Ayako Yagahara

Quantitative analysis of ontology research articles in the radiologic domain

To investigate the most advanced ontology research in health care and its impact on the radiologic domain, we proposed a concept identification and abstraction technique called “Concept Step”. This technique identifies a MeSH term, medical subject headings used in PubMed, in a sentence and climbs up through its hierarchy to reach an abstract concept. We developed original Java software to implement this technique. We tested it on 2,774 abstracts in health-care ontology research retrieved from MEDLINE on 23 October 2008. The total number of MeSH terms was 112,690. We counted a total of 33 MeSH terms (0.029%) in the radiologic domain. The most frequently occurring term was “radiology”, which occurred 21 times in the article set. Other frequent terms were “magnetic resonance imaging” and “tomography”, the counts of which were 4 and 3, respectively. A pair plot showed no correlation among the MeSH categories “Analytical Diagnostic and Therapeutic Techniques and Equipment”, “Anatomy”, “Biological Sciences”, and “Chemicals and Drugs”. We conclude that ontology research is well established in the biomedical domain, and that further study is required in the radiologic domain.

Development of terminology for mammographic techniques for radiological technologists

We are developing a mammographic ontology to share knowledge of the mammographic domain for radiologic technologists, with the aim of improving mammographic techniques. As a first step in constructing the ontology, we used mammography reference books to establish mammographic terminology for identifying currently available knowledge. This study proceeded in three steps: (1) determination of the domain and scope of the terminology, (2) lexical extraction, and (3) construction of hierarchical structures. We extracted terms mainly from three reference books and constructed the hierarchical structures manually. We compared features of the terms extracted from the three reference books. We constructed a terminology consisting of 440 subclasses grouped into 19 top-level classes: anatomic entity, image quality factor, findings, material, risk, breast, histological classification of breast tumors, role, foreign body, mammographic technique, physics, purpose of mammography examination, explanation of mammography examination, image development, abbreviation, quality control, equipment, interpretation, and evaluation of clinical imaging. The number of terms that occurred in the subclasses varied depending on which reference book was used. We developed a terminology of mammographic techniques for radiologic technologists consisting of 440 terms.

Construction of mammographic examination process ontology using bottom–up hierarchical task analysis

Describing complex mammography examination processes is important for improving the quality of mammograms. It is often difficult for experienced radiologic technologists to explain the process because their techniques depend on their experience and intuition. In our previous study, we analyzed the process using a new bottom–up hierarchical task analysis and identified key components of the process. Leveraging the results of the previous study, the purpose of this study was to construct a mammographic examination process ontology to formally describe the relationships between the process and image evaluation criteria to improve the quality of mammograms. First, we identified and created root classes: task, plan, and clinical image evaluation (CIE). Second, we described an “is-a” relation referring to the result of the previous study and the structure of the CIE. Third, the procedural steps in the ontology were described using the new properties: “isPerformedBefore,” “isPerformedAfter,” and “isPerformedAfterIfNecessary.” Finally, the relationships between tasks and CIEs were described using the “isAffectedBy” property to represent the influence of the process on image quality. In total, there were 219 classes in the ontology. By introducing new properties related to the process flow, a sophisticated mammography examination process could be visualized. In relationships between tasks and CIEs, it became clear that the tasks affecting the evaluation criteria related to positioning were greater in number than those for image quality. We developed a mammographic examination process ontology that makes knowledge explicit for a comprehensive mammography process. Our research will support education and help promote knowledge sharing about mammography examination expertise.

Development of a Knowledge-based Application Utilizing Ontologies for the Continuing Site-specific JJ1017 Master Maintenance.

The purpose of this study was to develop the JJ1017 Knowledge-based Application (JKA) to support the continuing maintenance of a site-specific JJ1017 master defined by the JJ1017 guideline as a standard radiologic procedure master for medical information systems that are being adopted by some medical facilities in Japan. The method consisted of the following three steps: (1) construction of the JJ1017 Ontology (JJOnt) as a knowledge base using the Hozo (an environment for building/using ontologies); (2) development of modules (operation, I/O, graph modules) that are required to continue the maintenance of a site-specific JJ1017 master; and (3) unit testing of the JKA that consists of the JJOnt and the modules. As a result, the number of classes included in the JJOnt was 21,697. Within the radiologic procedure classes included in the above, the ratio of a JJ1017 master code for an external beam radiotherapy was the highest (51%). In unit testing of the JKA, we checked the main operations (e.g., keyword search of a JJ1017 master code/code meaning, editing the description of classes, etc.). The JJOnt is a knowledge base for implementing features that medical technologists find necessary in medical information systems. To enable medical technologists to exchange/retrieve semantically accurate information while using medical information systems in the future, we expect the JKA to support the maintenance and improvement of the site-specific JJ1017 master.

An analysis of existing terminology towards constructing ontology in the field of the radiological technology

PURPOSE In 1994, Japanese Society of Radiological Technology (JSRT) constructed the lexicon in the field of radiologic technology. However, recently, latest lexicon is not updated yet. The purpose of this article is to compare the terminologies in clinical medicine with the others and to consider reconstructing the lexicon in the radiological technology. MATERIALS AND METHODS Our study selected three categories from the database of the academic society. These three groups were Clinical medicine (hereafter CM, 167 societies, includes JSRT), Psychology / Education (hereafter P/E, 104 societies), and Comprehensive synthetic engineering (hereafter CSE, 40 societies). First, all societies were surveyed to know whether there were any lexicon in their official website. Second, these terminologies were surveyed on the following criteria: (a) Media of lexicon, (b) Number of terms, (c) File type of lexicon, (d) Terms translated into English, (e) Way of searching terms, and (f) Number of committees of the terminology. RESULTS Lexicon in CM, P/E, and CSE had 20, 4, and 7. Compared with P/E and CSE, CM showed the following trends: (a) used electronic media frequently, (b) stored large number of terms (about 5,000 to 11,000), (c) enabled to download frequently, and (d) used the alphabet and Japanese syllabary order frequently. CONCLUSIONS Compared with the lexicon of P/E and CSE, terminology in CM tended to adopt the electronic media of lexicon and to have large number of terms. Additionally, many lexicons were expressed in English terms along with Japanese terms. Following massive lexicon of SNOMED-CT and RadLex, it is necessary to consider applying the web-based term searching and an ontological technique to the lexicon of radiological technology.

Quantitative evaluation of expression difference in report assignments between nursing and radiologic technology departments

Our purpose in this study was to investigate the expression differences in report assignments between students in nursing and radiologic technology departments. We have known that faculties could identify differences, such as word usage, through grading their students’ assignments. However, there are no reports in the literature dealing with expression differences in vocabulary usage in medical informatics education based on statistical techniques or other quantitative measures. The report assignment asked for students’ opinions in the event that they found a rare case of a disease in a hospital after they graduated from professional school. We processed student report data automatically, and we applied the space vector model and TF/IDF (term frequency/inverse document frequency) scoring to 129 report assignments. The similarity-score distributions among the assignments for these two departments were close to normal. We focused on the sets of terms that occurred exclusively in either department. For terms such as “radiation therapy” or “communication skills” that occurred in the radiologic technology department, the TF/IDF score was 8.01. The same score was obtained for terms such as “privacy guidelines” or “consent of patients” that occurred in the nursing department. These results will help faculties to provide a better education based on identified expression differences from students’ background knowledge.