Supporting the diagnosis of childhood brain tumours through structural reports and ontological reasoning

Morgan, Amy (2015). Supporting the diagnosis of childhood brain tumours through structural reports and ontological reasoning. University of Birmingham. M.Sc.

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Abstract

After Leukaemia, childhood brain tumours are the second most common form of cancer. The most accurate way to diagnosis a tumour is via a biopsy, but is not always possible. An alternative is Magnetic Resonance Spectroscopy (MRS) which analyses the chemical make-up of tissue and then used to make a diagnosis.
A patient's medical records are an important part of treatment, used to communicate findings from medical images. However, these are written using unclear and ambiguous free text. A solution is to produce records using Structured Reporting. This has been incorporated into the Digital Communications in Medicine (DICOM) Standard for established imaging modalities, but not for MRS.
An ontology was modelled to produce DICOM supported Structured Reports for MRS. Also, an algorithm to diagnosis different types of childhood brain cancer using MRS spectra was incorporated, allowing automated diagnostic support. A prototype Structured Reporting application was designed based on the ontology.
The ontology was able to produce Structured Reports that successfully diagnosed certain childhood brain tumours based on the MRS readings. Usability testing and the diagnostic aspect of the ontology garnered positive feedback as MRS data is only currently used to diagnosis whether the tissue is cancerous or not.

Type of Work:

Thesis (Masters by Research > M.Sc.)

Award Type:

Masters by Research > M.Sc.

Supervisor(s):