Symbolic innovation at the onset of the Upper Paleolithic in Eurasia shown by the personal ornaments from Tolbor-21 (Mongolia).

Figurative depictions in art first occur ca. 50,000 years ago in Europe, Africa, and Southeast Asia. Considered by most as an advanced form of symbolic behavior, they are restricted to our species. Here, we report a piece of ornament interpreted as a phallus-like representation. It was found in a 42,000 ca.-year-old Upper Paleolithic archaeological layer at the open-air archaeological site of Tolbor-21, in Mongolia. Mineralogical, microscopic, and rugosimetric analyses points toward the allochthonous origin of the pendant and a complex functional history. Three-dimensional phallic pendants are unknown in the Paleolithic record, and this discovery predates the earliest known sexed anthropomorphic representation. It attests that hunter-gatherer communities used sex anatomical attributes as symbols at a very early stage of their dispersal in the region. The pendant was produced during a period that overlaps with age estimates for early introgression events between Homo sapiens and Denisovans, and in a region where such encounters are plausible.

Denoising non-steady state dynamic PET data using a feed-forward neural network.

The quality of reconstructed dynamic PET images, as well as the statistical reliability of the estimated pharmacokinetic parameters is often compromised by high levels of statistical noise, particularly at the voxel level. Many denoising strategies have been proposed, both in the temporal and spatial domain, which substantially improve the signal to noise ratio of the reconstructed dynamic images. However, although most filtering approaches are fairly successful in reducing the spatio-temporal inter-voxel variability, they may also average out or completely eradicate the critically important temporal signature of a transient neurotransmitter activation response that may be present in a non-steady state dynamic PET study. In this work, we explore an approach towards temporal denoising of non-steady state dynamic PET images using an artificial neural network, which was trained to identify the temporal profile of a time-activity curve, while preserving any potential activation response. We evaluated the performance of a feed-forward perceptron neural network to improve the signal to noise ratio of dynamic [11C]raclopride activation studies and compared it with the widely used highly constrained back projection (HYPR) filter. Results on both simulated Geant4 Application for Tomographic Emission data of a realistic rat brain phantom and experimental animal data of a freely moving animal study showed that the proposed neural network can efficiently improve the noise characteristics of dynamic data in the temporal domain, while it can lead to a more reliable estimation of voxel-wise activation response in target region. In addition, improvements in signal-to-noise ratio achieved by denoising the dynamic data using the proposed neural network led to improved accuracy and precision of the estimated model parameters of the lp-ntPET model, compared to the HYPR filter. The performance of the proposed denoising approach strongly depends on the amount of noise in the dynamic PET data, with higher noise leading to substantially higher variability in the estimated parameters of the activation response. Overall, the feed-forward network led to a similar performance as the HYPR filter in terms of spatial denoising, but led to notable improvements in terms of temporal denoising, which in turn improved the estimation activation parameters.

Semi-supervised labelling of the femur in a whole-body post-mortem CT database using deep learning.

A deep learning pipeline was developed and used to localize and classify a variety of implants in the femur contained in whole-body post-mortem computed tomography (PMCT) scans. The results provide a proof-of-principle approach for labelling content not described in medical/autopsy reports. The pipeline, which incorporated residual networks and an autoencoder, was trained and tested using n = 450 full-body PMCT scans. For the localization component, Dice scores of 0.99, 0.96, and 0.98 and mean absolute errors of 3.2, 7.1, and 4.2 mm were obtained in the axial, coronal, and sagittal views, respectively. A regression analysis found the orientation of the implant to the scanner axis and also the relative positioning of extremities to be statistically significant factors. For the classification component, test cases were properly labelled as nail (N+), hip replacement (H+), knee replacement (K+) or without-implant (I-) with an accuracy >97%. The recall for I- and H+ cases was 1.00, but fell to 0.82 and 0.65 for cases with K+ and N+. This semi-automatic approach provides a generalized structure for image-based labelling of features, without requiring time-consuming segmentation.

Populations dynamics in Northern Eurasian forests: a long-term perspective from Northeast Asia.

The 'Northern Eurasian Greenbelt' (NEG) is the northern forest zone stretching from the Japanese Archipelago to Northern Europe. The NEG has created highly productive biomes for humanity to exploit since the end of the Pleistocene. This research explores how the ecological conditions in northern Eurasia contributed to and affected human migrations and cultural trajectories by synthesizing the complimentary viewpoints of environmental archaeology, Geographic Information Science (GIS), genetics and linguistics. First, the environmental archaeology perspective raises the possibility that the NEG functioned as a vessel fostering people to develop diverse cultures and engage in extensive cross-cultural exchanges. Second, geographical analysis of genomic data on mitochondrial DNA using GIS reveals the high probability that population dynamics in the southeastern NEG promoted the peopling of the Americas at the end of the Pleistocene. Finally, a linguistic examination of environmental- and landscape-related vocabulary of the proto-Turkic language groups enables the outline of their original cultural landscape and natural conditions, demonstrating significant cultural spheres, i.e. from southern Siberia to eastern Inner Mongolia during Neolithization. All of these results combine to suggest that the ecological complex in the southern edge of the NEG in northeast Asia played a significant role in peopling across the continents during prehistory.

The Northern Route for Human dispersal in Central and Northeast Asia: New evidence from the site of Tolbor-16, Mongolia.

The fossil record suggests that at least two major human dispersals occurred across the Eurasian steppe during the Late Pleistocene. Neanderthals and Modern Humans moved eastward into Central Asia, a region intermittently occupied by the enigmatic Denisovans. Genetic data indicates that the Denisovans interbred with Neanderthals near the Altai Mountains (South Siberia) but where and when they met H. sapiens is yet to be determined. Here we present archaeological evidence that document the timing and environmental context of a third long-distance population movement in Central Asia, during a temperate climatic event around 45,000 years ago. The early occurrence of the Initial Upper Palaeolithic, a techno-complex whose sudden appearance coincides with the first occurrence of H. sapiens in the Eurasian steppes, establishes an essential archaeological link between the Siberian Altai and Northwestern China . Such connection between regions provides empirical ground to discuss contacts between local and exogenous populations in Central and Northeast Asia during the Late Pleistocene.

Rigid motion correction of dual opposed planar projections in single photon imaging.

Awake and/or freely moving small animal single photon emission imaging allows the continuous study of molecules exhibiting slow kinetics without the need to restrain or anaesthetise the animals. Estimating motion free projections in freely moving small animal planar imaging can be considered as a limited angle tomography problem, except that we wish to estimate the 2D planar projections rather than the 3D volume, where the angular sampling in all three axes depends on the rotational motion of the animal. In this study, we hypothesise that the motion corrected planar projections estimated by reconstructing an estimate of the 3D volume using an iterative motion compensating reconstruction algorithm and integrating it along the projection path, will closely match the true, motion-less, planar distribution regardless of the object motion. We tested this hypothesis for the case of rigid motion using Monte-Carlo simulations and experimental phantom data based on a dual opposed detector system, where object motion was modelled with 6 degrees of freedom. In addition, we investigated the quantitative accuracy of the regional activity extracted from the geometric mean of opposing motion corrected planar projections. Results showed that it is feasible to estimate qualitatively accurate motion-corrected projections for a wide range of motions around all 3 axes. Errors in the geometric mean estimates of regional activity were relatively small and within 10% of expected true values. In addition, quantitative regional errors were dependent on the observed motion, as well as on the surrounding activity of overlapping organs. We conclude that both qualitatively and quantitatively accurate motion-free projections of the tracer distribution in a rigidly moving object can be estimated from dual opposed detectors using a correction approach within an iterative reconstruction framework and we expect this approach can be extended to the case of non-rigid motion.

Polarisation-based coincidence event discrimination: an in silico study towards a feasible scheme for Compton-PET.

Current positron emission tomography (PET) systems use temporally localised coincidence events discriminated by energy and time-of-flight information. The two annihilation photons are in an entangled polarisation state and, in principle, additional information from the polarisation correlation of photon pairs could be used to improve the accuracy of coincidence classification. In a previous study, we demonstrated that in principle, the polarisation correlation information could be transferred to an angular correlation in the distribution of scattered photon pairs in a planar Compton camera system. In the present study, we model a source-phantom-detector system using Geant4 and we develop a coincidence classification scheme that exploits the angular correlation of scattered annihilation quanta to improve the accuracy of coincidence detection. We find a [Formula: see text] image quality improvement in terms of the peak signal-to-noise ratio when scattered coincidence events are discriminated solely by their angular correlation, thus demonstrating the feasibility of this novel classification scheme. By integrating scatter events (both single-single and single-only) with unscattered coincidence events discriminated using conventional methods, our results suggest that Compton-PET may be a promising candidate for optimal emission tomographic imaging.

Experimental evaluation of the resolution improvement provided by a silicon PET probe.

A high-resolution PET system, which incorporates a silicon detector probe into a conventional PET scanner, has been proposed to obtain increased image quality in a limited region of interest. Detailed simulation studies have previously shown that the additional probe information improves the spatial resolution of the reconstructed image and increases lesion detectability, with no cost to other image quality measures. The current study expands on the previous work by using a laboratory prototype of the silicon PET-probe system to examine the resolution improvement in an experimental setting. Two different versions of the probe prototype were assessed, both consisting of a back-to-back pair of 1-mm thick silicon pad detectors, one arranged in 32 × 16 arrays of 1.4 mm × 1.4 mm pixels and the other in 40 × 26 arrays of 1.0 mm × 1.0 mm pixels. Each detector was read out by a set of VATAGP7 ASICs and a custom-designed data acquisition board which allowed trigger and data interfacing with the PET scanner, itself consisting of BGO block detectors segmented into 8 × 6 arrays of 6 mm × 12 mm × 30 mm crystals. Limited-angle probe data was acquired from a group of Na-22 point-like sources in order to observe the maximum resolution achievable using the probe system. Data from a Derenzo-like resolution phantom was acquired, then scaled to obtain similar statistical quality as that of previous simulation studies. In this case, images were reconstructed using measurements of the PET ring alone and with the inclusion of the probe data. Images of the Na-22 source demonstrated a resolution of 1.5 mm FWHM in the probe data, the PET ring resolution being approximately 6 mm. Profiles taken through the image of the Derenzo-like phantom showed a clear increase in spatial resolution. Improvements in peak-to-valley ratios of 50% and 38%, in the 4.8 mm and 4.0 mm phantom features respectively, were observed, while previously unresolvable 3.2 mm features were brought to light by the addition of the probe. These results support the possibility of improving the image resolution of a clinical PET scanner using the silicon PET-probe.

Evaluation of resistive-plate-chamber-based TOF-PET applied to in-beam particle therapy monitoring.

Particle therapy is a highly conformal radiotherapy technique which reduces the dose deposited to the surrounding normal tissues. In order to fully exploit its advantages, treatment monitoring is necessary to minimize uncertainties related to the dose delivery. Up to now, the only clinically feasible technique for the monitoring of therapeutic irradiation with particle beams is Positron Emission Tomography (PET). In this work we have compared a Resistive Plate Chamber (RPC)-based PET scanner with a scintillation-crystal-based PET scanner for this application. In general, the main advantages of the RPC-PET system are its excellent timing resolution, low cost, and the possibility of building large area systems. We simulated a partial-ring scanner based on an RPC prototype under construction within the Fondazione per Adroterapia Oncologica (TERA). For comparison with the crystal-based PET scanner we have chosen the geometry of a commercially available PET scanner, the Philips Gemini TF. The coincidence time resolution used in the simulations takes into account the current achievable values as well as expected improvements of both technologies. Several scenarios (including patient data) have been simulated to evaluate the performance of different scanners. Initial results have shown that the low sensitivity of the RPC hampers its application to hadron-beam monitoring, which has an intrinsically low positron yield compared to diagnostic PET. In addition, for in-beam PET there is a further data loss due to the partial ring configuration. In order to improve the performance of the RPC-based scanner, an improved version of the RPC detector (modifying the thickness of the gas and glass layers), providing a larger sensitivity, has been simulated and compared with an axially extended version of the crystal-based device. The improved version of the RPC shows better performance than the prototype, but the extended version of the crystal-based PET outperforms all other options.

Noise evaluation of Compton camera imaging for proton therapy.

Compton Cameras emerged as an alternative for real-time dose monitoring techniques for Particle Therapy (PT), based on the detection of prompt-gammas. As a consequence of the Compton scattering process, the gamma origin point can be restricted onto the surface of a cone (Compton cone). Through image reconstruction techniques, the distribution of the gamma emitters can be estimated, using cone-surfaces backprojections of the Compton cones through the image space, along with more sophisticated statistical methods to improve the image quality. To calculate the Compton cone required for image reconstruction, either two interactions, the last being photoelectric absorption, or three scatter interactions are needed. Because of the high energy of the photons in PT the first option might not be adequate, as the photon is not absorbed in general. However, the second option is less efficient. That is the reason to resort to spectral reconstructions, where the incoming γ energy is considered as a variable in the reconstruction inverse problem. Jointly with prompt gamma, secondary neutrons and scattered photons, not strongly correlated with the dose map, can also reach the imaging detector and produce false events. These events deteriorate the image quality. Also, high intensity beams can produce particle accumulation in the camera, which lead to an increase of random coincidences, meaning events which gather measurements from different incoming particles. The noise scenario is expected to be different if double or triple events are used, and consequently, the reconstructed images can be affected differently by spurious data. The aim of the present work is to study the effect of false events in the reconstructed image, evaluating their impact in the determination of the beam particle ranges. A simulation study that includes misidentified events (neutrons and random coincidences) in the final image of a Compton Telescope for PT monitoring is presented. The complete chain of detection, from the beam particle entering a phantom to the event classification, is simulated using FLUKA. The range determination is later estimated from the reconstructed image obtained from a two and three-event algorithm based on Maximum Likelihood Expectation Maximization. The neutron background and random coincidences due to a therapeutic-like time structure are analyzed for mono-energetic proton beams. The time structure of the beam is included in the simulations, which will affect the rate of particles entering the detector.