Personalized connectome fingerprints: Their importance in cognition from childhood to adult years.

Structural neural network architecture patterns in the human brain could be related to individual differences in phenotype, behavior, genetic determinants, and clinical outcomes from neuropsychiatric disorders. Recent studies have indicated that a personalized neural (brain) fingerprint can be identified from structural brain connectomes. However, the accuracy, reproducibility and translational potential of personalized fingerprints in terms of cognition is not yet fully determined. In this study, we introduce a dynamic connectome modeling approach to identify a critical set of white matter subnetworks that can be used as a personalized fingerprint. Several individual variable assessments were performed that demonstrate the accuracy and practicality of personalized fingerprint, specifically predicting the identity and IQ of middle age adults, and the developmental quotient in toddlers. Our findings suggest the fingerprint found by our dynamic modeling approach is sufficient for differentiation between individuals, and is also capable of predicting general intellectual ability across human development.

Systematic Assessment of Multispectral Voxel-Based Morphometry in Previously MRI-Negative Focal Epilepsy.

BACKGROUND AND PURPOSE: Voxel-based morphometry is widely used for detecting gray matter abnormalities in epilepsy. However, its performance with changing parameters, smoothing and statistical threshold, is debatable. More important, the potential yield of combining multiple MR imaging contrasts (multispectral voxel-based morphometry) is still unclear. Our aim was to objectify smoothing and statistical cutoffs and systematically compare the performance of multispectral voxel-based morphometry with existing T1 voxel-based morphometry in patients with focal epilepsy and previously negative MRI. MATERIALS AND METHODS: 3D T1-, T2-, and T2-weighted FLAIR scans were acquired for 62 healthy volunteers and 13 patients with MR imaging negative for focal epilepsy on a Magnetom Skyra 3T scanner with an isotropic resolution of 0.9 mm3. We systematically optimized the main voxel-based morphometry parameters, smoothing level and statistical cutoff, with T1 voxel-based morphometry as a reference. As a next step, the performance of multispectral voxel-based morphometry models, T1+T2, T1+FLAIR, and T1+T2+FLAIR, was compared with that of T1 voxel-based morphometry using gray matter concentration and gray matter volume analysis. RESULTS: We found the best performance of T1 at 12 mm and a T-threshold (statistical cutoff) of 3.7 for gray matter concentration analysis. When we incorporated these parameters, after expert visual interpretation of concordant and discordant findings, we identified T1+FLAIR as the best model with a concordant rate of 46.2% and a concordant rate/discordant rate of 1.20 compared with T1 with 30.8% and 0.67, respectively. Visual interpretation of voxel-based morphometry findings decreased concordant rates from 38.5%-46.2% to 15.4%-46.2% and discordant rates from 53.8%-84.6% to 30.8%-46.2% and increased specificity across models from 33.9%-40.3% to 46.8%-54.8%. CONCLUSIONS: Multispectral voxel-based morphometry, especially T1+FLAIR, can yield superior results over single-channel T1 in focal epilepsy patients with a negative conventional MR imaging.

T2 mapping outperforms normalised FLAIR in identifying hippocampal sclerosis.

RATIONALE: Qualitatively, FLAIR MR imaging is sensitive to the detection of hippocampal sclerosis (HS). Quantitative analysis of T2 maps provides a useful objective measure and increased sensitivity over visual inspection of T2-weighted scans. We aimed to determine whether quantification of normalised FLAIR is as sensitive as T2 mapping in detection of HS. METHOD: Dual echo T2 and FLAIR MR images were retrospectively analysed in 27 patients with histologically confirmed HS and increased T2 signal in ipsilateral hippocampus and 14 healthy controls. Regions of interest were manually segmented in all hippocampi aiming to avoid inclusion of CSF. Hippocampal T2 values and measures of normalised FLAIR Signal Intensity (nFSI) were compared in healthy and sclerotic hippocampi. RESULTS: HS was identified on T2 values with 100% sensitivity and 100% specificity. HS was identified on nFSI measures with 60% sensitivity and 93% specificity. CONCLUSION: T2 mapping is superior to nFSI for identification of HS.

Distributed, limbic gray matter atrophy in patients after bacterial meningitis.

BACKGROUND AND PURPOSE: The structural basis of cognitive sequelae after bacterial meningitis in humans is still poorly understood. In animal models and human autopsy cases, neuronal apoptosis of the hippocampal formation in particular seems to play an important role. Here, we aimed to analyze if BM entails MR imaging structural consequences in humans in vivo. MATERIALS AND METHODS: We applied voxel-based morphometry in a cohort of BM survivors with normal conventional MR imaging after resolution of the acute inflammation to assess morphologic differences. RESULTS: We found clear gray matter volume loss in the limbic system including the hippocampal formation, thalamus, and cingulate gyri bilaterally as well as in the temporal lobe. These results were corroborated by an alternative atlas-based method. CONCLUSIONS: Even in patients with normal routine MR imaging results, clear-cut gray matter atrophy with a mesial temporal/limbic pattern was evident. The anatomic distribution is compatible with the neuropsychological deficit commonly observed in patients after BM. The similarity of the observed atrophy may point to causal link between BM and mesial temporal epilepsy.

Differentiation of typical and atypical Parkinson syndromes by quantitative MR imaging.

BACKGROUND AND PURPOSE: The differential diagnosis of Parkinson syndromes remains a major challenge. Quantitative MR imaging can aid in this classification, but it is unclear which of the proposed techniques is best suited for this task. We, therefore, conducted a head-to-head study with different quantitative MR imaging measurements in patients with IPS, MSA-type Parkinson, PSP, and healthy elderly controls. MATERIALS AND METHODS: Thirty-one patients and 13 controls underwent a comprehensive quantitative MR imaging protocol including R2*-, R2- and R1-mapping, magnetization transfer, and DTI with manual region-of-interest measurements in basal ganglia regions. Group differences were assessed with a post hoc ANOVA with a Bonferroni error correction and an ROC. RESULTS: The best separation of MSA from IPS in patients and controls could be achieved with R2*-mapping in the PU, with an ROC AUC of ≤0.96, resulting in a sensitivity of 77.8% (with a specificity 100%). MD was increased in patients with PSP compared with controls and to a lesser extent compared with those with IPS and MSA in the SN. CONCLUSIONS: Among the applied quantitative MR imaging methods, R2*-mapping seems to have the best predictive power to separate patients with MSA from those with IPS, and DTI for identifying PSP.

Multi-site voxel-based morphometry--not quite there yet.

Voxel-based morphometry (VBM) is a widely applied method in computational neurosciences but it is currently recommended to compare only data collected at a single MRI scanner. Multi-site VBM would be a desirable approach to increase group size and, thus, statistical power. We aimed to assess if multi-site VBM is feasible on similar hardware and compare the magnitude of inter- and intra-scanner differences. 18 healthy subjects were scanned in two identical 3T MRI scanners using different head coil designs, twice in scanner A and once in scanner B. 3D T1-weighted images were processed with SPM8 and FSL4.1 and compared as paired t-test (scan versus re-scan) on a voxel basis by means of a general linear model (GLM). Additionally, coefficient-of-difference (coeffD) maps were calculated for respective pairs of gray matter segmentations. We found considerable inter-scanner differences clearly exceeding a commonly used GLM significance threshold of p<0.05 (FWE corrected). The spatial pattern of detected differences was dependent on whether SPM8 or FSL4.1 was used. The inclusion of global correcting factors either aggravated (SPM8) or reduced the GLM detected differences (FSL4.1). The coeffD analysis revealed markedly higher variability within the FSL4.1 stream both for the inter- and the intra-scanner comparison. A lowered bias cutoff (30 mm FWHM) in SPM8 improved the comparability for cortical areas. Intra-scanner scan/re-scan differences were generally weaker and did not exceed a p<0.05 (FWE corrected) threshold in the GLM analysis. At 3T profound inter-scanner differences are to be expected that could severely confound an unbalanced VBM analysis. These are like related to the receive bias of the radio-frequency hardware.

Defining Meyer's loop-temporal lobe resections, visual field deficits and diffusion tensor tractography.

Anterior temporal lobe resection is often complicated by superior quadrantic visual field deficits (VFDs). In some cases this can be severe enough to prohibit driving, even if a patient is free of seizures. These deficits are caused by damage to Meyer's loop of the optic radiation, which shows considerable heterogeneity in its anterior extent. This structure cannot be distinguished using clinical magnetic resonance imaging sequences. Diffusion tensor tractography is an advanced magnetic resonance imaging technique that enables the parcellation of white matter. Using seed voxels antero-lateral to the lateral geniculate nucleus, we applied this technique to 20 control subjects, and 21 postoperative patients. All patients had visual fields assessed with Goldmann perimetry at least three months after surgery. We measured the distance from the tip of Meyer's loop to the temporal pole and horn in all subjects. In addition, we measured the size of temporal lobe resection using postoperative T(1)-weighted images, and quantified VFDs. Nine patients suffered VFDs ranging from 22% to 87% of the contralateral superior quadrant. In patients, the range of distance from the tip of Meyer's loop to the temporal pole was 24-43 mm (mean 34 mm), and the range of distance from the tip of Meyer's loop to the temporal horn was -15 to +9 mm (mean 0 mm). In controls the range of distance from the tip of Meyer's loop to the temporal pole was 24-47 mm (mean 35 mm), and the range of distance from the tip of Meyer's loop to the temporal horn was -11 to +9 mm (mean 0 mm). Both quantitative and qualitative results were in accord with recent dissections of cadaveric brains, and analysis of postoperative VFDs and resection volumes. By applying a linear regression analysis we showed that both distance from the tip of Meyer's loop to the temporal pole and the size of resection were significant predictors of the postoperative VFDs. We conclude that there is considerable variation in the anterior extent of Meyer's loop. In view of this, diffusion tensor tractography of the optic radiation is a potentially useful method to assess an individual patient's risk of postoperative VFDs following anterior temporal lobe resection.