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Gibaud B, Forestier G, Feldmann C, Ferrigno G, Gonçalves P, Haidegger T, Julliard C, Katić D, Kenngott H, Maier-Hein L, März K, de Momi E, Nagy DÁ, Nakawala H, Neumann J, Neumuth T, Rojas Balderrama J, Speidel S, Wagner M, Jannin P. Toward a standard ontology of surgical process models. Int J Comput Assist Radiol Surg 2018; 13:1397-1408. [PMID: 30006820 DOI: 10.1007/s11548-018-1824-5] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2018] [Accepted: 07/05/2018] [Indexed: 12/15/2022]
Abstract
PURPOSE The development of common ontologies has recently been identified as one of the key challenges in the emerging field of surgical data science (SDS). However, past and existing initiatives in the domain of surgery have mainly been focussing on individual groups and failed to achieve widespread international acceptance by the research community. To address this challenge, the authors of this paper launched a European initiative-OntoSPM Collaborative Action-with the goal of establishing a framework for joint development of ontologies in the field of SDS. This manuscript summarizes the goals and the current status of the international initiative. METHODS A workshop was organized in 2016, gathering the main European research groups having experience in developing and using ontologies in this domain. It led to the conclusion that a common ontology for surgical process models (SPM) was absolutely needed, and that the existing OntoSPM ontology could provide a good starting point toward the collaborative design and promotion of common, standard ontologies on SPM. RESULTS The workshop led to the OntoSPM Collaborative Action-launched in mid-2016-with the objective to develop, maintain and promote the use of common ontologies of SPM relevant to the whole domain of SDS. The fundamental concept, the architecture, the management and curation of the common ontology have been established, making it ready for wider public use. CONCLUSION The OntoSPM Collaborative Action has been in operation for 24 months, with a growing dedicated membership. Its main result is a modular ontology, undergoing constant updates and extensions, based on the experts' suggestions. It remains an open collaborative action, which always welcomes new contributors and applications.
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Affiliation(s)
| | | | - Carolin Feldmann
- Division of Computer Assisted Medical Interventions, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | | | - Paulo Gonçalves
- Instituto Politécnico de Castelo Branco, Castelo Branco, Portugal.,IDMEC, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Tamás Haidegger
- Antal Bejczy Center for Intelligent Robotics, Óbuda University, Budapest, Hungary.,Austrian Center for Medical Innovation and Technology (ACMIT), Wiener Neustadt, Austria
| | - Chantal Julliard
- Inserm, LTSI - UMR_S 1099, Univ Rennes, Rennes, France.,LIRMM, Université de Montpellier, Montpellier, France.,Stryker GmbH, Freiburg, Germany
| | - Darko Katić
- Karlsruhe Institute of Technology, Institute for Anthropomatics and Robotics, Karlsruhe, Germany.,ArtiMinds Robotics GmbH, Karlsruhe, Germany
| | - Hannes Kenngott
- Department of General, Abdominal and Transplantation Surgery, University of Heidelberg, Heidelberg, Germany
| | - Lena Maier-Hein
- Division of Computer Assisted Medical Interventions, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Keno März
- Division of Computer Assisted Medical Interventions, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | | | - Dénes Ákos Nagy
- Antal Bejczy Center for Intelligent Robotics, Óbuda University, Budapest, Hungary.,Austrian Center for Medical Innovation and Technology (ACMIT), Wiener Neustadt, Austria
| | | | - Juliane Neumann
- Innovation Center Computer Assisted Surgery, Leipzig University, Leipzig, Germany
| | - Thomas Neumuth
- Innovation Center Computer Assisted Surgery, Leipzig University, Leipzig, Germany
| | | | | | - Martin Wagner
- Department of General, Abdominal and Transplantation Surgery, University of Heidelberg, Heidelberg, Germany
| | - Pierre Jannin
- Inserm, LTSI - UMR_S 1099, Univ Rennes, Rennes, France
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Patel NM, Michelini VV, Snell JM, Balu S, Hoyle AP, Parker JS, Hayward MC, Eberhard DA, Salazar AH, McNeillie P, Xu J, Huettner CS, Koyama T, Utro F, Rhrissorrakrai K, Norel R, Bilal E, Royyuru A, Parida L, Earp HS, Grilley-Olson JE, Hayes DN, Harvey SJ, Sharpless NE, Kim WY. Enhancing Next-Generation Sequencing-Guided Cancer Care Through Cognitive Computing. Oncologist 2017; 23:179-185. [PMID: 29158372 PMCID: PMC5813753 DOI: 10.1634/theoncologist.2017-0170] [Citation(s) in RCA: 64] [Impact Index Per Article: 9.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2017] [Accepted: 10/06/2017] [Indexed: 11/20/2022] Open
Abstract
Next‐generation sequencing (NGS) has emerged as an affordable and reproducible means to query tumors for somatic genetic anomalies. To help interpret somatic NGS data, many institutions have created a molecular tumor board to analyze the results of NGS and make recommendations. This article evaluates the utility of cognitive computing systems to analyze data for clinical decision‐making. Background. Using next‐generation sequencing (NGS) to guide cancer therapy has created challenges in analyzing and reporting large volumes of genomic data to patients and caregivers. Specifically, providing current, accurate information on newly approved therapies and open clinical trials requires considerable manual curation performed mainly by human “molecular tumor boards” (MTBs). The purpose of this study was to determine the utility of cognitive computing as performed by Watson for Genomics (WfG) compared with a human MTB. Materials and Methods. One thousand eighteen patient cases that previously underwent targeted exon sequencing at the University of North Carolina (UNC) and subsequent analysis by the UNCseq informatics pipeline and the UNC MTB between November 7, 2011, and May 12, 2015, were analyzed with WfG, a cognitive computing technology for genomic analysis. Results. Using a WfG‐curated actionable gene list, we identified additional genomic events of potential significance (not discovered by traditional MTB curation) in 323 (32%) patients. The majority of these additional genomic events were considered actionable based upon their ability to qualify patients for biomarker‐selected clinical trials. Indeed, the opening of a relevant clinical trial within 1 month prior to WfG analysis provided the rationale for identification of a new actionable event in nearly a quarter of the 323 patients. This automated analysis took <3 minutes per case. Conclusion. These results demonstrate that the interpretation and actionability of somatic NGS results are evolving too rapidly to rely solely on human curation. Molecular tumor boards empowered by cognitive computing could potentially improve patient care by providing a rapid, comprehensive approach for data analysis and consideration of up‐to‐date availability of clinical trials. Implications for Practice. The results of this study demonstrate that the interpretation and actionability of somatic next‐generation sequencing results are evolving too rapidly to rely solely on human curation. Molecular tumor boards empowered by cognitive computing can significantly improve patient care by providing a fast, cost‐effective, and comprehensive approach for data analysis in the delivery of precision medicine. Patients and physicians who are considering enrollment in clinical trials may benefit from the support of such tools applied to genomic data.
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Affiliation(s)
- Nirali M Patel
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
- Department of Pathology and Laboratory Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | | | - Jeff M Snell
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Saianand Balu
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Alan P Hoyle
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Joel S Parker
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Michele C Hayward
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - David A Eberhard
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
- Department of Pathology and Laboratory Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Ashley H Salazar
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | | | - Jia Xu
- IBM Watson Health, Cambridge, Massachusetts, USA
| | | | | | | | | | | | - Erhan Bilal
- IBM Research, Yorktown Heights, New York, USA
| | | | | | - H Shelton Earp
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
- Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Juneko E Grilley-Olson
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
- Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - D Neil Hayes
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
- Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | | | - Norman E Sharpless
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
- Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - William Y Kim
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
- Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
- Department of Urology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
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