Simultaneous adaptive smoothing of relaxometry and quantitative magnetization transfer mapping

Attempts for in-vivo histology require a high spatial resolution that comes with the price of a decreased signal-to-noise ratio. We present a novel iterative and multi-scale smoothing method for quantitative Magnetic Resonance Imaging (MRI) data that yield proton density, apparent transverse and longitudinal relaxation, and magnetization transfer maps. The method is based on the propagation-separation approach. The adaptivity of the procedure avoids the inherent bias from blurring subtle features in the calculated maps that is common for non-adaptive smoothing approaches. The characteristics of the methods were evaluated on a high-resolution data set (500 μ isotropic) from a single subject and quantified on data from a multi-subject study. The results show that the adaptive method is able to increase the signal-to-noise ratio in the calculated quantitative maps while largely avoiding the bias that is otherwise introduced by spatially blurring values across tissue borders. As a consequence, it preserves the intensity contrast between white and gray matter and the thin cortical ribbon

The Influence of Radio-Frequency Transmit Field Inhomogeneities on the Accuracy of G-ratio Weighted Imaging

G-ratio weighted imaging is a non-invasive, in-vivo MRI-based technique that aims at estimating an aggregated measure of relative myelination of axons across the entire brain white matter. The MR g-ratio and its constituents (axonal and myelin volume fraction) are more specific to the tissue microstructure than conventional MRI metrics targeting either the myelin or axonal compartment. To calculate the MR g-ratio, an MRI-based myelin-mapping technique is combined with an axon-sensitive MR technique (such as diffusion MRI). Correction for radio-frequency transmit (B1+) field inhomogeneities is crucial for myelin mapping techniques such as magnetization transfer saturation. Here we assessed the effect of B1+ correction on g-ratio weighted imaging. To this end, the B1+ field was measured and the B1+ corrected MR g-ratio was used as the reference in a Bland-Altman analysis. We found a substantial bias (≈-89%) and error (≈37%) relative to the dynamic range of g-ratio values in the white matter if the B1+ correction was not applied. Moreover, we tested the efficiency of a data-driven B1+ correction approach that was applied retrospectively without additional reference measurements. We found that it reduced the bias and error in the MR g-ratio by a factor of three. The data-driven correction is readily available in the open-source hMRI toolbox (www.hmri.info) which is embedded in the statistical parameter mapping (SPM) framework

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

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

Dysfunctional Activation of the Dorsolateral Prefrontal Cortex During Pain Anticipation Is Associated With Altered Subsequent Pain Experience in Fibromyalgia Patients

The ability to accurately predict pain is an adaptive feature in healthy individuals. However, in chronic pain, this mechanism may be selectively impaired and can lead to increased anxiety and excessive avoidance behavior. Recently, we reported the first data demonstrating brain activation in fibromyalgia (FM) patients during conditioned pain responses, in which FM patients revealed a tendency to form new pain-related associations rather than extinguishing irrelevant ones. The aim of the present study was to extend our previous analysis, to elucidate potential neural divergences between subjects with FM (n = 65) and healthy controls (HCs) (n = 33) during anticipatory information (ie, prior to painful stimulus onset). Using functional magnetic resonance imaging (fMRI), the current analyses include 1) a congruently cued paradigm of low and high pain predictive cues, followed by 2) an incongruently cued paradigm where low and high pain predictive cues were followed by an identical mid-intensity painful pressure. During incongruently cued high-pain associations, FM exhibited reduced left dorsolateral prefrontal cortex (dlPFC) activation compared to HCs, which was followed by an altered subsequent pain experience in FM, as patients continued to rate the following painful stimuli as high, even though the pressure had been lowered. During congruently cued low pain anticipation, FM exhibited decreased right dlPFC activation compared to HCs, as well as decreased brain connectivity between brain regions implicated in cognitive modulation of pain (dlPFC) and nociceptive processing (primary somatosensory cortex/postcentral gyrus [S1] and supplementary motor area [SMA]/midcingulate cortex [MCC]). These results may reflect an important feature of validating low pain expectations in HCs and help elucidate behavioral reports of impaired safety processing in FM patients. PERSPECTIVE: FM exhibited a stronger conditioned pain response for high-pain associations, which was associated with reduced dlPFC activation during the incongruent trial. During (congruent and incongruent) low pain associations, FM dlPFC brain activation remained indifferent. Imbalances in threat and safety pain perception may be an important target for psychotherapeutic interventions

Distinct aberrations in cerebral pain processing differentiating patients with fibromyalgia from patients with rheumatoid arthritis

The current study used functional magnetic resonance imaging to directly compare disease-relevant cerebral pain processing in well-characterized patient cohorts of fibromyalgia (FM, nociplastic pain) and rheumatoid arthritis (RA, nociceptive pain). Secondary aims were to identify pain-related cerebral alterations related to the severity of clinical symptoms such as pain intensity, depression, and anxiety. Twenty-six patients with FM (without RA-comorbidity) and 31 patients with RA (without FM-comorbidity) underwent functional magnetic resonance imaging while stimulated with subjectively calibrated painful pressures corresponding to a pain sensation of 50 mm on a 100-mm visual analogue scale. Stimulation sites were at the most inflamed proximal interphalangeal joint in the left hand in patients with RA and the left thumbnail in patients with FM, 2 sites that have previously been shown to yield the same brain activation in healthy controls. The current results revealed disease-distinct differences during pain modulation in RA and FM. Specifically, in response to painful stimulation, patients with FM compared to patients with RA exhibited increased brain activation in bilateral inferior parietal lobe (IPL), left inferior frontal gyrus (IFG)/ventrolateral prefrontal cortex (vlPFC) encapsulating left dorsolateral prefrontal cortex, and right IFG/vlPFC. However, patients with RA compared to patients with FM exhibited increased functional connectivity (during painful stimulation) between right and left IPL and sensorimotor network and between left IPL and frontoparietal network. Within the FM group only, anxiety scores positively correlated with pain-related brain activation in left dorsolateral prefrontal cortex and right IFG/vlPFC, which further highlights the complex interaction between affective (ie, anxiety scores) and sensory (ie, cerebral pain processing) dimensions in this patient group

Polymorphisms of the μ-opioid receptor gene influence cerebral pain processing in fibromyalgia

Background: Dysregulation of the μ-opioid receptor has been reported in fibromyalgia (FM) and was linked to pain severity. Here, we investigated the effect of the functional genetic polymorphism of the μ-opioid receptor gene (OPRM1) (rs1799971) on symptom severity, pain sensitivity and cerebral pain processing in FM subjects and healthy controls (HC). Methods: Symptom severity and pressure pain sensitivity was assessed in FM subjects (n = 70) and HC (n = 35). Cerebral pain-related activation was assessed by functional magnetic resonance imaging during individually calibrated painful pressure stimuli. Results: Fibromyalgia subjects were more pain sensitive but no significant differences in pain sensitivity or pain ratings were observed between OPRM1 genotypes. A significant difference was found in cerebral pain processing, with carriers of at least one G-allele showing increased activation in posterior cingulate cortex (PCC) extending to precentral gyrus, compared to AA homozygotes. This effect was significant in FM subjects but not in healthy participants, however, between-group comparisons did not yield significant results. Seed-based functional connectivity analysis was performed with the seed based on differences in PCC/precentral gyrus activation between OPRM1 genotypes during evoked pain across groups. G-allele carriers displayed decreased functional connectivity between PCC/precentral gyrus and prefrontal cortex. Conclusions: G-allele carriers showed increased activation in PCC/precentral gyrus but decreased functional connectivity with the frontal control network during pressure stimulation, suggesting different pain modulatory processes between OPRM1 genotypes involving altered fronto-parietal network involvement. Furthermore, our results suggest that the overall effects of the OPRM1 G-allele may be driven by FM subjects. Significance: We show that the functional polymorphism of the μ-opioid receptor gene OPRM1 was associated with alterations in the fronto-parietal network as well as with increased activation of posterior cingulum during evoked pain in FM. Thus, the OPRM1 polymorphism affects cerebral processing in brain regions implicated in salience, attention, and the default mode network. This finding is discussed in the light of pain and the opioid system, providing further evidence for a functional role of OPRM1 in cerebral pain processing

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

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

Simultaneous adaptive smoothing of relaxometry and quantitative magnetization transfer mapping

Attempts for in-vivo histology require a high spatial resolution that comes with the price of a decreased signal-to-noise ratio. We present a novel iterative and multi-scale smoothing method for quantitative Magnetic Resonance Imaging (MRI) data that yield proton density, apparent transverse and longitudinal relaxation, and magnetization transfer maps. The method is based on the propagation-separation approach. The adaptivity of the procedure avoids the inherent bias from blurring subtle features in the calculated maps that is common for non-adaptive smoothing approaches. The characteristics of the methods were evaluated on a high-resolution data set (500 mym isotropic) from a single subject and quantified on data from a multi-subject study. The results show that the adaptive method is able to increase the signal-to-noise ratio in the calculated quantitative maps while largely avoiding the bias that is otherwise introduced by spatially blurring values across tissue borders. As a consequence, it preserves the intensity contrast between white and gray matter and the thin cortical ribbon

The translocator protein gene is associated with endogenous pain modulation and the balance between glutamate and gamma-aminobutyric acid in fibromyalgia and healthy subjects : a multimodal neuroimaging study

A cerebral upregulation of the translocator protein (TSPO), a biomarker of glial activation, has been reported in fibromyalgia subjects (FMS). The TSPO binding affinity is genetically regulated by the Ala147Thr polymorphism in the TSPO gene (rs6971) and allows for a subject classification into high affinity binders (HABs) and mixed/low affinity binders (MLABs). The aim of the present multimodal neuroimaging study was to examine the associations of the TSPO polymorphism with: (1) conditioned pain modulation, (2) expectancy-modulated pain processing assessed during functional magnetic resonance imaging, and (3) the concentration and balance of glutamate and gamma-aminobutyric acid in the rostral anterior cingulate cortex and thalamus using proton magnetic resonance spectroscopy in FMS (n = 83) and healthy controls (n = 43). The influence of TSPO on endogenous pain modulation presented in the form of TSPO HABs, as opposed to MLABs, displaying less efficient descending pain inhibition and expectancy-induced reduction of pain. Translocator protein HABs in both groups (FM and healthy controls) were found to have higher thalamic glutamate concentrations and exhibit a pattern of positive correlations between glutamate and gamma-aminobutyric acid in the rostral anterior cingulate cortex, not seen in MLABs. Altogether, our findings point to TSPO-related mechanisms being HAB-dependent, brain region-specific, and non-FM-specific, although in FMS the disadvantage of an aberrant pain regulation combined with an HAB genetic set-up might hamper pain modulation more strongly. Our results provide evidence for an important role of TSPO in pain regulation and brain metabolism, thereby supporting the ongoing drug development targeting TSPO-associated mechanisms for pain relief