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Ryska A, Sapino A, Landolfi S, Valero IS, Cajal SRY, Oliveira P, Detillo P, Lianas L, Frexia F, Nicolosi PA, Monti T, Bussolati B, Marchiò C, Bussolati G. Glyoxal acid-free (GAF) histological fixative is a suitable alternative to formalin: results from an open-label comparative non-inferiority study. Virchows Arch 2023:10.1007/s00428-023-03692-6. [PMID: 37996705 DOI: 10.1007/s00428-023-03692-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2023] [Revised: 10/09/2023] [Accepted: 10/29/2023] [Indexed: 11/25/2023]
Abstract
Formalin, an aqueous solution of formaldehyde, has been the gold standard for fixation of histological samples for over a century. Despite its considerable advantages, growing evidence points to objective toxicity, particularly highlighting its carcinogenicity and mutagenic effects. In 2016, the European Union proposed a ban, but a temporary permission was granted in consideration of its fundamental role in the medical-diagnostic field. In the present study, we tested an innovative fixative, glyoxal acid-free (GAF) (a glyoxal solution deprived of acids), which allows optimal tissue fixation at structural and molecular level combined with the absence of toxicity and carcinogenic activity. An open-label, non-inferiority, multicentric trial was performed comparing fixation of histological specimens with GAF fixative vs standard phosphate-buffered formalin (PBF), evaluating the morphological preservation and the diagnostic value with four binary score questions answered by both the central pathology reviewer and local center reviewers. The mean of total score in the GAF vs PBF fixative groups was 3.7 ± 0.5 vs 3.9 ± 0.3 for the central reviewer and 3.8 ± 0.5 vs 4.0 ± 0.1 for the local pathologist reviewers, respectively. In terms of median value, similar results were observed between the two fixative groups, with a median value of 4.0. Data collected indicate the non-inferiority of GAF as compared to PBF for all organs tested. The present clinical performance study, performed following the international standard for performance evaluation of in vitro diagnostic medical devices, highlights the capability of GAF to ensure both structural preservation and diagnostic value of the preparations.
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Affiliation(s)
- Ales Ryska
- The Fingerland Department of Pathology, Charles University and Faculty Hospital, Hradec Kralove, Czech Republic
| | - Anna Sapino
- Candiolo Cancer Institute, FPO-IRCCS, Candiolo, Turin, Italy
- Department of Medical Sciences, University of Turin, Turin, Italy
| | - Stefania Landolfi
- Pathology Department, Hospital Universitari Vall d'Hebron, Barcelona, Spain
| | | | | | - Pedro Oliveira
- Department of Pathology, The Christie NHS Foundation Trust, Manchester, UK
| | | | - Luca Lianas
- Data-Intensive Computing Division, Center for Advanced Studies, Research and Development in Sardinia (CRS4), Pula, Italy
| | - Francesca Frexia
- Data-Intensive Computing Division, Center for Advanced Studies, Research and Development in Sardinia (CRS4), Pula, Italy
| | | | | | - Benedetta Bussolati
- Department of Molecular Biotechnology and Health Sciences, University of Turin, Turin, Italy
| | - Caterina Marchiò
- Candiolo Cancer Institute, FPO-IRCCS, Candiolo, Turin, Italy
- Department of Medical Sciences, University of Turin, Turin, Italy
| | - Gianni Bussolati
- Department of Medical Sciences, University of Turin, Turin, Italy.
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2
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Destefanis N, Fiano V, Milani L, Vasapolli P, Fiorentino M, Giunchi F, Lianas L, Del Rio M, Frexia F, Pireddu L, Molinaro L, Cassoni P, Papotti MG, Gontero P, Calleris G, Oderda M, Ricardi U, Iorio GC, Fariselli P, Isaevska E, Akre O, Zelic R, Pettersson A, Zugna D, Richiardi L. Cohort profile: the Turin prostate cancer prognostication (TPCP) cohort. Front Oncol 2023; 13:1242639. [PMID: 37869094 PMCID: PMC10587560 DOI: 10.3389/fonc.2023.1242639] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Accepted: 09/18/2023] [Indexed: 10/24/2023] Open
Abstract
Introduction Prostate cancer (PCa) is the most frequent tumor among men in Europe and has both indolent and aggressive forms. There are several treatment options, the choice of which depends on multiple factors. To further improve current prognostication models, we established the Turin Prostate Cancer Prognostication (TPCP) cohort, an Italian retrospective biopsy cohort of patients with PCa and long-term follow-up. This work presents this new cohort with its main characteristics and the distributions of some of its core variables, along with its potential contributions to PCa research. Methods The TPCP cohort includes consecutive non-metastatic patients with first positive biopsy for PCa performed between 2008 and 2013 at the main hospital in Turin, Italy. The follow-up ended on December 31st 2021. The primary outcome is the occurrence of metastasis; death from PCa and overall mortality are the secondary outcomes. In addition to numerous clinical variables, the study's prognostic variables include histopathologic information assigned by a centralized uropathology review using a digital pathology software system specialized for the study of PCa, tumor DNA methylation in candidate genes, and features extracted from digitized slide images via Deep Neural Networks. Results The cohort includes 891 patients followed-up for a median time of 10 years. During this period, 97 patients had progression to metastatic disease and 301 died; of these, 56 died from PCa. In total, 65.3% of the cohort has a Gleason score less than or equal to 3 + 4, and 44.5% has a clinical stage cT1. Consistent with previous studies, age and clinical stage at diagnosis are important prognostic factors: the crude cumulative incidence of metastatic disease during the 14-years of follow-up increases from 9.1% among patients younger than 64 to 16.2% for patients in the age group of 75-84, and from 6.1% for cT1 stage to 27.9% in cT3 stage. Discussion This study stands to be an important resource for updating existing prognostic models for PCa on an Italian cohort. In addition, the integrated collection of multi-modal data will allow development and/or validation of new models including new histopathological, digital, and molecular markers, with the goal of better directing clinical decisions to manage patients with PCa.
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Affiliation(s)
- Nicolas Destefanis
- Cancer Epidemiology Unit, Department of Medical Sciences, University of Turin, Turin, Italy
| | - Valentina Fiano
- Cancer Epidemiology Unit, Department of Medical Sciences, University of Turin, Turin, Italy
| | - Lorenzo Milani
- Cancer Epidemiology Unit, Department of Medical Sciences, University of Turin, Turin, Italy
| | - Paolo Vasapolli
- Cancer Epidemiology Unit, Department of Medical Sciences, University of Turin, Turin, Italy
| | - Michelangelo Fiorentino
- DIMEC Department of Medicine and Surgery, Alma Mater Studiorum, University of Bologna, Bologna, Italy
| | - Francesca Giunchi
- Department of Pathology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy
| | - Luca Lianas
- Visual and Data-intensive Computing, CRS4 (Center for Advanced Studies, Research and Development in Sardinia), Pula, Italy
| | - Mauro Del Rio
- Visual and Data-intensive Computing, CRS4 (Center for Advanced Studies, Research and Development in Sardinia), Pula, Italy
| | - Francesca Frexia
- Visual and Data-intensive Computing, CRS4 (Center for Advanced Studies, Research and Development in Sardinia), Pula, Italy
| | - Luca Pireddu
- Visual and Data-intensive Computing, CRS4 (Center for Advanced Studies, Research and Development in Sardinia), Pula, Italy
| | - Luca Molinaro
- Pathology Unit, Department of Medical Sciences, University of Turin, Turin, Italy
| | - Paola Cassoni
- Pathology Unit, Department of Medical Sciences, University of Turin, Turin, Italy
| | | | - Paolo Gontero
- Urology Unit, Department of Surgical Sciences, University of Turin, Molinette Hospital, Turin, Italy
| | - Giorgio Calleris
- Urology Unit, Department of Surgical Sciences, University of Turin, Molinette Hospital, Turin, Italy
| | - Marco Oderda
- Urology Unit, Department of Surgical Sciences, University of Turin, Molinette Hospital, Turin, Italy
| | | | | | - Piero Fariselli
- Computational Biomedicine Unit, Department of Medical Sciences, University of Turin, Turin, Italy
| | - Elena Isaevska
- Cancer Epidemiology Unit, Department of Medical Sciences, University of Turin, Turin, Italy
| | - Olof Akre
- Department of Molecular Medicine and Surgery, Section of Urology, Karolinska Institutet, Stockholm, Sweden
| | - Renata Zelic
- Department of Molecular Medicine and Surgery, Karolinska Institutet and Department of Pelvic Cancer, Karolinska University Hospital, Stockholm, Sweden
| | - Andreas Pettersson
- Clinical Epidemiology Division, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
| | - Daniela Zugna
- Cancer Epidemiology Unit, Department of Medical Sciences, University of Turin, Turin, Italy
| | - Lorenzo Richiardi
- Cancer Epidemiology Unit, Department of Medical Sciences, University of Turin, Turin, Italy
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Zelic R, Giunchi F, Fridfeldt J, Carlsson J, Davidsson S, Lianas L, Mascia C, Zugna D, Molinaro L, Vincent PH, Zanetti G, Andrén O, Richiardi L, Akre O, Fiorentino M, Pettersson A. Prognostic Utility of the Gleason Grading System Revisions and Histopathological Factors Beyond Gleason Grade. Clin Epidemiol 2022; 14:59-70. [PMID: 35082531 PMCID: PMC8784949 DOI: 10.2147/clep.s339140] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2021] [Accepted: 12/14/2021] [Indexed: 11/30/2022] Open
Abstract
Background The International Society of Urological Pathology (ISUP) revised the Gleason system in 2005 and 2014. The impact of these changes on prostate cancer (PCa) prognostication remains unclear. Objective To evaluate if the ISUP 2014 Gleason score (GS) predicts PCa death better than the pre-2005 GS, and if additional histopathological information can further improve PCa death prediction. Patients and Methods We conducted a case–control study nested among men in the National Prostate Cancer Register of Sweden diagnosed with non-metastatic PCa 1998–2015. We included 369 men who died from PCa (cases) and 369 men who did not (controls). Two uro-pathologists centrally re-reviewed biopsy ISUP 2014 Gleason grading, poorly formed glands, cribriform pattern, comedonecrosis, perineural invasion, intraductal, ductal and mucinous carcinoma, percentage Gleason 4, inflammation, high-grade prostatic intraepithelial neoplasia (HGPIN) and post-atrophic hyperplasia. Pre-2005 GS was back-transformed using i) information on cribriform pattern and/or poorly formed glands and ii) the diagnostic GS from the registry. Models were developed using Firth logistic regression and compared in terms of discrimination (AUC). Results The ISUP 2014 GS (AUC = 0.808) performed better than the pre-2005 GS when back-transformed using only cribriform pattern (AUC = 0.785) or both cribriform and poorly formed glands (AUC = 0.792), but not when back-transformed using only poorly formed glands (AUC = 0.800). Similarly, the ISUP 2014 GS performed better than the diagnostic GS (AUC = 0.808 vs 0.781). Comedonecrosis (AUC = 0.811), HGPIN (AUC = 0.810) and number of cores with ≥50% cancer (AUC = 0.810) predicted PCa death independently of the ISUP 2014 GS. Conclusion The Gleason Grading revisions have improved PCa death prediction, likely due to classifying cribriform patterns, rather than poorly formed glands, as Gleason 4. Comedonecrosis, HGPIN and number of cores with ≥50% cancer further improve PCa death discrimination slightly.
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Affiliation(s)
- Renata Zelic
- Clinical Epidemiology Division, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
- Correspondence: Renata Zelic Clinical Epidemiology Division, Department of Medicine Solna, Karolinska Institutet, K2 Medicin, Solna, K2 Klinisk epidemiologi K Ekström Smedby, Stockholm, 171 77, SwedenTel +46703136037Fax +46851779304 Email
| | - Francesca Giunchi
- Pathology Department, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy
| | - Jonna Fridfeldt
- Department of Urology, Faculty of Medicine and Health, Örebro University, Örebro, Sweden
| | - Jessica Carlsson
- Department of Urology, Faculty of Medicine and Health, Örebro University, Örebro, Sweden
| | - Sabina Davidsson
- Department of Urology, Faculty of Medicine and Health, Örebro University, Örebro, Sweden
| | - Luca Lianas
- Data-Intensive Computing Division, Center for Advanced Studies, Research and Development in Sardinia (CRS4), Pula, Italy
| | - Cecilia Mascia
- Data-Intensive Computing Division, Center for Advanced Studies, Research and Development in Sardinia (CRS4), Pula, Italy
| | - Daniela Zugna
- Cancer Epidemiology Unit, Department of Medical Sciences, University of Turin, and CPO-Piemonte, Turin, Italy
| | - Luca Molinaro
- Division of Pathology, A.O. Città della Salute e della Scienza Hospital, Turin, Italy
| | - Per Henrik Vincent
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Department of Urology, Karolinska University Hospital, Stockholm, Sweden
| | - Gianluigi Zanetti
- Data-Intensive Computing Division, Center for Advanced Studies, Research and Development in Sardinia (CRS4), Pula, Italy
| | - Ove Andrén
- Department of Urology, Faculty of Medicine and Health, Örebro University, Örebro, Sweden
| | - Lorenzo Richiardi
- Cancer Epidemiology Unit, Department of Medical Sciences, University of Turin, and CPO-Piemonte, Turin, Italy
| | - Olof Akre
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Department of Urology, Karolinska University Hospital, Stockholm, Sweden
| | | | - Andreas Pettersson
- Clinical Epidemiology Division, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
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Abstract
The FAIR Principles are a set of recommendations that aim to underpin knowledge discovery and integration by making the research outcomes Findable, Accessible, Interoperable and Reusable. These guidelines encourage the accurate recording and exchange of data, coupled with contextual information about their creation, expressed in domain-specific standards and machine-readable formats. This paper analyses the potential support to FAIRness of the openEHR specifications and reference implementation, by theoretically assessing their compliance with each of the 15 FAIR principles. Our study highlights how the openEHR approach, thanks to its computable semantics-oriented design, is inherently FAIR-enabling and is a promising implementation strategy for creating FAIR-compliant Clinical Data Repositories (CDRs).
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Affiliation(s)
- Francesca Frexia
- CRS4: Center for Advanced Studies, Research and Development in Sardinia, Italy
| | - Cecilia Mascia
- CRS4: Center for Advanced Studies, Research and Development in Sardinia, Italy
| | - Luca Lianas
- CRS4: Center for Advanced Studies, Research and Development in Sardinia, Italy
| | - Giovanni Delussu
- CRS4: Center for Advanced Studies, Research and Development in Sardinia, Italy
| | - Alessandro Sulis
- CRS4: Center for Advanced Studies, Research and Development in Sardinia, Italy
| | - Vittorio Meloni
- CRS4: Center for Advanced Studies, Research and Development in Sardinia, Italy
| | - Mauro Del Rio
- CRS4: Center for Advanced Studies, Research and Development in Sardinia, Italy
| | - Gianluigi Zanetti
- CRS4: Center for Advanced Studies, Research and Development in Sardinia, Italy
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5
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Zelic R, Giunchi F, Lianas L, Mascia C, Zanetti G, Andrén O, Fridfeldt J, Carlsson J, Davidsson S, Molinaro L, Vincent PH, Richiardi L, Akre O, Fiorentino M, Pettersson A. Interchangeability of light and virtual microscopy for histopathological evaluation of prostate cancer. Sci Rep 2021; 11:3257. [PMID: 33547336 PMCID: PMC7864946 DOI: 10.1038/s41598-021-82911-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2020] [Accepted: 12/29/2020] [Indexed: 01/01/2023] Open
Abstract
Virtual microscopy (VM) holds promise to reduce subjectivity as well as intra- and inter-observer variability for the histopathological evaluation of prostate cancer. We evaluated (i) the repeatability (intra-observer agreement) and reproducibility (inter-observer agreement) of the 2014 Gleason grading system and other selected features using standard light microscopy (LM) and an internally developed VM system, and (ii) the interchangeability of LM and VM. Two uro-pathologists reviewed 413 cores from 60 Swedish men diagnosed with non-metastatic prostate cancer 1998–2014. Reviewer 1 performed two reviews using both LM and VM. Reviewer 2 performed one review using both methods. The intra- and inter-observer agreement within and between LM and VM were assessed using Cohen’s kappa and Bland and Altman’s limits of agreement. We found good repeatability and reproducibility for both LM and VM, as well as interchangeability between LM and VM, for primary and secondary Gleason pattern, Gleason Grade Groups, poorly formed glands, cribriform pattern and comedonecrosis but not for the percentage of Gleason pattern 4. Our findings confirm the non-inferiority of VM compared to LM. The repeatability and reproducibility of percentage of Gleason pattern 4 was poor regardless of method used warranting further investigation and improvement before it is used in clinical practice.
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Affiliation(s)
- Renata Zelic
- Clinical Epidemiology Division, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden.
| | | | - Luca Lianas
- Data-Intensive Computing Division, Center for Advanced Studies, Research and Development in Sardinia (CRS4), Pula, Italy
| | - Cecilia Mascia
- Data-Intensive Computing Division, Center for Advanced Studies, Research and Development in Sardinia (CRS4), Pula, Italy
| | - Gianluigi Zanetti
- Data-Intensive Computing Division, Center for Advanced Studies, Research and Development in Sardinia (CRS4), Pula, Italy
| | - Ove Andrén
- Department of Urology, Faculty of Medicine and Health, Örebro University, Örebro, Sweden
| | - Jonna Fridfeldt
- Department of Urology, Faculty of Medicine and Health, Örebro University, Örebro, Sweden
| | - Jessica Carlsson
- Department of Urology, Faculty of Medicine and Health, Örebro University, Örebro, Sweden
| | - Sabina Davidsson
- Department of Urology, Faculty of Medicine and Health, Örebro University, Örebro, Sweden
| | - Luca Molinaro
- Division of Pathology, A.O. Città Della Salute e Della Scienza Hospital, Turin, Italy
| | - Per Henrik Vincent
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden.,Department of Urology, Karolinska University Hospital, Stockholm, Sweden
| | - Lorenzo Richiardi
- Cancer Epidemiology Unit, Department of Medical Sciences, University of Turin, and CPO-Piemonte, Turin, Italy
| | - Olof Akre
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden.,Department of Urology, Karolinska University Hospital, Stockholm, Sweden
| | | | - Andreas Pettersson
- Clinical Epidemiology Division, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
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Zelic R, Giunchi F, Fridfeldt J, Carlsson J, Davidsson S, Lianas L, Mascia C, Zugna D, Molinaro L, Vincent P, Zanetti G, Andrén O, Richiardi L, Akre O, Fiorentino M, Pettersson A. Prognostic utility of the Gleason grading system revisions. EUR UROL SUPPL 2020. [DOI: 10.1016/s2666-1683(20)33873-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022] Open
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Zelic R, Zugna D, Bottai M, Andrén O, Fridfeldt J, Carlsson J, Davidsson S, Fiano V, Fiorentino M, Giunchi F, Grasso C, Lianas L, Mascia C, Molinaro L, Zanetti G, Richiardi L, Pettersson A, Akre O. Estimation of Relative and Absolute Risks in a Competing-Risks Setting Using a Nested Case-Control Study Design: Example From the ProMort Study. Am J Epidemiol 2019; 188:1165-1173. [PMID: 30976789 PMCID: PMC8210820 DOI: 10.1093/aje/kwz026] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2017] [Revised: 01/28/2019] [Accepted: 01/29/2019] [Indexed: 12/16/2022] Open
Abstract
In this paper, we describe the Prognostic Factors for Mortality in Prostate Cancer (ProMort) study and use it to demonstrate how the weighted likelihood method can be used in nested case-control studies to estimate both relative and absolute risks in the competing-risks setting. ProMort is a case-control study nested within the National Prostate Cancer Register (NPCR) of Sweden, comprising 1,710 men diagnosed with low- or intermediate-risk prostate cancer between 1998 and 2011 who died from prostate cancer (cases) and 1,710 matched controls. Cause-specific hazard ratios and cumulative incidence functions (CIFs) for prostate cancer death were estimated in ProMort using weighted flexible parametric models and compared with the corresponding estimates from the NPCR cohort. We further drew 1,500 random nested case-control subsamples of the NPCR cohort and quantified the bias in the hazard ratio and CIF estimates. Finally, we compared the ProMort estimates with those obtained by augmenting competing-risks cases and by augmenting both competing-risks cases and controls. The hazard ratios for prostate cancer death estimated in ProMort were comparable to those in the NPCR. The hazard ratios for dying from other causes were biased, which introduced bias in the CIFs estimated in the competing-risks setting. When augmenting both competing-risks cases and controls, the bias was reduced.
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Affiliation(s)
- Renata Zelic
- Clinical Epidemiology Unit, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
| | - Daniela Zugna
- Cancer Epidemiology Unit, Department of Medical Sciences, University of Turin, Turin, Italy
- Centro di Riferimento per l’Epidemiologia e la Prevenzione Oncologica
| | - Matteo Bottai
- Unit of Biostatistics, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Ove Andrén
- Department of Urology, Faculty of Medicine and Health, Örebro University, Örebro, Sweden
| | - Jonna Fridfeldt
- Department of Urology, Faculty of Medicine and Health, Örebro University, Örebro, Sweden
| | - Jessica Carlsson
- Department of Urology, Faculty of Medicine and Health, Örebro University, Örebro, Sweden
| | - Sabina Davidsson
- Department of Urology, Faculty of Medicine and Health, Örebro University, Örebro, Sweden
| | - Valentina Fiano
- Cancer Epidemiology Unit, Department of Medical Sciences, University of Turin, Turin, Italy
- Centro di Riferimento per l’Epidemiologia e la Prevenzione Oncologica
| | - Michelangelo Fiorentino
- Pathology Service, Addarii Institute of Oncology, Sant’Orsola-Malpighi Hospital, Bologna, Italy
| | - Francesca Giunchi
- Pathology Service, Addarii Institute of Oncology, Sant’Orsola-Malpighi Hospital, Bologna, Italy
| | - Chiara Grasso
- Cancer Epidemiology Unit, Department of Medical Sciences, University of Turin, Turin, Italy
- Centro di Riferimento per l’Epidemiologia e la Prevenzione Oncologica
| | - Luca Lianas
- Data-Intensive Computing Division, Center for Advanced Studies, Research and Development in Sardinia, Pula, Italy
| | - Cecilia Mascia
- Data-Intensive Computing Division, Center for Advanced Studies, Research and Development in Sardinia, Pula, Italy
| | - Luca Molinaro
- Division of Pathology, Azienda Ospedaliero-Universitaria Città della Salute e della Scienza Hospital, Turin, Italy
| | - Gianluigi Zanetti
- Data-Intensive Computing Division, Center for Advanced Studies, Research and Development in Sardinia, Pula, Italy
| | - Lorenzo Richiardi
- Cancer Epidemiology Unit, Department of Medical Sciences, University of Turin, Turin, Italy
- Centro di Riferimento per l’Epidemiologia e la Prevenzione Oncologica
| | - Andreas Pettersson
- Clinical Epidemiology Unit, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
| | - Olof Akre
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Department of Urology, Karolinska University Hospital, Stockholm, Sweden
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8
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Delussu G, Lianas L, Frexia F, Zanetti G. A Scalable Data Access Layer to Manage Structured Heterogeneous Biomedical Data. PLoS One 2016; 11:e0168004. [PMID: 27936191 PMCID: PMC5148592 DOI: 10.1371/journal.pone.0168004] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2016] [Accepted: 11/24/2016] [Indexed: 01/10/2023] Open
Abstract
This work presents a scalable data access layer, called PyEHR, designed to support the implementation of data management systems for secondary use of structured heterogeneous biomedical and clinical data. PyEHR adopts the openEHR's formalisms to guarantee the decoupling of data descriptions from implementation details and exploits structure indexing to accelerate searches. Data persistence is guaranteed by a driver layer with a common driver interface. Interfaces for two NoSQL Database Management Systems are already implemented: MongoDB and Elasticsearch. We evaluated the scalability of PyEHR experimentally through two types of tests, called "Constant Load" and "Constant Number of Records", with queries of increasing complexity on synthetic datasets of ten million records each, containing very complex openEHR archetype structures, distributed on up to ten computing nodes.
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Affiliation(s)
| | - Luca Lianas
- Data-Intensive Computing Group, CRS4, Pula, Italy
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Abstract
Summary: BioBlend.objects is a new component of the BioBlend package, adding an object-oriented interface for the Galaxy REST-based application programming interface. It improves support for metacomputing on Galaxy entities by providing higher-level functionality and allowing users to more easily create programs to explore, query and create Galaxy datasets and workflows. Availability and implementation: BioBlend.objects is available online at https://github.com/afgane/bioblend. The new object-oriented API is implemented by the galaxy/objects subpackage. Contact:simone.leo@crs4.it
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Affiliation(s)
- Simone Leo
- CRS4, Polaris, 09010 Pula (CA), Università degli Studi di Cagliari, via Università 40, 09124 Cagliari, Italy and Ruđer Bošković Institute, 10000 Zagreb, Croatia CRS4, Polaris, 09010 Pula (CA), Università degli Studi di Cagliari, via Università 40, 09124 Cagliari, Italy and Ruđer Bošković Institute, 10000 Zagreb, Croatia
| | - Luca Pireddu
- CRS4, Polaris, 09010 Pula (CA), Università degli Studi di Cagliari, via Università 40, 09124 Cagliari, Italy and Ruđer Bošković Institute, 10000 Zagreb, Croatia CRS4, Polaris, 09010 Pula (CA), Università degli Studi di Cagliari, via Università 40, 09124 Cagliari, Italy and Ruđer Bošković Institute, 10000 Zagreb, Croatia
| | - Gianmauro Cuccuru
- CRS4, Polaris, 09010 Pula (CA), Università degli Studi di Cagliari, via Università 40, 09124 Cagliari, Italy and Ruđer Bošković Institute, 10000 Zagreb, Croatia
| | - Luca Lianas
- CRS4, Polaris, 09010 Pula (CA), Università degli Studi di Cagliari, via Università 40, 09124 Cagliari, Italy and Ruđer Bošković Institute, 10000 Zagreb, Croatia
| | - Nicola Soranzo
- CRS4, Polaris, 09010 Pula (CA), Università degli Studi di Cagliari, via Università 40, 09124 Cagliari, Italy and Ruđer Bošković Institute, 10000 Zagreb, Croatia
| | - Enis Afgan
- CRS4, Polaris, 09010 Pula (CA), Università degli Studi di Cagliari, via Università 40, 09124 Cagliari, Italy and Ruđer Bošković Institute, 10000 Zagreb, Croatia
| | - Gianluigi Zanetti
- CRS4, Polaris, 09010 Pula (CA), Università degli Studi di Cagliari, via Università 40, 09124 Cagliari, Italy and Ruđer Bošković Institute, 10000 Zagreb, Croatia
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Mongeau R, Casu MA, Pani L, Pillolla G, Lianas L, Giachetti A. Building a virtual archive using brain architecture and Web 3D to deliver neuropsychopharmacology content over the Internet. Comput Methods Programs Biomed 2008; 90:124-136. [PMID: 18262677 DOI: 10.1016/j.cmpb.2007.12.007] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/09/2007] [Revised: 12/04/2007] [Accepted: 12/15/2007] [Indexed: 05/25/2023]
Abstract
The vast amount of heterogeneous data generated in various fields of neurosciences such as neuropsychopharmacology can hardly be classified using traditional databases. We present here the concept of a virtual archive, spatially referenced over a simplified 3D brain map and accessible over the Internet. A simple prototype (available at http://aquatics.crs4.it/neuropsydat3d) has been realized using current Web-based virtual reality standards and technologies. It illustrates how primary literature or summary information can easily be retrieved through hyperlinks mapped onto a 3D schema while navigating through neuroanatomy. Furthermore, 3D navigation and visualization techniques are used to enhance the representation of brain's neurotransmitters, pathways and the involvement of specific brain areas in any particular physiological or behavioral functions. The system proposed shows how the use of a schematic spatial organization of data, widely exploited in other fields (e.g. Geographical Information Systems) can be extremely useful to develop efficient tools for research and teaching in neurosciences.
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Affiliation(s)
- R Mongeau
- Neuroscienze Pharmaness, Scientific and Technological Park of Sardinia, Sardegna Ricerche, Pula, Italy.
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