Appl Clin Inform 2016; 07(03): 803-816
DOI: 10.4338/ACI-2016-03-RA-0037
Research Article
Schattauer GmbH

Meta-generalis: A novel method for structuring information from radiology reports

Flavio Barbosa
1  Universidade de Sao Paulo Ribeirao Preto School of Medicine, Internal Medicine, Ribeirao Preto, Sao Paulo, Brazil
,
Agma Jucci Traina
2  Universidade de Sao Paulo Instituto de Ciencias Matematicas e de Computacao, Sao Carlos, SP, Brazil
,
Valdair Francisco Muglia
1  Universidade de Sao Paulo Ribeirao Preto School of Medicine, Internal Medicine, Ribeirao Preto, Sao Paulo, Brazil
› Author Affiliations
We would like to thank Prof. Maria Cristiane Galvao for helping us with her ontology and terminology expertise. We also thank Dr. Jose Daniel Oliveira for his diligence to provide MRI reports.
Further Information

Publication History

received: 31 March 2016

accepted: 22 July 2016

Publication Date:
19 December 2017 (online)

Summary

Background

A structured report for imaging exams aims at increasing the precision in information retrieval and communication between physicians. However, it is more concise than free text and may limit specialists’ descriptions of important findings not covered by pre-defined structures. A computational ontological structure derived from free texts designed by specialists may be a solution for this problem. Therefore, the goal of our study was to develop a methodology for structuring information in radiology reports covering specifications required for the Brazilian Portuguese language, including the terminology to be used.

Methods

We gathered 1,701 radiological reports of magnetic resonance imaging (MRI) studies of the lumbosacral spine from three different institutions. Techniques of text mining and ontological conceptualization of lexical units extracted were used to structure information. Ten radiologists, specialists in lumbosacral MRI, evaluated the textual superstructure and terminology extracted using an electronic questionnaire.

Results

The established methodology consists of six steps: 1) collection of radiology reports of a specific MRI examination; 2) textual decomposition; 3) normalization of lexical units; 4) identification of textual superstructures; 5) conceptualization of candidate-terms; and 6) evaluation of superstructures and extracted terminology by experts using an electronic questionnaire. Three different textual superstructures were identified, with terminological variations in the names of their textual categories. The number of candidate-terms conceptualized was 4,183, yielding 727 concepts. There were a total of 13,963 relationships between candidate-terms and concepts and 789 relationships among concepts.

Conclusions

The proposed methodology allowed structuring information in a more intuitive and practical way. Indications of three textual superstructures, extraction of lexicon units and the normalization and ontologically conceptualization were achieved while maintaining references to their respective categories and free text radiology reports.

Citation: Barbosa F, Traina AJ, Muglia VF. Meta-generalis: A novel method for structuring information from radiology reports.