Consensus-based technical recommendations for clinical translation of renal T1 and T2 mapping MRI

To develop technical recommendations on the acquisition and post-processing of renal longitudinal (T1) and transverse (T2) relaxation time mapping. A multidisciplinary panel consisting of 18 experts in the field of renal T1 and T2 mapping participated in a consensus project, which was initiated by the European Cooperation in Science and Technology Action PARENCHIMA CA16103. Consensus recommendations were formulated using a two-step modified Delphi method. The first survey consisted of 56 items on T1 mapping, of which 4 reached the pre-defined consensus threshold of 75% or higher. The second survey was expanded to include both T1 and T2 mapping, and consisted of 54 items of which 32 reached consensus. Recommendations based were formulated on hardware, patient preparation, acquisition, analysis and reporting. Consensus-based technical recommendations for renal T1 and T2 mapping were formulated. However, there was considerable lack of consensus for renal T1 and particularly renal T2 mapping, to some extent surprising considering the long history of relaxometry in MRI, highlighting key knowledge gaps that require further work. This paper should be regarded as a first step in a long-term evidence-based iterative process towards ever increasing harmonization of scan protocols across sites, to ultimately facilitate clinical implementation

Technical recommendations for clinical translation of renal MRI: a consensus project of the Cooperation in Science and Technology Action PARENCHIMA

Purpose The potential of renal MRI biomarkers has been increasingly recognised, but clinical translation requires more standardisation. The PARENCHIMA consensus project aims to develop and apply a process for generating technical recommendations on renal MRI. Methods A task force was formed in July 2018 focused on fve methods. A draft process for attaining consensus was distributed publicly for consultation and fnalised at an open meeting (Prague, October 2018). Four expert panels completed surveys between October 2018 and March 2019, discussed results and refned the surveys at a face-to-face meeting (Aarhus, March 2019) and completed a second round (May 2019). Results A seven-stage process was defned: (1) formation of expert panels; (2) defnition of the context of use; (3) literature review; (4) collection and comparison of MRI protocols; (5) consensus generation by an approximate Delphi method; (6) reporting of results in vendor-neutral and vendor-specifc terms; (7) ongoing review and updating. Application of the process resulted in 166 consensus statements. Conclusion The process generated meaningful technical recommendations across very diferent MRI methods, while allowing for improvement and refnement as open issues are resolved. The results are likely to be widely supported by the renal MRI community and thereby promote more harmonisation

Consensus-based technical recommendations for clinical translation of renal BOLD MRI.

Harmonization of acquisition and analysis protocols is an important step in the validation of BOLD MRI as a renal biomarker. This harmonization initiative provides technical recommendations based on a consensus report with the aim to move towards standardized protocols that facilitate clinical translation and comparison of data across sites. We used a recently published systematic review paper, which included a detailed summary of renal BOLD MRI technical parameters and areas of investigation in its supplementary material, as the starting point in developing the survey questionnaires for seeking consensus. Survey data were collected via the Delphi consensus process from 24 researchers on renal BOLD MRI exam preparation, data acquisition, data analysis, and interpretation. Consensus was defined as ≥ 75% unanimity in response. Among 31 survey questions, 14 achieved consensus resolution, 12 showed clear respondent preference (65-74% agreement), and 5 showed equal (50/50%) split in opinion among respondents. Recommendations for subject preparation, data acquisition, processing and reporting are given based on the survey results and review of the literature. These technical recommendations are aimed towards increased inter-site harmonization, a first step towards standardization of renal BOLD MRI protocols across sites. We expect this to be an iterative process updated dynamically based on progress in the field

Correction to: Consensus-based technical recommendations for clinical translation of renal diffusion-weighted MRI.

The article Consensus-based technical recommendations for clinical translation of renal diffusion-weighted MRI

Correction to: Consensus-based technical recommendations for clinical translation of renal diffusion-weighted MRI.

The article Consensus-based technical recommendations for clinical translation of renal diffusion-weighted MRI

Obesity, brain volume, and white matter microstructure at MRI: A cross-sectional UK biobank study

Background: Obesity has been associated with increased risk of accelerated cognitive decline and dementia, which suggests underlying neurobiological changes. Purpose: To investigate the associations between obesity and brain structure (overall and regional brain volumes, and white matter microstructure) assessed at MRI in a sample of the general population. Materials and Methods: Between March 2014 and January 2018, 12 087 participants (52.8% women [6381 of 12 087]; mean age, 62 years; age range, 45-76 years) in the prospective observational UK Biobank study underwent 3.0-T multiparametric (ie, three-dimensional T1-weighted diffusion tensor imaging [DTI]) brain imaging. Percentage of total body fat (TBF) was assessed by body impedance. Volumetric measures included brain volume, gray matter volume, white matter volume, volumes of subcortical gray matter structures, and regional cortical volumes. Global and tract-specific microstructure was assessed by fractional anisotropy (FA) and mean diffusivity (MD) by using DTI. Linear regression was performed by using TBF as determinant and brain measures as outcome variables, and effect estimates were expressed as standardized β values. Results: Mean body mass index was 26.6 kg/m2 ± 4.4 (standard deviation [SD]), mean TBF in men was 24.4% ± 5.5, and mean TBF in women was 35.5% ± 6.5. In men, TBF was negatively associated with all subcortical gray matter volumes (thalamus, caudate nucleus, putamen, globus pallidus, hippocampus, and nucleus accumbens) other than amygdala volume. In women, TBF was solely negatively associated with globus pallidus volume. In women and men, TBF was positively associated with global FA (women vs men, 0.05 vs 0.07 SD change in global FA per SD change in TBF; P <.001). TBF was negatively associated with global MD in women (-0.07 SD change in global MD per SD change in TBF; P <.001). Conclusion: These findings provide evidence that obesity is associated with smaller subcortical gray matter volumes. In addition, obesity was associated with higher coherence but lower magnitude of white matter microstructure, which suggests differential influences of obesity on the geometric organization of white matter microstructure

Erratum: Obesity, brain volume, and white matter microstructure at MRI: A cross-sectional UK biobank study (Radiology (2019) 291 (763-771) DOI: 10.1148/radiol.2019181012)

In an early online edition, Tables 3 and 4 were corrected to clarify that the two rows of data for Adjusted TBF (total body fat) pertained to Women and Men, respectively. This was corrected online and in print

Obesity, Brain Volume, and White Matter Microstructure at MRI: A Cross-sectional UK Biobank Study

Background Obesity has been associated with increased risk of accelerated cognitive decline and dementia, which suggests underlying neurobiological changes. Purpose To investigate the associations between obesity and brain structure (overall and regional brain volumes, and white matter microstructure) assessed at MRI in a sample of the general population. Materials and Methods Between March 2014 and January 2018, 12 087 participants (52.8% women [6381 of 12 087]; mean age, 62 years; age range, 45-76 years) in the prospective observational UK Biobank study underwent 3.0-T multiparametric (ie, three-dimensional T1-weighted diffusion tensor imaging [DTI]) brain imaging. Percentage of total body fat (TBF) was assessed by body impedance. Volumetric measures included brain volume, gray matter volume, white matter volume, volumes of subcortical gray matter structures, and regional cortical volumes. Global and tract-specific microstructure was assessed by fractional anisotropy (FA) and mean diffusivity (MD) by using DTI. Linear regression was performed by using TBF as determinant and brain measures as outcome variables, and effect estimates were expressed as standardized β values. Results Mean body mass index was 26.6 kg/m2 ± 4.4 (standard deviation [SD]), mean TBF in men was 24.4% ± 5.5, and mean TBF in women was 35.5% ± 6.5. In men, TBF was negatively associated with all subcortical gray matter volumes (thalamus, caudate nucleus, putamen, globus pallidus, hippocampus, and nucleus accumbens) other than amygdala volume. In women, TBF was solely negatively associated with globus pallidus volume. In women and men, TBF was positively associated with global FA (women vs men, 0.05 vs 0.07 SD change in global FA per SD change in TBF; P < .001). TBF was negatively associated with global MD in women (-0.07 SD change in global MD per SD change in TBF; P < .001). Conclusion These findings provide evidence that obesity is associated with smaller subcortical gray matter volumes. In addition, obesity was associated with higher coherence but lower magnitude of white matter microstructure, which suggests differential influences of obesity on the geometric organization of white matter microstructure

Obesity and the brain: structural and functional imaging studies, and opportunities for large-scale imaging genetics

Obesity has increasingly been recognized as a precursor of negative health outcomes including increased risk of dementia and accelerated cognitive decline. With the increase of sample sizes of population-based imaging studies, there is a growing level of evidence of changes in brain structure in obesity, such as brain atrophy and loss of white matter integrity. Functional imaging studies using positron emission tomography have highlighted the similarities between behavioral responses and dopaminergic pathways that regulate neuronal systems in both addiction and obesity. Functional magnetic resonance imaging studies have increasingly been applied to study the brain insulin sensitivity. Combining large-scale population-based imaging data with genotype data leads to new opportunities that enable the possibility to study brain differences in obesity and relate these to possible underlying genetic and molecular pathways. This chapter provides an overview of the existing literature of obesity in relation to the brain, and discusses findings and opportunities of imaging genetic studies to unravel underlying neurobiological pathways