Feasibility Study for a Microstrip Transmission Line RF Coil Integrated with a PET Detector Module in a 7T Human MR Imaging System.

PURPOSE: The purpose of this study was to do a feasibility study on a microstrip transmission line (MS) RF coil for a positron emission tomography (PET) insert in a 7 Tesla human MRI system. The proposed MS coil integrated the RF shield of the PET detector as the ground conductor of the coil. We called the integrated module "MS PET coil." METHODS: A single-channel MS PET coil was developed with an integrated RF-shielded PET detector module. For comparison, we also studied a conventional MS coil with a single-layer ground conductor. A lutetium fine silicate (LFS) scintillation crystal block (14 × 14 × 4-layer) with a silicon photomultiplier (Hamamatsu Photonics K.K., Shizuoka, Japan) and a front-end readout circuit board were mounted inside the shield cage of the MS PET coil. The MS PET coil was studied with and without PET detectors. All three coil configurations were studied with a homogeneous phantom in a 7T MRI system (Siemens Healthineers, Erlangen, Germany). PET data measurements were conducted using a Cesium-137 radiation point source. RESULTS: The MR images were similar for the MS coil and the empty MS PET coil, as well as for the cases of MS PET coil with and without PET measurements. Compared to the empty MS PET coil (without PET detector and cable RF shield), decreases in SNR, increases in image noise and RF power, and a slight decrease in resonance frequency were seen for the case of the MS PET coil with the detector and cable shield. Differences in the PET energy histograms or in the crystal identification maps with and without MRI measurements were negligible. CONCLUSIONS: Both the MRI and PET performances of the MS PET coil showed responses that matched the MS coil responses. The performance variations of MRI data with and without PET measurement and PET data with and without MR imaging were negligible.

High-resolution EEG source localization in personalized segmentation-free head model with multi-dipole fitting.

Objective. Electroencephalograms (EEGs) are often used to monitor brain activity. Several source localization methods have been proposed to estimate the location of brain activity corresponding to EEG readings. However, only a few studies evaluated source localization accuracy from measured EEG using personalized head models in a millimeter resolution. In this study, based on a volume conductor analysis of a high-resolution personalized human head model constructed from magnetic resonance images, a finite difference method was used to solve the forward problem and to reconstruct the field distribution.Approach. We used a personalized segmentation-free head model developed using machine learning techniques, in which the abrupt change of electrical conductivity occurred at the tissue interface is suppressed. Using this model, a smooth field distribution was obtained to address the forward problem. Next, multi-dipole fitting was conducted using EEG measurements for each subject (N= 10 male subjects, age: 22.5 ± 0.5), and the source location and electric field distribution were estimated.Main results.For measured somatosensory evoked potential for electrostimulation to the wrist, a multi-dipole model with lead field matrix computed with the volume conductor model was found to be superior than a single dipole model when using personalized segmentation-free models (6/10). The correlation coefficient between measured and estimated scalp potentials was 0.89 for segmentation-free head models and 0.71 for conventional segmented models. The proposed method is straightforward model development and comparable localization difference of the maximum electric field from the target wrist reported using fMR (i.e. 16.4 ± 5.2 mm) in previous study. For comparison, DUNEuro based on sLORETA was (EEG: 17.0 ± 4.0 mm). In addition, somatosensory evoked magnetic fields obtained by Magnetoencephalography was 25.3 ± 8.5 mm using three-layer sphere and sLORETA.Significance. For measured EEG signals, our procedures using personalized head models demonstrated that effective localization of the somatosensory cortex, which is located in a non-shallower cortex region. This method may be potentially applied for imaging brain activity located in other non-shallow regions.

Longitudinal reduction in brain volume in patients with schizophrenia and its association with cognitive function.

Establishing a brain biomarker for schizophrenia is strongly desirable not only to support diagnosis by psychiatrists but also to help track the progressive changes in the brain over the course of the illness. A brain morphological signature of schizophrenia was reported in a recent study and is defined by clusters of brain regions with reduced volume in schizophrenia patients compared to healthy individuals. This signature was proven to be effective at differentiating patients with schizophrenia from healthy individuals, suggesting that it is a good candidate brain biomarker of schizophrenia. However, the longitudinal characteristics of this signature have remained unclear. In this study, we examined whether these changes occurred over time and whether they were associated with clinical outcomes. We found a significant change in the brain morphological signature in schizophrenia patients with more brain volume loss than the natural, age-related reduction in healthy individuals, suggesting that this change can capture a progressive morphological change in the brain. We further found a significant association between changes in the brain morphological signature and changes in the full-scale intelligence quotient (IQ). The patients with IQ improvement showed preserved brain morphological signatures, whereas the patients without IQ improvement showed progressive changes in the brain morphological signature, suggesting a link between potential recovery of intellectual abilities and the speed of brain pathology progression. We conclude that the brain morphological signature is a brain biomarker that can be used to evaluate progressive changes in the brain that are associated with cognitive impairment due to schizophrenia.

Beyond the Global Brain Differences: Intraindividual Variability Differences in 1q21.1 Distal and 15q11.2 BP1-BP2 Deletion Carriers.

BACKGROUND: Carriers of the 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants exhibit regional and global brain differences compared with noncarriers. However, interpreting regional differences is challenging if a global difference drives the regional brain differences. Intraindividual variability measures can be used to test for regional differences beyond global differences in brain structure. METHODS: Magnetic resonance imaging data were used to obtain regional brain values for 1q21.1 distal deletion (n = 30) and duplication (n = 27) and 15q11.2 BP1-BP2 deletion (n = 170) and duplication (n = 243) carriers and matched noncarriers (n = 2350). Regional intra-deviation scores, i.e., the standardized difference between an individual's regional difference and global difference, were used to test for regional differences that diverge from the global difference. RESULTS: For the 1q21.1 distal deletion carriers, cortical surface area for regions in the medial visual cortex, posterior cingulate, and temporal pole differed less and regions in the prefrontal and superior temporal cortex differed more than the global difference in cortical surface area. For the 15q11.2 BP1-BP2 deletion carriers, cortical thickness in regions in the medial visual cortex, auditory cortex, and temporal pole differed less and the prefrontal and somatosensory cortex differed more than the global difference in cortical thickness. CONCLUSIONS: We find evidence for regional effects beyond differences in global brain measures in 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants. The results provide new insight into brain profiling of the 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants, with the potential to increase understanding of the mechanisms involved in altered neurodevelopment.

Cortical similarities in psychiatric and mood disorders identified in federated VBM analysis via COINSTAC.

Structural neuroimaging studies have identified a combination of shared and disorder-specific patterns of gray matter (GM) deficits across psychiatric disorders. Pooling large data allows for examination of a possible common neuroanatomical basis that may identify a certain vulnerability for mental illness. Large-scale collaborative research is already facilitated by data repositories, institutionally supported databases, and data archives. However, these data-sharing methodologies can suffer from significant barriers. Federated approaches augment these approaches by enabling access or more sophisticated, shareable and scaled-up analyses of large-scale data. We examined GM alterations using Collaborative Informatics and Neuroimaging Suite Toolkit for Anonymous Computation, an open-source, decentralized analysis application. Through federated analysis of eight sites, we identified significant overlap in the GM patterns (n = 4,102) of individuals with schizophrenia, major depressive disorder, and autism spectrum disorder. These results show cortical and subcortical regions that may indicate a shared vulnerability to psychiatric disorders.

Verifying the Accuracy of Hemodynamic Analysis Using High Spatial Resolution 3D Phase-contrast MR Imaging on a 7T MR System: Comparison with a 3T System.

PURPOSE: Hemodynamics is important in the initiation, growth, and rupture of intracranial aneurysms. Since intracranial aneurysms are small, a high-field MR system with high spatial resolution and high SNR is desirable for this hemodynamic analysis. The purpose of this study was to investigate whether the accuracy of MR fluid dynamic (MRFD) results based on 3D phase-contrast MR (3D PC MR, non-electrocardiogram[ECG]-gated 4D Flow MRI) data from a human cerebrovascular phantom and human healthy subjects obtained by a 7T MR system was superior to those by a 3T MR system. METHODS: 3D PC MR and 3D time of flight MR angiography (3D TOF MRA) imaging were performed on a 3T MR system and a 7T MR system for a human cerebrovascular phantom and 10 healthy human subjects, and MRFD analysis was performed using these data. The MRFD results from each MR system were then compared with the following items based on the computational fluid dynamics (CFD) results: 3D velocity vector field; correlation coefficient (R), angular similarity index (ASI), and magnitude similarity index (MSI) of blood flow velocity vectors. RESULTS: In the MRFD results of 3D velocity vectors of the cerebrovascular phantom, noise-like vectors were observed near the vascular wall on the 3T MR system, but no noise was observed on the 7T MR system, showing results similar to those of CFD. In the MRFD results of the cerebrovascular phantom and healthy subjects, the correlation coefficients R, ASI, and MSI of the 7T MR system were higher than those of the 3T MR system, and ASI and MSI of healthy human subjects were significantly different between the two systems. CONCLUSIONS: The accuracy of high spatial resolution MRFD using the 7T MR system exceeded that of the 3T MR system.