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This study evaluated the MRI-derived fat fraction (FF), from a Cooling-reheating protocol, for estimating the cold-induced brown adipose tissue (BAT) metabolic rate of glucose (MR glu ) and changes in lipid content, perfusion and arterial blood volume (V A ) within cervical-supraclavicular fat (sBAT). Twelve volunteers underwent PET/MRI at baseline, during cold exposure and reheating. For each temperature condition, perfusion and V A were quantified with dynamic [ 15 O]water-PET, and FF, with water-fat MRI. MR glu was assessed with dynamic [ 18 F]fluorodeoxyglucose-PET during cold exposure. sBAT was defined using anatomical criteria, and its subregion sBAT HI , by MR glu  > 11 μmol/100 cm 3 /min. For all temperature conditions, sBAT-FF correlated negatively with sBAT-MR glu (ρ ≤ − 0.87). After 3 h of cold, sBAT-FF decreased (− 2.13 percentage points) but tended to normalize during reheating although sBAT HI -FF remained low. sBAT-perfusion and sBAT-V A increased during cold exposure (perfusion: + 5.2 ml/100 cm 3 /min, V A : + 4.0 ml/100 cm 3 ). sBAT-perfusion remained elevated and sBAT-V A normalized during reheating. Regardless of temperature condition during the Cooling-reheating protocol, sBAT-FF could predict the cold-induced sBAT-MR glu . The FF decreases observed after reheating were mainly due to lipid consumption, but could potentially be underestimated due to intracellular lipid replenishment. The influence of perfusion and V A , on the changes in FF observed during cold exposure, could not be ruled out.

Brown adipose tissue (BAT) expends chemical energy to produce heat, which makes it a potential therapeutic target for combating metabolic dysfunction and overweight/obesity by increasing its metabolic activity. The most well-established method for measuring BAT metabolic activity is glucose uptake rate (GUR) measured using 18 F-fluorodeoxyglucose (FDG) positron emission tomography (PET). However, this is expensive and exposes the subjects to potentially harmful radiation. Cheaper and safer methods are warranted for large-scale or longitudinal studies. Potential alternatives include infrared thermography (IRT) and magnetic resonance imaging (MRI). The aim of this study was to evaluate and further develop these techniques. Twelve healthy adult subjects were studied. The BAT GUR was measured using 18 F-FDG PET during individualized cooling. The temperatures of the supraclavicular fossae and a control region were measured using IRT during a simple cooling protocol. The fat fraction and effective transverse relaxation rate of BAT were measured using MRI without any cooling intervention. Simple and multiple linear regressions were employed to evaluate how well the MRI and IRT measurements could estimate the GUR. Results showed that both IRT and MRI measurements correlated with the GUR. This suggest that these measurements may be suitable for estimating the cold-induced BAT GUR in future studies.

BackgroundA valid photon attenuation correction (AC) method is instrumental for obtaining quantitatively correct PET images. Integrated PET/MR systems provide no direct information on attenuation, and novel methods for MR-based AC (MRAC) are still under investigation. Evaluations of various AC methods have mainly focused on static brain PET acquisitions. In this study, we determined the validity of three MRAC methods in a dynamic PET/MR study of the brain.MethodsNine participants underwent dynamic brain PET/MR scanning using the dopamine transporter radioligand [11C]PE2I. Three MRAC methods were evaluated: single-atlas (Atlas), multi-atlas (MaxProb) and zero-echo-time (ZTE). The 68Ge-transmission data from a previous stand-alone PET scan was used as reference method. Parametric relative delivery (R1) images and binding potential (BPND) maps were generated using cerebellar grey matter as reference region. Evaluation was based on bias in MRAC maps, accuracy and precision of [11C]PE2I BPND and R1 estimates, and [11C]PE2I time-activity curves. BPND was examined for striatal regions and R1 in clusters of regions across the brain.ResultsFor BPND, ZTE-MRAC showed the highest accuracy (bias < 2%) in striatal regions. Atlas-MRAC exhibited a significant bias in caudate nucleus (− 12%) while MaxProb-MRAC revealed a substantial, non-significant bias in the putamen (9%). R1 estimates had a marginal bias for all MRAC methods (− 1.0–3.2%). MaxProb-MRAC showed the largest intersubject variability for both R1 and BPND. Standardized uptake values (SUV) of striatal regions displayed the strongest average bias for ZTE-MRAC (~ 10%), although constant over time and with the smallest intersubject variability. Atlas-MRAC had highest variation in bias over time (+10 to − 10%), followed by MaxProb-MRAC (+5 to − 5%), but MaxProb showed the lowest mean bias. For the cerebellum, MaxProb-MRAC showed the highest variability while bias was constant over time for Atlas- and ZTE-MRAC.ConclusionsBoth Maxprob- and ZTE-MRAC performed better than Atlas-MRAC when using a 68Ge transmission scan as reference method. Overall, ZTE-MRAC showed the highest precision and accuracy in outcome parameters of dynamic [11C]PE2I PET analysis with use of kinetic modelling.

Recent progress in functional neuroimaging research has provided the opportunity to probe at the brain's intrinsic functional architecture. Synchronized spontaneous neuronal activity is present in the form of resting-state networks in the brain even in the absence of external stimuli. The objective of this study was to investigate the presence of resting-state networks in the unsedated infant brain born at full term. Using functional MRI, we investigated spontaneous low-frequency signal fluctuations in 19 healthy full-term infants. Resting-state functional MRI data acquired during natural sleep was analyzed using independent component analysis. We found five resting-state networks in the unsedated infant brain born at full term, encompassing sensory cortices, parietal and temporal areas, and the prefrontal cortex. In addition, we found evidence for a resting-state network that enclosed the bilateral basal ganglia.

BackgroundMRI does not offer a direct method to obtain attenuation correction maps as its predecessors (stand-alone PET and PET/CT), and bone visualisation is particularly challenging. Recently, zero-echo-time (ZTE) was suggested for MR-based attenuation correction (AC). The aim of this work was to evaluate ZTE- and atlas-AC by comparison to 68Ge-transmission scan-based AC.Nine patients underwent brain PET/MR and stand-alone PET scanning using the dopamine transporter ligand 11C-PE2I. For each of them, two AC maps were obtained from the MR images: an atlas-based, obtained from T1-weighted LAVA-FLEX imaging with cortical bone inserted using a CT-based atlas, and an AC map generated from proton-density-weighted ZTE images. Stand-alone PET 68Ge-transmission AC map was used as gold standard. PET images were reconstructed using the three AC methods and standardised uptake value (SUV) values for the striatal, limbic and cortical regions, as well as the cerebellum (VOIs) were compared. SUV ratio (SUVR) values normalised for the cerebellum were also assessed. Bias, precision and agreement were calculated; statistical significance was evaluated using Wilcoxon matched-pairs signed-rank test.ResultsBoth ZTE- and atlas-AC showed a similar bias of 6–8% in SUV values across the regions. Correlation coefficients with 68Ge-AC were consistently high for ZTE-AC (r 0.99 for all regions), whereas they were lower for atlas-AC, varying from 0.99 in the striatum to 0.88 in the posterior cortical regions. SUVR showed an overall bias of 2.9 and 0.5% for atlas-AC and ZTE-AC, respectively. Correlations with 68Ge-AC were higher for ZTE-AC, varying from 0.99 in the striatum to 0.96 in the limbic regions, compared to atlas-AC (0.99 striatum to 0.77 posterior cortex).ConclusionsAbsolute SUV values showed less variability for ZTE-AC than for atlas-AC when compared to 68Ge-AC, but bias was similar for both methods. This bias is largely caused by higher linear attenuation coefficients in atlas- and ZTE-AC image compared to 68Ge-images. For SUVR, bias was lower when using ZTE-AC than for atlas-AC. ZTE-AC shows to be a more robust technique than atlas-AC in terms of both intra- and inter-patient variability.

Cerebral blood flow (CBF) measurements are of high clinical value and can be acquired non-invasively with no radiation exposure using pseudo-continuous arterial spin labeling (ASL). The aim of this study was to evaluate accordance in resting state CBF between ASL (CBFASL) and 15O-water positron emission tomography (PET) (CBFPET) acquired simultaneously on an integrated 3T PET/MR system. The data comprised ASL and dynamic 15O-water PET data with arterial blood sampling of eighteen subjects (eight patients with focal epilepsy and ten healthy controls, age 21 to 61 years). 15O-water PET parametric CBF images were generated using a basis function implementation of the single tissue compartment model. Cortical and subcortical regions were automatically segmented using Freesurfer. Average CBFASL and CBFPET in grey matter were 60 ± 20 and 75 ± 22 mL/100 g/min respectively, with a relatively high correlation (r = 0.78, p < 0.001). Bland-Altman analysis revealed poor agreement (bias = −15 mL/100 g/min, lower and upper limits of agreements = −16 and 45 mL/100 g/min, respectively) with a negative relationship. Accounting for the negative relationship, the width of the limits of agreement could be narrowed from 61 mL/100 g/min to 35 mL/100 g/min using regression-based limits of agreements. Although a high correlation between CBFASL and CBFPET was found, the agreement in absolute CBF values was not sufficient for ASL to be used interchangeably with 15O-water PET.

Brown adipose tissue (BAT) expends chemical energy to produce heat, which makes it a potential therapeutic target for combating metabolic dysfunction and overweight/obesity by increasing its metabolic activity. The most well-established method for measuring BAT metabolic activity is glucose uptake rate (GUR) measured using F-fluorodeoxyglucose (FDG) positron emission tomography (PET). However, this is expensive and exposes the subjects to potentially harmful radiation. Cheaper and safer methods are warranted for large-scale or longitudinal studies. Potential alternatives include infrared thermography (IRT) and magnetic resonance imaging (MRI). The aim of this study was to evaluate and further develop these techniques. Twelve healthy adult subjects were studied. The BAT GUR was measured using F-FDG PET during individualized cooling. The temperatures of the supraclavicular fossae and a control region were measured using IRT during a simple cooling protocol. The fat fraction and effective transverse relaxation rate of BAT were measured using MRI without any cooling intervention. Simple and multiple linear regressions were employed to evaluate how well the MRI and IRT measurements could estimate the GUR. Results showed that both IRT and MRI measurements correlated with the GUR. This suggest that these measurements may be suitable for estimating the cold-induced BAT GUR in future studies.

Cerebral blood flow (CBF) measurements are of high clinical value and can be acquired non-invasively with no radiation exposure using pseudo-continuous arterial spin labeling (ASL). The aim of this study was to evaluate accordance in resting state CBF between ASL (CBF ASL ) and 15 O-water positron emission tomography (PET) (CBF PET ) acquired simultaneously on an integrated 3T PET/MR system. The data comprised ASL and dynamic 15 O-water PET data with arterial blood sampling of eighteen subjects (eight patients with focal epilepsy and ten healthy controls, age 21 to 61 years). 15 O-water PET parametric CBF images were generated using a basis function implementation of the single tissue compartment model. Cortical and subcortical regions were automatically segmented using Freesurfer. Average CBF ASL and CBF PET in grey matter were 60 ± 20 and 75 ± 22 mL/100 g/min respectively, with a relatively high correlation (r = 0.78, p < 0.001). Bland-Altman analysis revealed poor agreement (bias = −15 mL/100 g/min, lower and upper limits of agreements = −16 and 45 mL/100 g/min, respectively) with a negative relationship. Accounting for the negative relationship, the width of the limits of agreement could be narrowed from 61 mL/100 g/min to 35 mL/100 g/min using regression-based limits of agreements. Although a high correlation between CBF ASL and CBF PET was found, the agreement in absolute CBF values was not sufficient for ASL to be used interchangeably with 15 O-water PET.

Background: A valid photon attenuation correction (AC) method is instrumental for obtaining quantitatively correct PET images. Integrated PET/MR systems provide no direct information on attenuation, and novel methods for MR-based AC (MRAC) are still under investigation. Evaluations of various AC methods have mainly focused on static brain PET acquisitions. In this study we determined the validity of three MRAC methods in a dynamic PET/MR study of the brain. Methods: Nine participants underwent dynamic brain PET/MR scanning using the dopamine transporter radioligand [11C]PE2I. Three MRAC methods were evaluated: single-atlas (Atlas), multi-atlas (MaxProb) and zero-echo-time (ZTE). The 68Ge-transmission data from a previous stand-alone PET scan was used as reference method. Parametric relative delivery (R1) images and binding potential (BPND) maps were generated using cerebellar grey matter as reference region. Evaluation was based on bias in MRAC maps, accuracy and precision of [11C]PE2I BPND and R1 estimates, and [11C]PE2I time-activity curves. BPND was examined for striatal regions and R1 in clusters of regions across the brain. Results: For BPND, ZTE-MRAC showed the highest accuracy (bias < 2%) in striatal regions[JMSS1] . Atlas-MRAC exhibited a significant bias in caudate nucleus (-12%) while MaxProb-MRAC revealed a substantial, non-significant bias in putamen (9%). R1 estimates had a marginal bias for all MRAC methods (-1.0-3.2%). MaxProb-MRAC showed the largest intersubject variability for both R1 and BPND. Standardized uptake values (SUV) of striatal regions displayed the strongest average bias for ZTE-MRAC (~10%), although constant over time and with the smallest inter-subject variability. Atlas-MRAC had highest variation in bias over time (+10 to -10%), followed by MaxProb-MRAC (+5 to -5%), but MaxProb showed the lowest mean bias. For cerebellum, MaxProb-MRAC showed highest variability while bias was constant over time for Atlas- and ZTE-MRAC. Conclusions: Both Maxprob and ZTE-MRAC performed better than Atlas-MRAC when using a 68Ge transmission scan as reference method. Overall, ZTE-MRAC showed the highest precision and accuracy in outcome parameters of dynamic [11C]PE2I PET analysis with use of kinetic modelling.

Pituitary neuroendocrine tumors (PitNETs) are common, generally benign tumors with complex clinical characteristics related to hormone hypersecretion and/or growing sellar tumor mass. PitNETs can be classified based on the expression pattern of anterior pituitary hormones and three main transcriptions factors (TF), SF1, PIT1 and TPIT that regulate differentiation of adenohypophysial cells. Here, we have extended this classification based on the global transcriptomics landscape using tumor tissue from a well-defined cohort comprising 51 PitNETs of different clinical and histological types. The molecular profiles were compared with current classification schemes based on immunohistochemistry. Our results identified three main clusters of PitNETs that were aligned with the main pituitary TFs expression patterns. Our analyses enabled further identification of specific genes and expression patterns, including both known and unknown genes, that could distinguish the three different classes of PitNETs. We conclude that the current classification of PitNETs based on the expression of SF1, PIT1 and TPIT reflects three distinct subtypes of PitNETs with different underlying biology and partly independent from the expression of corresponding hormones. The transcriptomic analysis reveals several potentially targetable tumor-driving genes with previously unknown role in pituitary tumorigenesis.