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Methodological consensus on clinical proton MRS of the brain: Review and recommendations.

ABSTRACT: Proton MRS (1 H MRS) provides noninvasive, quantitative metabolite profiles of tissue and has been shown to aid the clinical management of several brain diseases. Although most modern clinical MR scanners support MRS capabilities, routine use is largely restricted to specialized centers with good access to MR research support. Widespread adoption has been slow for several reasons, and technical challenges toward obtaining reliable good-quality results have been identified as a contributing factor. Considerable progress has been made by the research community to address many of these challenges, and in this paper a consensus is presented on deficiencies in widely available MRS methodology and validated improvements that are currently in routine use at several clinical research institutions. In particular, the localization error for the PRESS localization sequence was found to be unacceptably high at 3 T, and use of the semi-adiabatic localization by adiabatic selective refocusing sequence is a recommended solution. Incorporation of simulated metabolite basis sets into analysis routines is recommended for reliably capturing the full spectral detail available from short TE acquisitions. In addition, the importance of achieving a highly homogenous static magnetic field (B0 ) in the acquisition region is emphasized, and the limitations of current methods and hardware are discussed. Most recommendations require only software improvements, greatly enhancing the capabilities of clinical MRS on existing hardware. Implementation of these recommendations should strengthen current clinical applications and advance progress toward developing and validating new MRS biomarkers for clinical use.

SUBMITTER: Wilson M

PROVIDER: S-EPMC7179569 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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Methodological consensus on clinical proton MRS of the brain: Review and recommendations.

Wilson Martin M Andronesi Ovidiu O Barker Peter B PB Bartha Robert R Bizzi Alberto A Bolan Patrick J PJ Brindle Kevin M KM Choi In-Young IY Cudalbu Cristina C Dydak Ulrike U Emir Uzay E UE Gonzalez Ramon G RG Gruber Stephan S Gruetter Rolf R Gupta Rakesh K RK Heerschap Arend A Henning Anke A Hetherington Hoby P HP Huppi Petra S PS Hurd Ralph E RE Kantarci Kejal K Kauppinen Risto A RA Klomp Dennis W J DWJ Kreis Roland R Kruiskamp Marijn J MJ Leach Martin O MO Lin Alexander P AP Luijten Peter R PR Marjańska Małgorzata M Maudsley Andrew A AA Meyerhoff Dieter J DJ Mountford Carolyn E CE Mullins Paul G PG Murdoch James B JB Nelson Sarah J SJ Noeske Ralph R Öz Gülin G Pan Julie W JW Peet Andrew C AC Poptani Harish H Posse Stefan S Ratai Eva-Maria EM Salibi Nouha N Scheenen Tom W J TWJ Smith Ian C P ICP Soher Brian J BJ Tkáč Ivan I Vigneron Daniel B DB Howe Franklyn A FA

Magnetic resonance in medicine 20190328 2

Proton MRS (<sup>1</sup> H MRS) provides noninvasive, quantitative metabolite profiles of tissue and has been shown to aid the clinical management of several brain diseases. Although most modern clinical MR scanners support MRS capabilities, routine use is largely restricted to specialized centers with good access to MR research support. Widespread adoption has been slow for several reasons, and technical challenges toward obtaining reliable good-quality results have been identified as a contrib ...[more]

PMID: 30919510

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Project description:BackgroundHealth economic evaluation of digital nursing technologies (DNT) is important to provide information that helps avoid undesirable developments and implementations as well as increase the chances of success of developed applications. At the same time, studies and evidence on cost-effectiveness are still very rare in this field. Review studies in related technology areas such as telemedicine frequently criticise the quality and comparability of health economic evaluations conducted in this field. Based on a content analysis of methodological literature on the economic evaluation of innovative (digital) technologies in health and nursing, this article aims to identify specific challenges in this research area and offers recommendations on how to address these challenges to promote more sound health economic evaluations in the future.MethodsA rapid review was conducted, consisting of a systematic search in the Pubmed database as well as Google Scholar. In addition, the literature lists of the analysed texts were scoured for additional texts to be included. Methodological literature, single studies, and reviews were included. A total of 536 studies were screened, of which 29 were included in the full text analysis.ResultsBased on the systematic content analysis of the studies under consideration, 10 specific methodological challenges are identified, and the methodological recommendations were examined for consideration. A particular focus was given to whether specific methodological approaches might be needed in the context of evaluating the efficiency of DNT.ConclusionMany of the challenges identified for the health economic evaluations of digital nursing technologies are comparable to those of other complex health care interventions. The recommendations discussed can help to alleviate those challenges. Future research should focus on alternative approaches to assessing causality in different phases of technology development while maintaining high evidence standards. High-evidence economic assessment of technologies in nursing care should be carried out in routine use, especially if they are intended to be reimbursed by the social insurance.

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Dataset Information

Methodological consensus on clinical proton MRS of the brain: Review and recommendations.

Publications

Methodological consensus on clinical proton MRS of the brain: Review and recommendations.

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