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Abstract Background In liver computed tomography (CT), tailoring the contrast injection to the patient’s specific characteristics is relevant for optimal imaging and patient safety. We evaluated a novel algorithm engineered for personalized contrast injection to achieve reproducible liver enhancement centered on 50 HU. Methods From September 2020 to August 31, 2022, CT data from consecutive adult patients were prospectively collected at our multicenter premises. Inclusion criteria consisted of an abdominal CT referral for cancer staging or follow-up. For all examinations, a web interface incorporating data from the radiology information system (patient details and examination information) and radiographer-inputted data (patient fat-free mass, imaging center, kVp, contrast agent details, and imaging phase) were used. Calculated contrast volume and injection rate were manually entered into the CT console controlling the injector. Iopamidol 370 mgI/mL or Iohexol 350 mgI/mL were used, and kVp varied (80, 100, or 120) based on patient habitus. Results We enrolled 384 patients (mean age 61.2 years, range 21.1–94.5). The amount of administered iodine dose (gI) was not significantly different across contrast agents (p = 0.700), while a significant increase in iodine dose was observed with increasing kVp (p

Time series forecasting has witnessed a rapid proliferation of novel neural network approaches in recent times. However, performances in terms of benchmarking results are generally not consistent, and it is complicated to determine in which cases one approach fits better than another. Therefore, we propose adopting a data-centric perspective for benchmarking neural network architectures on time series forecasting by generating ad hoc synthetic datasets. In particular, we combine sinusoidal functions to synthesize univariate time series data for multi-input-multi-output prediction tasks. We compare the most popular architectures for time series, namely long short-term memory (LSTM) networks, convolutional neural networks (CNNs), and transformers, and directly connect their performance with different controlled data characteristics, such as the sequence length, noise and frequency, and delay length. Our findings suggest that transformers are the best architecture for dealing with different delay lengths. In contrast, for different noise and frequency levels and different sequence lengths, LSTM is the best-performing architecture by a significant amount. Based on our insights, we derive recommendations which allow machine learning (ML) practitioners to decide which architecture to apply, given the dataset’s characteristics.

We present a checklist of spiders inhabiting the Pelagie archipelago and Pantelleria island, in the Strait of Sicily (Southern Italy). Data were compiled from both literature sources and unpublished materials stored in museum collections. In total, we report new data on 100 species, bringing the total number of species documented for the islands of the Strait of Sicily to 148. Among these, 8 are new for Europe and 9 new for Italy. The island of Lampedusa hosts the highest number of species (107), followed by Pantelleria (63) and Linosa (25). The most represented families are Gnaphosidae in Lampedusa and Linosa, while Salticidae is dominant in Pantelleria. Most of the species present on the islands of the Strait of Sicily have a Holarctic distribution. Several rare species are recorded, including Haplodrassus crassipes (Lucas, 1846), Palliduphantes labilis (Simon, 1913) and Xysticus promiscuus O. Pickard-Cambridge, 1876. In addition, the female of Poecilochroa loricata Kritscher, 1996 (Gnaphosidae) is here described and illustrated for the first time. As revealed by the study of the species-area relationship, the islands of the Strait of Sicily host a higher number of species compared to other small islands in Italy. Accordingly, species richness recorded in Lampedusa and Linosa is higher than expected, while further investigations are suggested to increase knowledge of the local spider diversity.

The welfare of animals under human care is often assessed by observing behaviours indicative of stress or discomfort, such as stereotypical behaviour (SB), which often shows as repetitive, invariant pacing. Traditional behaviour monitoring methods, however, are labour-intensive and subject to observer bias. Our study presents an innovative automated approach utilising computer vision and machine learning to non-invasively detect and analyse SB in managed populations, exemplified by a longitudinal study of two polar bears. We designed an animal tracking framework to localise and identify individual animals in the enclosure. After determining their position on the enclosure map via homographic transformation, we refined the resulting trajectories using a particle filter. Finally, we classified the trajectory patterns as SB or normal behaviour using a lightweight random forest approach with an accuracy of 94.9 %. The system not only allows for continuous, objective monitoring of animal behaviours but also provides insights into seasonal variations in SB, illustrating its potential for improving animal welfare in zoological settings. Ultimately, we analysed 607 days for the occurrence of SB, allowing us to discuss seasonal patterns of SB in both the male and female polar bear monitored. This work advances the field of animal welfare research by introducing a scalable, efficient method for the long-term, automated detection and monitoring of stereotypical behaviour, paving the way for its application across various settings and species that can be continuously monitored with cameras. We made the code publicly available at https://github.com/team-vera/stereotypy-detector.

Abstract Background This study systematically compares the impact of innovative deep learning image reconstruction (DLIR, TrueFidelity) to conventionally used iterative reconstruction (IR) on nodule volumetry and subjective image quality (IQ) at highly reduced radiation doses. This is essential in the context of low-dose CT lung cancer screening where accurate volumetry and characterization of pulmonary nodules in repeated CT scanning are indispensable. Materials and methods A standardized CT dataset was established using an anthropomorphic chest phantom (Lungman, Kyoto Kaguku Inc., Kyoto, Japan) containing a set of 3D-printed lung nodules including six diameters (4 to 9 mm) and three morphology classes (lobular, spiculated, smooth), with an established ground truth. Images were acquired at varying radiation doses (6.04, 3.03, 1.54, 0.77, 0.41 and 0.20 mGy) and reconstructed with combinations of reconstruction kernels (soft and hard kernel) and reconstruction algorithms (ASIR-V and DLIR at low, medium and high strength). Semi-automatic volumetry measurements and subjective image quality scores recorded by five radiologists were analyzed with multiple linear regression and mixed-effect ordinal logistic regression models. Results Volumetric errors of nodules imaged with DLIR are up to 50% lower compared to ASIR-V, especially at radiation doses below 1 mGy and when reconstructed with a hard kernel. Also, across all nodule diameters and morphologies, volumetric errors are commonly lower with DLIR. Furthermore, DLIR renders higher subjective IQ, especially at the sub-mGy doses. Radiologists were up to nine times more likely to score the highest IQ-score to these images compared to those reconstructed with ASIR-V. Lung nodules with irregular margins and small diameters also had an increased likelihood (up to five times more likely) to be ascribed the best IQ scores when reconstructed with DLIR. Conclusion We observed that DLIR performs as good as or even outperforms conventionally used reconstruction algorithms in terms of volumetric accuracy and subjective IQ of nodules in an anthropomorphic chest phantom. As such, DLIR potentially allows to lower the radiation dose to participants of lung cancer screening without compromising accurate measurement and characterization of lung nodules.

The prediction of the remaining time for business processes is a major task in predictive process monitoring (PPM). In the last years, various machine learning methods were introduced which reduced error levels steadily. However, the commonly applied metric for optimization and evaluation, the Mean Absolute Error (MAE), has limitations regarding its interpretability. In this work we introduce and evaluate the normalized Mean Absolute Error (nMAE) as an interpretable metric for model evaluation. It accounts for different kinds of label shifts, which are a special type of concept drift that can distort remaining time results. We investigate these concepts in a thorough benchmark study and use them to assess the current state of remaining time prediction for business processes. This includes the evaluation of four different baseline models, identifying the most accurate one. Furthermore, our study compares three different state-of-the-art methods, namely XGBoost, DA-LSTM, and PGT-Net. In contrary to prior studies we find that there is no significant difference in the performance between these models. Additionally, using the nMAE as evaluation metric we find that these models do not perform reasonably well on a range of event logs. Initial ideas for this behaviour are discussed and consolidated along with other findings from the case study into a comprehensive list motivating future research directions.

Online education continues its growth trajectory benefitting public four-year institutions of higher education as well as private universities. Recently, private non-profits have experienced double-digit increases despite late entry into online education. Situated within the context of a private nonprofit institution and its recently developed asynchronous online program, the purpose of this paper is to examine the teaching experiences of first-time business professors as seen through the lens of a SWOT analysis. Designed to capture the views of three stakeholders: Students, Faculty, and the Institution, the SWOT analysis suggests that local and regional research may yield untapped sources of opportunity for online programs at non-profit institutions.

Urban freshwater ecosystems often involve the introduction of predator species that affect biodiversity via both direct and indirect effects of predation, altering the distribution of prey species. Yet, limited research has explored indirect effects on aquatic invertebrates in urban pondscapes. Here, we use Dytiscidae as our study taxon to investigate how predator-prey interaction modifies the habitat use and habitat selection of macroinvertebrates in ponds of an urban landscape. We sampled dytiscids in 11 ponds with, and 15 ponds without fish, in Helsinki, Finland, during 2018 – 2020, and emergent plant cover in pond margins as a proxy for the quantity of prey refuges. We found (i) at the pond scale, vegetation cover can mitigate the negative effects of predators on dytiscid species richness and abundance, and dytiscids prefer microhabitats with bulrush and sedges to microhabitats with no vegetation or common reeds, reflecting the importance of providing aquatic plants with high structural complexity as prey refuges. (ii) At the landscape scale, small-sized dytiscids favour fishless habitats, and the community-weighted mean body size of dytiscids has seasonal fluctuations, with smaller body sizes in May and June than in July in fishless ponds, indicating that dytiscids select habitats to regulate their investment in vigilance according to their life cycles. Our findings highlight that predation can alter the habitat use and habitat selection of aquatic invertebrates. Mitigating predation risk at both the habitat scale and the landscape scale is crucial to facilitate the fitness of aquatic invertebrates, especially small-sized species, to promote their diversity in urban pondscapes.

Electroretinography is a method of electrophysiological testing, which allows diagnosing diseases associated with disorders of the vascular structures of the retina. The classical analysis of the electroretinogram is based on assessing four parameters of the amplitude-time representation and often needs to be specified further using alternative diagnostic methods. This study proposes the use of an original physician decision support algorithm for diagnosing retinal dystrophy. The proposed algorithm is based on machine learning methods and uses parameters extracted from the wavelet scalogram of pediatric and adult electroretinogram signals. The study also uses a labeled database of pediatric and adult electroretinogram signals recorded using a computerized electrophysiological workstation EP-1000 (Tomey GmbH) at the IRTC Eye Microsurgery Ekaterinburg Center. The scientific novelty of this study consists in the development of special mathematical and algorithmic software for analyzing a procedure for extracting wavelet scalogram parameters of the electroretinogram signal using the cwt function of the PyWT. The basis function is a Gaussian wavelet of order 8. Also, the scientific novelty includes the development of an algorithm for analyzing electroretinogram signals that implements the classification of adult (pediatric) electroretinogram signals 19 (20) percent more accurately than classical analysis.

En las últimas décadas, los cambios en el estudio del catolicismo se vieron alentados por el propio proceso de profesionalización disciplinar, que se desarrolló en el país desde los años ochenta, en el que influyó el impacto de la coyuntura política, fuertemente marcada por las consecuencias del terrorismo de Estado. Más recientemente, los historiadores comenzaron a prestar más atención a grupos y tendencias hasta entonces poco investigados. Surgieron nuevos estudios que alumbraron recodos inexplorados del catolicismo argentino. En esta línea, diversos trabajos reconstruyeron los círculos de seguidores de Jacques Maritain. Por otro lado, comenzaron a estudiarse también los sectores democristianos del Partido Popular de Buenos Aires. Dicho grupo encabezó, en el plano local, iniciativas internacionales alentadas por Luigi Sturzo como el Comité por la Paz Civil y Religiosa en España y People and Freedom Group (P&F). En este artículo, proponemos un recorrido panorámico por algunas de las principales vertientes del antifascismo católico con el propósito de analizar los puntos de convergencia, así como las principales divergencias que, entre otros factores, les impidieron compartir un mismo espacio intelectual y político durante las décadas de 1930 y 1940.

Mutations in the VAV1 guanine nucleotide exchange factor 1 have been recently found in peripheral T cell lymphoma and nonsmall‐cell lung cancer (NSCLC). To understand their pathogenic potential, we generated a gene‐edited mouse model that expresses a VAV1 mutant protein that recapitulates the signalling alterations present in the VAV1 mutant subclass most frequently found in tumours. We could not detect any overt tumourigenic process in those mice. However, the concurrent elimination of the Trp53 tumour suppressor gene in them drives T cell lymphomagenesis. This process represents an exacerbation of the normal functions that wild‐type VAV1 plays in follicular helper T cells. We also found that, in combination with the Kras oncogene, the VAV1 mutant version favours progression of NSCLC. These data indicate that VAV1 mutations play critical, although highly cell‐type‐specific, roles in tumourigenesis. They also indicate that such functions are contingent on the mutational landscape of the tumours involved.

Summary: Background: The incidence of endometrial cancer is increasing worldwide. While delays in diagnosis reduce survival, case molecular misclassification might be associated with under- and over-treatment. The objective of this study was to evaluate genetic alterations to detect and molecularly classify cases of endometrial cancer using non-invasive samples. Methods: Consecutive patients with incident endometrial cancer (N = 139) and controls (N = 107) from a recent Spanish case–control study were included in this analysis. Overall, 339 cervicovaginal samples (out of which 228 were clinician-collected and 111 were self-collected) were analysed using a test based on next-generation sequencing (NGS), which targets 47 genes. Immunohistochemical markers were evaluated in 133 tumour samples. A total of 159 samples were used to train the detection algorithm and 180 samples were used for validation. Findings: Overall, 73% (N = 94 out of 129 clinician-collected samples, and N = 66 out of 90 self-collected samples) of endometrial cancer cases had detectable mutations in clinician-collected and self-collected samples, while the specificity was 80% (79/99) for clinician-collected samples and 90% (19/21) for self-collected samples. The molecular classifications obtained using tumour samples and non-invasive gynaecologic samples in our study showed moderate-to-good agreement. The molecular classification of cases of endometrial cancer into four groups using NGS of both clinician-collected and self-collected cervicovaginal samples yielded significant differences in disease-free survival. The cases with mutations in POLE had an excellent prognosis, whereas the cases with TP53 mutations had the poorest clinical outcome, which is consistent with the data on tumour samples. Interpretation: This study classified endometrial cancer cases into four molecular groups based on the analysis of cervicovaginal samples that showed significant differences in disease-free survival. The molecular classification of endometrial cancer in non-invasive samples may improve patient care and survival by indicating the early need for aggressive surgery, as well as reducing referrals to highly specialized hospitals in cancers with good prognosis. Validation in independent sets will confirm the potential for molecular classification in non-invasive samples. Funding: This study was funded by a competitive grant from Instituto de Salud Carlos III through the projects PI19/01835, PI23/00790, and FI20/00031, CIBERESP CB06/02/0073 and CIBERONC CB16/12/00231, CB16/12/00234 (Co-funded by European Regional Development Fund. ERDF: A way to build Europe). Samples and data were provided by Biobank HUB-ICO-IDIBELL, integrated into the Spanish Biobank Network, and funded by the Instituto de Salud Carlos III (PT20/00171) and by Xarxa de Bancs de Tumors de Catalunya (XBTC) sponsored by Pla Director d’Oncologia de Catalunya. This work was supported in part by the AECC, Grupos estables (GCTRA18014MATI). It also counts with the support of the Secretariat for Universities and Research of the Department of Business and Knowledge of the Generalitat de Catalunya, and grants to support the activities of research groups 2021SGR01354 and 2021SGR1112.

Reseñas iberoamericanas

Within the 9th European Framework programme, since 2021 EUROfusion is operating five tokamaks under the auspices of a single Task Force called ‘Tokamak Exploitation’. The goal is to benefit from the complementary capabilities of each machine in a coordinated way and help in developing a scientific output scalable to future largre machines. The programme of this Task Force ensures that ASDEX Upgrade, MAST-U, TCV, WEST and JET (since 2022) work together to achieve the objectives of Missions 1 and 2 of the EUROfusion Roadmap: i) demonstrate plasma scenarios that increase the success margin of ITER and satisfy the requirements of DEMO and, ii) demonstrate an integrated approach that can handle the large power leaving ITER and DEMO plasmas. The Tokamak Exploitation task force has therefore organized experiments on these two missions with the goal to strengthen the physics and operational basis for the ITER baseline scenario and for exploiting the recent plasma exhaust enhancements in all four devices (PEX: Plasma EXhaust) for exploring the solution for handling heat and particle exhaust in ITER and develop the conceptual solutions for DEMO. The ITER Baseline scenario has been developed in a similar way in ASDEX Upgrade, TCV and JET. Key risks for ITER such as disruptions and run-aways have been also investigated in TCV, ASDEX Upgrade and JET. Experiments have explored successfully different divertor configurations (standard, super-X, snowflakes) in MAST-U and TCV and studied tungsten melting in WEST and ASDEX Upgrade. The input from the smaller devices to JET has also been proven successful to set-up novel control schemes on disruption avoidance and detachment.

In 2021 JET exploited its unique capabilities to operate with T and D–T fuel with an ITER-like Be/W wall (JET-ILW). This second major JET D–T campaign (DTE2), after DTE1 in 1997, represented the culmination of a series of JET enhancements—new fusion diagnostics, new T injection capabilities, refurbishment of the T plant, increased auxiliary heating, in-vessel calibration of 14 MeV neutron yield monitors—as well as significant advances in plasma theory and modelling in the fusion community. DTE2 was complemented by a sequence of isotope physics campaigns encompassing operation in pure tritium at high T-NBI power. Carefully conducted for safe operation with tritium, the new T and D–T experiments used 1 kg of T (vs 100 g in DTE1), yielding the most fusion reactor relevant D–T plasmas to date and expanding our understanding of isotopes and D–T mixture physics. Furthermore, since the JET T and DTE2 campaigns occurred almost 25 years after the last major D–T tokamak experiment, it was also a strategic goal of the European fusion programme to refresh operational experience of a nuclear tokamak to prepare staff for ITER operation. The key physics results of the JET T and DTE2 experiments, carried out within the EUROfusion JET1 work package, are reported in this paper. Progress in the technological exploitation of JET D–T operations, development and validation of nuclear codes, neutronic tools and techniques for ITER operations carried out by EUROfusion (started within the Horizon 2020 Framework Programme and continuing under the Horizon Europe FP) are reported in (Litaudon et al Nucl. Fusion accepted), while JET experience on T and D–T operations is presented in (King et al Nucl. Fusion submitted).

In magnetic fusion devices, error field (EF) sources, spurious magnetic field perturbations, need to be identified and corrected for safe and stable (disruption-free) tokamak operation. Within Work Package Tokamak Exploitation RT04, a series of studies have been carried out to test the portability of the novel non-disruptive method, designed and tested in DIII-D (Paz-Soldan et al 2022 Nucl. Fusion 62 126007), and to perform an assessment of model-based EF control strategies towards their applicability in ITER. In this paper, the lessons learned, the physical mechanism behind the magnetic island healing, which relies on enhanced viscous torque that acts against the static electro-magnetic torque, and the main control achievements are reported, together with the first design of the asynchronous EF correction current/density controller for ITER.

The RFX-mod2 installation is planned to be completed by 2024 and the start of operations is expected in 2025. The high flexibility of the machine (already tested in the previous RFX-mod experiment) allows operation in Reversed Field Pinch and tokamak configuration as well as ultra-low q pulses. In this work we present predictive analysis on transport, performances and plasma control in RFX-mod2 in view of the first experimental campaigns.

Abstract Background Musculoskeletal disorders are very common in patients with diabetes mellitus (DM). The upper limb is one of the regions that is most frequently affected generally presenting limited joint mobility, pain, and a decreased muscle strength. Most clinical trials with a focus on shoulder musculoskeletal rehabilitation are carried out in patients who do not present DM. Thus, the purpose of the present study is to compare the effects of two distinct treatment protocols (conventional shoulder musculoskeletal rehabilitation combined with aerobic exercises versus solely conventional shoulder musculoskeletal rehabilitation) on shoulder pain, function, strength, kinematics, and supraspinatus tendon thickness in patients with type 2 DM after 12 weeks of intervention and a subsequent follow-up at week 20. Methods A randomized controlled superiority trial will be conducted. Participants with a clinical diagnosis of type 2 DM of both sexes, age between 40 and 70 years, presenting shoulder pain will be randomly assigned to one of the following groups: (1) conventional shoulder musculoskeletal rehabilitation combined with aerobic exercises; (2) solely conventional shoulder musculoskeletal rehabilitation. All individuals will be evaluated before starting the treatment protocol (baseline) and at the end of treatment (post 12 weeks) and as a follow-up at 20 weeks. The shoulder function assessed by the SPADI (Shoulder Pain and Disability Index) questionnaire will be considered as primary outcome; the secondary outcome will be shoulder pain, measured with NPRS scales. Other outcomes will include range of motion, measured using a digital inclinometer; isometric shoulder muscle strength, measured using a manual muscle dynamometer; shoulder kinematics, measured using three-dimensional inertial units measurement; supraspinatus tendon thickness, measured using an ultrasound; AGE accumulation, using a skin autofluorescence measurement; and HbA1c (hemoglobin a1c), fasting glucose and lipid profile measured by a simple blood test. Discussion DM is a highly prevalent disease and a public health problem worldwide, and the upper extremity musculoskeletal disorders in DM are barely recognized and largely underestimated. In this way, it would be interesting to analyze if the combination of aerobic exercises with conventional musculoskeletal rehabilitation protocols could generate better results in the functionality, pain, mobility and an improvement in the biochemical aspects related to the hyperglycemia of these patients compared to solely the conventional musculoskeletal rehabilitation. Trial registration ClinicalTrials.gov NCT04817514. Registered on March 26, 2021.

Controlled nanocluster growth via nanoconfinement is an attractive approach as it allows for geometry control and potential surface-chemistry modification simultaneously. However, it is still not a straight-forward method and much of its success depends on the nature and possibly concentration of functionalities on the cavity walls that surround the clusters. To independently probe the effect of the nature and number of functional groups on the controlled Pd nanocluster growth within the pores of the metal–organic frameworks, Pd-laden UiO-66 analogues with mono- and bi-functionalised linkers of amino and methyl groups were successfully prepared and studied in a combined experimental–computational approach. The nature of the functional groups determines the strength of host–guest interactions, while the number of functional groups affects the extent of Pd loading. The interplay of these two effects means that for a successful Pd embedding, mono-functionalised host matrices are more favourable. Interestingly, in the context of the present and previous research, we find that host frameworks with functional groups displaying higher Lewis basicity are more successful at controlled Pd NC growth via nanoconfinement in MOFs. [ABSTRACT FROM AUTHOR]

Time series forecasting has witnessed a rapid proliferation of novel neural network approaches in recent times. However, performances in terms of benchmarking results are generally not consistent, and it is complicated to determine in which cases one approach fits better than another. Therefore, we propose adopting a data-centric perspective for benchmarking neural network architectures on time series forecasting by generating ad hoc synthetic datasets. In particular, we combine sinusoidal functions to synthesize univariate time series data for multi-input-multi-output prediction tasks. We compare the most popular architectures for time series, namely long short-term memory (LSTM) networks, convolutional neural networks (CNNs), and transformers, and directly connect their performance with different controlled data characteristics, such as the sequence length, noise and frequency, and delay length. Our findings suggest that transformers are the best architecture for dealing with different delay lengths. In contrast, for different noise and frequency levels and different sequence lengths, LSTM is the best-performing architecture by a significant amount. Based on our insights, we derive recommendations which allow machine learning (ML) practitioners to decide which architecture to apply, given the dataset's characteristics. [ABSTRACT FROM AUTHOR]

Sulfuric acid and dimethylamine vapours in the atmosphere can form molecular clusters, which participate in new particle formation events. In this work, we have produced, measured, and identified clusters of sulfuric acid and dimethylamine using an electrospray ionizer coupled with a planar-differential mobility analyser, connected to an atmospheric pressure interface time-of-flight mass spectrometer (ESI–DMA–APi-TOF MS). This set-up is suitable for evaluating the extent of fragmentation of the charged clusters inside the instrument. We evaluated the fragmentation of 11 negatively charged clusters both experimentally and using a statistical model based on quantum chemical data. The results allowed us to quantify the fragmentation of the studied clusters and to reconstruct the mass spectrum by removing the artifacts due to the fragmentation.

IntroductionThe impact of multi-domain preventive interventions on older adults, in particular on those with higher risk to develop Alzheimer's disease (AD), could be beneficial, as it may delay cognitive decline. However, the precise mechanism of such positive impact is not fully understood and may involve brain reserve and adaptability of brain functional connectivity (FC).MethodsTo determine the effect of multidomain interventions (involving physical activity, cognitive training, nutritional counseling alone or in combination with omega-3 fatty acid supplementation and vs. a placebo) on the brain, longitudinal FC changes were assessed after 36 months of intervention on 100 older adults (above 70 year-old) with subjective cognitive complaints.ResultsNo global change in FC was detected after uni or multidomain preventive interventions. However, an effect of omega-3 fatty acid supplementation dependent on cognitive decline status was underlined for frontoparietal, salience, visual and sensorimotor networks FC. These findings were independent of the cortical thickness and vascular burden.DiscussionThese results emphasize the importance of patient stratification, based on risk factors, for preventive interventions.

Abstract Background The role of image-derived biomarkers in recurrent oligometastatic Prostate Cancer (PCa) is unexplored. This paper aimed to evaluate [18F]FMCH PET/CT radiomic analysis in patients with recurrent PCa after primary radical therapy. Specifically, we tested intra-patient lesions similarity in oligometastatic and plurimetastatic PCa, comparing the two most used definitions of oligometastatic disease. Methods PCa patients eligible for [18F]FMCH PET/CT presenting biochemical failure after first-line curative treatments were invited to participate in this prospective observational trial. PET/CT images of 92 patients were visually and quantitatively analyzed. Each patient was classified as oligometastatic or plurimetastatic according to the total number of detected lesions (up to 3 and up to 5 or > 3 and > 5, respectively). Univariate and intra-patient lesions' similarity analysis were performed. Results [18F]FMCH PET/CT identified 370 lesions, anatomically classified as regional lymph nodes and distant metastases. Thirty-eight and 54 patients were designed oligometastatic and plurimetastatic, respectively, using a 3-lesion threshold. The number of oligometastic scaled up to 60 patients (thus 32 plurimetastatic patients) with a 5-lesion threshold. Similarity analysis showed high lesions' heterogeneity. Grouping patients according to the number of metastases, patients with oligometastatic PCa defined with a 5-lesion threshold presented lesions heterogeneity comparable to plurimetastic patients. Lesions within patients having a limited tumor burden as defined by three lesions were characterized by less heterogeneity. Conclusions We found a comparable heterogeneity between patients with up to five lesions and plurimetastic patients, while patients with up to three lesions were less heterogeneous than plurimetastatic patients, featuring different cells phenotypes in the two groups. Our results supported the use of a 3-lesion threshold to define oligometastatic PCa.

Abstract Introduction Cervical cytology is a well‐stablished cervical cancer screening method. However, due to the anatomical continuity of the genital tract, it can also detect signs of endometrial disease. Our aim was to estimate the sensitivity of cervical cytology in endometrial cancer detection and prognosis in a large population over a 30‐year period in a large academic tertiary hospital in Spain. Methodology We performed a search for women diagnosed with endometrial cancer from 1990 to 2020, who were surgically treated and had a previous cervical cytology result. Information Technologies Department databases from Bellvitge University Hospital and the Screenwide case–control study's database were used. Cervical cytology results were classified as abnormal when squamous lesions, glandular atypia or malignant cells were identified. Results Overall, we evaluated 371 women with endometrial cancer and a documented cervical cytology performed within 3 years previous to surgical treatment. Overall, the sensitivity of cervical cytology for endometrial cancer detection was 25.6%. Several clinico‐pathological characteristics, such as non‐endometrioid histology and a higher stage, were correlated with higher sensitivity. Discussion We observed a low sensitivity of cervical cytology to effectively diagnose endometrial cancer. However, recent technological advances using genomics and epigenomics may offer a promising perspective to detect endometrial cancer with high sensitivity in these cervical specimens.

Rita Viglialoro,1,2,* Enrica Esposito,1,2,* Roberta Zanca,1,2 Marco Gessi,3 Tommaso Depalo,1,2 Gayane Aghakhanyan,1,2 Francesco Bartoli,1,2 Martina Sollini,4,5 Paola Anna Erba1,2,6 1Regional Center of Nuclear Medicine, Department of Translational Research and New Technology in Medicine, University of Pisa, Pisa, Italy; 2Azienda Ospedaliero Universitaria Pisana, Pisa, Italy; 3Neuropathology Unit, Division of Pathology Fondazione Policlinico Universitario “A.Gemelli” IRCCS, Università Cattolica del Sacro Cuore, Roma, Italy; 4Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, 20090, Italy; 5IRCCS Humanitas Research Hospital, Rozzano, Milan, Italy; 6Department of Nuclear Medicine and Molecular Imaging, Medical Imaging Centre, University Medical Center Groningen, Groningen, the Netherlands*These authors contributed equally to this workCorrespondence: Paola Anna ErbaDepartment of Translational Research and New Technology in Medicine, via Savi 10, Pisa, 56126, ItalyTel +39-050-992115Fax +39-050-992124Email p.erba@unipi.itAbstract: Brain metastases from prostate cancer typically occur in the more advanced stages of the disease. Clinically, the early diagnosis of visceral disease is crucial, impacting on patient’s management and prognosis. Although magnetic resonance imaging (MRI) is the modality of choice for the detection of brain metastases, it is not routinely performed in the surveillance of prostate cancer patients unless neurological manifestations appear. Prostate-specific membrane antigen (PSMA) is a glycoprotein, a membrane-bound metallopeptidase, overexpressed in more than 90% of prostate cancer cells. This molecular target is a suitable tissue biomarker for prostate cancer functional imaging. We present a case of a 73-year gentleman diagnosed with prostate adenocarcinoma and surgically treated (pT3bN1Mx, Gleason Score of 9) in February 2016. Subsequently, he underwent androgen deprivation therapy because of the occurrence of a bone metastasis. Between 2016 and January 2019 PSA levels were maintained under control. Starting from September 2019, it progressively raised up to 0.85 ng/mL with a doubling time of 3.3 months. Therefore, he performed a [68Ga]Ga-PSMA-11 PET/CT which showed a focal radiopharmaceutical uptake in the right temporal lobe corresponding to the presence of a rounded cystic lesion on brain MRI. The subsequent excisional biopsy diagnosed a prostate adenocarcinoma metastasis. PSMA expression has been reported in brain parenchyma after ischemic strokes and in some brain tumors including gliomas, meningiomas, and neurofibromas. In our case, the lack of symptoms and the relatively low PSA level raised questions about the nature of the lesion, posing the differential diagnosis between brain metastases and primary brain tumor. Finally, our case shows the capability of [68Ga]Ga-PSMA-11 PET/CT to detect metachronous distant brain metastases in a low biochemical recurrent asymptomatic prostate cancer patient, indicating that proper acquisition – from the vertex to thigh – should be always considered, regardless of the PSA level.Keywords: [68Ga]Ga-PSMA-11 PET/CT, biochemical recurrence, brain metastases, multimodal imaging, prostate cancer, PSA