Diffusion-weighted MR spectroscopy of the prostate.

PURPOSE: Prostate tissue has a complex microstructure, mainly composed of epithelial and stromal cells, and of extracellular (acinar-luminal) spaces. Diffusion-weighted MR spectroscopy (DW-MRS) is ideally suited to explore complex microstructure in vivo with metabolites selectively distributed in different subspaces. To date, this technique has been applied to brain and muscle. This study presents the development and pioneering utilization of 1H-DW-MRS in the prostate, accompanied by in vitro studies to support interpretations of in vivo findings. METHODS: Nine healthy volunteers underwent a prostate MR examination (mean age, 56 years; range, 31-66). Metabolic complexation was studied in vitro using solutions with major compounds found in prostatic fluid of the lumen. DW-MRS was performed at 3 T with a non-water-suppressed single-voxel sequence with metabolite-cycling to concurrently measure metabolite and water signals. The water signal was used in postprocessing as a reference in a motion-compensation scheme. The spectra were fitted simultaneously in the spectral and diffusion-weighting dimensions. Apparent diffusion coefficients (ADCs) were derived by fitting signal decays that were assumed to be mono-exponential for metabolites and biexponential for water. RESULTS: DW-MRS of the prostate revealed relatively low ADCs for Cho and Cr compounds, aligning with their intracellular location and higher ADCs for citrate and spermine supporting their luminal origin. In vitro assessments of the ADCs of citrate and spermine demonstrated their complex formation and protein binding. Tissue concentrations of MRS-detectable metabolites were as expected for the voxel location. CONCLUSIONS: This work successfully demonstrates the feasibility of 1H-DW-MRS of the prostate and its potential for providing valuable microstructural information.

Replicability of proton MR spectroscopic imaging findings in mild traumatic brain injury: Implications for clinical applications.

PURPOSE: Proton magnetic resonance spectroscopy (1H MRS) offers biomarkers of metabolic damage after mild traumatic brain injury (mTBI), but a lack of replicability studies hampers clinical translation. In a conceptual replication study design, the results reported in four previous publications were used as the hypotheses (H1-H7), specifically: abnormalities in patients are diffuse (H1), confined to white matter (WM) (H2), comprise low N-acetyl-aspartate (NAA) levels and normal choline (Cho), creatine (Cr) and myo-inositol (mI) (H3), and correlate with clinical outcome (H4); additionally, a lack of findings in regional subcortical WM (H5) and deep gray matter (GM) structures (H6), except for higher mI in patients' putamen (H7). METHODS: 26 mTBI patients (20 female, age 36.5 ± 12.5 [mean ± standard deviation] years), within two months from injury and 21 age-, sex-, and education-matched healthy controls were scanned at 3 Tesla with 3D echo-planar spectroscopic imaging. To test H1-H3, global analysis using linear regression was used to obtain metabolite levels of GM and WM in each brain lobe. For H4, patients were stratified into non-recovered and recovered subgroups using the Glasgow Outcome Scale Extended. To test H5-H7, regional analysis using spectral averaging estimated metabolite levels in four GM and six WM structures segmented from T1-weighted MRI. The Mann-Whitney U test and weighted least squares analysis of covariance were used to examine mean group differences in metabolite levels between all patients and all controls (H1-H3, H5-H7), and between recovered and non-recovered patients and their respectively matched controls (H4). Replicability was defined as the support or failure to support the null hypotheses in accordance with the content of H1-H7, and was further evaluated using percent differences, coefficients of variation, and effect size (Cohen's d). RESULTS: Patients' occipital lobe WM Cho and Cr levels were 6.0% and 4.6% higher than controls', respectively (Cho, d = 0.37, p = 0.04; Cr, d = 0.63, p = 0.03). The same findings, i.e., higher patients' occipital lobe WM Cho and Cr (both p = 0.01), but with larger percent differences (Cho, 8.6%; Cr, 6.3%) and effect sizes (Cho, d = 0.52; Cr, d = 0.88) were found in the comparison of non-recovered patients to their matched controls. For the lobar WM Cho and Cr comparisons without statistical significance (frontal, parietal, temporal), unidirectional effect sizes were observed (Cho, d = 0.07 - 0.37; Cr, d = 0.27 - 0.63). No differences were found in any metabolite in any lobe in the comparison between recovered patients and their matched controls. In the regional analyses, no differences in metabolite levels were found in any GM or WM region, but all WM regions (posterior, frontal, corona radiata, and the genu, body, and splenium of the corpus callosum) exhibited unidirectional effect sizes for Cho and Cr (Cho, d = 0.03 - 0.34; Cr, d = 0.16 - 0.51). CONCLUSIONS: We replicated findings of diffuse WM injury, which correlated with clinical outcome (supporting H1-H2, H4). These findings, however, were among the glial markers Cho and Cr, not the neuronal marker NAA (not supporting H3). No differences were found in regional GM and WM metabolite levels (supporting H5-H6), nor in putaminal mI (not supporting H7). Unidirectional effect sizes of higher patients' Cho and Cr within all WM analyses suggest widespread injury, and are in line with the conclusion from the previous publications, i.e., that detection of WM injury may be more dependent upon sensitivity of the 1H MRS technique than on the selection of specific regions. The findings lend further support to the corollary that clinic-ready 1H MRS biomarkers for mTBI may best be achieved by using high signal-to-noise-ratio single-voxels placed anywhere within WM. The biochemical signature of the injury, however, may differ and therefore absolute levels, rather than ratios may be preferred. Future replication efforts should further test the generalizability of these findings.

Characterization of prostate cancer with MR spectroscopic imaging and diffusion-weighted imaging at 3 Tesla.

PURPOSE: To retrospectively measure metabolic ratios and apparent diffusion coefficient (ADC) values from 3-Tesla MR spectroscopic imaging (MRSI) and diffusion-weighted imaging (DWI) in benign and malignant peripheral zone (PZ) prostate tissue, assess the parameters' associations with malignancy, and develop and test rules for classifying benign and malignant PZ tissue using whole-mount step-section pathology as the reference standard. METHODS: This HIPAA-compliant, IRB-approved study included 67 men (median age, 61 years; range, 41-74 years) with biopsy-proven prostate cancer who underwent preoperative 3 T endorectal multiparametric MRI and had ≥1 PZ lesion >0.1 cm3 at whole-mount histopathology. In benign and malignant PZ regions identified from pathology, voxel-based choline/citrate, polyamines/choline, polyamines/creatine, and (choline + polyamines + creatine)/citrate ratios were averaged, as were ADC values. Patients were randomly split into training and test sets; rules for separating benign from malignant regions were generated with classification and regression tree (CART) analysis and assessed on the test set for sensitivity and specificity. Odds ratios (OR) were evaluated using generalized estimating equations. RESULTS: CART analysis of all parameters identified only ADC and (choline + polyamines + creatine)/citrate as significant predictors of cancer. Sensitivity and specificity, respectively, were 0.81 and 0.82 with MRSI-derived, 0.98 and 0.51 with DWI-derived, and 0.79 and 0.90 with MRSI + DWI-derived classification rules. Areas under the curves (AUC) in the test set were 0.93 (0.87-0.97) with ADC, 0.82 (0.72-0.91) with MRSI, and 0.96 (0.92-0.99) with MRSI + ADC. CONCLUSION: We developed statistically-based rules for identifying PZ cancer using 3-Tesla MRSI, DWI, and MRSI + DWI and demonstrated the potential value of MRSI + DWI.

Spectral decomposition for resolving partial volume effects in MRSI.

PURPOSE: Estimation of brain metabolite concentrations by MR spectroscopic imaging (MRSI) is complicated by partial volume contributions from different tissues. This study evaluates a method for increasing tissue specificity that incorporates prior knowledge of tissue distributions. METHODS: A spectral decomposition (sDec) technique was evaluated for separation of spectra from white matter (WM) and gray matter (GM), and for measurements in small brain regions using whole-brain MRSI. Simulation and in vivo studies compare results of metabolite quantifications obtained with the sDec technique to those obtained by spectral fitting of individual voxels using mean values and linear regression against tissue fractions and spectral fitting of regionally integrated spectra. RESULTS: Simulation studies showed that, for GM and the putamen, the sDec method offers < 2% and 3.5% error, respectively, in metabolite estimates. These errors are considerably reduced in comparison to methods that do not account for partial volume effects or use regressions against tissue fractions. In an analysis of data from 197 studies, significant differences in mean metabolite values and changes with age were found. Spectral decomposition resulted in significantly better linewidth, signal-to-noise ratio, and spectral fitting quality as compared to individual spectral analysis. Moreover, significant partial volume effects were seen on correlations of neurometabolite estimates with age. CONCLUSION: The sDec analysis approach is of considerable value in studies of pathologies that may preferentially affect WM or GM, as well as smaller brain regions significantly affected by partial volume effects. Magn Reson Med 79:2886-2895, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Stratification of the aggressiveness of prostate cancer using pre-biopsy multiparametric MRI (mpMRI).

Risk stratification, based on the Gleason score (GS) of a prostate biopsy, is an important decision-making tool in prostate cancer management. As low-grade disease may not need active intervention, the ability to identify aggressive cancers on imaging could limit the need for prostate biopsies. We assessed the ability of multiparametric MRI (mpMRI) in pre-biopsy risk stratification of men with prostate cancer. One hundred and twenty men suspected to have prostate cancer underwent mpMRI (diffusion MRI and MR spectroscopic imaging) prior to biopsy. Twenty-six had cancer and were stratified into three groups based on GS: low grade (GS ≤ 6), intermediate grade (GS = 7) and high grade (GS ≥ 8). A total of 910 regions of interest (ROIs) from the peripheral zone (PZ, range 25-45) were analyzed from these 26 patients. The metabolite ratio [citrate/(choline + creatine)] and apparent diffusion coefficient (ADC) of voxels were calculated for the PZ regions corresponding to the biopsy cores and compared with histology. The median metabolite ratios for low-grade, intermediate-grade and high-grade cancer were 0.29 (range: 0.16, 0.61), 0.17 (range: 0.13, 0.32) and 0.13 (range: 0.05, 0.23), respectively (p = 0.004). The corresponding mean ADCs (×10(-3) mm(2) /s) for low-grade, intermediate-grade and high-grade cancer were 0.99 ± 0.08, 0.86 ± 0.11 and 0.69 ± 0.12, respectively (p < 0.0001). The combined ADC and metabolite ratio model showed strong discriminatory ability to differentiate subjects with GS ≤ 6 from subjects with GS ≥ 7 with an area under the curve of 94%. These data indicate that pre-biopsy mpMRI may stratify PCa aggressiveness noninvasively. As the recent literature data suggest that men with GS ≤ 6 cancer may not need radical therapy, our data may help limit the need for biopsy and allow informed decision making for clinical intervention. Copyright © 2015 John Wiley & Sons, Ltd.