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BACKGROUND: Accurate analysis of quantitative PET data plays a crucial role in studying small, specific brain structures. The integration of PET and MRI through an integrated PET/MR system presents an opportunity to leverage the benefits of precisely aligned structural MRI and molecular PET images in both spatial and temporal dimensions. However, in many clinical workflows, PET studies are often performed without the aid of individually matched structural MRI scans, primarily for the sake of convenience in the data collection and brain segmentation possesses. Currently, two commonly employed segmentation strategies for brain PET analysis are distinguished: methods with or without MRI registration and methods employing either atlas-based or individual-based algorithms. Moreover, the development of artificial intelligence (AI)-assisted methods for predicting brain segmentation holds promise but requires further validation of their efficiency and accuracy for clinical applications. This study aims to compare and evaluate the correlations, consistencies, and differences among the above-mentioned brain segmentation strategies in quantification of brain metabolism in 18F-FDG PET/MR analysis. RESULTS: Strong correlations were observed among all methods (r = 0.932 to 0.999, P < 0.001). The variances attributable to subject and brain region were higher than those caused by segmentation methods (P < 0.001). However, intraclass correlation coefficient (ICC)s between methods with or without MRI registration ranged from 0.924 to 0.975, while ICCs between methods with atlas- or individual-based algorithms ranged from 0.741 to 0.879. Brain regions exhibiting significant standardized uptake values (SUV) differences due to segmentation methods were the basal ganglia nuclei (maximum to 11.50 ± 4.67%), and various cerebral cortexes in temporal and occipital regions (maximum to 18.03 ± 5.52%). The AI-based method demonstrated high correlation (r = 0.998 and 0.999, P < 0.001) and ICC (0.998 and 0.997) with FreeSurfer, substantially reducing the time from 8.13 h to 57 s on per subject. CONCLUSIONS: Different segmentation methods may have impact on the calculation of brain metabolism in basal ganglia nuclei and specific cerebral cortexes. The AI-based approach offers improved efficiency and is recommended for its enhanced performance.
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Objective:To investigate the differences in cerebral oxygen metabolism in healthy volunteers at three altitude areas by MR quantitative magnetic susceptibility imaging (QSM) combined with three-dimensional arterial spin labeling (3D-ASL).Methods:From March 2019 to October 2020, Zhengzhou Han Chinese volunteers recruited from the First Affiliated Hospital of Zhengzhou University, Xining Han Chinese volunteers recruited from the Fifth People′s Hospital of Qinghai Province, Lhasa Han Chinese volunteers and Tibetan volunteers recruited from Lhasa People′s Hospital were collected. They were divided into 21-30 age group, 31-40 age group, and 41-50 age group. All the volunteers underwent MR QSM combined with 3D-ASL sequence imaging, and oxygen extraction fraction (OEF) and cerebral blood flow (CBF) images of gray matter, and white matter were collected, OEF and CBF values were obtained, and cerebral metabolic rate of oxygen (CMRO 2) values were calculated. The comparison of various indicators among multiple groups was conducted using one-way ANOVA, and pairwise comparisons were conducted using LSD- t test. Results:A total of 132 volunteers were included, including 38 Han Chinese volunteers in Zhengzhou, 9 in the 21-30 age group, 13 in the 31-40 age group and 16 in the 41-50 age group; 27 Han Chinese volunteers in Xining, including 9 in the 21-30 age group, 8 in the 31-40 age group and 10 in the 41-50 age group; 34 Han Chinese volunteers in Lhasa, including 13 in the 21-30 age group, 11 in the 31-40 age group and 10 in the 41-50 age group; and 33 Tibetan volunteers in Lhasa, including 10 in the 21-30 age group, 10 in the 31-40 age group and 13 in the 41-50 age group. In the group aged 21-30 years, the overall difference in brain gray matter OEF values among volunteers from different altitudes was statistically significant ( P<0.05), with statistically significant differences in OEF values between Tibetans in Lhasa and Han Chinese in Xining, Han Chinese in Lhasa ( P<0.05). The overall difference in CMRO 2 values in the gray matter of volunteers at different altitudes was statistically significant ( P<0.05), with significant differences in CMRO 2 values between Lhasa Tibetan and Han Chinese in Zhengzhou, Han Chinese in Xining, Han Chinese in Lhasa ( P<0.05). In the 31-40 age group, there were statistically significant differences in the overall CBF values of gray and white matter among volunteers from different altitudes ( P<0.05). Among them, there were statistically significant differences in the CBF values of gray and white matter between Han Chinese in Zhengzhou and Han in Xining, Han Chinese in Lhasa, Lhasa Tibetan ( P<0.05). The overall differences in OEF values of gray matter and white matter among volunteers at different altitudes were statistically significant ( P<0.05). Among them, there were statistically significant differences in OEF values of gray matter and white matter between the Han Chinese in Zhengzhou and the Han Chinese in Xining, the Han Chinese in Lhasa ( P<0.05). There was also a statistically significant difference in OEF values of gray matter and white matter between the Han Chinese in Lhasa and the Tibetan in Lhasa ( P<0.05). The overall difference in CMRO 2 values in gray and white matter among volunteers from different altitudes was statistically significant ( P<0.05). Among them, there was a statistically significant difference in CMRO 2 values of cerebral gray matter between Lhasa Tibetans and Zhengzhou Han, Xining Han, Lhasa Han ( P<0.05), and there was a statistically significant difference in CMRO 2 values of cerebral white matter between Lhasa Tibetans and Zhengzhou Han, Lhasa Han ( P<0.05). Conclusions:The cerebral oxygen metabolism of Tibetan living in the plateau is characterized by low oxygen consumption, low blood oxygen dependence and high tissue oxygen utilization. The CMRO 2 of the Han people who migrated to the plateau for a long time is maintained at a certain level, similar to that in the plain area. The effects of age factors on CBF, OEF and CMRO 2 are small.
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OBJECTIVE: This study intends to track whole-brain functional connectivity strength (FCS) changes and the lateralization index (LI) in left basal ganglia (BG) ischemic stroke patients. METHODS: Twenty-five patients (N = 25; aged 52.73 ± 10.51 years) with five visits at <7, 14, 30, 90, and 180 days and 26 healthy controls (HCs; N = 26; 51.84 ± 8.06 years) were examined with resting-state functional magnetic resonance imaging (rs-fMRI) and motor function testing. FCS and LI were calculated through constructing the voxel-based brain functional network. One-way analysis of covariance (ANOVA) was first performed to obtain longitudinal FCS and LI changes in patients among the five visits (Bonferroni corrected, P < 0.05). Then, pairwise comparisons of FCS and LI were obtained during the five visits, and the two-sample t test was used to examine between-group differences in FCS [family-wise error (FWE) corrected, P < 0.05] and LI. Correlations between connectivity metrics (FCS and LI) and motor function were further assessed. RESULTS: Compared to HCs, decreased FCS in the patients localized in the calcarine and inferior occipital gyrus (IOG), while increased FCS gathered in the middle prefrontal cortex (MPFC), middle frontal gyrus, and insula (P < 0.05). The LI and FCS of patients first decreased and then increased, which showed significant differences compared with HCs (P < 0.05) and demonstrated a transition at the 30-day visit. Additionally, LI at the third visit was significantly different from those at the other visits (P < 0.05). No significant longitudinal correlations were observed between motor function and FCS or LI (P > 0.05). CONCLUSION: Focal ischemic stroke in the left BG leads to extensive alterations in the FCS. Strong plasticity in the functional networks could be reorganized in different temporal dynamics to facilitate motor recovery after BG stroke, contribute to diagnosing the disease course, and estimate the intervention treatment.
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Primate studies indicate that the pyramidal tract (PyT) could originate from Brodmann area (BA) 6. However, in humans, the accurate origin of PyT from BA 6 is still uncertain owing to difficulties in visualizing anatomical features such as the fanning shape at the corona radiata and multiple crossings at the semioval centrum. High angular-resolution diffusion imaging (HARDI) could reliably replicate these anatomical features. We explored the origin of the human PyT from BA 6 using HARDI. With HARDI data of 30 adults from the Massachusetts General Hospital-Human Connectome Project (MGH-HCP) database and the HCP 1021 template (average of 1021 HCP diffusion data), we visualized the PyT at the 30-averaged group level and the 1021 large-sample level and validated the observations in each of the individuals. Endpoints of the fibers within each subregion were quantified. PyT fibers originating from the BA 6 were consistently visualized in all images. Specifically, the bilateral supplementary motor area (SMA) and dorsal premotor area (dPMA) were consistently found to contribute to the PyT. PyT fibers from BA 6 and those from BA 4 exhibited a twisting topology. The PyT contains fibers originating from the SMA and dPMA in BA 6. Infarction of these regions or aging would result in incomplete provision of information to the PyT and concomitant decreases in motor planning and coordination abilities.