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Author Debora Gil; Katerine Diaz; Carles Sanchez; Aura Hernandez-Sabate edit   pdf
url  openurl
  Title Early Screening of SARS-CoV-2 by Intelligent Analysis of X-Ray Images Type Miscellaneous
  Year 2020 Publication Arxiv Abbreviated Journal  
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  Abstract Future SARS-CoV-2 virus outbreak COVID-XX might possibly occur during the next years. However the pathology in humans is so recent that many clinical aspects, like early detection of complications, side effects after recovery or early screening, are currently unknown. In spite of the number of cases of COVID-19, its rapid spread putting many sanitary systems in the edge of collapse has hindered proper collection and analysis of the data related to COVID-19 clinical aspects. We describe an interdisciplinary initiative that integrates clinical research, with image diagnostics and the use of new technologies such as artificial intelligence and radiomics with the aim of clarifying some of SARS-CoV-2 open questions. The whole initiative addresses 3 main points: 1) collection of standardize data including images, clinical data and analytics; 2) COVID-19 screening for its early diagnosis at primary care centers; 3) define radiomic signatures of COVID-19 evolution and associated pathologies for the early treatment of complications. In particular, in this paper we present a general overview of the project, the experimental design and first results of X-ray COVID-19 detection using a classic approach based on HoG and feature selection. Our experiments include a comparison to some recent methods for COVID-19 screening in X-Ray and an exploratory analysis of the feasibility of X-Ray COVID-19 screening. Results show that classic approaches can outperform deep-learning methods in this experimental setting, indicate the feasibility of early COVID-19 screening and that non-COVID infiltration is the group of patients most similar to COVID-19 in terms of radiological description of X-ray. Therefore, an efficient COVID-19 screening should be complemented with other clinical data to better discriminate these cases.  
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  Notes IAM; 600.139; 600.145; 601.337 Approved no  
  Call Number Admin @ si @ GDS2020 Serial 3474  
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Author Oriol Ramos Terrades; Albert Berenguel; Debora Gil edit   pdf
url  openurl
  Title A flexible outlier detector based on a topology given by graph communities Type Miscellaneous
  Year 2020 Publication Arxiv Abbreviated Journal  
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  Abstract Outlier, or anomaly, detection is essential for optimal performance of machine learning methods and statistical predictive models. It is not just a technical step in a data cleaning process but a key topic in many fields such as fraudulent document detection, in medical applications and assisted diagnosis systems or detecting security threats. In contrast to population-based methods, neighborhood based local approaches are simple flexible methods that have the potential to perform well in small sample size unbalanced problems. However, a main concern of local approaches is the impact that the computation of each sample neighborhood has on the method performance. Most approaches use a distance in the feature space to define a single neighborhood that requires careful selection of several parameters. This work presents a local approach based on a local measure of the heterogeneity of sample labels in the feature space considered as a topological manifold. Topology is computed using the communities of a weighted graph codifying mutual nearest neighbors in the feature space. This way, we provide with a set of multiple neighborhoods able to describe the structure of complex spaces without parameter fine tuning. The extensive experiments on real-world data sets show that our approach overall outperforms, both, local and global strategies in multi and single view settings.  
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  Notes IAM; DAG; 600.139; 600.145; 600.140; 600.121 Approved no  
  Call Number Admin @ si @ RBG2020 Serial 3475  
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Author Guillermo Torres; Debora Gil edit  openurl
  Title A multi-shape loss function with adaptive class balancing for the segmentation of lung structures Type Journal Article
  Year 2020 Publication International Journal of Computer Assisted Radiology and Surgery Abbreviated Journal IJCAR  
  Volume 15 Issue 1 Pages S154-55  
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  Notes IAM Approved no  
  Call Number Admin @ si @ ToG2020 Serial 3590  
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Author Sonia Baeza; R.Domingo; M.Salcedo; G.Moragas; J.Deportos; I.Garcia Olive; Carles Sanchez; Debora Gil; Antoni Rosell edit  url
openurl 
  Title Artificial Intelligence to Optimize Pulmonary Embolism Diagnosis During Covid-19 Pandemic by Perfusion SPECT/CT, a Pilot Study Type Journal Article
  Year 2021 Publication American Journal of Respiratory and Critical Care Medicine Abbreviated Journal  
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  Notes IAM; 600.145 Approved no  
  Call Number Admin @ si @ BDS2021 Serial 3591  
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Author Mireia Sole; Joan Blanco; Debora Gil; Oliver Valero; Alvaro Pascual; B. Cardenas; G. Fonseka; E. Anton; Richard Frodsham; Francesca Vidal; Zaida Sarrate edit  url
openurl 
  Title Chromosomal positioning in spermatogenic cells is influenced by chromosomal factors associated with gene activity, bouquet formation, and meiotic sex-chromosome inactivation Type Journal Article
  Year 2021 Publication Chromosoma Abbreviated Journal  
  Volume 130 Issue Pages 163-175  
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  Abstract Chromosome territoriality is not random along the cell cycle and it is mainly governed by intrinsic chromosome factors and gene expression patterns. Conversely, very few studies have explored the factors that determine chromosome territoriality and its influencing factors during meiosis. In this study, we analysed chromosome positioning in murine spermatogenic cells using three-dimensionally fluorescence in situ hybridization-based methodology, which allows the analysis of the entire karyotype. The main objective of the study was to decipher chromosome positioning in a radial axis (all analysed germ-cell nuclei) and longitudinal axis (only spermatozoa) and to identify the chromosomal factors that regulate such an arrangement. Results demonstrated that the radial positioning of chromosomes during spermatogenesis was cell-type specific and influenced by chromosomal factors associated to gene activity. Chromosomes with specific features that enhance transcription (high GC content, high gene density and high numbers of predicted expressed genes) were preferentially observed in the inner part of the nucleus in virtually all cell types. Moreover, the position of the sex chromosomes was influenced by their transcriptional status, from the periphery of the nucleus when its activity was repressed (pachytene) to a more internal position when it is partially activated (spermatid). At pachytene, chromosome positioning was also influenced by chromosome size due to the bouquet formation. Longitudinal chromosome positioning in the sperm nucleus was not random either, suggesting the importance of ordered longitudinal positioning for the release and activation of the paternal genome after fertilisation.  
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  Notes IAM; 600.145 Approved no  
  Call Number Admin @ si @ SBG2021 Serial 3592  
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Author Marta Ligero; Alonso Garcia Ruiz; Cristina Viaplana; Guillermo Villacampa; Maria V Raciti; Jaid Landa; Ignacio Matos; Juan Martin Liberal; Maria Ochoa de Olza; Cinta Hierro; Joaquin Mateo; Macarena Gonzalez; Rafael Morales Barrera; Cristina Suarez; Jordi Rodon; Elena Elez; Irene Braña; Eva Muñoz-Couselo; Ana Oaknin; Roberta Fasani; Paolo Nuciforo; Debora Gil; Carlota Rubio Perez; Joan Seoane; Enriqueta Felip; Manuel Escobar; Josep Tabernero; Joan Carles; Rodrigo Dienstmann; Elena Garralda; Raquel Perez Lopez edit  url
doi  openurl
  Title A CT-based radiomics signature is associated with response to immune checkpoint inhibitors in advanced solid tumors Type Journal Article
  Year 2021 Publication Radiology Abbreviated Journal  
  Volume 299 Issue 1 Pages 109-119  
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  Abstract Background Reliable predictive imaging markers of response to immune checkpoint inhibitors are needed. Purpose To develop and validate a pretreatment CT-based radiomics signature to predict response to immune checkpoint inhibitors in advanced solid tumors. Materials and Methods In this retrospective study, a radiomics signature was developed in patients with advanced solid tumors (including breast, cervix, gastrointestinal) treated with anti-programmed cell death-1 or programmed cell death ligand-1 monotherapy from August 2012 to May 2018 (cohort 1). This was tested in patients with bladder and lung cancer (cohorts 2 and 3). Radiomics variables were extracted from all metastases delineated at pretreatment CT and selected by using an elastic-net model. A regression model combined radiomics and clinical variables with response as the end point. Biologic validation of the radiomics score with RNA profiling of cytotoxic cells (cohort 4) was assessed with Mann-Whitney analysis. Results The radiomics signature was developed in 85 patients (cohort 1: mean age, 58 years ± 13 [standard deviation]; 43 men) and tested on 46 patients (cohort 2: mean age, 70 years ± 12; 37 men) and 47 patients (cohort 3: mean age, 64 years ± 11; 40 men). Biologic validation was performed in a further cohort of 20 patients (cohort 4: mean age, 60 years ± 13; 14 men). The radiomics signature was associated with clinical response to immune checkpoint inhibitors (area under the curve [AUC], 0.70; 95% CI: 0.64, 0.77; P < .001). In cohorts 2 and 3, the AUC was 0.67 (95% CI: 0.58, 0.76) and 0.67 (95% CI: 0.56, 0.77; P < .001), respectively. A radiomics-clinical signature (including baseline albumin level and lymphocyte count) improved on radiomics-only performance (AUC, 0.74 [95% CI: 0.63, 0.84; P < .001]; Akaike information criterion, 107.00 and 109.90, respectively). Conclusion A pretreatment CT-based radiomics signature is associated with response to immune checkpoint inhibitors, likely reflecting the tumor immunophenotype. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Summers in this issue.  
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  Notes IAM; 600.145 Approved no  
  Call Number Admin @ si @ LGV2021 Serial 3593  
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Author Debora Gil; Oriol Ramos Terrades; Raquel Perez edit  doi
openurl 
  Title Topological Radiomics (TOPiomics): Early Detection of Genetic Abnormalities in Cancer Treatment Evolution Type Book Chapter
  Year 2021 Publication Extended Abstracts GEOMVAP 2019, Trends in Mathematics 15 Abbreviated Journal  
  Volume 15 Issue Pages 89–93  
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  Abstract Abnormalities in radiomic measures correlate to genomic alterations prone to alter the outcome of personalized anti-cancer treatments. TOPiomics is a new method for the early detection of variations in tumor imaging phenotype from a topological structure in multi-view radiomic spaces.  
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  Publisher Springer Nature Place of Publication Editor  
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  Notes IAM; DAG; 600.120; 600.145; 600.139 Approved no  
  Call Number Admin @ si @ GRP2021 Serial 3594  
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Author Miquel Angel Piera; Jose Luis Muñoz; Debora Gil; Gonzalo Martin; Jordi Manzano edit  doi
openurl 
  Title A Socio-Technical Simulation Model for the Design of the Future Single Pilot Cockpit: An Opportunity to Improve Pilot Performance Type Journal Article
  Year 2022 Publication IEEE Access Abbreviated Journal ACCESS  
  Volume 10 Issue Pages 22330-22343  
  Keywords Human factors ; Performance evaluation ; Simulation; Sociotechnical systems ; System performance  
  Abstract The future deployment of single pilot operations must be supported by new cockpit computer services. Such services require an adaptive context-aware integration of technical functionalities with the concurrent tasks that a pilot must deal with. Advanced artificial intelligence supporting services and improved communication capabilities are the key enabling technologies that will render future cockpits more integrated with the present digitalized air traffic management system. However, an issue in the integration of such technologies is the lack of socio-technical analysis in the design of these teaming mechanisms. A key factor in determining how and when a service support should be provided is the dynamic evolution of pilot workload. This paper investigates how the socio-technical model-based systems engineering approach paves the way for the design of a digital assistant framework by formalizing this workload. The model was validated in an Airbus A-320 cockpit simulator, and the results confirmed the degraded pilot behavioral model and the performance impact according to different contextual flight deck information. This study contributes to practical knowledge for designing human-machine task-sharing systems.  
  Address Feb 2022  
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  Notes IAM; Approved no  
  Call Number Admin @ si @ PMG2022 Serial 3697  
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Author Guillermo Torres; Sonia Baeza; Carles Sanchez; Ignasi Guasch; Antoni Rosell; Debora Gil edit  doi
openurl 
  Title An Intelligent Radiomic Approach for Lung Cancer Screening Type Journal Article
  Year 2022 Publication Applied Sciences Abbreviated Journal APPLSCI  
  Volume 12 Issue 3 Pages 1568  
  Keywords Lung cancer; Early diagnosis; Screening; Neural networks; Image embedding; Architecture optimization  
  Abstract The efficiency of lung cancer screening for reducing mortality is hindered by the high rate of false positives. Artificial intelligence applied to radiomics could help to early discard benign cases from the analysis of CT scans. The available amount of data and the fact that benign cases are a minority, constitutes a main challenge for the successful use of state of the art methods (like deep learning), which can be biased, over-fitted and lack of clinical reproducibility. We present an hybrid approach combining the potential of radiomic features to characterize nodules in CT scans and the generalization of the feed forward networks. In order to obtain maximal reproducibility with minimal training data, we propose an embedding of nodules based on the statistical significance of radiomic features for malignancy detection. This representation space of lesions is the input to a feed
forward network, which architecture and hyperparameters are optimized using own-defined metrics of the diagnostic power of the whole system. Results of the best model on an independent set of patients achieve 100% of sensitivity and 83% of specificity (AUC = 0.94) for malignancy detection.
 
  Address Jan 2022  
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  Notes IAM; 600.139; 600.145 Approved no  
  Call Number Admin @ si @ TBS2022 Serial 3699  
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Author Juan Borrego-Carazo; Carles Sanchez; David Castells; Jordi Carrabina; Debora Gil edit   pdf
doi  openurl
  Title BronchoPose: an analysis of data and model configuration for vision-based bronchoscopy pose estimation Type Journal Article
  Year 2023 Publication Computer Methods and Programs in Biomedicine Abbreviated Journal CMPB  
  Volume 228 Issue Pages 107241  
  Keywords Videobronchoscopy guiding; Deep learning; Architecture optimization; Datasets; Standardized evaluation framework; Pose estimation  
  Abstract Vision-based bronchoscopy (VB) models require the registration of the virtual lung model with the frames from the video bronchoscopy to provide effective guidance during the biopsy. The registration can be achieved by either tracking the position and orientation of the bronchoscopy camera or by calibrating its deviation from the pose (position and orientation) simulated in the virtual lung model. Recent advances in neural networks and temporal image processing have provided new opportunities for guided bronchoscopy. However, such progress has been hindered by the lack of comparative experimental conditions.
In the present paper, we share a novel synthetic dataset allowing for a fair comparison of methods. Moreover, this paper investigates several neural network architectures for the learning of temporal information at different levels of subject personalization. In order to improve orientation measurement, we also present a standardized comparison framework and a novel metric for camera orientation learning. Results on the dataset show that the proposed metric and architectures, as well as the standardized conditions, provide notable improvements to current state-of-the-art camera pose estimation in video bronchoscopy.
 
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  Publisher Elsevier Place of Publication Editor  
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  Notes IAM; Approved no  
  Call Number Admin @ si @ BSC2023 Serial 3702  
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