Noninvasive evaluation of cerebral glioma grade by using multivoxel 3D proton MR spectroscopy

Objective

To determine whether metabolite ratios in multivoxel 3D proton MR spectroscopy (¹H MRS) is different between low-grade and high-grade gliomas and may be useful for glioma grading.

Materials and Methods

Thirty-nine patients (23 male and 16 female; 22-75 years old; mean age, 44.92±12.65 years) suspected of having gliomas underwent 3D ¹H MRS examinations. Metabolite ratios [choline (Cho)/creatine (Cr), N-acetylaspartate (NAA)/Cr and Cho/NAA] were measured. Tumor grade was determined by using the histopathologic grading. Receiver operating characteristic analysis of metabolite ratios was performed, and optimum thresholds for tumor grading were determined. The resulting sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for identifying high-grade gliomas were calculated.

Results

Diagnostic-quality 3D ¹H MRS with readily quantifiable Cho, Cr and NAA peaks was obtained in 94.87% of the cases. The Cho/Cr and Cho/NAA ratios were significantly higher in high-grade than in low-grade glioma (P<.001), whereas the NAA/Cr ratios were significantly lower in high-grade than in low-grade glioma (P<.001). Receiver operating characteristic analysis demonstrated a threshold value of 2.04 for Cho/Cr ratio to provide sensitivity, specificity, PPV and NPV of 84.00%, 83.33%, 91.30% and 71.43%, respectively. Threshold value of 2.20 for Cho/NAA ratio resulted in sensitivity, specificity, PPV and NPV of 88.00%, 66.67%, 84.62% and 72.73%, respectively. Overall diagnostic accuracy was not statistically significantly different between Cho/Cr and Cho/NAA ratios (χ²=0.093, P=.76).

Conclusion

Metabolite ratios of low-grade gliomas were significantly different from high-grade gliomas. Cho/Cr and Cho/NAA ratios could have the superior diagnostic performance in predicting the glioma grade.     

Fast quantification of proton magnetic resonance spectroscopic imaging with artificial neural networks

Accurate quantification of the MRSI-observed regional distribution of metabolites involves relatively long processing times. This is particularly true in dealing with large amount of data that is typically acquired in multi-center clinical studies. To significantly shorten the processing time, an artificial neural network (ANN)-based approach was explored for quantifying the phase corrected (as opposed to magnitude) spectra. Specifically, in these studies radial basis function neural network (RBFNN) was used. This method was tested on simulated and normal human brain data acquired at 3T. The N-acetyl aspartate (NAA)/creatine (Cr), choline (Cho)/Cr, glutamate+glutamine (Glx)/Cr, and myo-inositol (mI)/Cr ratios in normal subjects were compared with the line fitting (LF) technique and jMRUI-AMARES analysis, and published values. The average NAA/Cr, Cho/Cr, Glx/Cr and mI/Cr ratios in normal controls were found to be 1.58+/-0.13, 0.9+/-0.08, 0.7+/-0.17 and 0.42+/-0.07, respectively. The corresponding ratios using the LF and jMRUI-AMARES methods were 1.6+/-0.11, 0.95+/-0.08, 0.78+/-0.18, 0.49+/-0.1 and 1.61+/-0.15, 0.78+/-0.07, 0.61+/-0.18, 0.42+/-0.13, respectively. These results agree with those published in literature. Bland-Altman analysis indicated an excellent agreement and minimal bias between the results obtained with RBFNN and other methods. The computational time for the current method was 15s compared to approximately 10 min for the LF-based analysis.     

Quantification of human brain metabolites from in vivo 1H NMR magnitude spectra using automated artificial neural network analysis

Long echo time (TE=270 ms) in vivo proton NMR spectra resembling human brain metabolite patterns were simulated for lineshape fitting (LF) and quantitative artificial neural network (ANN) analyses. A set of experimental in vivo 1H NMR spectra were first analyzed by the LF method to match the signal-to-noise ratios and linewidths of simulated spectra to those in the experimental data. The performance of constructed ANNs was compared for the peak area determinations of choline-containing compounds (Cho), total creatine (Cr), and N-acetyl aspartate (NAA) signals using both manually phase-corrected and magnitude spectra as inputs. The peak area data from ANN and LF analyses for simulated spectra yielded high correlation coefficients demonstrating that the peak areas quantified with ANN gave similar results as LF analysis. Thus, a fully automated ANN method based on magnitude spectra has demonstrated potential for quantification of in vivo metabolites from long echo time spectroscopic imaging.     

Short echo time multislice proton magnetic resonance spectroscopic imaging in human brain: metabolite distributions and reliability.

Multislice proton magnetic resonance spectroscopic imaging (1H MRSI) at 25 ms echo time was used to measure concentrations of myo-inositol (mI), N-acetylaspartate (NAA), and creatine (Cr) and choline (Cho) in ten normal subjects between 22 and 84 years of age (mean age 44 +/- 18 years). By co-analysis with MRI based tissue segmentation results, metabolite distributions were analyzed for each tissue type and for different brain regions. Measurement reliability was evaluated using intraclass correlation coefficients (ICC). Significant differences in metabolite distributions were found for all metabolites. mI of frontal gray matter was 84% of parietal gray matter and 87% of white matter. NAA of frontal gray matter was 86% of parietal gray matter and 85% of white matter. Cho of frontal gray matter was 125% of parietal gray matter and 59% of white matter and Cho of parietal gray matter was 47% of white matter. Cr of parietal gray matter was 113% of white matter. Reliability was relatively high (ICC from.70 to.93) for all metabolites in white matter and for NAA and Cr in gray matter, though limited (ICC less than.63) for mI and Cho in gray matter. These findings indicate that voxel gray/white matter contributions, regional variations in metabolite concentrations, and reliability limitations must be considered when interpreting 1H MR spectra of the brain.     

Differentiation between intra-axial metastatic tumor progression and radiation injury following fractionated radiation therapy or stereotactic radiosurgery using MR spectroscopy, perfusion MR imaging or volume progression modeling

Objective

To determine the accuracy of magnetic resonance spectroscopy (MRS), perfusion MR imaging (MRP), or volume modeling in distinguishing tumor progression from radiation injury following radiotherapy for brain metastasis.

Methods

Twenty-six patients with 33 intra-axial metastatic lesions who underwent MRS (n=41) with or without MRP (n=32) after cranial irradiation were retrospectively studied. The final diagnosis was based on histopathology (n=4) or magnetic resonance imaging (MRI) follow-up with clinical correlation (n=29). Cho/Cr (choline/creatinine), Cho/NAA (choline/N-acetylaspartate), Cho/nCho (choline/contralateral normal brain choline) ratios were retrospectively calculated for the multi-voxel MRS. Relative cerebral blood volume (rCBV), relative peak height (rPH) and percentage of signal-intensity recovery (PSR) were also retrospectively derived for the MRPs. Tumor volumes were determined using manual segmentation method and analyzed using different volume progression modeling. Different ratios or models were tested and plotted on the receiver operating characteristic curve (ROC), with their performances quantified as area under the ROC curve (AUC). MRI follow-up time was calculated from the date of initial radiotherapy until the last MRI or the last MRI before surgical diagnosis.

Results

Median MRI follow-up was 16 months (range: 2-33). Thirty percent of lesions (n=10) were determined to be radiation injury; 70% (n=23) were determined to be tumor progression. For the MRS, Cho/nCho had the best performance (AUC of 0.612), and Cho/nCho >1.2 had 33% sensitivity and 100% specificity in predicting tumor progression. For the MRP, rCBV had the best performance (AUC of 0.802), and rCBV >2 had 56% sensitivity and 100% specificity. The best volume model was percent increase (AUC of 0.891); 65% tumor volume increase had 100% sensitivity and 80% specificity.

Conclusion

Cho/nCho of MRS, rCBV of MRP, and percent increase of MRI volume modeling provide the best discrimination of intra-axial metastatic tumor progression from radiation injury for their respective modalities. Cho/nCho and rCBV appear to have high specificities but low sensitivities. In contrast, percent volume increase of 65% can be a highly sensitive and moderately specific predictor for tumor progression after radiotherapy. Future incorporation of 65% volume increase as a pretest selection criterion may compensate for the low sensitivities of MRS and MRP.     

A chemical shift imaging study on regional metabolite distribution in a CADASIL family

A chemical shift imaging (CSI) study was performed to directly assess relative concentrations of N-acetylaspartate (NAA), Cho and Cr metabolites in normal- and abnormal-appearing brain tissue of asymptomatic and symptomatic members of a single family with a neuropathologic, genetic and electrophysiological confirmed diagnosis of cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy. The aim of the investigation was to evaluate clinical findings and metabolite abnormalities as early appearance of axonal injury in this syndrome. The main findings related statistically significant decreases in the mean metabolite ratios for NAA/Cr, NAA/Cho and Cho/Cr in the anterior parts in comparison with the posterior parts of the centrum semiovale in symptomatic and asymptomatic patients. The effect was considerably greater in the symptomatic patients, indicating a strong correlation between CSI and pathology results. No differences were found between the two areas in the control group. Although lactate signals were hardly detectable in individual spectra, there was a trend toward increased Lac/Cr values in the anterior parts with respect to the posterior parts in the patient group, with the effect particularly evident in the asymptomatic subjects with the gene mutation.     

Comparison of diffusion tensor,dynamic susceptibility contrast MRI and Tc-Tetrofosmin brain SPECT for the detection of recurrent high-grade glioma

Introduction

Treatment induced necrosis is a relatively frequent finding in patients treated for high-grade glioma. Differentiation by imaging modalities between glioma recurrence and treatment induced necrosis is not always straightforward. This is a comparative study of diffusion tensor imaging (DTI), dynamic susceptibility contrast MRI and ^99mTc-Tetrofosmin brain single-photon emission computed tomography (SPECT) for differentiation of recurrent glioma from treatment induced necrosis.

Methods

A prospective study was made of 30 patients treated for high-grade glioma who had suspected recurrent tumor on follow-up MRI. All had been treated by surgical resection of the tumor followed by standard postoperative radiotherapy with chemotherapy. No residual tumor had been found on brain imaging immediately after the initial treatment. All the patients were studied with dynamic susceptibility contrast brain MRI and, within a week, ^99mTc-Tetrofosmin brain SPECT.

Results

Both ^99mTc-Tetrofosmin brain SPECT and dynamic susceptibility contrast MRI could discriminate between tumor recurrence and treatment induced necrosis with 100% sensitivity and 100% specificity. An apparent diffusion coefficient (ADC) ratio cut-off value of 1.27 could differentiate recurrence from treatment induced necrosis with 65% sensitivity and 100% specificity and a fractional anisotropy (FA) ratio cut-off value of 0.47 could differentiate recurrence from treatment induced necrosis with 57% sensitivity and 100% specificity. A significant correlation was demonstrated between ^99mTc-Tetrofosmin uptake ratio and rCBV (P = 0.003).

Conclusions

Dynamic susceptibility contrast MRI and brain SPECT with ^99mTc-Tetrofosmin had the same accuracy and may be used to detect recurrent tumor following treatment for glioma. DTI also showed promise for the detection of recurrent tumor, but was inferior to both dynamic susceptibility contrast MRI and brain SPECT.     

Serial Precision of Metabolite Peak Area Ratios and Water Referenced Metabolite Peak Areas in Proton MR Spectroscopy of the Human Brain

The precision of cerebral proton magnetic resonance spectroscopy (MRS) measurements is critical both in the clinical setting and for research purposes. Marshall et al. have recently concluded that “disappointing in vivo repeatability…is likely to limit” the ability of MRS to detect modest changes. We present here a comprehensive study of the precision of short- and long-term metabolite peak area ratios and water referenced metabolite peak areas for long echo time point resolved spectroscopy (PRESS) spectra (repetition time (TR) = 2000 ms, echo time (TE) = 136 ms) acquired from the occipital lobes of normal volunteers and a phantom using a conventional whole body 1.5 T MR system and conventional acquisition and analysis protocols. Short-term in vitro precision determined by five repeat scans on five occasions was excellent as measured by a mean coefficient of variation (NAA/Cho = 1.3%, NAA/Cr + PCr = 1.0%, Cho/Cr + PCr = 1.6%, NAA/H₂O = 0.5%, Cho/H₂O = 1.2%, Cr + PCr/H₂O = 0.8%). Long term in vitro precision using 100 spectra acquired over 2 years was also very good (NAA/Cho = 2.7%, NAA/Cr + PCr = 1.4%, Cho/Cr + PCr = 2.2%, NAA/H₂O = 1.5%, Cho/H₂O = 2.4%, Cr + PCr/H₂O = 1.5%). Short-term in vivo precision determined by five repeat scans in a single scanning session on eight subjects was also excellent (NAA/Cho = 5.2%, NAA/Cr + PCr = 3.0%, Cho/Cr + PCr = 6.6%, NAA/H₂O = 1.4%, Cho/H₂O = 4.9%, Cr + PCr/H₂O = 2.7%) and only worsened slightly for long-term in vivo precision determined by five repeat scans on eight subjects over 3 months (NAA/Cho = 5.2%, NAA/Cr + PCr = 4.8%, Cho/Cr + PCr = 7.7%, NAA/H₂O = 2.5%, Cho/H₂O = 6.4%, Cr + PCr/H₂O = 3.8%). We attribute the excellent precision reported here to the use of highly automated techniques for voxel shimming, water suppression and peak area measurements. These results allow us to repudiate Marshall’s assertion regarding disappointing repeatability of in vivo MRS.     

Experimental hypoxic–ischemic encephalopathy: comparison of apparent diffusion coefficients and proton magnetic resonance spectroscopy

This study aims to compare the apparent diffusion coefficients (ADCs) and proton magnetic resonance spectroscopy (¹H-MRS) in the first 24 h of acute hypoxic-ischemic brain damage (HIBD) in piglets. Twenty-five 7-day-old piglets were subjected to transient bilateral common carotid artery occlusion followed by ventilation with 4% oxygen for 1 h. Diffusion-weighted imaging (DWI) and ¹H-MRS were performed on cessation of the insult or at 3, 6, 12 or 24 h after resuscitation (all n=5). ADCs, N-acetylaspartate/choline (NAA/Cho), NAA/creatine (NAA/Cr), lactate/NAA (Lac/NAA), Lac/Cho and Lac/Cr were calculated. Cerebral injury was evaluated by pathological study and Hsp70 immunohistochemical analysis. On cessation of the insult, ADCs, NAA/Cho and NAA/Cr reduced, Lac/NAA, Lac/Cho and Lac/Cr increased. From 3 to 12 h after resuscitation, ADCs, Lac/NAA, Lac/Cho and Lac/Cr recovered, NAA/Cho and NAA/Cr reduced. Twenty-four hours after resuscitation, ADCs reduced once more, Lac/NAA, Lac/Cho and Lac/Cr increased again, whereas NAA/Cho and NAA/Cr decreased continuously. Pathological study revealed mild cerebral edema on cessation of the insult and more and more severe cerebral injury after resuscitation. No Hsp70-positive cells were detected on cessation of the insult. From 3 to 12 hours after resuscitation, Hsp70-positive cells gradually increased. Twenty-four hours after resuscitation, Hsp70-positive cells decreased. Throughout the experiment, changes in NAA/Cho and pathology had the best correlation (R=–0.729). In conclusion, NAA/Cho is the most precise ratio to reflect the pathological changes of early HIBD. Transient ADCs and Lac ratios recovery do not predict the reversal of histological damage of early HIBD. Reducing astrocytic swelling is of great clinical significance.     

MR evaluation of breast lesions obtained by diffusion-weighted imaging with background body signal suppression (DWIBS) and correlations with histological findings

Objectives

Diffusion imaging represents a new imaging tool for the diagnosis of breast cancer. This study aims to investigate the role of diffusion-weighted MRI with background body signal suppression (DWIBS) for evaluating breast lesions.

Methods

90 patients were prospectively evaluated by MRI with STIR, TSE-T2, contrast enhanced THRIVE-T1 and DWIBS sequences. DWIBS were analyzed searching for the presence of breast lesions and calculating the ADC value. ADC values of ≤ 1.44 × 10^- 3 mm²/s were considered suspicious for malignancy. This analysis was then compared with the histological findings. Sensitivity, specificity, diagnostic accuracy (DA), positive predictive value (PPV) and negative (NPV) were calculated.

Results

In 53/90 (59%) patients, DWIBS indicated the presence of breast lesions, 16 (30%) with ADC values of  > 1.44 and 37 (70%) with ADC ≤ 1.44. The comparison with histology showed 25 malignant and 28 benign lesions. DWIBS sequences obtained sensitivity, specificity, DA, PPV and NPV values of 100, 82, 87, 68 and 100%, respectively.

Conclusion

DWIBS can be proposed in the MRI breast protocol representing an accurate diagnostic complement.     

颐脑解郁方对抑郁大鼠脑1H波谱的干预作用

该文主要研究抑郁大鼠脑的¹H MRS变化及颐脑解郁方的干预作用. 将雄性Wistar大鼠随机分为正常组、模型组、西药组和中药组,每组5只. 正常组常规饲养,模型组、中药组和西药组给予21 d的慢性不可预知的温和应激. 应激结束中药组予颐脑解郁方、西药组予盐酸氟西汀进行干预. 干预结束后,通过检测左侧海马及前额叶皮质N-乙酰天门冬氨酸（NAA）、胆碱（Cho）、肌酸（Cr）等代谢物水平,分别计算NAA、Cho与Cr的比值,进而对脑组织代谢进行定性及定量分析. 得到：1. 海马区域：与正常组相比,模型组、西药组大鼠海马NAA/Cr降低（P<0.01）,中药组大鼠NAA/Cr与模型组相比升高（P<0.05）;与正常组相比,模型组Cho/Cr升高（P<0.05）,中药组Cho/Cr比模型组显著低（P<0.01）. 2. 前皮质区域：与正常组相比,模型组、西药组大鼠前皮质NAA/Cr降低（P<0.01）,中药组大鼠NAA/Cr较模型组显著升高（P<0.01）;模型组、西药组Cho/Cr与正常组相比显著升高（P<0.01）;与模型组相比,中药组、西药组Cho/Cr降低（P<0.01,P<0.05）. 这些结果说明颐脑解郁方可改善大鼠海马和前皮质的物质代谢,推测其抗抑郁作用主要与调节脑组织异常代谢有关.     

Spectroscopic imaging of radiation-induced effects in the white matter of glioma patients

External radiation therapy of brain tumors may cause adverse effects on normal brain tissue, resulting in severe neuropsychological and cognitive impairment. We investigated the late delayed radiation effects in the white matter (WM) using (1)H magnetic resonance spectroscopic imaging ((1)HMRSI). Nine glioma patients with local radiation-induced signal abnormalities in the T(2)-weighted MR images were studied with nine age- and sex-matched controls. The metabolite ratios in the radiation-induced hyper intensity area (RIHA) and in the normal appearing white matter (NAWM) of the patients were compared with respective WM areas of the controls. In RIHA, choline/creatine (Cho/Cr) was 17% decreased (1.22 +/- 0.13 vs 1.47 +/- 0.16, p = 0.0027, significant (s), unpaired Student's t test with Bonferroni correction) in the patients compared to the controls, while there was no difference in N-acetyl aspartate/Cr (NAA/Cr) (2.49 +/- 0.57 vs 2.98 +/- 0.32, p = 0.039) or NAA/Cho (2. 03 +/- 0.40 vs 2.04 +/- 0.17, p = 0.95). In NAWM, Cho/Cr was 24% decreased (1.21 +/- 0.15 vs 1.59 +/- 0.13, p < 0.0001, s) and NAA/Cho was 20% increased (2.49 +/- 0.49 vs 1.98 +/- 0.15, p = 0. 0082, s) in the patients compared to the controls, while there was no difference in NAA/Cr (2.99 +/- 0.46 vs 3.16 +/- 0.32, p = 0.38). NAA(RIHA)/NAA(NAWM) was 25% decreased (0.75 +/- 0.20 vs 1.00 +/- 0. 12, p = 0.0043, s) and Cr(RIHA)/Cr(NAWM) was 16% decreased (0.89 +/- 0.15 vs 1.06 +/- 0.10, p = 0.013, s) in the patients compared to the controls, while there was no difference in Cho(RIHA)/Cho(NAWM) (0.92 +/- 0.23 vs 0.98 +/- 0.10, p = 0.47). (1)HMRSI reveals widespread chemical changes in the WM after radiation therapy. In RIHA, there is loss of NAA, Cho, and Cr implying axonal and membrane damage and in NAWM, there is loss of Cho, reflecting membrane damage.     

Improvement of PI-RADS-dependent prostate cancer classification by quantitative image assessment using radiomics or mean ADC

BackgroundCurrently, interpretation of prostate MRI is performed qualitatively. Quantitative assessment of the mean apparent diffusion coefficient (mADC) is promising to improve diagnostic accuracy while radiomic machine learning (RML) allows to probe complex parameter spaces to identify the most promising multi-parametric models. We have previously developed quantitative RML and ADC classifiers for prediction of clinically significant prostate cancer (sPC) from prostate MRI, however these have not been combined with radiologist PI-RADS assessment.PurposeTo propose and evaluate diagnostic algorithms combining quantitative ADC or RML and qualitative PI-RADS assessment for prediction of sPC.Methods and populationThe previously published quantitative models (RML and mADC) were utilized to construct four algorithms: 1) Down(ADC) and 2) Down(RML): clinically detected PI-RADS positive prostate lesions (defined as either PI-RADS≥3 or ≥4) were downgraded to MRI negative upon negative quantitative assessment; and 3) Up(ADC) and 4) Up(RML): MRI-negative lesions were upgraded to MRI-positive upon positive assessment of quantitative parameters. Analyses were performed at the individual lesion level and the patient level in 133 consecutive patients with suspicion for clinically significant prostate cancer (sPC, International Society of Urological Pathology (ISUP) grade group≥2), the test set subcohort of a previously published patient population. McNemar test was used to compare differences in sensitivity, specificity and accuracy. Differences between lesions of different prostate zones were assessed using ANOVA. Reduction in false positive assessments was assessed as ratios.ResultsCompared to clinical assessment at the PI-RADS≥4 cut-off alone, algorithms Down(ADC/RML) improved specificity from 43% to 65% (p = 0.001)/62% (p = 0.003), while sensitivity did not change significantly at 89% compared to 87% (p = 1.0)/89% (unchanged) on the patient level. Reduction of false positive lesions was 50% [26/52] in the PZ and 53% [15/28] in the TZ. Algorithms Up(ADC/RML) led, on a patient basis, to an unfavorable loss of specificity from 43% to 30% (p = 0.039)/32% (p = 0.106), with insignificant increase of sensitivity from 89% to 96%/96% (both p = 1.0). Compared to clinical assessment at the PI-RADS≥3 cut-off alone, similar results were observed for Down(ADC) with significantly increased specificity from 2% to 23% (p < 0.001) and unchanged sensitivity on the lesion level; patient level specificity increased only non-significantly.ConclusionDowngrading PI-RADS≥3 and ≥ 4 lesions based on quantitative mADC measurements or RML classifiers can increase diagnostic accuracy by enhancing specificity and preserving sensitivity for detection of sPC and reduce false positives.     

Computational-Based Approach for Predicting Porosity of Electrospun Nanofiber Mats Using Response Surface Methodology and Artificial Neural Network Methods

Comparative studies between response surface methodology (RSM) and artificial neural network (ANN) methods to find the effects of electrospinning parameters on the porosity of nanofiber mats is described. The four important electrospinning parameters studied included solution concentration (wt.%), applied voltage (kV), spinning distance (cm) and volume flow rate (mL/h). It was found that the applied voltage and solution concentration are the two critical parameters affecting the porosity of the nanofiber mats. The two approaches were compared for their modeling and optimization capabilities with the modeling capability of RSM showing superiority over ANN, having comparatively lower values of errors. The mean relative error for the RSM and ANN models were 1.97% and 2.62% and the root mean square errors (RMSE) were 1.50 and 1.95, respectively. The superiority of the RSM-based approach is due to its high prediction accuracy and the ability to compute the combined effects of the electrospinning factors on the porosity of the nanofiber mats.     

Metabolite ratios to assumed stable creatine level may confound the quantification of proton brain MR spectroscopy

In localized brain proton MR spectroscopy ((1)H-MRS), metabolites' levels are often expressed as ratios, rather than as absolute concentrations. Frequently, their denominator is the creatine [Cr], which level is explicitly assumed to be stable in normal as well as in many pathologic states. The rationale is that ratios self-correct for imager and localization method differences, gain instabilities, regional susceptibility variations and partial volume effects. The implicit assumption is that these benefits are worth their cost(w)-(w) propagation of the individual variation of each of the ratio's components. To test this hypothesis, absolute levels of N-acetylaspartate [NAA], choline [Cho] and [Cr] were quantified in various regions of the brains of 8 volunteers, using 3-dimensional (3D) (1)H-MRS at 1.5 T. The results show that in over 50% of approximately 2000 voxels examined, [NAA]/[Cr] and [Cho]/[Cr] exhibited higher coefficients of variations (CV) than [NAA] and [Cho] individually. Furthermore, in approximately 33% of these voxels, the ratios' CVs exceeded even the combined constituents' CVs. Consequently, basing metabolite quantification on ratios and assuming stable [Cr] introduces more variability into (1)H-MRS than it prevents. Therefore, its cost exceeds the benefit.     

Pediatric abdominal masses: diagnostic accuracy of diffusion weighted MRI

Purpose

To retrospectively identify apparent diffusion coefficient (ADC) values of pediatric abdominal mass lesions, to determine whether measured ADC of the lesions and signal intensity on diffusion-weighted (DW) images allow discrimination between benign and malignant mass lesions.

Materials and Methods

Approval for this retrospective study was obtained from the institutional review board. Children with abdominal mass lesions, who were examined by DW magnetic resonance imaging (MRI) were included in this study. DW MR images were obtained in the axial plane by using a non breath-hold single-shot spin-echo sequence on a 1.5-T MR scanner. ADCs were calculated for each lesion. ADC values were compared with Mann–Whitney U test. Receiver operating characteristic curve analysis was performed to determine cut-off values for ADC. The results of visual assessment on b800 images and ADC map images were compared with chi-square test.

Results

Thirty-one abdominal mass lesions (16 benign, 15 malignant) in 26 patients (15 girls, 11 boys, ranging from 2 days to 17 years with 6.9 years mean) underwent MRI. Benign lesions had significantly higher ADC values than malignant ones (P<.001). The mean ADCs of malignant lesions were 0.84±1.7×10⁻³ mm²/s, while the mean ADCs of the benign ones were 2.28±1.00×10⁻³ mm²/s. With respect to cutoff values of ADC: 1.11×10⁻³ mm²/s, sensitivity and negative predictive values were 100%, specificity was 78.6% and positive predictive value was 83.3%. For b800 and ADC map images, there were statistically significant differences on visual assessment. All malignant lesions had variable degrees of high signal intensity whereas eight of the 16 benign ones had low signal intensities on b800 images (P<.001). On ADC map images, all malignant lesions were hypointense and most of the benign ones (n=11, 68.7%) were hyperintense (P<.001).

Conclusion

DW imaging can be used for reliable discrimination of benign and malignant pediatric abdominal mass lesions based on considerable differences in the ADC values and signal intensity changes.     

Repeatability of echo-planar-based diffusion measurements of the human prostate at 3 T

Echo-planar-based diffusion-weighted imaging (DWI) of the prostate is increasingly being suggested as a viable technique, complementing information derived from conventional magnetic resonance imaging methods for use in tissue discrimination. DWI has also been suggested as a potentially useful tool in the assessment of tumor response to treatment. In this study, the repeatability of apparent diffusion coefficient (ADC) values obtained from both DWI and diffusion tensor imaging (DTI) has been assessed as a precursor to determining the magnitude of treatment-induced changes required for reliable detection. The repeatability values of DWI and DTI were found to be similar, with ADC values repeatable to within 35% or less over a short time period of a few minutes and a longer time period of a month. Fractional anisotropy measurements were found to be less repeatable (between 26% and 71%), and any changes duly recorded in longitudinal studies must therefore be treated with a degree of caution.     

Anisotropic diffusion of metabolites in peripheral nerve using diffusion weighted magnetic resonance spectroscopy at ultra-high field

Although the diffusivity and anisotropy of water has been investigated thoroughly in ordered axonal systems (i.e., nervous tissue), there have been very few studies on the directional dependence of diffusion of metabolites. In this study, the mean apparent diffusion coefficient (Trace/3 ADC) and fractional anisotropy (FA) values of the intracellular metabolites N-acetyl aspartate (NAA), creatine and phosphocreatine (tCr), choline (Cho), taurine (Tau), and glutamate and glutamine (Glx) were measured parallel and perpendicular to the length of excised frog sciatic nerve using a water suppressed, diffusion-weighted, spin-echo pulse sequence at 18.8T. The degree of anisotropy (FA) of NAA (0.41+/-0.09) was determined to be less than tCr (0.59+/-0.07) and Cho (0.61+/-0.11), which is consistent with previously reported human studies of white matter. In contrast, Glx diffusion was found to be almost isotropic with an FA value of 0.20+/-0.06. The differences of FA between the metabolites is most likely due to their differing micro-environments and could be beneficial as an indicator of compartment specific changes with disease, information not readily available with water diffusion.     

Molality as a unit of measure for expressing 1H MRS brain metabolite concentrations in vivo

Absolute concentrations of cerebral metabolite in in vivo 1H magnetic resonance spectroscopy studies (1H-MRS) are widely reported in molar units as moles per liter of tissue, or in molal units as moles per kilogram of tissue. Such measurements require external referencing or assumptions as to local water content. To reduce the scan time, avoid assumptions that may be invalid under specific pathologies, and provide a universally accessible referencing procedure, we suggest that metabolite concentrations from 1H-MRS measurements in vivo be reported in molal units as moles per kilogram of tissue water. Using internal water referencing, a two-compartment water model, a simulated brain spectrum for peak identification, and a spectroscopic bi-exponential spin-spin relaxation segmentation technique, we measured the absolute concentrations for the four common 1H brain metabolites: choline (Cho), myo-inositol (mIno), phosphocreatine + creatine (Cr), and N-acetyl-aspartate (NAA), in the hippocampal region (n = 26) and along the Sylvian fissure (n = 61) of 35 healthy adults. A stimulated echo localization method (20 ms echo time, 10 ms mixing time, 4 s repetition time) yielded metabolite concentrations, uncorrected for metabolite relaxation or contributions from macromolecule resonances, that were expectantly higher than with molar literature values. Along the Sylvian fissure the average concentrations (coefficient of variation (CV)) in mmoles/kg of tissue water were 17.6 (12%) for NAA, 14.2 (9%) for Cr, 3.6 (13%) for Cho, and 13.2 (15%) for mIno. Respective values for the hippocampal region were 15.7 (20%), 14.7 (16%), 4.6 (19%), and 17.7 (26%). The concentrations of the two regions were significantly different (p 相似文献   

Differential MRI diagnosis between brain abscesses and necrotic or cystic brain tumors using the apparent diffusion coefficient and normalized diffusion-weighted images

Magnetic Resonance Diffusion-Weighted Imaging (DWI) has been reported to be helpful for the differential diagnosis between abscesses and cystic/necrotic brain tumors. However the number of patients is still limited, and the sensitivity and specificity of the method remain to be confirmed. The primary purpose of this study was to investigate a larger sample of patients, all investigated under the same experimental conditions, in order to obtain statistically significant data. Moreover, there is no consensus about the appropriate values of b required to use to make an accurate diagnosis from DWI. The secondary purpose of this study was to determine the discriminating threshold b values for raw diffusion-weighted images and for normalized diffusion-weighted images. On the basis of 14 abscesses, 10 high-grade gliomas and 2 metastases, we show that the calculation of accurate Apparent Diffusion Coefficient (ADC) values gives a specificity rate of 100%. Without ADC calculation, we show that image normalization is required to make an accurate differential diagnosis, and we highlight the ability of DWI to discriminate between brain abscesses and cystic/necrotic brain tumors using normalized signal intensity at lower b values (503 s/mm(2)) than usual.