Open Access

Increasing evidence about the central nervous representation of pain in the brain suggests that the operculo-insular cortex is a crucial part of the pain matrix. The pain-specificity of a brain region may be tested by administering nociceptive stimuli while controlling for unspecific activations by administering non-nociceptive stimuli. We applied this paradigm to nasal chemosensation, delivering trigeminal or olfactory stimuli, to verify the pain-specificity of the operculo-insular cortex. In detail, brain activations due to intranasal stimulation induced by non-nociceptive olfactory stimuli of hydrogen sulfide (5 ppm) or vanillin (0.8 ppm) were used to mask brain activations due to somatosensory, clearly nociceptive trigeminal stimulations with gaseous carbon dioxide (75% v/v). Functional magnetic resonance (fMRI) images were recorded from 12 healthy volunteers in a 3T head scanner during stimulus administration using an event-related design. We found that significantly more activations following nociceptive than non-nociceptive stimuli were localized bilaterally in two restricted clusters in the brain containing the primary and secondary somatosensory areas and the insular cortices consistent with the operculo-insular cortex. However, these activations completely disappeared when eliminating activations associated with the administration of olfactory stimuli, which were small but measurable. While the present experiments verify that the operculo-insular cortex plays a role in the processing of nociceptive input, they also show that it is not a pain-exclusive brain region and allow, in the experimental context, for the interpretation that the operculo-insular cortex splay a major role in the detection of and responding to salient events, whether or not these events are nociceptive or painful.

Purpose: To investigate cortical thickness and cortical quantitative T2 values as imaging markers of microstructural tissue damage in patients with unilateral high-grade internal carotid artery occlusive disease (ICAOD). Methods: A total of 22 patients with ≥70% stenosis (mean age 64.8 years) and 20 older healthy control subjects (mean age 70.8 years) underwent structural magnetic resonance imaging (MRI) and high-resolution quantitative (q)T2 mapping. Generalized linear mixed models (GLMM) controlling for age and white matter lesion volume were employed to investigate the effect of ICAOD on imaging parameters of cortical microstructural integrity in multivariate analyses. Results: There was a significant main effect (p < 0.05) of the group (patients/controls) on both cortical thickness and cortical qT2 values with cortical thinning and increased cortical qT2 in patients compared to controls, irrespective of the hemisphere. The presence of upstream carotid stenosis had a significant main effect on cortical qT2 values (p = 0.01) leading to increased qT2 in the poststenotic hemisphere, which was not found for cortical thickness. The GLMM showed that in general cortical thickness was decreased and cortical qT2 values were increased with increasing age (p < 0.05). Conclusion: Unilateral high-grade carotid occlusive disease is associated with widespread cortical thinning and prolongation of cortical qT2, presumably reflecting hypoperfusion-related microstructural cortical damage similar to accelerated aging of the cerebral cortex. Cortical thinning and increase of cortical qT2 seem to reflect different aspects and different pathophysiological states of cortical degeneration. Quantitative T2 mapping might be a sensitive imaging biomarker for early cortical microstructural damage.

Oxygenation-sensitive spin relaxation time T2′ and relaxation rate R2′ (1/T2′) are presumed to be markers of the cerebral oxygen extraction fraction (OEF) in acute ischemic stroke. In this study, we investigate the relationship of T2′/R2′ with dynamic susceptibility contrast-based relative cerebral blood flow (rCBF) in acute ischemic stroke to assess their plausibility as surrogate markers of the ischemic penumbra. Twenty-one consecutive patients with internal carotid artery and/or middle cerebral artery occlusion were studied at 3.0 T. A physiological model of the cerebral vasculature (VM) was used to process PWI raw data in addition to a conventional deconvolution technique. T2′, R2′, and rCBF values were extracted from the ischemic core and hypoperfused areas. Within hypoperfused tissue, no correlation was found between deconvolved rCBF and T2′ (r = −0.05, p = 0.788), or R2′ (r = 0.039, p = 0.836). In contrast, we found a strong positive correlation with T2′ (r = 0.444, p = 0.006) and negative correlation with R2′ (r = −0.494, p = 0.0025) for rCBFVM, indicating increasing OEF with decreasing CBF and that rCBF based on the vascular model may be more closely related to metabolic disturbances. Further research to refine and validate these techniques may enable their use as MRI-based surrogate markers of the ischemic penumbra for selecting stroke patients for interventional treatment strategies.

Highlights • Increased values in SVD, suggesting reduced oxygen extraction fraction (OEF). • Vascular dysfunction and microstructural impairment limit OEF capacity. • Association between prolonged and more alkaline intracellular pH. • Adaptation of intracellular energy metabolism compensates for reduced OEF. Abstract Background: We aimed to investigate whether combined phosphorous (31P) magnetic resonance spectroscopic imaging (MRSI) and quantitative T′2 mapping are able to detect alterations of the cerebral oxygen extraction fraction (OEF) and intracellular pH (pHi) as markers the of cellular energy metabolism in cerebral small vessel disease (SVD). Materials and methods: 32 patients with SVD and 17 age-matched healthy control subjects were examined with 3-dimensional 31P MRSI and oxygenation-sensitive quantitative T′2 mapping (1/T′2 = 1/T2* - 1/T2) at 3 Tesla (T). PHi was measured within the white matter hyperintensities (WMH) in SVD patients. Quantitative T′2 values were averaged across the entire white matter (WM). Furthermore, T′2 values were extracted from normal-appearing WM (NAWM) and the WMH and compared between patients and controls. Results: Quantitative T′2 values were significantly increased across the entire WM and in the NAWM in patients compared to control subjects (149.51 ± 16.94 vs. 138.19 ± 12.66 ms and 147.45 ± 18.14 vs. 137.99 ± 12.19 ms, p < 0.05). WM T′2 values correlated significantly with the WMH load (ρ=0.441, p = 0.006). Increased T′2 was significantly associated with more alkaline pHi (ρ=0.299, p < 0.05). Both T′2 and pHi were significantly positively correlated with vascular pulsatility in the distal carotid arteries (ρ=0.596, p = 0.001 and ρ=0.452, p = 0.016). Conclusions: This exploratory study found evidence of impaired cerebral OEF in SVD, which is associated with intracellular alkalosis as an adaptive mechanism. The employed techniques provide new insights into the pathophysiology of SVD with regard to disease-related consequences on the cellular metabolic state.

Highlights • The goal was to assess the intra- and inter-scanner reproducibility of qMRI data. • Mean scan-rescan variations were not exceeding 2.14%. • Mean inter-scanner model deviations were not exceeding 5.21%. • Provided that identical acquisition sequences are used, discrepancies between qMRI data acquired with different scanner models are low. Abstract Background: Quantitative MRI (qMRI) techniques allow assessing cerebral tissue properties. However, previous studies on the accuracy of quantitative T1 and T2 mapping reported a scanner model bias of up to 10% for T1 and up to 23% for T2. Such differences would render multi-centre qMRI studies difficult and raise fundamental questions about the general precision of qMRI. A problem in previous studies was that different methods were used for qMRI parameter mapping or for measuring the transmitted radio frequency field B1 which is critical for qMRI techniques requiring corrections for B1 non-uniformities. Aims: The goal was to assess the intra- and inter-scanner reproducibility of qMRI data at 3 ​T, using two different scanner models from the same vendor with exactly the same multiparametric acquisition protocol. Methods: Proton density (PD), T1, T2* and T2 mapping was performed on healthy subjects and on a phantom, performing each measurement twice for each of two scanner models. Although the scanners had different hardware and software versions, identical imaging sequences were used for PD, T1 and T2* mapping, adapting the codes of an existing protocol on the older system line by line to match the software version of the newer scanner. For T2-mapping, the respective manufacturer’s sequence was used which depended on the software version. However, system-dependent corrections were carried out in this case. Reproducibility was assessed by average values in regions of interest. Results: Mean scan-rescan variations were not exceeding 2.14%, with average values of 1.23% and 1.56% for the new and old system, respectively. Inter-scanner model deviations were not exceeding 5.21% with average values of about 2.2–3.8% for PD, 2.5–3.0% for T2*, 1.6–3.1% for T1 and 3.3–5.2% for T2. Conclusions: Provided that identical acquisition sequences are used, discrepancies between qMRI data acquired with different scanner models are low. The level of systematic differences reported in this work may help to interpret multi-centre data.