[Magnetic resonance imaging spectroscopy. Part 1: Basics]

Image-based state-of-the-art techniques for the identification and classification of brain diseases: a review

Detection and classification methods have a vital and important role in identifying brain diseases. Timely detection and classification of brain diseases enable an accurate identification and effective management of brain impairment. Brain disorders are commonly most spreadable diseases and the diagnosing process is time-consuming and highly expensive. There is an utmost need to develop effective and advantageous methods for brain diseases detection and characterization. Magnetic resonance imaging (MRI), computed tomography (CT), and other various brain imaging scans are used to identify different brain diseases and disorders. Brain imaging scans are the efficient tool to understand the anatomical changes in brain in fast and accurate manner. These different brain imaging scans used with segmentation techniques and along with machine learning and deep learning techniques give maximum accuracy and efficiency. This paper focuses on different conventional approaches, machine learning and deep learning techniques used for the detection, and classification of brain diseases and abnormalities. This paper also summarizes the research gap and problems in the existing techniques used for detection and classification of brain disorders. Comparison and evaluation of different machine learning and deep learning techniques in terms of efficiency and accuracy are also highlighted in this paper. Furthermore, different brain diseases like leukoariaosis, Alzheimer's, Parkinson's, and Wilson's disorder are studied in the scope of machine learning and deep learning techniques.

Residue analysis of a synthetic glucocorticoid in liver samples by a 1HMR spectroscopy approach: An exploratory study on animal model

Betamethasone is a glucocorticoid authorised in cattle for the treatment of metabolic and inflammatory diseases, but, in Europe, it is illegally employed to improve productive performances. LC-MS/MS is the official control method of veterinary drugs residues in food of animal origin. An experimental study was developed to evaluate the feasibility of proton magnetic resonance spectroscopy (1H-MRS) as a potential alternative approach to detect the presence of betamethasone residues. Eight rat liver samples were collected 24 h post-betamethasone-treatment from experimental and control animals and were analysed by 1H-MRS using a 7-Tesla MRI scanner. 1H-MR reference spectra both of the Bentelan formulation used for treatment, and of three solutions of betamethasone in dimethyl sulphoxide (DMSO) at 5, 10 and 100 mM, respectively, were acquired to fit analyte-peaks in the liver samples spectra. Betamethasone-peaks were found only in the 100 mM betamethasone in DMSO solution spectrum. Betamethasone residues were not detected in any of the tissue samples analysed, probably related to the low concentration of injected drug. These findings allow us to establish, for the first time in the literature, the detection limit (in the range 10-100 mM) of betamethasone for the 7-Tesla MRI scanner used here. Given this very-low sensitivity, we conclude that the evaluated 1H-MR spectroscopy approach is not suitable for the detection of betamethasone residues in edible tissues, since the maximum residue limit imposed by Commission Regulation (EC) 37/2010 for betamethasone in the liver, and metabolic concentrations required to be detected in animal samples from livestock, are far below the detection limit we found.

[Technique of proton and phosphorous MR spectroscopy]

CLINICAL/METHODICAL ISSUE

Magnetic resonance spectroscopy (MRS) is an important non-invasive method that can reveal the concentration and spatial distribution of particular biochemically relevant tissue metabolites.

STANDARD RADIOLOGICAL METHODS

Proton MRS is routinely applicable in the clinical setting providing good quality results even with a moderate magnetic field strength of 1.5 T. Relative values of metabolite concentrations are mostly used for the assessment of metabolic disorders.

METHODICAL INNOVATIONS

Absolute quantification of metabolites can be achieved by means of internal or external reference scans. Phosphorous MRS extends the range of detectable molecules to energy and cell membrane metabolism.

PERFORMANCE

The lower detection limit of metabolite concentrations is in the range of some mmol/kg. Depending on the magnetic field strength, MRS enables a spatial resolution of a few milliliters.

ACHIEVEMENTS

The use of phosphorous MRS is considerably limited because higher field strengths of at least 3.0 T and additional expensive hardware for signal processing are required.

Basic Principles and Clinical Applications of Magnetic Resonance Spectroscopy in Neuroradiology

Magnetic resonance spectroscopy is a powerful tool to assist daily clinical diagnostics. This review is intended to give an overview on basic principles of the technology, discuss some of its technical aspects, and present typical applications in daily clinical routine in neuroradiology.

[Basic principles of MR spectroscopy]

MR spectroscopy (MRS) is a non-invasive method for investigating tissue metabolism. In the clinical setting proton spectroscopy based on the hydrogen nucleus ((1)H) is primarily used for determining concentrations of important brain metabolites. This paper illustrates the physicochemical principles of MRS and the requirements for high quality spectra. Moreover, different techniques for acquiring localized spectra are demonstrated.

[Hyperfine structure analysis in magnetic resonance spectroscopy: from astrophysical measurements towards endogenous biosensors in human tissue]

The hyperfine interaction of two spins is a well studied effect in atomic systems. Magnetic resonance experiments demonstrate that the detectable dipole transitions are determined by the magnetic moments of the constituents and the external magnetic field. Transferring the corresponding quantum mechanics to molecular bound nuclear spins allows for precise prediction of NMR spectra obtained from metabolites in human tissue. This molecular hyperfine structure has been neglected so far in in vivo NMR spectroscopy but contains useful information, especially when studying molecular dynamics. This contribution represents a review of the concept of applying the Breit-Rabi formalism to coupled nuclear spins and discusses the immobilization of different metabolites in anisotropic tissue revealed by 1H NMR spectra of carnosine, phosphocreatine and taurine. Comparison of atomic and molecular spin systems allows for statements on the biological constraints for direct spin-spin interactions. Moreover, the relevance of hyperfine effects on the line shapes of multiplets of indirectly-coupled spin systems with more than two constituents can be predicted by analyzing quantum mechanical parameters. As an example, the superposition of eigenstates of the A MX system of adenosine 5'-triphosphate and its application for better quantification of 31P-NMR spectra will be discussed.

Applications of MRS in the evaluation of focal malignant brain lesions

Magnetic resonance spectroscopy (MRS) has clinically been most extensively used for assessing brain disorders, particularly tumors. With 1-H spectroscopy at intermediate echo times, resonances from choline, creatine, N-acetyl-aspartate (NAA), lactate, and free fatty acids can be resolved well enough to assist in diagnosis under routine conditions. Generally, an increased concentration of choline is found in all primary and secondary brain tumors, and the degree of increase correlates with the degree of anaplasia. Further indicators of anaplasia are the presence of lactate, indicating hypoxia, and of fatty acids, indicating necrosis. According to literature, the sensitivity of a combination of proton spectroscopy with contrast-enhanced dynamic susceptibility-weighted imaging for high-grade components in gliomas is better than conventional contrast-enhanced imaging alone. Today, proton spectroscopy is clearly indicated for differentiating radiation-induced damage from recurrences of irradiated brain tumors.