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Diffusion-weighted MRI (DWI) is an important tool for oncology research, with great clinical potential for the classification and monitoring of breast lesions. The utility of parameters derived from DWI, however, is influenced by specific analysis choices. The purpose of this study was to critically evaluate repeatability and curve-fitting performance of common DWI signal representations, for a prospective cohort of patients with benign breast lesions. Twenty informed, consented patients with confirmed benign breast lesions underwent repeated DWI (3 T) using: sagittal single-shot spin-echo echo planar imaging, bipolar encoding, TR/TE: 11,600/86 ms, FOV: 180 x 180 mm, matrix: 90 x 90, slices: 60 x 2.5 mm, iPAT: GRAPPA 2, fat suppression, and 13 b-values: 0-700 s/mm2 . A phase-reversed scan (b = 0 s/mm2 ) was acquired for distortion correction. Voxel-wise repeat-measures coefficients of variation (CoVs) were derived for monoexponential (apparent diffusion coefficient [ADC]), biexponential (intravoxel incoherent motion: f, D, D*) and stretched exponential (α, DDC) across the parameter histograms for lesion regions of interest (ROIs). Goodness-of-fit for each representation was assessed by Bayesian information criterion. The volume of interest (VOI) definition was repeatable (CoV 13.9%). Within lesions, and across both visits and the cohort, there was no dominant best-fit model, with all representations giving the best fit for a fraction of the voxels. Diffusivity measures from the signal representations (ADC, D, DDC) all showed good repeatability (CoV 50%). The stretching exponent α was repeatable (CoV < 12%). This pattern of repeatability was consistent over the central part of the parameter percentiles. Assumptions often made in diffusion studies about analysis choices will influence the detectability of changes, potentially obscuring useful information. No single signal representation prevails within or across lesions, or across repeated visits; parameter robustness is therefore a critical consideration. Our results suggest that stretched exponential representation is more repeatable than biexponential, with pseudodiffusion parameters unlikely to provide clinically useful biomarkers.

Background In vivo magnetic resonance spectroscopy (MRS) enables non-invasive measurements of tumor metabolites. Choline-containing metabolites play a key role in tumor metabolism. Purpose To explore whether preoperative MRS-derived tumor choline levels are associated with clinical and histological features in endometrial carcinomas. Material and Methods Preoperative pelvic magnetic resonance imaging (MRI) (1.5T), including structural and diffusion-weighted imaging and localized multivoxel proton MR (1H-MR) spectroscopy, was performed in 77 prospectively included patients with histologically confirmed endometrial carcinomas. Relative levels of total choline-containing metabolites (tCho) in tumor and myometrium were measured using the ratios: tCho/Creatine; tCho/Water; and tCho/Noise. MRS parameters were analyzed in relation to histological subtype and grade, surgicopathological staging parameters, MRI-measured tumor volume, and tumor apparent diffusion coefficient (ADC) value and clinical outcome. Results Tumor tissue had significantly higher ratios for tCho/Creatine, tCho/Water, and tCho/Noise than normal myometrial tissue ( P s = 0.25; P = 0.03). Conclusion High choline levels in tumor are associated with high-risk features. In vivo MRS may potentially aid in the preoperative risk stratification in endometrial cancer.

Objectives To investigate the reliability of simultaneous positron emission tomography and magnetic resonance imaging (PET/MRI)-derived biomarkers using semi-automated Gaussian mixture model (GMM) segmentation on PET images, against conventional manual tumor segmentation on dynamic contrast-enhanced (DCE) images. Materials and methods Twenty-four breast cancer patients underwent PET/MRI (following 18F-fluorodeoxyglucose (18F-FDG) injection) at baseline and during neoadjuvant treatment, yielding 53 data sets (24 untreated, 29 treated). Two-dimensional tumor segmentation was performed manually on DCE–MRI images (manual DCE) and using GMM with corresponding PET images (GMM–PET). Tumor area and mean apparent diffusion coefficient (ADC) derived from both segmentation methods were compared, and spatial overlap between the segmentations was assessed with Dice similarity coefficient and center-of-gravity displacement. Results No significant differences were observed between mean ADC and tumor area derived from manual DCE segmentation and GMM–PET. There were strong positive correlations for tumor area and ADC derived from manual DCE and GMM–PET for untreated and treated lesions. The mean Dice score for GMM–PET was 0.770 and 0.649 for untreated and treated lesions, respectively. Discussion Using PET/MRI, tumor area and mean ADC value estimated with a GMM–PET can replicate manual DCE tumor definition from MRI for monitoring neoadjuvant treatment response in breast cancer.

Purpose To evaluate the relative change of the apparent diffusion coefficient (ADC) at low- and medium-b-value regimens as a surrogate marker of microcirculation, to study its correlation with dynamic contrast agent-enhanced (DCE) magnetic resonance (MR) imaging-derived parameters, and to assess its potential for differentiation between malignant and benign breast tumors. Materials and Methods Ethics approval and informed consent were obtained. From May 2013 to June 2015, 61 patients diagnosed with either malignant or benign breast tumors were prospectively recruited. All patients were scanned with a 3-T MR imager, including diffusion-weighted imaging (DWI) and DCE MR imaging. Parametric analysis of DWI and DCE MR imaging was performed, including a proposed marker, relative enhanced diffusivity (RED). Spearman correlation was calculated between DCE MR imaging and DWI parameters, and the potential of the different DWI-derived parameters for differentiation between malignant and benign breast tumors was analyzed by dividing the sample into equally sized training and test sets. Optimal cut-off values were determined with receiver operating characteristic curve analysis in the training set, which were then used to evaluate the independent test set. Results RED had a Spearman rank correlation of 0.61 with the initial area under the curve calculated from DCE MR imaging. Furthermore, RED differentiated cancers from benign tumors with an overall accuracy of 90% (27 of 30) on the test set with 88.2% (15 of 17) sensitivity and 92.3% (12 of 13) specificity. Conclusion This study presents promising results introducing a simplified approach to assess results from a DWI protocol sensitive to the intravoxel incoherent motion effect by using only three b values. This approach could potentially aid in the differentiation, characterization, and monitoring of breast pathologies. © RSNA, 2016 Online supplemental material is available for this article.

Background To compare “standard” diffusion weighted imaging, and diffusion tensor imaging (DTI) of 2nd and 4th-order for the differentiation of malignant and benign breast lesions. Methods Seventy-one patients were imaged at 3 Tesla with a 16-channel breast coil. A diffusion weighted MRI sequence including b = 0 and b = 700 in 30 directions was obtained for all patients. The image data were fitted to three different diffusion models: isotropic model – apparent diffusion coefficient (ADC), 2nd-order tensor model (the standard model used for DTI) and a 4th-order tensor model, with increased degrees of freedom to describe anisotropy. The ability of the fitted parameters in the different models to differentiate between malignant and benign tumors was analyzed. Results Seventy-two breast lesions were analyzed, out of which 38 corresponded to malignant and 34 to benign tumors. ADC (using any model) presented the highest discriminative ability of malignant from benign tumors with a receiver operating characteristic area under the curve (AUC) of 0.968, and sensitivity and specificity of 94.1% and 94.7% respectively for a 1.33 × 10−3 mm2/s cutoff. Anisotropy measurements presented high statistical significance between malignant and benign tumors (P < 0.001), but with lower discriminative ability of malignant from benign tumors than ADC (AUC of 0.896 and 0.897 for fractional anisotropy and generalized anisotropy respectively). Statistical significant difference was found between generalized anisotropy and fractional anisotropy for cancers (P < 0.001) but not for benign lesions (P = 0.87). Conclusion While anisotropy parameters have the potential to provide additional value for breast applications as demonstrated in this study, ADC exhibited the highest differentiation power between malignant and benign breast tumors. J. Magn. Reson. Imaging 2015.

Magnetic resonance (MR) modalities are routine imaging tools in the diagnosis and management of gliomas. MR spectroscopic imaging (MRSI), which relies on the metabolic characteristics of tissues, has been developed to accelerate the understanding of gliomas and to aid in effective clinical decision making and development of targeted therapies. In this review, the potentials and practical challenges to frequently use this technique in clinical management of gliomas are discussed. The applications of new biomarkers detectable by MRSI in differential glioma diagnosis, pre- and post-treatment evaluations, and neurosurgery are also addressed.

Metastasis to the brain is a feared complication of systemic cancer, associated with significant morbidity and poor prognosis. A better understanding of the tumor metabolism might help us meet the challenges in controlling brain metastases. The study aims to characterize the metabolic profile of brain metastases of different origin using high resolution magic angle spinning (HR-MAS) magnetic resonance spectroscopy (MRS) to correlate the metabolic profiles to clinical and pathological information. Biopsy samples of human brain metastases (n = 49) were investigated. A significant correlation between lipid signals and necrosis in brain metastases was observed (p < 0.01), irrespective of their primary origin. The principal component analysis (PCA) showed that brain metastases from malignant melanomas cluster together, while lung carcinomas were metabolically heterogeneous and overlap with other subtypes. Metastatic melanomas have higher amounts of glycerophosphocholine than other brain metastases. A significant correlation between microscopically visible lipid droplets estimated by Nile Red staining and MR visible lipid signals was observed in metastatic lung carcinomas (p = 0.01), indicating that the proton MR visible lipid signals arise from cytoplasmic lipid droplets. MRS-based metabolomic profiling is a useful tool for exploring the metabolic profiles of metastatic brain tumors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Purpose: To assess the reproducibility of 1H-MR spectroscopic imaging (MRSI) of the human brain at 3T with volume selection by a double spin echo sequence for localization with adiabatic refocusing pulses (semi-LASER). Materials and Methods: Twenty volunteers in two different institutions were measured twice with the same pulse sequence at an echo time of 30 msec. Magnetic resonance (MR) spectra were analyzed with LCModel with a simulated basis set including an experimentally acquired macromolecular signal profile. For specific regions in the brain mean metabolite levels, within and between subject variance, and the coefficient of variation (CoV) were calculated (for taurine, glutamate, total N-acetylaspartate, total creatine, total choline, myo-inositol + glycine, and glutamate + glutamine). Results: Repeated measurements showed no significant differences with a paired t-test and a high reproducibility (CoV ranging from 3%–30% throughout the selected volume). Mean metabolite levels and CoV obtained in similar regions in the brain did not differ significantly between two contributing institutions. The major source of differences between different measurements was identified to be the between-subject variations in the volunteers. Conclusion: We conclude that semi-LASER 1H-MRSI at 3T is an adequate method to obtain quantitative and reproducible measures of metabolite levels over large parts of the brain, applicable across multiple centers. J. Magn. Reson. Imaging 2010;31:61–70. © 2009 Wiley-Liss, Inc.

Fifteen podzolic forest soils in Norway covering sites with a wide range of atmospheric deposition rates were assayed for their contents of pollutant Pb. Samples from the Of, Oh, E, B, and C horizons were studied. Nitricadd soluble contents of Pb and the corresponding stable Pb isotope ratios were determined by sector field inductively coupled plasma-mass spectrometry (ICP-MS). On the basis of existing knowledge on 2 0 6 Pb/ 2 0 7 Pb ratios in atmospheric deposition over Norway across time, the percentage of the Pb supplied by air pollution was calculated for the various samples and soil horizons, assuming that the C horizon was undisturbed. More than 90% of O horizon Pb was from pollution, even at remote sites in the far north. Significant fractions of Pb were pollution-derived also in the E and B horizons at most sites. In the south, more than half of the Pb derived from air pollution has now moved to the upper mineral horizons. Stable Pb isotope ratios are a very predse tool for revealing Pb pollution in terrestrial ecosystems. The present work suggests that similar studies should be done in other parts of the world to objectively assess the anthropogenic contribution to surface soil Pb.

Distributions of 21 major and trace elements in HNO3 extracts of different horizons were studied in 13 podzol profiles from the boreal forest in different parts of Norway using ICP–MS. On the basis of ratios between the HNO3-extractable fractions in the various horizons some general trends were elucidated. Two different groups of elements concentrated in the humus layer relative to the mineral horizons were identified, one mainly associated with contributions from air pollution (As, Cd, Sb, Pb), another one with plant nutrient circulation (K, Ca, Mn and to a lesser extent Mg, Co, Ni, Rb) and some with both mechanisms (Cu, Zn, Tl). The elements most clearly enriched along with Fe in the B horizon were V, Pb, Al, and Cr in that order, Pb partly because of leaching from the polluted organic surface soil. Four soils in the far south showed a behaviour distinctly different from the rest and were treated as a separate group. Relative to the more northerly sites the surface horizons of these soils were strongly depleted in lithogenic elements (Mg, Al, K, Ca, Sc, V, Cr, Mn, Fe, Co, La) and enriched in elements typical of long-range transport of pollutants (As, Cd, Sb, Tl, Pb). Also the B horizon in the southern soils was strongly depleted in the lithogenic group elements, including Fe and the associated metals. The main reason for this difference is assumed to be the greater influence of transboundary air pollution and associated metals and stronger soil acidification in the far south of the country.

Amyotrophic lateral sclerosis (ALS) and parkinsonism-dementia complex (PDC) are neurodegenerative disorders that occurred with extremely high frequency among the native population on Guam, especially in the 1950s and 1960s, but have substantially declined over the last half-century. The etiology of these diseases is unknown, but the most plausible hypothesis centers on imbalances in essential and toxic metals. We have determined the concentrations of Cd, Co, Cu, Fe, Mn, Rb, V, and Zn in formalin-fixed brain tissue collected during the period 1979-1983 from eight Guamanian patients with ALS, four with PDC, and five control subjects using high-resolution inductively coupled plasma-mass spectrometry. The concentrations of Cd are markedly and significantly elevated both in gray and white matter in ALS, but not in PDC patients. The concentrations of Zn are elevated for both patient groups, in both gray and white matter, but only the difference in gray matter for PDC is significant. For the other metals, no significant differences are found.

Insect larvae of the orders ephemeroptera (mayflies), plecoptera (stoneflies) and tricoptera (caddisflies) were investigated with respect to possible use as biomonitors of heavy metal pollution in rivers affected by current or previous mining activity. Samples from two rivers in central Norway were collected 3 times during the summer of 1985 and analyzed for Cu, Zn. and Cd. Of the three orders, mayflies was the only showing promise for further work. Repeated sampling of mayflies in one of the rivers in 1993 showed the same levels of Zn and Cd as before, whereas the copper level was reduced by a factor of 3. This may be explained by measures taken by the mining company upstream the sampling sites, reducing considerably the downstream transport of particles. Apparently Cu in this river is associated with particles to a much greater extent than Zn and Cd.

The prognosis and treatment of astrocytomas, which are primary brain tumors, vary depending on the grade of the tumor, necessitating a precise preoperative classification. Magnetic resonance spectroscopy (MRS) provides information about metabolites in tissues and is an emerging noninvasive tool to improve diagnostic accuracy in patients with intracranial neoplasia.To investigate whether ex vivo MRS could differentiate World Health Organization grade II (A-II) and IV astrocytomas (glioblastomas; GBM) and to correlate MR spectral profiles with clinical parameters.Patients with A-II and GBM (n = 58) scheduled for surgical resection were enrolled. Tumor specimens were collected during surgery and stored in liquid nitrogen before being analyzed with high-resolution magic angle spinning MRS. The tumors were histopathologically classified according to World Health Organization criteria as GBM (n = 48) and A-II (n = 10).Multivariate analysis of ex vivo proton high-resolution magic angle spinning spectra MRS showed differences in the metabolic profiles of different grades of astrocytomas. A-II had higher levels of glycerophosphocholine and myo-inositol than GBM. The latter had more phosphocholine, glycine, and lipids. We observed a significant metabolic difference between recurrent and nonrecurrent GBM (P.001). Primary GBM had more phosphocholine than recurrent GBM. A significant correlation (P.001) between lipid and lactate signals and histologically estimated percentage of necrosis was observed in GBM. Spectral profiles were not correlated with age, survival, or magnetic resonance imaging-defined tumor volume.Ex vivo MRS can differentiate astrocytomas based on their metabolic profiles.

Personalized medicine is increasingly important in cancer treatment for its role in staging and its potential to improve stratification of patients. Different types of molecules, genes, proteins, and metabolites are being extensively explored as potential biomarkers. This review discusses the major findings and potential of tissue metabolites determined by high-resolution magic angle spinning magnetic resonance spectroscopy for cancer detection, characterization, and treatment monitoring. Cancer Res; 70(17); 6692–6. ©2010 AACR.

Background Metastases to the central nervous system from different primary cancers are an oncologic challenge as the overall prognosis for these patients is generally poor. The incidence of brain metastases varies with type of primary cancer and is probably increasing due to improved therapies of extracranial metastases prolonging patient's overall survival and thereby time for brain metastases to develop. In addition, the greater access to improved neuroimaging techniques can provide earlier diagnosis. The aim of this study was to investigate the feasibility of using proton magnetic resonance spectroscopy (MRS) and multivariate analyses to characterize brain metastases originating from different primary cancers, to assess changes in spectra during radiation treatment and to correlate the spectra to clinical outcome after treatment. Methods Patients (n = 26) with brain metastases were examined using single voxel MRS at a 3T clinical MR system. Five patients were excluded due to poor spectral quality. The spectra were obtained before start (n = 21 patients), immediately after (n = 6 patients) and two months after end of treatment (n = 4 patients). Principal component analysis (PCA) and partial least square regression analysis (PLS) were applied in order to identify clustering of spectra due to origin of metastases and to relate clinical outcome (survival) of the patients to spectral data from the first MR examination. Results The PCA results indicated that brain metastases from primary lung and breast cancer were separated into two clusters, while the metastases from malignant melanomas showed no uniformity. The PLS analysis showed a significant correlation between MR spectral data and survival five months after MRS before start of treatment. Conclusion MRS determined metabolic profiles analysed by PCA and PLS might give valuable clinical information when planning and evaluating the treatment of brain metastases, and also when deciding to terminate further therapies.

The objectives of this study were to (a) explore the spectral characteristics of brain metastases, focusing on the origin of the primary cancer, and (b) evaluate the correlation with clinical outcome using multivariate analysis. High-resolution magic angle spinning (HR-MAS) MR spectra (n = 26) were obtained from 16 patients with brain metastases using a Bruker Avance DRX600 instrument. Standard pulse-acquired and spin-echo (TE 32 and 285 ms) (1)H spectra were obtained. These were examined using principal component analysis (PCA) and partial least squares regression analysis (PLS) relating spectral data to clinical outcome. The PCA score plot of pulse-acquired HR-MAS spectra showed a trend of clustering due to the origin of the metastases, mainly based on differences in the lipid signals at 1.3 and 0.9 ppm. With PLS, spectra of patients who died less than 5 months after surgery appeared to cluster in the lower left quadrant of the score plot. These preliminary results on brain metastasis classification and prediction of survival must be validated in a larger patient cohort. However, the possibility of differentiating metastases according to origin and predicting survival on the basis of HR-MAS spectra suggests that this method may be useful for diagnosing and planning treatment for brain metastases and also for guiding decisions about terminating further treatment.

Purpose: To investigate whether improvements in signal-to-noise ratio (SNR) and spectral resolution are found in spectra from patients with brain metastases obtained at higher magnetic field strengths using standard clinical instrumentation. Material and Methods: Six patients with brain metastases, 13 healthy volunteers, and a phantom containing brain metabolites were examined using two clinical MR instruments operating at 1.5T (Siemens) and 3T (Philips) with standard clinical head coils. Spectra were obtained using a point resolved spectroscopy pulse sequence, echo times (TE) 32 ms and 144 ms, and repetition time 2000 ms from a volume-of-interest (VOI) of size 15×15×15 mm3. SNR and spectral resolution of the metabolites N-acetylaspartate, choline, and creatine compounds in spectra from 3T were compared to the 1.5T spectra. Results: In general, spectral resolution was improved by 25–30% at higher magnetic field strength. Only minor improvements in SNR were obtained at 3T using short echo time and 20–50% at long echo time. Conclusion: SNR and spectral resolution were improved at higher magnetic field strength, especially with TE 144 ms, including spectra from patients with heterogeneous brain tumors. However, differences in the defined effective VOI, particularly at short echo time, reduced the expected effect of increased magnetic field strength on the measured SNR.

Children with very low birth weight (VLBW) have a significantly increased risk of later neurodevelopmental problems, while infants born small for gestational age (SGA) at term are also at some risk of developing neurological impairment. To investigate possible brain metabolite differences in adolescents with VLBW, SGA at term and controls by proton in vivo magnetic resonance spectroscopy (MRS) at 1.5 T. MR spectra were acquired from volumes localized in the left frontal lobe, containing mainly white matter (54 subjects). Peak areas of N-acetyl aspartate (NAA), choline (Cho) and creatine (Cr) were determined, and the peak area ratio of NAA to Cr, total Cho to Cr, or NAA to Cho calculated. Probabilistic neural network (PNN) analysis was performed utilizing the chemical shift region containing resonances from NAA, Cho and Cr as inputs. No significant difference in the peak area ratios could be found using the Kruskal-Wallis test. By application of PNN, a correct classification of 52 of the 54 adolescents with a sensitivity and specificity exceeding 93% for all groups was achieved. Small, yet systematic, differences in brain metabolite distribution among the groups were confirmed by PNN analysis.

The concentrations of manganese, copper, and zinc in cerebrospinal fluid (CSF) from patients with multiple sclerosis (MS) and patients with no known neurological disease (control group) were measured. Manganese and copper levels were determined by two different analytical methods: atomic absorption spectrometry (AAS) and high-resolution inductively coupled plasma-mass spectrometry (HR-ICP-MS), whereas zinc levels were determined by HR-ICP-MS only. Manganese levels (mean+/-SEM) were significantly decreased in the CSF of MS patients (1.07+/-0.13 microg/L, ICP-MS; 1.08+/-0.11 microg/L, AAS) compared to the levels in the control group (1.78+/-0.26 microg/L, ICP-MS; 1.51+/-0.17 microg/L, AAS). Copper levels were significantly elevated in the CSF of MS patients (10.90+/-1.11 microg/L; ICP-MS, 11.53+/-0.83 microg/L, AAS) compared to the levels in the control group (8.67+/-0.49 microg/L, ICP-MS; 9.10+/-0.62 microg/L, AAS). There were no significant differences between the CSF zinc levels of MS and control patients. The physiological basis for the differences in manganese and copper concentrations between MS patients and controls is unknown, but could be related to alterations in the manganese- containing enzyme glutamine synthetase and the copper-containing enzyme cytochrome oxidase.