Gutenberg Open Science: Structured reporting in radiology enables epidemiological analysis through data mining: urolithiasis as a use case

Please use this identifier to cite or link to this item: http://doi.org/10.25358/openscience-9464

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DC Field	Value	Language
dc.contributor.author	Jorg, Tobias	-
dc.contributor.author	Halfmann, Moritz C.	-
dc.contributor.author	Rölz, Niklas	-
dc.contributor.author	Mager, René	-
dc.contributor.author	Pinto dos Santos, Daniel	-
dc.contributor.author	Düber, Christoph	-
dc.contributor.author	Mildenberger, Peter	-
dc.contributor.author	Müller, Lukas	-
dc.date.accessioned	2023-08-28T10:21:43Z	-
dc.date.available	2023-08-28T10:21:43Z	-
dc.date.issued	2023	-
dc.identifier.uri	https://openscience.ub.uni-mainz.de/handle/20.500.12030/9482	-
dc.description.abstract	Purpose To investigate the epidemiology and distribution of disease characteristics of urolithiasis by data mining structured radiology reports. Methods The content of structured radiology reports of 2028 urolithiasis CTs was extracted from the department’s structured reporting (SR) platform. The investigated cohort represented the full spectrum of a tertiary care center, including mostly symptomatic outpatients as well as inpatients. The prevalences of urolithiasis in general and of nephro- and ureterolithasis were calculated. The distributions of age, sex, calculus size, density and location, and the number of ureteral and renal calculi were calculated. For ureterolithiasis, the impact of calculus characteristics on the degree of possible obstructive uropathy was calculated. Results The prevalence of urolithiasis in the investigated cohort was 72%. Of those patients, 25% had nephrolithiasis, 40% ureterolithiasis, and 35% combined nephro- and ureterolithiasis. The sex distribution was 2.3:1 (M:F). The median patient age was 50 years (IQR 36–62). The median number of calculi per patient was 1. The median size of calculi was 4 mm, and the median density was 734 HU. Of the patients who suffered from ureterolithiasis, 81% showed obstructive uropathy, with 2nd-degree uropathy being the most common. Calculus characteristics showed no impact on the degree of obstructive uropathy. Conclusion SR-based data mining is a simple method by which to obtain epidemiologic data and distributions of disease characteristics, for the investigated cohort of urolithiasis patients. The added information can be useful for multiple purposes, such as clinical quality assurance, radiation protection, and scientific or economic investigations. To benefit from these, the consistent use of SR is mandatory. However, in clinical routine SR usage can be elaborate and requires radiologists to adapt.	en_GB
dc.language.iso	eng	de
dc.rights	CC BY	*
dc.rights.uri	https://creativecommons.org/licenses/by/4.0/	*
dc.subject.ddc	610 Medizin	de_DE
dc.subject.ddc	610 Medical sciences	en_GB
dc.title	Structured reporting in radiology enables epidemiological analysis through data mining: urolithiasis as a use case	en_GB
dc.type	Zeitschriftenaufsatz	de
dc.identifier.doi	http://doi.org/10.25358/openscience-9464	-
jgu.type.dinitype	article	en_GB
jgu.type.version	Published version	de
jgu.type.resource	Text	de
jgu.organisation.department	FB 04 Medizin	de
jgu.organisation.number	2700	-
jgu.organisation.name	Johannes Gutenberg-Universität Mainz	-
jgu.rights.accessrights	openAccess	-
jgu.journal.title	Abdominal radiology	de
jgu.journal.volume	Version of Record (VoR)	de
jgu.publisher.year	2023	-
jgu.publisher.name	Springer US	de
jgu.publisher.place	Boston, MA	de
jgu.publisher.issn	2366-0058	de
jgu.organisation.place	Mainz	-
jgu.subject.ddccode	610	de
jgu.publisher.doi	10.1007/s00261-023-04006-9	de
jgu.organisation.ror	https://ror.org/023b0x485	-
Appears in collections:	DFG-491381577-H

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