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Author Angels Barbera; Ruth Marginet Flinch; Montserrat Martin; Jose L Mate; Albert Oriol; Fina Martinez-Soler; Tomas Santalucia; Pedro L. Fernandez edit  url
doi  openurl
  Title The Immunohistochemical Expression of Programmed Death Ligand 1 Type Journal Article
  Year 2020 Publication Applied Immunohistochemistry & Molecular Morphology Abbreviated Journal AIMM  
  Volume Issue Pages  
  Keywords  
  Abstract Humanized antibodies targeting programmed death receptor 1 (PD-1) or its ligand (PD-L1) have been approved for the treatment of different cancers. Some of these antibodies show a correlation between the tissue expression of PD-L1 and response. Evaluation of PD-L1 expression presents multiple challenges, but some preanalytical issues such as tissue fixation have been scarcely evaluated. With the hypothesis that immunohistochemical staining of PD-L1 may be impacted by the time of specimen fixation, we evaluated differences in its expression in tonsil samples exposed to predefined fixation times. Random nontumoral tonsillectomy specimens were blindly evaluated in tissue microarray slides after staining with SP142 and SP263 antibodies. With fixation times ranging from 12 to 72 hours, between 2.8% and 6.1% of the samples were considered to be suboptimally stained, with no differences between the 2 antibodies within these fixation times. A significantly higher proportion of samples exposed to a fixation time of 96 hours presented suboptimal immunostaining (15.6%, P<0.0001). In addition, suboptimally stained spots were 20.8% using SP142 and 10.4% using SP263 after 96 hours of fixation (P=0.046). In conclusion, the quality of staining for PD-L1 in tonsil samples decreased with overfixation of the specimen at times >72 hours. Samples exposed to formaldehyde for longer periods presented suboptimal results for both clones, but the SP142 antibody presented a significantly lower tolerance to formalin overexposure than SP263. These results indicate the relevance of a controlled preanalytical processing of samples and particularly the length of fixation of tumor specimens.  
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  Notes IAM; 600.139; 600.145 Approved no  
  Call Number Admin @ si @ BMM2020 Serial 3470  
Permanent link to this record
 

 
Author Ester Conde; Susana Herandez; Rebeca Martinez; Barbara Angulo; Javier de Castro; Ana Collazo; Beatriz Jimenez; Alfonso Muriel; Jose Luis Mate; Teresa Moran; Ignacio Aranda; Bartomeu Massuti; Federico Rojo; Manuel Domine; Irene Sansano; Felipe Garcia; Enriqueta Felip; Nuria Mancheno; Oscar Juan; Julian Sanz; Jose Luis Gonzalez; Lidia Atienza; Esperanza Arriola; I. Abdulkader; J.Garcia; C. Camacho; D. Rodriguez; D. Teixido; N. Reguart; A.Gonzalez; M. Lazaro; MD. Lozano; J. Gomez; M. Lopez; L Pijuan; M Salido; E. Arriola; A. Company; A. Insa; I. Esteban; M. Saiz; E. Azkona; R. Alvarez; A. Artal; ML. Plaza; D. Aguiar; AB. Enguita, A. Benito; L. Paz; P. Garrido; F. Lopez edit  url
doi  openurl
  Title Assessment of a New ROS1 Immunohistochemistry Clone (SP384) for the Identification of ROS1 Rearrangements in Patients with Non–Small Cell Lung Carcinoma: the ROSING Study Type Journal Article
  Year 2019 Publication Journal of Thoracic Oncology Abbreviated Journal  
  Volume 14 Issue 12 Pages 2120-2132  
  Keywords  
  Abstract Introduction
The ROS1 gene rearrangement has become an important biomarker in NSCLC. The College of American Pathologists/International Association for the Study of Lung Cancer/Association for Molecular Pathology testing guidelines support the use of ROS1 immunohistochemistry (IHC) as a screening test, followed by confirmation with fluorescence in situ hybridization (FISH) or a molecular test in all positive results. We have evaluated a novel anti-ROS1 IHC antibody (SP384) in a large multicenter series to obtain real-world data.

Methods
A total of 43 ROS1 FISH–positive and 193 ROS1 FISH–negative NSCLC samples were studied. All specimens were screened by using two antibodies (clone D4D6 from Cell Signaling Technology and clone SP384 from Ventana Medical Systems), and the different interpretation criteria were compared with break-apart FISH (Vysis). FISH-positive samples were also analyzed with next-generation sequencing (Oncomine Dx Target Test Panel, Thermo Fisher Scientific).

Results
An H-score of 150 or higher or the presence of at least 70% of tumor cells with an intensity of staining of 2+ or higher by the SP384 clone was the optimal cutoff value (both with 93% sensitivity and 100% specificity). The D4D6 clone showed similar results, with an H-score of at least 100 (91% sensitivity and 100% specificity). ROS1 expression in normal lung was more frequent with use of the SP384 clone (p < 0.0001). The ezrin gene (EZR)-ROS1 variant was associated with membranous staining and an isolated green signal FISH pattern (p = 0.001 and p = 0.017, respectively).

Conclusions
The new SP384 ROS1 IHC clone showed excellent sensitivity without compromising specificity, so it is another excellent analytical option for the proposed testing algorithm.
 
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  Notes IAM; 600.139; 600.145 Approved no  
  Call Number Admin @ si @ CHM2019 Serial 3471  
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Author Debora Gil; Guillermo Torres edit  openurl
  Title A multi-shape loss function with adaptive class balancing for the segmentation of lung structures Type Conference Article
  Year 2020 Publication 34th International Congress and Exhibition on Computer Assisted Radiology & Surgery Abbreviated Journal  
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  Abstract  
  Address Virtual; June 2020  
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  Series Editor (up) Series Title Abbreviated Series Title  
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  ISSN ISBN Medium  
  Area Expedition Conference CARS  
  Notes IAM; 600.139; 600.145 Approved no  
  Call Number Admin @ si @ GiT2020 Serial 3472  
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Author Debora Gil; Oriol Ramos Terrades; Raquel Perez edit  openurl
  Title Topological Radiomics (TOPiomics): Early Detection of Genetic Abnormalities in Cancer Treatment Evolution Type Conference Article
  Year 2020 Publication Women in Geometry and Topology Abbreviated Journal  
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  Abstract  
  Address Barcelona; September 2019  
  Corporate Author Thesis  
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  Notes IAM; DAG; 600.139; 600.145; 600.121 Approved no  
  Call Number Admin @ si @ GRP2020 Serial 3473  
Permanent link to this record
 

 
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  
  Volume Issue Pages  
  Keywords  
  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  
  Volume Issue Pages  
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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 Teresa Moran; Vanesa Quiroga; Beatriz Cirauqui; Laia Vila; Maria Gil-Moreno; Enric Carcereny; Mireia Margeli; Ana Muñoz-Marmol; Jose Luis Mate; Jose Maria Velarde; Miguel Angel Molina; Rafael Rosell edit  url
doi  openurl
  Title A Single-Center Retrospective Study of Patients with Double Primary Cancers: Breast Cancer and EGFR-Mutant Non-Small Cell Lung Cancer Type Journal Article
  Year 2019 Publication Oncology Research and Treatment Abbreviated Journal  
  Volume 42 Issue 3 Pages 107-114  
  Keywords  
  Abstract Background: Second primary malignancies (SPM) in the lung are not common in breast cancer (BC) patients. EGFR-mutant lung cancer (LC) is a separate molecular subset, and the co-existence of EGFR-mutant LC and BC has not been explored. We hypothesized that EGFR-mutant LC patients could have higher rates of primary BC than those with EGFR-wild type (WT).

Methods: We collected data on clinical and molecular characteristics and outcomes of female patients with LC and a previous or simultaneous history of primary BC treated in our hospital from 2008 to 2014.

Results: Data on treatment, follow-up, and EGFR mutation status were available for 356 patients. 17.7% (11/62) of patients with EGFR mutations had BC, compared to 1.02% (3/294) of EGFR-WT patients (p < 0.001). Both tumors were metachronous in 81.8%, with LC diagnosed 9 years after the diagnosis of BC. 5 of the 6 (83.3%) BC patients treated with radiotherapy developed LC in an area within the radiation field. No EGFR mutations were detected in BC tissue and no HER2 expression was detected in LC samples.

Conclusion: SPM in the lung and breast occur more frequently among EGFR-mutant compared to EGFR-WT LC patients. Radiotherapy for BC may increase the risk of developing primary LC.
 
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  Series Editor (up) Series Title Abbreviated Series Title  
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  Area Expedition Conference  
  Notes IAM; 600.139; 600.145 Approved no  
  Call Number Admin @ si @ MQC2019 Serial 3476  
Permanent link to this record
 

 
Author Esmitt Ramirez; Carles Sanchez; Debora Gil edit   pdf
url  doi
openurl 
  Title Localizing Pulmonary Lesions Using Fuzzy Deep Learning Type Conference Article
  Year 2019 Publication 21st International Symposium on Symbolic and Numeric Algorithms for Scientific Computing Abbreviated Journal  
  Volume Issue Pages 290-294  
  Keywords  
  Abstract The usage of medical images is part of the clinical daily in several healthcare centers around the world. Particularly, Computer Tomography (CT) images are an important key in the early detection of suspicious lung lesions. The CT image exploration allows the detection of lung lesions before any invasive procedure (e.g. bronchoscopy, biopsy). The effective localization of lesions is performed using different image processing and computer vision techniques. Lately, the usage of deep learning models into medical imaging from detection to prediction shown that is a powerful tool for Computer-aided software. In this paper, we present an approach to localize pulmonary lung lesion using fuzzy deep learning. Our approach uses a simple convolutional neural network based using the LIDC-IDRI dataset. Each image is divided into patches associated a probability vector (fuzzy) according their belonging to anatomical structures on a CT. We showcase our approach as part of a full CAD system to exploration, planning, guiding and detection of pulmonary lesions.  
  Address Timisoara; Rumania; September 2019  
  Corporate Author Thesis  
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  Notes IAM; 600.145; 600.140; 601.337; 601.323 Approved no  
  Call Number Admin @ si @ RSG2019 Serial 3531  
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Author Patricia Marquez; Debora Gil ; Aura Hernandez-Sabate edit   pdf
doi  isbn
openurl 
  Title Error Analysis for Lucas-Kanade Based Schemes Type Conference Article
  Year 2012 Publication 9th International Conference on Image Analysis and Recognition Abbreviated Journal  
  Volume 7324 Issue I Pages 184-191  
  Keywords Optical flow, Confidence measure, Lucas-Kanade, Cardiac Magnetic Resonance  
  Abstract Optical flow is a valuable tool for motion analysis in medical imaging sequences. A reliable application requires determining the accuracy of the computed optical flow. This is a main challenge given the absence of ground truth in medical sequences. This paper presents an error analysis of Lucas-Kanade schemes in terms of intrinsic design errors and numerical stability of the algorithm. Our analysis provides a confidence measure that is naturally correlated to the accuracy of the flow field. Our experiments show the higher predictive value of our confidence measure compared to existing measures.  
  Address Aveiro, Portugal  
  Corporate Author Thesis  
  Publisher Springer-Verlag Berlin Heidelberg Place of Publication Editor  
  Language english Summary Language Original Title  
  Series Editor (up) Campilho, Aurélio and Kamel, Mohamed Series Title Lecture Notes in Computer Science Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-31294-6 Medium  
  Area Expedition Conference ICIAR  
  Notes IAM Approved no  
  Call Number IAM @ iam @ MGH2012a Serial 1899  
Permanent link to this record
 

 
Author Eric Amiel edit   pdf
url  openurl
  Title Visualisation de vaisseaux sanguins Type Report
  Year 2005 Publication Rapport de Stage Abbreviated Journal  
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  Corporate Author Université Paul Sabatier Toulouse III Thesis Bachelor's thesis  
  Publisher Université Paul Sabatier Toulouse III Place of Publication Toulouse Editor Enric Marti  
  Language French Summary Language French Original Title  
  Series Editor (up) IUP Systèmes Intelligents Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes IAM Approved no  
  Call Number IAM @ iam @ Ami2005 Serial 1690  
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