Methanogenesis from methylamines in Methanosarcina barkeri Fusaro

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Characterization of transmission images for use in resolution recovery of cardiac PET imaging

Cardiac PET images suffer from partial volume (PV) losses, a result of motion and limited resolution. A correction can be made using an extravascular (EV) density image, constructed via the subtraction of a blood volume (BV) image from a transmission image (TX, image of tissue density). The ability of the EV image to correct for PV losses is dependent on the noise in the TX image, and by errors in alignment between the TX and BV images. A TX image can be obtained in either a pre-injection or post-injection mode, depending on whether it is taken before or after injection of activity to the subject. The purpose of this study was to determine which TX image best minimizes errors in the EV image. A simple plastic cardiac phantom was used to compare the two TX modes. Calculation and comparison of the centers was used to determine the pre-injection misalignment. Pre-injection offset was -0.33±0.85 mm vertically, and -0.64±0.72 mm horizontally from the post-injection image. A CoV of 0.0231 ±0.004 and 0.0374±0.006 was measured for the pre and post-injection images respectively. These results indicate that the pre-injection TX has the best statistical quality, but provides poor alignment

Involvement of methyltransferase-activating protein and methyltransferase 2 isoenzyme II in methylamine:coenzyme M methyltransferase reactions in Methanosarcina barkeri Fusaro

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Resolution recovery with 3D PET extravascuclar density imaging

Interpretation of FDG PET images is complicated by partial volume (PV) averaging, a result of cardiac motion and limited scanner resolution. An extravascular (EV) density image, created from the subtraction of a blood pool scan from a transmission scan, can be used for correction of PV averaging. Computer simulations were performed to develop this method. The PSF of the scanner was measured and found to be Gaussian with a FWHM of 9.7 mm. Images were subsequently created through convolution of a true activity distribution with the PSF. The simulations showed that the EV density image could perfectly correct for PV effects, and predicted a value of 0.67 g/cc for the EV image, later validated using a cardiac phantom (0.68 +/- 0.016 g/cc). Measurements on a plastic phantom with a constant myocardial thickness of 10 mm were performed to validate the proposed method. A 32% reduction in myocardial activity was found before correction, significantly less than the true value (p<0.001). Application of the EV density image yielded the true myocardial activity (p=ns) after an artifact inherent to phantom studies was accounted for. These results indicate that PV averaging within the myocardium can be accurately corrected using an EV density image

Kinetic model-based factor analysis of dynamic sequences for 82-rubidium cardiac positron emission tomography

Purpose: Factor analysis has been pursued as a means to decompose dynamic cardiac PET images into different tissue types based on their unique temporal signatures to improve quantification of physiological function. In this work, the authors present a novel kinetic model-based (MB) method that includes physiological models of factor relationships within the decomposition process. The physiological accuracy of MB decomposed 82Rb cardiac PET images is evaluated using simulated and experimental data. Precision of myocardial blood flow (MBF) measurement is also evaluated. Methods: A gamma-variate model was used to describe the transport of 82Rb in arterial blood from the right to left ventricle, and a one-compartment model to describe the exchange between blood and myocardium. Simulations of canine and rat heart imaging were performed to evaluate parameter estimation errors. Arterial blood sampling in rats and 11CO blood pool imaging in dogs were used to evaluate factor and structure accuracy. Variable infusion duration studies in canine were used to evaluate MB structure and global MBF reproducibility. All results were compared to a previously published minimal structure overlap (MSO) method. Results: Canine heart simulations demonstrated that MB has lower root-mean-square error (RMSE) than MSO for both factor (0.2% vs 0.5%, p<0.001 MB vs MSO, respectively) and structure (3.0% vs 4.7%, p<0.001) estimations, as with rat heart simulations (factors: 0.2% vs 0.9%, p<0.001 and structures: 3.0% vs 6.7%, p<0.001). MB blood factors compared to arterial blood samples in rats had lower RMSE than MSO (1.6% vs 2.2%, p=0.025). There was no difference in the RMSE of blood structures compared to a 11CO blood pool image in dogs (8.5% vs 8.8%, p=0.23). Myocardial structures were more reproducible with MB than with MSO (RMSE=3.9% vs 6.2%, p<0.001), as were blood structures (RMSE=4.9% vs 5.6%, p=0.006). Finally, MBF values tended to be more reproducible with MB compared to MSO (CV=10% vs 18%, p=0.16). The execution time of MB was, on average, 2.4 times shorter than MSO (p<0.001) due to fewer free parameters. Conclusions: Kinetic model-based factor analysis can be used to provide physiologically accurate decomposition of 82Rb dynamic PET images, and may improve the precision of MBF quantification

The energy metabolism of Methanomicrococcus blatticola: physiological and biochemical aspects

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