Ontology based support for brain tumour study


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Ontology based support for brain tumour study

  1. 1. Ontology-based Support for Brain Tumour Study Subhashis Das MSLIS 2011-13 DRTC, Indian Statistical Institute
  2. 2. Presentation Structure Introduction and background Problems of current informaton retrieval systems Why I chose Ontology Ontology building method Use Conclusion
  3. 3. IntroductionFor the diagnosis and detection of brain tumourComputer based diagnosis system proves to be helpfulBrain tumour is one of the most deadly diseases in IndiaIt contributes significantly to morbidityPoor prognosis
  4. 4. Background Diagnosis using MRI & MRS is the main way of detection  Brain tumours remain an important cause of morbidity and mortality and afflict a large percentage of the World population.  In children over 1 year of age, brain tumours are the most common solid malignancies that cause disease-related death. MRI: Magnetic Resonance Imaging; MRS: Magnetic Resonance Scan
  5. 5. Why I chose brain tumours? Clinical importance  Important cause of morbidity and mortality in adults and children  Few improvements in outcome  New approaches to management needed via greater understanding
  6. 6. Problems in IR Current information retrieval systems mostly  Keyword search,  Low precision.  Junk retrieval
  7. 7. So what is the solution? Ontology based information system
  8. 8. What an ontology is and isnot?
  9. 9. Rumours about ontologies Ontologies are overly publicised:  “Ontology” is becoming a buzz word  “Ontology” can “say” whatever one intends to say  “Ontology” means inference  “Ontology” is the ultimate solution for interoperability
  10. 10. Ontology A common language/vocabulary/terminology for various participants  Formalised in an unambiguous representation  For software agents, human experts, patients To assist in communication between humans and computer To achieve interoperability To improve the design and quality of software systems
  11. 11. Ontology A “static” conceptualisation of the world  “What is?” rather than “How does?”  Allows reasoning which respects the translation of concepts as sets of (possible) individuals  Provides the underlying knowledge model for other types of reasoning, e.g. Rule Based, Case Based etc.  Ontology enhance the semantics of terms by providing richer relationships between the terms of vocabulary
  12. 12. Why OWL (Web OntologyLanguage)? Reasoning capability  Subsumption relationship (is-a)  Relies on necessary and sufficient definition of concepts  Good for maintaining a consistent ontology W3C standard  Good support: existing systems and tools  Good compatibility:  Many ontologies are developed in owl or will be translated into owl  Good extensibility
  13. 13. Benefits The analysis and combination of the information the result will be presented in a way that makes it easier for the user to have an overview of the up-to-date knowledge about brain tumour. The inherited organization of ontologies adds taxonomical context to search result making it easier for the research to spot conceptual relationships in data. Any one can find relationship between different factors that are responsible for brain tumour.
  14. 14. Other benefits Eliminating redundant effort Significant head-start Interoperability with other ontologies Community acceptance
  15. 15. Methodology Identification of the terminology Analysis Synthesis Standardization Ordering Sources: Giunchiglia, Fausto; Dutta, Biswanath;Maltese, Vincenzo and Farazi, Feroz (2012): A facet-based methodology for the construction of a large-scale geospatial ontology
  16. 16. Identification of theterminology Information sources National Brain Tumor Society (http://www.braintumor.org)-USA) American Brain Tumor Association (http://www.abta.org/) Brain Tumor Foundation of Canada (http://www.braintumour.ca/) Brain Tumor Association of Western Australia (http://braintumourwa.com) Resource pre-processing Mapping the resources Integration of the resources
  17. 17. Analysis and synthesis The formal terms collected during the previous phase are analyzed per genus. With the synthesis, formal terms are arrange into facets
  18. 18. StandardizationSNOMED CT®Systematized Nomenclature of Medicine-Clinical Term (SNOMED CT) more than 311,000 active concepts with unique meanings and formallogic-based definitions organized into 19 hierarchies.Medical Subject Headings (MeSH)The MeSH is a controlled vocabulary developed by the National Libraryof Medicine (NLM) for indexing and retrieval of biomedical literature,including MEDLINEMore than 1,77,000 entry Sources: http://www.ncbi.nlm.nih.gov/mesh and http://viw2.vetmed.vt.edu/sct/menu.cfm
  19. 19. Principles of building braintumour ontologyThe constructed brain tumour ontology has four main branchesTypes- Describing different types of brain tumourSymptoms- Describing symptoms of brain tumourCauses- Causes responsible for brain tumour which are mainlyenvironmental and geneticTreatments- Giving an overview of all treatments possible for thatparticular type of brain tumour
  20. 20. Types Primary tumors of the brain  Gliomas  Lowest grade tumors  Lower grade malignancies  Higher-grade malignancies  Highest-grade malignancies  Meningioma  Primitive neuroectodermal tumors (PNET)  Pituitary tumors  Pineal Tumors  Choroid plexus tumors  Other, more benign primary tumors  Tumors of nerves and/or nerve sheaths  Cyst  Other primary tumors, including skull base  Primary Central Nervous System Lymphoma (PCNSL) Metastatic brain tumors and carcinomatous meningitis
  21. 21. Symptoms A new seizure in an adult Gradual loss of movement or sensation in an arm or leg Unsteadiness or imbalance, especially if it is associated with headache Loss of vision in one or both eyes, especially if the vision loss is more peripheral Double vision, especially if it is associated with headache Hearing loss with or without dizziness Speech difficulty of gradual onset Other symptoms may also include nausea or vomiting that is most severe in the morning, confusion and disorientation, and memory loss. The following symptoms are usually not caused by a brain tumor, but may sometimes be: Headache A change in behavior
  22. 22. Genetic-Causes The ontology explain that brain tumour have different types which also further divided into subtypes. Brain tumour is caused by causes which can be genetic or environmental.
  23. 23. Environmental causes
  24. 24. Treatment There is a corresponding symptoms of observable characteristics of an ill individual and treatment possible for the disorder that can be chemotherapy, surgery, psychotherapy or medication.
  25. 25. Demo Now I show you how I build ontology using Protégé 4.1 ontology editor
  26. 26. Use For physician If a medical practitioner queries the system, she/he will mainly be interested in Symptoms Possible treatment
  27. 27. Use When a physician cannot identify disease.
  28. 28. Use For researchers Its helps on drug discovery Its directed or may allow researcher to narrow down the region of interest on particular gene  Neurofibromatosis 1 (NF1 gene),  Neurofibromatosis 2 (NF2 gene),  Turcots (APC gene),  Gorlins (PTCH gene),  Li-Fraumeni syndrome (TP53 gene).
  29. 29. Limitation of ontology model Assertion errors Relevance errors Encoding errors
  30. 30. Conclusions and future work A computer-base brain tumour ontology support the works of researcher in gathering information on brain tumour research and allows user across the world to intelligently access new scientific information much more quickly. Shared knowledge improves research efficiency and effectiveness, as it helps to avoid unnecessary redundancy in doing the same experiments.
  31. 31. Reference National Brain Tumor Society (http://www.braintumor.org)-USA American Brain Tumor Association (http://www.abta.org/) Brain Tumor foundation of Canada (http://www.braintumour.ca/) Brain Tumor Association of Western Australia (http://braintumourwa.com) Snomed-CT ( http://www.ihtsdo.org/snomed-ct/) Medical Subject Headings (http://www.nlm.nih.gov/pubs/factsheets/mesh.html) Hadzic, Maja and Chang, Elizabeth (2005): Ontology-based support for human disease study. IEEE, 2005, pp.1-7.