| 41. |
- Johansson, Jarkko, et al.
(författare)
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Amphetamine-induced dopamine release in rat : Whole-brain spatiotemporal analysis with [11C]raclopride and positron emission tomography
- 2024
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Ingår i: Journal of Cerebral Blood Flow and Metabolism. - : Sage Publications. - 0271-678X .- 1559-7016. ; 44:3, s. 434-445
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Tidskriftsartikel (refereegranskat)abstract
- Whole-brain mapping of drug effects are needed to understand the neural underpinnings of drug-related behaviors. Amphetamine administration is associated with robust increases in striatal dopamine (DA) release. Dopaminergic terminals are, however, present across several associative brain regions, which may contribute to behavioral effects of amphetamine. Yet the assessment of DA release has been restricted to a few brain regions of interest. The present work employed positron emission tomography (PET) with [11C]raclopride to investigate regional and temporal characteristics of amphetamine-induced DA release across twenty sessions in adult female Sprague Dawley rats. Amphetamine was injected intravenously (2 mg/kg) to cause displacement of [11C]raclopride binding from DA D2-like receptors, assessed using temporally sensitive pharmacokinetic PET model (lp-ntPET). We show amphetamine-induced [11C]raclopride displacement in the basal ganglia, and no changes following saline injections. Peak occupancy was highest in nucleus accumbens, followed by caudate-putamen and globus pallidus. Importantly, significant amphetamine-induced displacement was also observed in several extrastriatal regions, and specifically in thalamus, insula, orbitofrontal cortex, and secondary somatosensory area. For these, peak occupancy occurred later and was lower as compared to the striatum. Collectively, these findings demonstrate distinct amphetamine-induced DA responses across the brain, and that [11C]raclopride-PET can be employed to detect such spatiotemporal differences.
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| 42. |
- Jonasson, Lars, 1983-, et al.
(författare)
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Simulating effects of brain atrophy in longitudinal PET imaging with an anthropomorphic brain phantom
- 2017
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Ingår i: Physics in Medicine and Biology. - : Institute of Physics Publishing (IOPP). - 0031-9155 .- 1361-6560. ; 62:13, s. 5213-5227
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Tidskriftsartikel (refereegranskat)abstract
- In longitudinal positron emission tomography (PET), the presence of volumetric changes over time can lead to an overestimation or underestimation of the true changes in the quantified PET signal due to the partial volume effect (PVE) introduced by the limited spatial resolution of existing PET cameras and reconstruction algorithms. Here, a 3D-printed anthropomorphic brain phantom with attachable striata in three sizes was designed to enable controlled volumetric changes. Using a method to eliminate the non-radioactive plastic wall, and manipulating BP levels by adding different number of events from list-mode acquisitions, we investigated the artificial volume dependence of BP due to PVE, and potential bias arising from varying BP. Comparing multiple reconstruction algorithms we found that a high-resolution ordered- subsets maximization algorithm with spatially variant point-spread function resolution modeling provided the most accurate data. For striatum, the BP changed by 0.08% for every 1% volume change, but for smaller volumes such as the posterior caudate the artificial change in BP was as high as 0.7% per 1% volume change. A simple gross correction for striatal volume is unsatisfactory, as the amplitude of the PVE on the BP differs depending on where in the striatum the change occurred. Therefore, to correctly interpret age-related longitudinal changes in the BP, we must account for volumetric changes also within a structure, rather than across the whole volume. The present 3D-printing technology, combined with the wall removal method, can be implemented to gain knowledge about the predictable bias introduced by the PVE differences in uptake regions of varying shape.
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| 43. |
- Jonasson, My, et al.
(författare)
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Striatal dopamine transporter and receptor availability correlate with relative cerebral blood flow measured with [11C]PE2I, [18F]FE-PE2I and [11C]raclopride PET in healthy individuals
- 2023
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Ingår i: Journal of Cerebral Blood Flow and Metabolism. - : Sage Publications. - 0271-678X .- 1559-7016. ; 43:7, s. 1206-1215
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Tidskriftsartikel (refereegranskat)abstract
- The aim of this retrospective study was to investigate relationships between relative cerebral blood flow and striatal dopamine transporter and dopamine D2/3 availability in healthy subjects. The data comprised dynamic PET scans with two dopamine transporter tracers [11C]PE2I (n = 20) and [18F]FE-PE2I (n = 20) and the D2/3 tracer [11C]raclopride (n = 18). Subjects with a [11C]PE2I scan also underwent a dynamic scan with the serotonin transporter tracer [11C]DASB. Binding potential (BPND) and relative tracer delivery (R1) values were calculated on regional and voxel-level. Striatal R1 and BPND values were correlated, using either an MRI-based volume of interest (VOI) or an isocontour VOI based on the parametric BPND image. An inter-tracer comparison between [11C]PE2I BPND and [11C]DASB R1 was done on a VOI-level and simulations were performed to investigate whether the constraints of the modeling could cause correlation of the parameters. A positive association was found between BPND and R1 for all three dopamine tracers. A similar correlation was found for the inter-tracer correlation between [11C]PE2I BPND and [11C]DASB R1. Simulations showed that this relationship was not caused by cross-correlation between parameters in the kinetic model. In conclusion, these results suggest an association between resting-state striatal dopamine function and relative blood flow in healthy subjects.
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| 44. |
- Jonasson Stiernman, Lars, 1983-, et al.
(författare)
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Dissociations between glucose metabolism and blood oxygenation in the human default mode network revealed by simultaneous PET-fMRI
- 2021
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Ingår i: Proceedings of the National Academy of Sciences of the United States of America. - : Proceedings of the National Academy of Sciences. - 0027-8424 .- 1091-6490. ; 118:27
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Tidskriftsartikel (refereegranskat)abstract
- The finding of reduced functional MRI (fMRI) activity in the default mode network (DMN) during externally focused cognitive control has been highly influential to our understanding of human brain function. However, these negative fMRI responses, measured as relative decreases in the blood-oxygenation-level-dependent (BOLD) response between rest and task, have also prompted major questions of interpretation. Using hybrid functional positron emission tomography (PET)-MRI, this study shows that task-positive and -negative BOLD responses do not reflect antagonistic patterns of synaptic metabolism. Task-positive BOLD responses in attention and control networks were accompanied by concomitant increases in glucose metabolism during cognitive control, but metabolism in widespread DMN remained high during rest and task despite negative BOLD responses. Dissociations between glucose metabolism and the BOLD response specific to the DMN reveal functional heterogeneity in this network and demonstrate that negative BOLD responses during cognitive control should not be interpreted to reflect relative increases in metabolic activity during rest. Rather, neurovascular coupling underlying BOLD response patterns during rest and task in DMN appears fundamentally different from BOLD responses in other association networks during cognitive control.
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| 45. |
- Jonsson, Josefin, et al.
(författare)
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Does 18F-FDG PET/CT change the surgical management of potentially resectable colorectal liver metastases?
- 2022
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Ingår i: Scandinavian Journal of Surgery. - : Sage Publications. - 1457-4969 .- 1799-7267. ; 111:1
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Tidskriftsartikel (refereegranskat)abstract
- PURPOSE: Resectability assessment of patients with colorectal liver metastases is based on computed tomography and liver magnetic resonance imaging. Addition of fluorine-18-fluorodeoxyglucose positron emission tomography/computed tomography has been recommended, but the impact of the added information remains unclear. The primary aim of this study was to determine how preoperative positron emission tomography/computed tomography changed management in patients with potentially resectable colorectal liver metastases. The secondary aim was to investigate whether findings on positron emission tomography/computed tomography correlated to metastatic disease in cases with extended surgery and influenced oncological outcomes. METHODS: A retrospective observational study of the impact of adding positron emission tomography/computed tomography to conventional imaging in the surgical decision-making of colorectal liver metastases. All patients with colorectal liver metastases diagnosed by conventional imaging were included and assessed by a multidisciplinary team conference at Umeå University Hospital between June 2013 and December 2017. Eligibility criteria were all patients with potentially resectable colorectal liver metastases. Patients who underwent preoperative positron emission tomography/computed tomography in addition to conventional radiology were compared with those who underwent conventional imaging only. RESULTS: 151/220 patients underwent preoperative positron emission tomography/computed tomography. Findings on positron emission tomography/computed tomography changed the management in 10.6% of the patients. Eight patients were excluded from surgery after detection by positron emission tomography/computed tomography of extrahepatic disease. Eight patients underwent more extended surgery than initially planned due to positron emission tomography/computed tomography. Five of these positron emission tomography-positive resected sites were verified by pathology as metastatic disease. No difference in overall survival was seen following surgical resection in patients with and without a preoperative positron emission tomography/computed tomography. CONCLUSIONS: Preoperative positron emission tomography/computed tomography resulted in a changed surgical management in 10.6% of cases in a selected cohort.
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| 46. |
- Jonsson, Per, et al.
(författare)
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Formation of Blood Foam in the Air Trap During Hemodialysis Due to Insufficient Automatic Priming of Dialyzers
- 2018
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Ingår i: Artificial Organs. - : Wiley. - 0160-564X .- 1525-1594. ; 42:5, s. 533-539
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Tidskriftsartikel (refereegranskat)abstract
- We were encouraged to investigate the reasons for large amounts of foam observed in bloodlines during hemodialysis (HD). Foam was visible in the venous air trap within the Artis Gambro dialysis device. Estimates of the extent of foam were graded (0no foam, 10extensive foam) by two persons that were blind to the type of dialyzer used. Thirty-seven patients were involved in the dialysis procedures. Consecutive dialyses were graded using dialyzers from Fresenius Medical Care (CorDiax dialyzers that were used for high flux HDFX80 and FX100, and for hemodiafiltrationFX1000). The extracorporeal circuit was primed automatically by dialysate using Gambro Artis software 8.15 006 (Gambro, Dasco, Medolla Italy, Baxter, Chicago, IL, USA). The priming volume recommended by the manufacturer was 1100 mL, whereas our center uses 1500 mL. Extensive amounts of blood foam were visual in the air traps. Although the manufacturer recommended extension of priming volume up to 3000 mL, this did not eliminate the foam. Microbubble measurement during HD revealed the air to derive from the dialyzers. When changing to PF210H dialyzers (Baxter) and using a priming volume of 1500 mL, the foam was significantly less (P<0.01). The extent of foam correlated with the size of the FX-dialyzer surface (P=0.002). The auto-priming program was updated to version 8.21 by the manufacturer and the extent of foam in the air trap using FX dialyzers was now reduced and there was no longer a difference between FX and PF dialyzers, although less foam was still visible in the venous air trap during several dialyses. In conclusion, this study urgently calls attention to blood foam development in the venous air trap when using Artis devices and priming software 8.15 in combination with Fresenius dialyzers. Updated auto-priming software (version 8.21) of Artis should be requested to reduce the extent of foam for the Fresenius dialyzers. Other interactions may also be present. We recommend further studies to clarify these problems. Meanwhile caution is warranted for the combined use of dialysis devices and dialyzers with incompatible automatic priming.
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| 47. |
- Kuttner, Samuel, et al.
(författare)
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Cerebral blood flow measurements with 15O-water PET using a non-invasive machine-learning-derived arterial input function
- 2021
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Ingår i: Journal of Cerebral Blood Flow and Metabolism. - : Sage Publications. - 0271-678X .- 1559-7016. ; 41:9, s. 2229-2241
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Tidskriftsartikel (refereegranskat)abstract
- Cerebral blood flow (CBF) can be measured with dynamic positron emission tomography (PET) of 15O-labeled water by using tracer kinetic modelling. However, for quantification of regional CBF, an arterial input function (AIF), obtained from arterial blood sampling, is required. In this work we evaluated a novel, non-invasive approach for input function prediction based on machine learning (MLIF), against AIF for CBF PET measurements in human subjects. Twenty-five subjects underwent two 10 min dynamic 15O-water brain PET scans with continuous arterial blood sampling, before (baseline) and following acetazolamide medication. Three different image-derived time-activity curves were automatically segmented from the carotid arteries and used as input into a Gaussian process-based AIF prediction model, considering both baseline and acetazolamide scans as training data. The MLIF approach was evaluated by comparing AIF and MLIF curves, as well as whole-brain grey matter CBF values estimated by kinetic modelling derived with either AIF or MLIF.The results showed that AIF and MLIF curves were similar and that corresponding CBF values were highly correlated and successfully differentiated before and after acetazolamide medication. In conclusion, our non-invasive MLIF method shows potential to replace the AIF obtained from blood sampling for CBF measurements using 15O-water PET and kinetic modelling.
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| 48. |
- Kuttner, Samuel, et al.
(författare)
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Machine learning derived input-function in a dynamic 18F-FDG PET study of mice
- 2020
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Ingår i: Biomedical Engineering & Physics Express. - : Institute of Physics Publishing (IOPP). - 2057-1976. ; 6:1
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Tidskriftsartikel (refereegranskat)abstract
- Tracer kinetic modelling, based on dynamic 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) is used to quantify glucose metabolism in humans and animals. Knowledge of the arterial input-function (AIF) is required for such measurements. Our aim was to explore two non-invasive machine learning-based models, for AIF prediction in a small-animal dynamic FDG PET study. 7 tissue regions were delineated in images from 68 FDG PET/computed tomography mouse scans. Two machine learning-based models were trained for AIF prediction, based on Gaussian processes (GP) and a long short-term memory (LSTM) recurrent neural network, respectively. Because blood data were unavailable, a reference AIF was formed by fitting an established AIF model to vena cava and left ventricle image data. The predicted and reference AIFs were compared by the area under curve (AUC) and root mean square error (RMSE). Net-influx rate constants, Ki , were calculated with a two-tissue compartment model, using both predicted and reference AIFs for three tissue regions in each mouse scan, and compared by means of error, ratio, correlation coefficient, P value and Bland-Altman analysis. The impact of different tissue regions on AIF prediction was evaluated by training a GP and an LSTM model on subsets of tissue regions, and calculating the RMSE between the reference and the predicted AIF curve. Both models generated AIFs with AUCs similar to reference. The LSTM models resulted in lower AIF RMSE, compared to GP. Ki from both models agreed well with reference values, with no significant differences. Myocardium was highlighted as important for AIF prediction, but AIFs with similar RMSE were obtained also without myocardium in the input data. Machine learning can be used for accurate and non-invasive prediction of an image-derived reference AIF in FDG studies of mice. We recommend the LSTM approach, as this model predicts AIFs with lower errors, compared to GP.
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| 49. |
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