Measuring Annual Sedimentation through High Accuracy UAV-Photogrammetry Data and Comparison with RUSLE and PESERA Erosion Models

Model-based soil erosion studies have increased in number, given the availability of geodata and the recent technological advances. However, their accuracy remains rather questionable since the scarcity of field records hinders the validation of simulated values. In this context, this study aims to present a method for measuring sediment deposition at a typical Mediterranean catchment (870 ha) in Greece through high spatial resolution field measurements acquired by an Unmanned Aerial Vehicle (UAV) survey. Three-dimensional modeling is considered to be an emerging technique for surface change detection. The UAV-derived point cloud comparison, applying the Structure-from-Motion (SfM) technique at the Platana sediment retention dam test site, quantified annual topsoil change in cm-scale accuracy (0.02–0.03 m), delivering mean sediment yield of 1620 m3 ± 180 m3 or 6.05 t ha−1yr−1 and 3500 m3 ± 194 m3 or 13 t ha−1yr−1 for the 2020–2021 and 2021–2022 estimation. Moreover, the widely applied PESERA and RUSLE models estimated the 2020–2021 mean sediment yield at 1.12 t ha−1yr−1 and 3.51 t ha−1yr−1, respectively, while an increase was evident during the 2021–2022 simulation (2.49 t ha−1yr−1 and 3.56 t ha−1yr−1, respectively). Both applications appear to underestimate the net soil loss rate, with RUSLE being closer to the measured results. The difference is mostly attributed to the model’s limitation to simulate gully erosion or to a C-factor misinterpretation. To the authors’ better knowledge, this study is among the few UAV applications employed to acquire high-accuracy soil loss measurements. The results proved extremely useful in our attempt to measure sediment yield at the cm scale through UAV-SfM and decipher the regional soil erosion and sediment transport pattern, also offering a direct assessment of the retention dams’ life expectancy.Greece and the European UnionPeer Reviewe

Image Reconstruction Analysis for Positron Emission Tomography with Heterostructured Scintillators

The concept of structure engineering has been proposed for exploring the next generation of radiation detectors with improved performance. A TOF-PET geometry with heterostructured scintillators with a pixel size of 3.0x3.1x15 mm3 was simulated using Monte Carlo. The heterostructures consisted of alternating layers of BGO as a dense material with high stopping power and plastic (EJ232) as a fast light emitter. The detector time resolution was calculated as a function of the deposited and shared energy in both materials on an event-by-event basis. While sensitivity was reduced to 32% for 100 μm thick plastic layers and 52% for 50 μm, the CTR distribution improved to 204±49 ps and 220±41 ps respectively, compared to 276 ps that we considered for bulk BGO. The complex distribution of timing resolutions was accounted for in the reconstruction. We divided the events into three groups based on their CTR and modeled them with different Gaussian TOF kernels. On a NEMA IQ phantom, the heterostructures had better contrast recovery in early iterations. On the other hand, BGO achieved a better contrast to noise ratio (CNR) after the 15th iteration due to the higher sensitivity. The developed simulation and reconstruction methods constitute new tools for evaluating different detector designs with complex time responses

Monte Carlo simulations of the GE Signa PET/MR for different radioisotopes

NEMA characterization of PET systems is generally based on(18)F because it is the most relevant radioisotope for the clinical use of PET.F-18 has a half-life of 109.7 min and decays into stable(18)O via beta+ emission with a probability of over 96% and a maximum positron energy of 0.633 MeV. Other commercially available PET radioisotopes, such as(82)Rb and(68)Ga have more complex decay schemes with a variety of prompt gammas, which can directly fall into the energy window and induce false coincidence detections by the PET scanner. Methods Aim of this work was three-fold: (A) Develop a GATE model of the GE Signa PET/MR to perform realistic and relevant Monte Carlo simulations (B) Validate this model with published sensitivity and Noise Equivalent Count Rate (NECR) data for(18)F and(68)Ga (C) Use the validated GATE-model to predict the system performance for other PET isotopes including(11)C,O-15,N-13,Rb-82, and(68)Ga and to evaluate the effect of a 3T magnetic field on the positron range. Results Simulated sensitivity and NECR tests performed with the GATE-model for different radioisotopes were in line with literature values. Simulated sensitivities for(18)F and(68)Ga were 21.2 and 19.0/kBq, respectively, for the center position and 21.1 and 19.0 cps/kBq, respectively, for the 10 cm off-center position compared to the corresponding measured values of 21.8 and 20.0 cps/kBq for the center position and 21.1 and 19.6 cps/kBq for the 10 cm off-center position. In terms of NECR, the simulated peak NECR was 216.8 kcps at 17.40 kBq/ml for(18)F and 207.1 kcps at 20.10 kBq/ml for(68)Ga compared to the measured peak NECR of 216.8 kcps at 18.60 kBq/ml and 205.6 kcps at 20.40 kBq/ml for(18)F and(68)Ga, respectively. For(11)C,N-13, and(15)O, results confirmed a peak NECR similar to(18)F with the effective activity concentration scaled by the inverse of the positron fraction. For(82)Rb, and(68)Ga, the peak NECR was lower than for(18)F while the corresponding activity concentrations were higher. For the higher energy positron emitters, the positron range was confirmed to be tissue-dependent with a reduction of the positron range by a factor of 3 to 4 in the plane perpendicular to the magnetic field and an increased positron range along the direction of the magnetic field. Conclusion Monte-Carlo simulations were used to predict sensitivity and NECR performance of GE Signa PET/MR for(18)F,O-15,N-13,C-11,Rb-82, and(68)Ga radioisotopes and were in line with literature data. Simulations confirmed that sensitivity and NECR were influenced by the particular decay scheme of each isotope. As expected, the positron range decreased in the direction perpendicular to the 3T magnetic field. However, this will be only partially improving the resolution properties of a clinical PET/MR system due to the limiting spatial resolution of the PET detector

Spill-in counts in the quantification of 18 F-florbetapir on Aβ-negative subjects: the effect of including white matter in the reference region

Background: We aim to provide a systematic study of the impact of white matter (WM) spill-in on the calculation of standardized uptake value ratios (SUVRs) on Aβnegative subjects, and we study the effect of including WM in the reference region as a compensation. In addition, different partial volume correction (PVC) methods are applied and evaluated. Methods: We evaluated magnetic resonance imaging and 18F-AV-45 positron emission tomography data from 122 cognitively normal (CN) patients recruited at the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Cortex SUVRs were obtained by using the cerebellar grey matter (CGM) (SUVRCGM) and the whole cerebellum (SUVRWC) as reference regions. The correlations between the different SUVRs and the WM uptake (WM-SUVRCGM) were studied in patients, and in a well-controlled framework based on Monte Carlo (MC) simulation. Activity maps for the MC simulation were derived from ADNI patients by using a voxel-wise iterative process (BrainViset). Ten WM uptakes covering the spectrum of WM values obtained from patient data were simulated for different patients. Three different PVC methods were tested (a) the regional voxel-based (RBV), (b) the iterative Yang (iY), and (c) a simplified analytical correction derived from our MC simulation. Results: WM-SUVRCGM followed a normal distribution with an average of 1.79 and a standard deviation of 0.243 (13.6%). SUVRCGM was linearly correlated to WM-SUVRCGM (r = 0.82, linear fit slope = 0.28). SUVRWC was linearly correlated to WM-SUVRCGM (r = 0.64, linear fit slope = 0.13). Our MC results showed that these correlations are compatible with those produced by isolated spill-in effect (slopes of 0.23 and 0.11). The impact of the spill-in was mitigated by using PVC for SUVRCGM (slopes of 0.06 and 0.07 for iY and RBV), while SUVRWC showed a negative correlation with SUVRCGM after PVC. The proposed analytical correction also reduced the observed correlations when applied to patient data (r = 0.27 for SUVRCGM, r = 0.18 for SUVRWC). Conclusions: There is a high correlation between WM uptake and the measured SUVR due to spill-in effect, and that this effect is reduced when including WM in the reference region. We also evaluated the performance of PVC, and we proposed an analytical correction that can be applied to preprocessed data.This work was partially supported by the project PI16/01416 (ISCIII co-funded FEDER) and RYC-2015/17430(Ramón y Cajal, PA)S

SIRF: Synergistic Image Reconstruction Framework

The combination of positron emission tomography (PET) with magnetic resonance (MR) imaging opens the way to more accurate diagnosis and improved patient management. At present, the data acquired by PET-MR scanners are essentially processed separately, but the opportunity to improve accuracy of the tomographic reconstruction via synergy of the two imaging techniques is an active area of research. In this paper, we present Release 2.1.0 of the CCP-PETMR Synergistic Image Reconstruction Framework (SIRF) software suite, providing an open-source software platform for efficient implementation and validation of novel reconstruction algorithms. SIRF provides user-friendly Python and MATLAB interfaces built on top of C++ libraries. SIRF uses advanced PET and MR reconstruction software packages and tools. Currently, for PET this is Software for Tomographic Image Reconstruction (STIR); for MR, Gadgetron and ISMRMRD; and for image registration tools, NiftyReg. The software aims to be capable of reconstructing images from acquired scanner data, whilst being simple enough to be used for educational purposes

SIRF: Synergistic Image Reconstruction Framework

The combination of positron emission tomography (PET) with magnetic resonance (MR) imaging opens the way to more accurate diagnosis and improved patient management. At present, the data acquired by PET-MR scanners are essentially processed separately, but the opportunity to improve accuracy of the tomographic reconstruction via synergy of the two imaging techniques is an active area of research. In this paper, we present Release 2.1.0 of the CCP-PETMR Synergistic Image Reconstruction Framework (SIRF) software suite, providing an open-source software platform for efficient implementation and validation of novel reconstruction algorithms. SIRF provides user-friendly Python and MATLAB interfaces built on top of C++ libraries. SIRF uses advanced PET and MR reconstruction software packages and tools. Currently, for PET this is Software for Tomographic Image Reconstruction (STIR); for MR, Gadgetron and ISMRMRD; and for image registration tools, NiftyReg. The software aims to be capable of reconstructing images from acquired scanner data, whilst being simple enough to be used for educational purposes. The most recent version of the software can be downloaded from http://www.ccppetmr.ac.uk/downloads and https://github.com/CCPPETMR/. Program summary: Program Title: Synergistic Image Reconstruction Framework (SIRF) Program Files DOI: http://dx.doi.org/10.17632/s45f5jh55j.1 Licensing provisions: GPLv3 and Apache-2.0 Programming languages: C++, C, Python, MATLAB Nature of problem: In current practice, data acquired by PET-MR scanners are processed separately. Methods for improving the accuracy of the tomographic reconstruction using the synergy of the two imaging techniques are actively being investigated by the PET-MR research and development community, however, practical application is heavily reliant on software. Open-source software available to the PET-MR community – such as the PET package (STIR) (Thielemans et al., 2012) and the MR package Gadgetron (Hansen and Sørensen, 2013) – provide a basis for new synergistic PET-MR software. However, these two software packages are independent and have very different software architectures. They are mostly written in C++ but many researchers in the PET-MR community are more familiar with script-style languages, such as Python and MATLAB, which enable rapid prototyping of novel reconstruction algorithms. In the current situation it is difficult for researchers to exploit any synergy between PET and MR data. Furthermore, techniques from one field cannot easily be applied in the other. Solution method: In SIRF, the bulk of computation is performed by available advanced open-source reconstruction and registration software (currently STIR, Gadgetron and NiftyReg) that can use multithreading and GPUs. The SIRF C++ code provides a thin layer on top of these existing libraries. The SIRF layer has unified data-containers and access mechanisms. This C++ layer provides the basis for a simple and intuitive Python and MATLAB interface, enabling users to quickly develop and test their reconstruction algorithms using these scripting languages only. At the same time, advanced users proficient in C++ can directly utilise wider SIRF functionality via the SIRF C++ libraries that we provide

Investigating the Correlation of Tectonic and Morphometric Characteristics with the Hydrological Response in a Greek River Catchment Using Earth Observation and Geospatial Analysis Techniques

Morphometric analysis can be used to investigate catchment dynamics and tectonic processes responsible for the development of drainage catchments and to support flood risk assessment. In this study, a comparative GIS-based morphometric analysis between the main southern and northern sub-catchments of the Sperchios River basin, Central Greece, was performed, using geospatial and remote sensing data. The goal was to investigate their correlation with the peculiar geotectonic activity and the frequent flash-flood events that occur in the river floodplain. All sub-catchments characteristics are linked with the geological formation types of the area, in combination with ongoing tectonic activity. The results indicate that drainage network development is significantly controlled by the region’s overall tectonic activity. The morphometric characteristics—i.e., bifurcation ratio, drainage density, circularity ratio, elongation ratio and water concentration–time values, reflect the flood-prone character of the southern part of Sperchios River catchment in comparison to the northern part, especially during intense rainfall events. The study can provide valuable insight into identifying how morphometric characteristics are associated with increased flood hazard

Combined study on clastogenic, aneugenic and apoptotic properties of doxorubicin in human cells in vitro

Abstract Background Doxorubicin is a widely used anticancer drug due to its broad spectrum of antitumor activity. Various mechanisms have been proposed for its cytostatic activity, including DNA intercalation, topoisomerase II inhibition, generation of free radicals and apoptosis. The present study aims to further clarify the cytostatic activity of doxorubicin by its specific effect on (a) DNA damage, (b) micronucleation and (c) apoptosis, using a combination of different methods and cell systems such as human lymphocytes and HL-60 human leukemic cells. DNA lesions were analyzed by the alkaline comet assay in combination with formamidopyrimidine (Fpg) and human 8-oxoguanine (hOGG1) repair enzymes. Micronucleation was investigated by the Cytokinesis-Block Micronucleus assay (CBMN) in combination with Fluorescence In Situ Hybridization analysis. Impairment on mitotic apparatus was investigated by double immunofluorescence of β- and γ-tubulin. Apoptotic cell frequency was determined by the CBMN cytome assay. Complementary to the above, caspase-3 level was investigated by Western blot. Results It was found that doxorubicin generates DNA breakage induced by oxidative damage in DNA bases, which can be repaired by the Fpg and hOGG1 enzymes. Increased micronucleus frequency was identified mainly through chromosome breakage and, at a lesser extent, through chromosome delay. Analysis of mitotic spindle showed disturbance of chromosome orientation and centrosome duplication and/or separation, leading to aneuploidy. Enhanced frequency of apoptotic leukemic cells was also observed. Caspase-3 seems to be involved in the generation of apoptosis. Conclusions The aforementioned findings derived from different treatment schedules, doses and time of exposure on primary versus transformed cells extend our knowledge about doxorubicin genotoxicity and contribute to the better understanding of the mechanisms by which doxorubicin induces genotoxic effects on human cells

Time-Of-Flight PET Image Reconstruction with Complex Timing Kernels: The Case of BGO Cherenkov Photons

Time-of-Flight (TOF) reconstruction in Positron Emission Tomographic (PET) scanners uses a single kernel to reconstruct all events. However, recently developed detectors combining prompt emission and typical scintillation signal produce output events with different timing spreads. One such detectors technology is based on BGO crystals with Cherenkov photons. Thanks to fast silicon photo-multipliers sensitive in the near-ultraviolet and high-frequency electronic readout, the faint Cherenkov signal produced by the interaction of 511 keV gamma photons can be detected as faster pulse rise times. We present initial results from a Monte Carlo simulation and image reconstruction platform for detectors with multiple timing resolutions in this work. Simulated timing spreads show excellent agreement with the experimental measurements. In addition, the reconstruction software can reconstruct images using listmode and projection data. In terms of contrast recovery, the proposed multi-kernel model with BGO-Cherenkov detectors presents a similar recovery as a typical Gaussian model with LYSO detectors and timing resolution 213 ps. To the best of our knowledge, the use of multiple complex TOF kernels in image reconstruction has not been investigated in the past. However, further optimisations are needed in order to obtain the best possible results

TOF-PET image reconstruction with multiple timing kernels applied on Cherenkov radiation in BGO

Today Time-Of-Flight (TOF), in PET scanners, assumes a single, well-defined timing resolution for all events. However, recent BGO-Cherenkov detectors, combining prompt Cherenkov emission and the typical BGO scintillation, can sort events into multiple timing kernels, best described by Gaussian mixture models. The number of Cherenkov photons detected per event impacts directly the detector time resolution and signal rise time, which can later be used to improve the coincidence timing resolution. This work presents a simulation toolkit which applies multiple timing spreads on the coincident events and an image reconstruction that incorporates this information. A full cylindrical BGO-Cherenkov PET model was compared, in terms of contrast recovery and contrast-to-noise ratio, against an LYSO model with a time resolution of 213 ps. Two reconstruction approaches for the mixture kernels were tested; mixture Gaussian and decomposed simple Gaussian kernels. The decomposed model used the exact mixture component applied during the simulation. Images reconstructed using mixture kernels provided similar mean value and less noise than the decomposed. However, typically, more iterations were needed. Similarly, the LYSO model, with a single TOF kernel, converged faster than the BGO-Cherenkov with multiple kernels. The results indicate that model complexity slows down convergence. However, due to the higher sensitivity, the contrast-to-noise ratio was 26.4% better for the BGO model