Tritium and radiocarbon in the water column of the Red Sea.

Despite being the busiest transient sea in the world due to the Suez Canal, radionuclide distribution studies in seawater and sediment of the Red Sea remain rare. A sampling expedition in the Red Sea was conducted from June 9 to July 6, 2021, visiting a transect of several deep sampling stations located along the central axis of the basin from the Gulf of Aqaba to the southern Red Sea (near Farasan Island, Saudi Arabia). The collected seawater profile samples were analyzed for tritium, radiocarbon and oxygen-18. The observed tritium levels in surface waters of the Red Sea peaked at 0.3-0.4 TU, similar to the values observed in the western Arabian Sea (decay corrected). The values observed at waters below 150 m were around 0.2 TU, however, at depths of 450 and 750 m, tritium minima (<0.2 TU) were observed, which could be associated with a partial return flow of bottom waters from the southern to the northern Red Sea. At two stations at the depth of about 550 m, deep Δ14C minima were observed as well (-4‰ and -10‰), documenting ongoing transport of carbon in the water column, important for sink of anthropogenic carbon.

Advanced quantitative evaluation of PET systems using the ACR phantom and NiftyPET software.

PURPOSE: A novel phantom-imaging platform, a set of software tools, for automated and high-precision imaging of the American College of Radiology (ACR) positron emission tomography (PET) phantom for PET/magnetic resonance (PET/MR) and PET/computed tomography (PET/CT) systems is proposed. METHODS: The key feature of this platform is the vector graphics design that facilitates the automated measurement of the knife-edge response function and hence image resolution, using composite volume of interest templates in a 0.5 mm resolution grid applied to all inserts of the phantom. Furthermore, the proposed platform enables the generation of an accurate µ $\mu$ -map for PET/MR systems with a robust alignment based on two-stage image registration using specifically designed PET templates. The proposed platform is based on the open-source NiftyPET software package used to generate multiple list-mode data bootstrap realizations and image reconstructions to determine the precision of the two-stage registration and any image-derived statistics. For all the analyses, iterative image reconstruction was employed with and without modeled shift-invariant point spread function and with varying iterations of the ordered subsets expectation maximization (OSEM) algorithm. The impact of the activity outside the field of view (FOV) was assessed using two acquisitions of 30 min each, with and without the activity outside the FOV. RESULTS: The utility of the platform has been demonstrated by providing a standard and an advanced phantom analysis including the estimation of spatial resolution using all cylindrical inserts. In the imaging planes close to the edge of the axial FOV, we observed deterioration in the quantitative accuracy, reduced resolution (FWHM increased by 1-2 mm), reduced contrast, and background uniformity due to the activity outside the FOV. Although it slows convergence, the PSF reconstruction had a positive impact on resolution and contrast recovery, but the degree of improvement depended on the regions. The uncertainty analysis based on bootstrap resampling of raw PET data indicated high precision of the two-stage registration. CONCLUSIONS: We demonstrated that phantom imaging using the proposed methodology with the metric of spatial resolution and multiple bootstrap realizations may be helpful in more accurate evaluation of PET systems as well as in facilitating fine tuning for optimal imaging parameters in PET/MR and PET/CT clinical research studies.