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Objective Comparison Using Guideline-based Query of Conventional Radiological Reports and Structured Reports.
Máté E Maros1, Ralf Wenz2, Alex Förster1
1Department of Neuroradiology, University Medical Center Mannheim, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.
In Vivo (Athens, Greece)
|June 25, 2018
Summary
Structured reports (SR) significantly outperform conventional free-text reports (cFTR) in stroke imaging analysis. A text-mining algorithm demonstrated SRs provide a more objective and scalable quality measure for radiology adoption.
Area of Science:
- Radiology
- Medical Informatics
- Natural Language Processing
Background:
- Feasibility study of a text-mining algorithm for comparing structured reports (SR) and conventional free-text reports (cFTR).
- Utilizes guideline-based key terms for objective comparison.
- An open-source online version with multilingual capabilities was developed.
Purpose of the Study:
- To objectively compare SRs and cFTRs using a text-mining-based scoring algorithm.
- To evaluate the feasibility of using cosine similarity score (CSS) for report comparison.
- To provide a scalable quality measure for radiology reporting.
Main Methods:
- Re-assessment of 25 stroke MRIs by two blinded readers (inexperienced and experienced).
- Comparison of SRs and cFTRs against guideline queries using CSS.
- Statistical analysis with Wilcoxon signed-rank test.
Main Results:
- All pathological findings (18/18) were identified in both SRs and cFTRs.
- SRs from the inexperienced reader showed significantly higher CSS (median 0.145) than cFTRs (median 0.102).
- The CSS demonstrated robustness to query variations.
Conclusions:
- Objective, guideline-based comparison of SRs and cFTRs using CSS is feasible.
- CSS serves as a scalable quality measure.
- This method can facilitate the adoption of SRs across radiology.
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