Optical to Planar X-ray Mouse Image Mapping in Preclinical Nuclear Medicine Using Conditional Adversarial Networks

In the current work, a pix2pix conditional generative adversarial network has been evaluated as a potential solution for generating adequately accurate synthesized morphological X-ray images by translating standard photographic images of mice. Such an approach will benefit 2D functional molecular imaging techniques, such as planar radioisotope and/or fluorescence/bioluminescence imaging, by providing high-resolution information for anatomical mapping, but not for diagnosis, using conventional photographic sensors. Planar functional imaging offers an efficient alternative to biodistribution ex vivo studies and/or 3D high-end molecular imaging systems since it can be effectively used to track new tracers and study the accumulation from zero point in time post-injection. The superimposition of functional information with an artificially produced X-ray image may enhance overall image information in such systems without added complexity and cost. The network has been trained in 700 input (photography)/ground truth (X-ray) paired mouse images and evaluated using a test dataset composed of 80 photographic images and 80 ground truth X-ray images. Performance metrics such as peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM) and Fréchet inception distance (FID) were used to quantitatively evaluate the proposed approach in the acquired dataset

Artificial intelligence: Deep learning in oncological radiomics and challenges of interpretability and data harmonization

International audienceOver the last decade there has been an extensive evolution in the Artificial Intelligence (AI) field. Modern radiation oncology is based on the exploitation of advanced computational methods aiming to personalization and high diagnostic and therapeutic precision. The quantity of the available imaging data and the increased developments of Machine Learning (ML), particularly Deep Learning (DL), triggered the research on uncovering "hidden" biomarkers and quantitative features from anatomical and functional medical images. Deep Neural Networks (DNN) have achieved outstanding performance and broad implementation in image processing tasks. Lately, DNNs have been considered for radiomics and their potentials for explainable AI (XAI) may help classification and prediction in clinical practice. However, most of them are using limited datasets and lack generalized applicability. In this study we review the basics of radiomics feature extraction, DNNs in image analysis, and major interpretability methods that help enable explainable AI. Furthermore, we discuss the crucial requirement of multicenter recruitment of large datasets, increasing the biomarkers variability, so as to establish the potential clinical value of radiomics and the development of robust explainable AI models

Measurements of neutron cross sections for advanced nuclear energy systems at n_TOF (CERN)

The n_TOF facility operates at CERN with the aim of addressing the request of high accuracy nuclear data for advanced nuclear energy systems as well as for nuclear astrophysics. Thanks to the features of the neutron beam, important results have been obtained on neutron induced fission and capture cross sections of U, Pu and minor actinides. Recently the construction of another beam line has started; the new line will be complementary to the first one, allowing to further extend the experimental program foreseen for next measurement campaigns

Neutron cross-sections for advanced nuclear systems: the n_TOF project at CERN

The study of neutron-induced reactions is of high relevance in a wide variety of fields, ranging from stellar nucleosynthesis and fundamental nuclear physics to applications of nuclear technology. In nuclear energy, high accuracy neutron data are needed for the development of Generation IV fast reactors and accelerator driven systems, these last aimed specifically at nuclear waste incineration, as well as for research on innovative fuel cycles. In this context, a high luminosity Neutron Time Of Flight facility, n_TOF, is operating at CERN since more than a decade, with the aim of providing new, high accuracy and high resolution neutron cross-sections. Thanks to the features of the neutron beam, a rich experimental program relevant to nuclear technology has been carried out so far. The program will be further expanded in the near future, thanks in particular to a new high-flux experimental area, now under construction

238U(n, γ) reaction cross section measurement with C6D6 detectors at the n_TOF CERN facility

The radiative capture cross section of 238U is very important for the developing of new reactor technologies and the safety of existing ones. Here the preliminary results of the 238U(n,γ) cross section measurement performed at n_TOF with C6D6 scintillation detectors are presented, paying particular attention to data reduction and background subtraction

Neutron capture cross section measurement of 238U at the CERN n_TOF facility in the energy region from 1 eV to 700 keV

The aim of this work is to provide a precise and accurate measurement of the 238U(n,γ) reaction cross section in the energy region from 1 eV to 700 keV. This reaction is of fundamental importance for the design calculations of nuclear reactors, governing the behavior of the reactor core. In particular, fast reactors, which are experiencing a growing interest for their ability to burn radioactive waste, operate in the high energy region of the neutron spectrum. In this energy region most recent evaluations disagree due to inconsistencies in the existing measurements of up to 15%. In addition, the assessment of nuclear data uncertainty performed for innovative reactor systems shows that the uncertainty in the radiative capture cross section of 238U should be further reduced to 1–3% in the energy region from 20 eV to 25 keV. To this purpose, addressed by the Nuclear Energy Agency as a priority nuclear data need, complementary experiments, one at the GELINA and two at the n_TOF facility, were proposed and carried out within the 7th Framework Project ANDES of the European Commission. The results of one of these 238U(n,γ) measurements performed at the n_TOF CERN facility are presented in this work. The γ-ray cascade following the radiative neutron capture has been detected exploiting a setup of two C6D6 liquid scintillators. Resonance parameters obtained from this work are on average in excellent agreement with the ones reported in evaluated libraries. In the unresolved resonance region, this work yields a cross section in agreement with evaluated libraries up to 80 keV, while for higher energies our results are significantly higher

Experimental neutron capture data of 58Ni from the CERN n_TOF facility

The neutron capture cross section of 58Ni was measured at the neutron time of flight facility n_TOF at CERN, from 27 meV to 400 keV neutron energy. Special care has been taken to identify all the possible sources of background, with the so-called neutron background obtained for the first time using high-precision GEANT4 simulations. The energy range up to 122 keV was treated as the resolved resonance region, where 51 resonances were identified and analyzed by a multilevel R-matrix code SAMMY. Above 122 keV the code SESH was used in analyzing the unresolved resonance region of the capture yield. Maxwellian averaged cross sections were calculated in the temperature range of kT = 5 – 100 keV, and their astrophysical implications were investigated

GEANT4 simulation of the neutron background of the C6D6 set-up for capture studies at n_TOF

The neutron sensitivity of the C6D6 detector setup used at n_TOF facility for capture measurements has been studied by means of detailed GEANT4 simulations. A realistic software replica of the entire n_TOF experimental hall, including the neutron beam line, sample, detector supports and the walls of the experimental area has been implemented in the simulations. The simulations have been analyzed in the same manner as experimental data, in particular by applying the Pulse Height Weighting Technique. The simulations have been validated against a measurement of the neutron background performed with a natC sample, showing an excellent agreement above 1 keV. At lower energies, an additional component in the measured natC yield has been discovered, which prevents the use of natC data for neutron background estimates at neutron energies below a few hundred eV. The origin and time structure of the neutron background have been derived from the simulations. Examples of the neutron background for two different samples are demonstrating the important role of accurate simulations of the neutron background in capture cross-section measurements

Fission fragment angular distribution measurements of 235U and 238U at CERN n_TOF facility

Neutron-induced fission cross sections of 238U and 235U are used as standards in the fast neutron region up to 200 MeV. A high accuracy of the standards is relevant to experimentally determine other neutron reaction cross sections. Therefore, the detection effciency should be corrected by using the angular distribution of the fission fragments (FFAD), which are barely known above 20 MeV. In addition, the angular distribution of the fragments produced in the fission of highly excited and deformed nuclei is an important observable to investigate the nuclear fission process. In order to measure the FFAD of neutron-induced reactions, a fission detection setup based on parallel-plate avalanche counters (PPACs) has been developed and successfully used at the CERN-n_TOF facility. In this work, we present the preliminary results on the analysis of new 235U(n,f) and 238U(n,f) data in the extended energy range up to 200 MeV compared to the existing experimental data