ArticleJournal of imaging informatics in medicine2026
A High-Accuracy Rule-Based Algorithm for Automated Extraction of Coronary Artery Calcium Scores from Mixed-Language Radiology Reports.
Article in Journal of imaging informatics in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Coronary artery calcium (CAC) score is a vital biomarker for cardiovascular risk stratification, yet this value is often locked within unstructured radiology reports. Manual extraction is impractical for large-scale research, while automated extraction is hindered in multilingual settings where reports feature complex, mixed-language text. This study aimed to develop a rule-based algorithm to extract CAC scores from mixed Chinese-English radiology reports. This retrospective study analyzed 21,874 free-text cardiac CT reports (2004-2024) from a Taiwanese center. Authored by 23 radiologists, the reports showed high stylistic diversity and a 96.7% prevalence of mixed text. An iterative rule-based algorithm was developed and validated against a gold standard established by the manual review of two independent physicians, with discrepancies adjudicated by a third expert. The algorithm achieved 99.98% accuracy, correctly identifying scores in 21,870 reports, with 100% coverage. It processed the dataset in 17.59 seconds, contrasting with an estimated 21 hours for manual review. Error analysis revealed that the rare misclassifications (n=4) were exclusively attributable to linguistic ambiguity involving multiple unseparated numeric values, rather than algorithmic failure in pattern recognition. This rule-based algorithm accurately and efficiently extracts structured data from complex multilingual radiology reports. This automated approach provides a practical solution to unlock valuable historical clinical data for large-scale cardiovascular research, overcoming a major barrier in multilingual clinical informatics.
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