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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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  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  
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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  
  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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  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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  Area Expedition Conference SYNASC  
  Notes IAM; 600.145; 600.140; 601.337; 601.323 Approved no  
  Call Number Admin @ si @ RSG2019 Serial 3531  
Permanent link to this record
 

 
Author David Roche; Debora Gil; Jesus Giraldo edit   pdf
url  openurl
  Title Assessing agonist efficacy in an uncertain Em world Type Conference Article
  Year 2012 Publication 40th Keystone Symposia on mollecular and celular biology Abbreviated Journal  
  Volume Issue Pages 79  
  Keywords  
  Abstract The operational model of agonism has been widely used for the analysis of agonist action since its formulation in 1983. The model includes the Em parameter, which is defined as the maximum response of the system. The methods for Em estimation provide Em values not significantly higher than the maximum responses achieved by full agonists. However, it has been found that that some classes of compounds as, for instance, superagonists and positive allosteric modulators can increase the full agonist maximum response, implying upper limits for Em and thereby posing doubts on the validity of Em estimates. Because of the correlation between Em and operational efficacy, τ, wrong Em estimates will yield wrong τ estimates.
In this presentation, the operational model of agonism and various methods for the simulation of allosteric modulation will be analyzed. Alternatives for curve fitting will be presented and discussed.
 
  Address Fairmont Banff Springs, Banff, Alberta, Canada  
  Corporate Author Keystone Symposia Thesis  
  Publisher Keystone Symposia Place of Publication Editor (up) A. Christopoulus and M. Bouvier  
  Language english Summary Language english Original Title  
  Series Editor Keystone Symposia Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference KSMCB  
  Notes IAM Approved no  
  Call Number IAM @ iam @ RGG2012 Serial 1855  
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Author Debora Gil; Petia Radeva edit   pdf
openurl 
  Title Inhibition of False Landmarks Type Book Chapter
  Year 2004 Publication Recent Advances in Artificial Intelligence Research and Development Abbreviated Journal  
  Volume Issue Pages 233-244  
  Keywords  
  Abstract We argue that a corner detector should be based on the degree of continuity of the tangent vector to the image level sets, work on the image domain and need no assumptions on neither the image local structure nor the particular geometry of the corner/junction. An operator measuring the degree of differentiability of the projection matrix on the image gradient fulfills the above requirements. Its high sensitivity to changes in vector directions makes it suitable for landmark location in real images prone to need smoothing to reduce the impact of noise. Because using smoothing kernels leads to corner misplacement, we suggest an alternative fake response remover based on the receptive field inhibition of spurious details. The combination of both orientation discontinuity detection and noise inhibition produce our Inhibition Orientation Energy (IOE) landmark locator.  
  Address  
  Corporate Author Thesis  
  Publisher IOS Press Place of Publication Barcelona (Spain) Editor (up) al, J.V. et  
  Language Summary Language Original Title  
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  Notes IAM;MILAB Approved no  
  Call Number IAM @ iam @ GiR2004a Serial 1533  
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