quantitative proton magnetic resonance spectroscopic imaging (MRSI) is assisted by knowledge of the percentage of gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) within each MRSI voxel. Usually, this information is determined from T(1)-weighted magnetic resonance images (MRI) that have a much higher spatial resolution than the MRSI data. While this approach works well, it is time-consuming. In this article, a rapid data acquisition and analysis procedure for image segmentation is described, which is based on collection of several, thick slice, fast spin echo images (FSE) of different contrast. Tissue segmentation is performed with linear "Eigenimage" filtering and normalization. The method was compared to standard segmentation techniques using high-resolution 3D T(1)-weighted MRI in five subjects. Excellent correlation between the two techniques was obtained, with voxel-wise regression analysis giving GM: R2 = 0.893 +/- 0.098, WM: R2 = 0.892 +/- 0.089, ln(CSF): R2 = 0.831 +/- 0.082). Test-retest analysis in one individual yielded an excellent agreement of measurements with R2 higher than 0.926 in all three tissue classes. Application of FSE/EI segmentation to a sample proton MRSI dataset yielded results similar to prior publications. It is concluded that FSE imaging in conjunction with Eigenimage analysis is a rapid and reliable way of segmenting brain tissue for application to proton MRSI.

Novel methodology for the archiving and interactive reading of clinical magnetic resonance spectroscopic imaging.

Archiving clinical magnetic resonance spectroscopic imaging (MRSI) data and presenting the data to specialists (e.g., neuroradiologists, neurosurgeons, neurologists, neuro-oncologists, and MR scientists) who work in different physical locations is a practical problem of significance. This communication describes a novel solution. The study hypothesis was that it is possible to use widely available distributed computing techniques to create a clinical MRSI user interface addressable from any personal computer with a suitable network connection. A worldwide web MRSI archive and interface system was created that permits the user to interactively view individual MRSI voxel spectra with correlation to MR images and to parametric spectroscopic images. Web browser software (i.e., Netscape and Internet Explorer) permits users in various physical locations to access centrally archived MRSI data using a variety of operating systems and client workstations. The system was used for archiving and displaying more than 1000 clinical MRSI studies performed at the authors' institution. The system also permits MRSI data to be viewed via the Internet from distant locations worldwide. The study illustrates that widely available software operating within highly distributed electronic networks can be used for archiving and interactive reading of large amounts of clinical MRSI data.

Alzheimer disease and subcortical ischemic vascular dementia: evaluation by combining MR imaging segmentation and H-1 MR spectroscopic imaging.

To determine the association between H-1 magnetic resonance (MR) spectroscopic imaging and MR imaging differences in subjects with Alzheimer disease (AD) or subcortical ischemic vascular dementia (SIVD) versus control subjects and if both studies combined enable discrimination of AD from control subjects better than either study alone. Measures were obtained in nine AD, eight SIVD, and 11 control subjects with MR imaging segmentation software. Statistically significantly lower N-acetylaspartate/choline-containing metabolites (Cho) and higher Cho/creatine-containing metabolites in posterior mesial gray matter in AD versus control subjects were independent of MR imagining differences. Combined measures allowed correct classification of AD and control subjects, but none of the MR measures allowed accurate discrimination between AD and SIVD subjects. Between-group differences in tissue-type contributions to H-1 MR spectroscopic imaging voxels must be accounted for when reporting H-1 MR spectroscopic imaging data in AD, SIVD, and control subjects. Combined studies allowed more accurate discrimination between AD and control subjects than either study alone.

2964. Showing up the mercury cycle: Edwards, T. & McBride, B.C. (1975). Biosynthesis and degradation of methylmercury in human faeces. Nature, Lond.253, 462

The aim of this study was to evaluate volumetric proton magnetic resonance spectroscopic imaging (MRSI) for localization of epileptogenic foci in neocortical epilepsy.Twenty-five subjects reporting seizures considered to be of neocortical origin were recruited to take part in a 3-T MR study that included high-resolution structural MRI and a whole-brain MRSI acquisition. Using a fully automated MRSI processing protocol, maps for signal intensity normalized N-acetylaspartate (NAA), creatine, and choline were created, together with the relative volume fraction of grey-matter, white-matter, and CSF within each MRSI voxel. Analyses were performed using visual observation of the metabolite and metabolite ratio maps; voxel-based calculation of differences in these metabolite maps relative to normal controls; comparison of average grey-matter and white-matter metabolite values over each lobar volume; and examination of relative left–right asymmetry factors by brain region.Data from 14 subjects were suitable for inclusion in the analysis. Eight subjects had MRI-visible pathologies that were associated with decreases in NAA/creatine, which extended beyond the volume indicated by the MRI. Five subjects demonstrated no significant metabolic alterations using any of the analysis methods, and one subject had no findings on MRI or MRSI.This proof of principle study supports previous evidence that alterations of MR-detected brain metabolites can be detected in tissue areas affected by neocortical seizure activity, while additionally demonstrating advantages of the volumetric MRSI approach.