The complex structural organization of the white matter of the brain can be depicted in vivo in great detail with advanced diffusion magnetic resonance (MR) imaging schemes. Diffusion MR imaging ...techniques are increasingly varied, from the simplest and most commonly used technique-the mapping of apparent diffusion coefficient values-to the more complex, such as diffusion tensor imaging, q-ball imaging, diffusion spectrum imaging, and tractography. The type of structural information obtained differs according to the technique used. To fully understand how diffusion MR imaging works, it is helpful to be familiar with the physical principles of water diffusion in the brain and the conceptual basis of each imaging technique. Knowledge of the technique-specific requirements with regard to hardware and acquisition time, as well as the advantages, limitations, and potential interpretation pitfalls of each technique, is especially useful.
We studied in a clinical setting the age dependent T1 relaxation time as a marker of normal late brain maturation and compared it to conventional techniques, namely the apparent diffusion coefficient ...(ADC).
Forty-two healthy subjects ranging from ages 1 year to 20 years were included in our study. T1 brain maps in which the intensity of each pixel corresponded to T1 relaxation times were generated based on MR imaging data acquired using a MP2RAGE sequence. During the same session, diffusion tensor imaging data was collected. T1 relaxation times and ADC in white matter and grey matter were measured in seven clinically relevant regions of interest and were correlated to subjects' age.
In the basal ganglia, there was a small, yet significant, decrease in T1 relaxation time (-0.45 ≤R≤-0.59, p<10-2) and ADC (-0.60≤R≤-0.65, p<10-4) as a function of age. In the frontal and parietal white matter, there was a significant decrease in T1 relaxation time (-0.62≤R≤-0.68, p<10-4) and ADC (-0.81≤R≤-0.85, p<10-4) as a function of age. T1 relaxation time changes in the corpus callosum and internal capsule were less relevant for this age range. There was no significant difference between the correlation of T1 relaxation time and ADC with respect to age (p-value = 0.39). The correlation between T1 relaxation and ADC is strong in the white matter but only moderate in basal ganglia over this age period.
T1 relaxation time is a marker of brain maturation or myelination during late brain development. Between the age of 1 and 20 years, T1 relaxation time decreases as a function of age in the white matter and basal ganglia. The greatest changes occur in frontal and parietal white matter. These regions are known to mature in the final stage of development and are mainly composed of association circuits. Age-correlation is not significantly different between T1 relaxation time and ADC. Therefore, T1 relaxation time does not appear to be a superior marker of brain maturation than ADC but may be considered as complementary owing the intrinsic differences in bio-physical sensitivity. This work may serve as normative ranges in clinical imaging routines.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Whether signals from different sensory modalities converge and interact within primary cortices in humans is unresolved, despite emerging evidence in animals. This is partially because of debates ...concerning the appropriate analyses of functional magnetic resonance imaging (fMRI) data in response to multisensory phenomena. Using event-related fMRI, we observed that simple auditory stimuli (noise bursts) activated primary visual cortices and that simple visual stimuli (checkerboards) activated primary auditory cortices, indicative of multisensory convergence. Moreover, analyses of blood oxygen level–dependent response dynamics revealed facilitation of hemodynamic response peak latencies and slopes for multisensory auditory–visual stimuli versus either unisensory condition, indicative of multisensory interactions within primary sensory cortices. Neural processing at the lowest cortical levels can be modulated by interactions between the senses. Temporal information in fMRI data can reveal these modulations and overcome analytic and interpretational challenges of more traditional procedures. In addition to providing an essential translational link with animal models, these results suggest that longstanding notions of cortical organization need to be revised to include multisensory interactions as an inherent component of functional brain organization.
To suppress the noise, by sacrificing some of the signal homogeneity for numerical stability, in uniform T1 weighted (T1w) images obtained with the magnetization prepared 2 rapid gradient echoes ...sequence (MP2RAGE) and to compare the clinical utility of these robust T1w images against the uniform T1w images.
8 healthy subjects (29.0 ± 4.1 years; 6 Male), who provided written consent, underwent two scan sessions within a 24 hour period on a 7T head-only scanner. The uniform and robust T1w image volumes were calculated inline on the scanner. Two experienced radiologists qualitatively rated the images for: general image quality; 7T specific artefacts; and, local structure definition. Voxel-based and volume-based morphometry packages were used to compare the segmentation quality between the uniform and robust images. Statistical differences were evaluated by using a positive sided Wilcoxon rank test.
The robust image suppresses background noise inside and outside the skull. The inhomogeneity introduced was ranked as mild. The robust image was significantly ranked higher than the uniform image for both observers (observer 1/2, p-value = 0.0006/0.0004). In particular, an improved delineation of the pituitary gland, cerebellar lobes was observed in the robust versus uniform T1w image. The reproducibility of the segmentation results between repeat scans improved (p-value = 0.0004) from an average volumetric difference across structures of ≈ 6.6% to ≈ 2.4% for the uniform image and robust T1w image respectively.
The robust T1w image enables MP2RAGE to produce, clinically familiar T1w images, in addition to T1 maps, which can be readily used in uniform morphometry packages.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Measurement of microvascular perfusion with Intravoxel Incoherent Motion (IVIM) MRI is gaining interest. Yet, the physiological influences on the IVIM perfusion parameters ("pseudo-diffusion" ...coefficient D*, perfusion fraction f, and flow related parameter fD*) remain insufficiently characterized. In this article, we hypothesize that D* and fD*, which depend on blood speed, should vary during the cardiac cycle. We extended the IVIM model to include time dependence of D* = D*(t), and demonstrate in the healthy human brain that both parameters D* and fD* are significantly larger during systole than diastole, while the diffusion coefficient D and f do not vary significantly. The results non-invasively demonstrate the pulsatility of the brain's microvasculature.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Voxel-based morphometry from conventional T1-weighted images has proved effective to quantify Alzheimer's disease (AD) related brain atrophy and to enable fairly accurate automated classification of ...AD patients, mild cognitive impaired patients (MCI) and elderly controls. Little is known, however, about the classification power of volume-based morphometry, where features of interest consist of a few brain structure volumes (e.g. hippocampi, lobes, ventricles) as opposed to hundreds of thousands of voxel-wise gray matter concentrations. In this work, we experimentally evaluate two distinct volume-based morphometry algorithms (FreeSurfer and an in-house algorithm called MorphoBox) for automatic disease classification on a standardized data set from the Alzheimer's Disease Neuroimaging Initiative. Results indicate that both algorithms achieve classification accuracy comparable to the conventional whole-brain voxel-based morphometry pipeline using SPM for AD vs elderly controls and MCI vs controls, and higher accuracy for classification of AD vs MCI and early vs late AD converters, thereby demonstrating the potential of volume-based morphometry to assist diagnosis of mild cognitive impairment and Alzheimer's disease.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
BACKGROUND AND PURPOSE—Early arterial recanalization in acute ischemic stroke is strongly associated with better outcomes. However, early worsening of arterial patency was seldom studied. We ...investigated potential predictors and long-term prognosis of worsening of arterial patency at 24 hours after stroke onset.
METHODS—Patients from the Acute Stroke Registry and Analysis of Lausanne registry including admission and 24-hour vascular imaging (computed tomography or magnetic resonance angiography) were included. Worsening of arterial patency was defined as a new occlusion and significant stenosis in any extracranial or intracranial artery, comparing 24 hours with admission imaging. Variables associated with worsening of arterial patency were assessed by stepwise multiple logistic regression. The impact of arterial worsening on 3-month outcome was investigated with an adjusted modified Rankin Scale shift analysis.
RESULTS—Among 2152 included patients, 1387 (64.5%) received intravenous thrombolysis and endovascular treatment, and 65 (3.0%) experienced 24-hour worsening of arterial patency. In multivariable analysis, history of hypertension seemed protective (adjusted odds ratio aOR, 0.45; 95% CI, 0.27–0.75) while higher admission National Institutes of Health Stroke Scale (aOR, 1.06; 95% CI, 1.02–1.10), intracranial (aOR, 4.78; 95% CI, 2.03–11.25) and extracranial stenosis (aOR, 3.67; 95% CI, 1.95–6.93), and good collaterals (aOR, 3.71; 95% CI, 1.54–8.95) were independent predictors of worsening of arterial patency. Its occurrence was associated with a major unfavorable shift in the distribution of the modified Rankin Scale at 3 months (aOR, 5.97; 95% CI, 3.64–9.79).
CONCLUSIONS—Stroke severity and admission vascular imaging findings may help to identify patients at a higher risk of developing worsening of arterial patency at 24 hours. The impact of worsening of arterial patency on long-term outcome warrants better methods to detect and prevent this early complication.
Purpose
The thalamus is an important brain structure and neurosurgical target, but its constituting nuclei are challenging to image non‐invasively. Recently, susceptibility‐weighted imaging (SWI) at ...ultra‐high field has shown promising capabilities for thalamic nuclei mapping. In this work, several methodological improvements were explored to enhance SWI quality and contrast, and specifically its ability for thalamic imaging.
Methods
High‐resolution SWI was performed at 7T in healthy participants, and the following techniques were applied: (a) monitoring and retrospective correction of head motion and B0 perturbations using integrated MR navigators, (b) segmentation and removal of venous vessels on the SWI data using vessel enhancement filtering, and (c) contrast enhancement by tuning the parameters of the SWI phase‐magnitude combination. The resulting improvements were evaluated with quantitative metrics of image quality, and by comparison to anatomo‐histological thalamic atlases.
Results
Even with sub‐millimeter motion and natural breathing, motion and field correction produced clear improvements in both magnitude and phase data quality (76% and 41%, respectively). The improvements were stronger in cases of larger motion/field deviations, mitigating the dependence of image quality on subject performance. Optimizing the SWI phase‐magnitude combination yielded substantial improvements in image contrast, particularly in the thalamus, well beyond previously reported SWI results. The atlas comparisons provided compelling evidence of anatomical correspondence between SWI features and several thalamic nuclei, for example, the ventral intermediate nucleus. Vein detection performed favorably inside the thalamus, and vein removal further improved visualization.
Conclusion
Altogether, the proposed developments substantially improve high‐resolution SWI, particularly for thalamic nuclei imaging.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Evidence from psychophysical studies in normal and brain-damaged subjects suggests that auditory information relevant to recognition and localization are processed by distinct neuronal populations. ...We report here on anatomical segregation of these populations. Brain activation associated with performance in sound identification and localization was investigated in 18 normal subjects using fMRI. Three conditions were used: (i) comparison of spatial stimuli simulated with interaural time differences; (ii) identification of environmental sounds; and (iii) rest. Conditions (i) and (ii) required acknowledgment of predefined targets by pressing a button. After coregistering, images were normalized and smoothed. Activation patterns were analyzed using SPM99 for individual subjects and for the whole group. Sound recognition and localization activated, as compared to rest, inferior colliculus, medial geniculate body, Heschl gyrus, and parts of the temporal, parietal, and frontal convexity bilaterally. The activation pattern on the fronto-temporo-parietal convexity differed in the two conditions. Middle temporal gyrus and precuneus bilaterally and the posterior part of left inferior frontal gyrus were more activated by recognition than by localization. Lower part of inferior parietal lobule and posterior parts of middle and inferior frontal gyri were more activated, bilaterally, by localization than by recognition. Regions selectively activated by sound recognition, but not those selectively activated by localization, were significantly larger in women. Passive listening paradigm revealed segregated pathways on superior temporal gyrus and inferior parietal lobule. Thus, anatomically distinct networks are involved in sound recognition and sound localization.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Sound localization relies on the analysis of interaural time and intensity differences, as well as attenuation patterns by the outer ear. We investigated the relative contributions of interaural time ...and intensity difference cues to sound localization by testing 60 healthy subjects: 25 with focal left and 25 with focal right hemispheric brain damage. Group and single-case behavioural analyses, as well as anatomo-clinical correlations, confirmed that deficits were more frequent and much more severe after right than left hemispheric lesions and for the processing of interaural time than intensity difference cues. For spatial processing based on interaural time difference cues, different error types were evident in the individual data. Deficits in discriminating between neighbouring positions occurred in both hemispaces after focal right hemispheric brain damage, but were restricted to the contralesional hemispace after focal left hemispheric brain damage. Alloacusis (perceptual shifts across the midline) occurred only after focal right hemispheric brain damage and was associated with minor or severe deficits in position discrimination. During spatial processing based on interaural intensity cues, deficits were less severe in the right hemispheric brain damage than left hemispheric brain damage group and no alloacusis occurred. These results, matched to anatomical data, suggest the existence of a binaural sound localization system predominantly based on interaural time difference cues and primarily supported by the right hemisphere. More generally, our data suggest that two distinct mechanisms contribute to: (i) the precise computation of spatial coordinates allowing spatial comparison within the contralateral hemispace for the left hemisphere and the whole space for the right hemisphere; and (ii) the building up of global auditory spatial representations in right temporo-parietal cortices.
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