P Tofts. Chichester: John Wiley & Sons, 2003, pp 617, £175.00. ISBN 0-470-84721-2

We have waited for a long time for a comprehensive book on magnetic resonance (MR) techniques that will appeal to the neurologist/neuroradiologist as well as the physicist and researcher. A book that is right up to date and is relevant across the board for all who are interested in the technique and that deals with quantification.

Paul Tofts has produced a book that is in the coffee table style, in the best sense of …

https://jnnp.bmj.com/content/jnnp/75/10/1511.1.full.pdf

Quantitative MRI of the brain—measuring changes caused by disease

https://repository.kulib.kyoto-u.ac.jp/dspace/bitstream/2433/253174/1/yigak04579.pdf

Neurite imaging reveals microstructural variations in human cerebral cortical gray matter.

https://serval.unil.ch/resource/serval:BIB_2202C51D02B1.P001/REF.pdf

hMRI – A toolbox for quantitative MRI in neuroscience and clinical research

Resting-state functional magnetic resonance imaging (RS-fMRI) has demonstrated disrupted default mode network (DMN) connectivity in a number of pain conditions, including migraine. However, the significance of altered resting-state brain functional connectivity in migraine is still unknown. The present study is aimed to explore DMN functional connectivity in patients with migraine without aura (MwoA) and investigate its clinical significance. To calculate and compare the resting-state functional connectivity of the DMN in 20 patients with MwoA, during the interictal period, and 20 gender- and age-matched HC, Brain Voyager QX was used. Voxel-based morphometry was used to assess whether between-group differences in DMN functional connectivity were related to structural differences. Secondary analyses explored associations between DMN functional connectivity, clinical and neuropsychological features of migraineurs. In comparison to HC, patients with MwoA showed decreased connectivity in prefrontal and temporal regions of the DMN. Functional abnormalities were unrelated to detectable structural abnormalities or clinical and neuropsychological features of migraineurs. Our study provides further evidence of disrupted DMN connectivity in patients with MwoA. We hypothesize that a DMN dysfunction may be related to behavioural processes such as a maladaptive response to stress which seems to characterize patients with migraine.

/pdf/disrupted-default-mode-network-connectivity-in-migraine-331nmo4hig.pdf

Disrupted default mode network connectivity in migraine without aura

Microstructural imaging of human neocortex in vivo.

The NODDI-DTI signal model is a modification of the NODDI signal model that formally allows interpretation of standard single-shell DTI data in terms of biophysical parameters in healthy human white matter (WM). The NODDI-DTI signal model contains no CSF compartment, restricting application to voxels without CSF partial-volume contamination. This modification allowed derivation of analytical relations between parameters representing axon density and dispersion, and DTI invariants (MD and FA) from the NODDI-DTI signal model. These relations formally allow extraction of biophysical parameters from DTI data. NODDI-DTI parameters were estimated by applying the proposed analytical relations to DTI parameters estimated from the first shell of data, and compared to parameters estimated by fitting the NODDI-DTI model to both shells of data (reference dataset) in the WM of 14 in vivo diffusion datasets recorded with two different protocols, and in simulated data. The first two datasets were also fit to the NODDI-DTI model using only the first shell (as for DTI) of data. NODDI-DTI parameters estimated from DTI, and NODDI-DTI parameters estimated by fitting the model to the first shell of data gave similar errors compared to two-shell NODDI-DTI estimates. The simulations showed the NODDI-DTI method to be more noise-robust than the two-shell fitting procedure. The NODDI-DTI method gave unphysical parameter estimates in a small percentage of voxels, reflecting voxelwise DTI estimation error or NODDI-DTI model invalidity. In the course of evaluating the NODDI-DTI model, it was found that diffusional kurtosis strongly biased DTI-based MD values, and so, making assumptions based on healthy WM, a novel heuristic correction requiring only DTI data was derived and used to mitigate this bias. Since validations were only performed on healthy WM, application to grey matter or pathological WM would require further validation. Our results demonstrate NODDI-DTI to be a promising model and technique to interpret restricted datasets acquired for DTI analysis in healthy white matter with greater biophysical specificity, though its limitations must be borne in mind.

/pdf/noddi-dti-estimating-neurite-orientation-and-dispersion-bi206mv4zl.pdf

NODDI-DTI: Estimating Neurite Orientation and Dispersion Parameters from a Diffusion Tensor in Healthy White Matter.

A recent method, denoted in vivo g-ratio-weighted imaging, has related the microscopic g-ratio, only accessible by ex vivo histology, to noninvasive MRI markers for the fiber volume fraction (FVF) and myelin volume fraction (MVF). Different MRI markers have been proposed for g-ratio weighted imaging, leaving open the question which combination of imaging markers is optimal. To address this question, the repeatability and comparability of four g-ratio methods based on different combinations of, respectively, two imaging markers for FVF (tract-fiber density, TFD, and neurite orientation dispersion and density imaging, NODDI) and two imaging markers for MVF (magnetization transfer saturation rate, MT, and, from proton density maps, macromolecular tissue volume, MTV) were tested in a scan-rescan experiment in two groups. Moreover, it was tested how the repeatability and comparability were affected by two key processing steps, namely the masking of unreliable voxels (e.g., due to partial volume effects) at the group level and the calibration value used to link MRI markers to MVF (and FVF). Our data showed that repeatability and comparability depend largely on the marker for the FVF (NODDI outperformed TFD), and that they were improved by masking. Overall, the g-ratio method based on NODDI and MT showed the highest repeatability (90%) and lowest variability between groups (3.5%). Finally, our results indicate that the calibration procedure is crucial, for example, calibration to a lower g-ratio value (g = 0.6) than the commonly used one (g = 0.7) can change not only repeatability and comparability but also the reported dependency on the FVF imaging marker. Hum Brain Mapp 39:24-41, 2018. © 2017 Wiley Periodicals, Inc.

/pdf/four-in-vivo-g-ratio-weighted-imaging-methods-comparability-silitz1f9o.pdf

Four in vivo g‐ratio‐weighted imaging methods: Comparability and repeatability at the group level

Purpose of reviewThe objective of this review is to give an overview of recent advances regarding structural changes and altered neural connectivity associated with chronic headache syndromes, focusing on migraine.Recent findingsIn conjunction with a recent boost of studies investigating exercise de

Microstructural and network abnormalities in headache.

In the past, nocebo manipulations have been found to modulate pain perception and influence long-term habituation to pain. Recently, neural correlates accompanying this finding have been identified: habituation over days is mirrored by decreased activity in pain-processing brain areas, whereas nocebo-specific modulation specifically involves the opercular cortex. Focusing on duration and central network characteristics of nocebo information in a longitudinal heat pain paradigm, we investigated 40 healthy participants over a period of 21 consecutive days, whereof sessions on days 1, 8, 14, and 21 were performed during functional magnetic resonance imaging scanning. Negative context information was given to half of the participants, inducing a nocebo manipulation through verbal suggestions. The analysis was focused on brain areas associated with habituation and nocebo effects and identified coupled brain regions using functional connectivity analysis. Decreased pain perception over days was reflected in reduced blood oxygenation level dependent signal in pain-processing areas, such as the insula and somatosensory cortices, whereas increased rostral anterior cingulate cortex activation reflected the central correlate for habituation over time. Habituation was significantly less pronounced in the nocebo group. Consistent with previous results, the nocebo manipulation not only modulated pain perception but also was accompanied by the activation of the operculum over an extended period of time. Importantly, the operculum exhibited changes in coupling during nociceptive input over time, as demonstrated by decreased connectivity with the basal ganglia and pinpoints differences, depending on whether a nocebo context was given. These data suggest that negative verbal suggestions prognosticating increasing pain may prevail by modulating basal ganglia–thalamocortical loops.

Nocebo context modulates long-term habituation to heat pain and influences functional connectivity of the operculum.

Functional brain networks and the perception of pain can fluctuate over time. However, how the time-dependent reconfiguration of functional brain networks contributes to chronic pain remains largely unexplained. Here, we explored time-varying changes in brain network integration and segregation during pain over a disease-affected area (joint) compared to a neutral site (thumbnail) in 28 patients with rheumatoid arthritis (RA) in comparison with 22 healthy controls (HC). During functional magnetic resonance imaging, all subjects received individually calibrated pain pressures corresponding to visual analog scale 50 mm at joint and thumbnail. We implemented a novel approach to track changes of task-based network connectivity over time. Within this framework, we quantified measures of integration (participation coefficient, PC) and segregation (within-module degree z-score). Using these network measures at multiple spatial scales, both at the level of single nodes (brain regions) and communities (clusters of nodes), we found that PC at the community level was generally higher in RA patients compared to HC during and after painful pressure over the inflamed joint and corresponding site in HC. This shows that all brain communities integrate more in RA patients than in HC for time points following painful stimulation to a disease-relevant body site. However, the elevated community-related integration seen in patients appeared to not pertain uniquely to painful stimulation at the inflamed joint, but also at the neutral thumbnail, as integration and segregation at the community level did not differ across body sites in patients. Moreover, there was no specific nodal contribution to brain network integration or segregation. Altogether, our findings indicate widespread and persistent changes in network interaction in RA patients compared to HC in response to painful stimulation.

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Isabel Ellerbrock

Papers

NODDI-DTI: Estimating Neurite Orientation and Dispersion Parameters from a Diffusion Tensor in Healthy White Matter.

Four in vivo g‐ratio‐weighted imaging methods: Comparability and repeatability at the group level

Microstructural and network abnormalities in headache.

Nocebo context modulates long-term habituation to heat pain and influences functional connectivity of the operculum.

Multiple spatial scale mapping of time-resolved brain network reconfiguration during evoked pain in patients with rheumatoid arthritis