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Background: Alzheimer's disease (AD) is one of the most common causes of dementia in old people. Neuronal deficits such as loss of memory, language and problem-solving are severely compromised in affected patients. The molecular features of AD are Aβ deposits in plaques or in oligomeric structures and neurofibrillary tau tangles in brain. However, the challenge is that Aβ is only one piece of the puzzle, and recent findings continue to support the hypothesis that their presence is not sufficient to predict decline along the AD outcome. In this regard, metabolomic-based techniques are acquiring a growing interest for either the early diagnosis of diseases or the therapy monitoring. Mass spectrometry is one the most common analytical platforms used for detection, quantification, and characterization of metabolic biomarkers. In the past years, both targeted and untargeted strategies have been applied to identify possible interesting compounds. Aim of review: The overall goal of this review is to guide the reader through the most recent studies in which LC–MS-based metabolomics has been proposed as a powerful tool for the identification of new diagnostic biomarkers in AD. To this aim, herein studies spanning the period 2009–2020 have been reported. Advantages and disadvantages of targeted vs untargeted metabolomic approaches have been outlined and critically discussed. [ABSTRACT FROM AUTHOR]

This study aimed to evaluate the usefulness of proton MR spectroscopic imaging ((1)H-MRSI) at 3 T in differentiating high- from low-grade gliomas, and tumour from necrosis, oedema or normal tissue. Forty-four patients with brain gliomas and four with meningiomas were retrospectively reviewed. The normalised metabolites choline (nCho), N-acetylaspartate (nNAA), creatine (nCr) and lactate/lipids (nLL), and the metabolite ratios Cho/NAA, NAA/Cr and Cho/Cr were calculated. Necrotic-appearing areas showed two spectroscopic patterns: "necrosis" with variable nCho and high nLL, and "cystic necrosis" with variable nLL or nonevident peaks. Peri-enhancing oedematous-appearing areas showed three spectroscopic patterns ("tumour" with abnormal Cho/NAA, "oedema" with normal Cho/NAA and "tumour/oedema" with normal nCho and abnormal Cho/NAA) in gliomas, and one ("oedema") in meningiomas. Peri-enhancing or peri-tumour normal-appearing areas showed two patterns ("infiltrated" with abnormal nCho and/or Cho/NAA and "normal" with normal spectra) in gliomas and one ("normal") in meningiomas. Discriminant analysis showed that classification accuracy between high- and low-grade glioma masses was better with normalised metabolites or all parameters together than metabolite ratios and that among peri-enhancing areas was much better with normalised metabolites. The analysis of spatial distribution of normalised metabolites by 3-T (1)H-MRSI helps to discriminate among different tissues, offering information not available with conventional MRI. [ABSTRACT FROM AUTHOR]

Proton magnetic resonance spectroscopy ((1)H-MRS) provides specific metabolic information not otherwise observable by any other imaging method. (1)H-MRS of the brain at 3 T is a new tool in the modern neuroradiological armamentarium whose main advantages, with respect to the well-established and technologically advanced 1.5-T (1)H-MRS, include a higher signal-to-noise ratio, with a consequent increase in spatial and temporal resolutions, and better spectral resolution. These advantages allow the acquisition of higher quality and more easily quantifiable spectra in smaller voxels and/or in shorter times, and increase the sensitivity in metabolite detection. However, these advantages may be hampered by intrinsic field-dependent technical issues, such as decreased T(2) signal, chemical shift dispersion errors, J-modulation anomalies, increased magnetic susceptibility, eddy current artifacts, challenges in designing and obtaining appropriate radiofrequency coils, magnetic field instability and safety hazards. All these limitations have been tackled by manufacturers and researchers and have received one or more solutions. Furthermore, advanced (1)H-MRS techniques, such as specific spectral editing, fast (1)H-MRS imaging and diffusion tensor (1)H-MRS imaging, have been successfully implemented at 3 T. However, easier and more robust implementations of these techniques are still needed before they can become more widely used and undertake most of the clinical and research (1)H-MRS applications. [ABSTRACT FROM AUTHOR]

Contrast-enhanced MR imaging is the method of choice for routine assessment of brain tumors, but it has limited sensitivity and specificity. We verified if the addition of metabolic, diffusion and hemodynamic information improved the definition of glioma extent and grade. Thirty-one patients with cerebral gliomas (21 high- and 10 low-grade) underwent conventional MR imaging, proton MR spectroscopic imaging (1H-MRSI), diffusion weighted imaging (DWI) and perfusion weighted imaging (PWI) at 3 Tesla, before undergoing surgery and histological confirmation. Normalized metabolite signals, including choline (Cho), N-acetylaspartate (NAA), creatine and lactate/lipids, were obtained by 1H-MRSI; apparent diffusion coefficient (ADC) by DWI; and relative cerebral blood volume (rCBV) by PWI. Perienhancing areas with abnormal MR signal showed 3 multiparametric patterns: “tumor”, with abnormal Cho/NAA ratio, lower ADC and higher rCBV; “edema”, with normal Cho/NAA ratio, higher ADC and lower rCBV; and “tumor/edema”, with abnormal Cho/NAA ratio and intermediate ADC and rCBV. Perienhancing areas with normal MR signal showed 2 multiparametric patterns: “infiltrated”, with high Cho and/or abnormal Cho/NAA ratio; and “normal”, with normal spectra. Stepwise discriminant analysis showed that the better classification accuracy of perienhancing areas was achieved when regarding all MR variables, while 1H-MRSI variables and rCBV better differentiated high- from low-grade gliomas. Multiparametric MR assessment of gliomas, based on 1H-MRSI, PWI and DWI, discriminates infiltrating tumor from surrounding vasogenic edema or normal tissues, and high- from low-grade gliomas. This approach may provide useful information for guiding stereotactic biopsies, surgical resection and radiation treatment. [ABSTRACT FROM AUTHOR]

We reviewed the brain MRI of 66 patients with the adult form of myotonic dystrophy type 1 (DM1) to evaluate the extent and significance of white matter involvement and to look for a pattern of MRI abnormalities suggestive of DM1. White matter lesions (WMLs) and large Virchow Robin spaces (VRSs) were rated by semiquantitative methods and the signal intensity of white matter superior and posterior to the trigones (WMPST) by reference to standard images. Disease duration was correlated positively with WML and negatively with VRS scores. Patients were divided into four groups according to increasing severity of WMPST involvement: group A with mild WMPST hyperintensity, group B with large VRSs and mild or moderate WMPST hyperintensity, group C with moderate WMPST hyperintensity or mild WMPST hyperintensity with small WMLs, group D with severe WMPST hyperintensity or moderate WMPST hyperintensity with small WMLs. Disease duration, muscular impairment, lobar WMLs and brain atrophy significantly increased from groups A and B (not significantly different) to C and from C to D, while convexity VRSs significantly decreased from group B to C and from C to D. Lobar white matter involvement in DM1 seems progressive during the disease and may be characterized initially by large VRSs or mild WMPST hyperintensity, then by small WMLs or moderate WMPST hyperintensity, and finally by more extensive and confluent WMLs or diffuse white matter hyperintensity and by brain atrophy. [ABSTRACT FROM AUTHOR]

An assessment of the detectability of white matter lesions and of concordance between observers with different levels of MRI reading experience was performed with comparative evaluation of spin-echo MRI images and of corresponding “multispectral”maps in 16 patients with definite multiple sclerosis (MS). Multispectral maps were obtained by means of a recently described post-processing technique based on the simultaneous display of MRI parameters and a standardized colour scale with red, green and blue coding for relaxation rates R1 and R2 and proton density, respectively. Spin-echo images on films and multispectral maps displayed on a personal computer were randomly rated at 2-month intervals. Interobserver concordance (k-test) was assessed among three readers with different levels of MRI experience (an experienced neuroradiologist, a radiology resident and a neurologist). For multispectral maps we found increased interobserver concordance with the experienced neuroradiologist (multispectral vs conventional images: k = 0.77 vs 0.66 for the radiology resident and 0.66 vs 0.56 for the neurologist), an increased number of detected lesions and decreased reading time. Multispectral maps permit easy detection of MS lesions and may improve interobserver concordance compared with conventional spin-echo studies. [ABSTRACT FROM AUTHOR]

It is still debated whether non-specific preclinical symptoms of Alzheimer's disease (AD) can have diagnostic relevance. We followed the evolution from cognitively normal to AD by NMR-based metabolomics of blood sera. Multivariate statistical analysis of the NMR profiles yielded models that discriminated subjective memory decline (SMD), mild cognitive impairment (MCI) and AD. We validated a panel of six statistically significant metabolites that predicted SMD, MCI and AD in a blind cohort with sensitivity values ranging from 88 to 95% and receiver operating characteristic values from 0.88 to 0.99. However, lower values of specificity, accuracy and precision were observed for the models involving SMD and MCI, which is in line with the pathological heterogeneity indicated by clinical data. This excludes a "linear" molecular evolution of the pathology, pointing to the presence of overlapping "gray-zones" due to the reciprocal interference of the intermediate stages. Yet, the clear difference observed in the metabolic pathways of each model suggests that pathway dysregulations could be investigated for diagnostic purposes. [ABSTRACT FROM AUTHOR]