Datenbankbasierte digitale retrospektive Auswertung von Patientenkollektiven in der Radioonkologie

• Verfasst von: Kessel, Kerstin [VerfasserIn]
• Verfasst von: Habermehl, Daniel [VerfasserIn]
• Verfasst von: Bougatf, Nina [VerfasserIn]
• Verfasst von: Debus, Jürgen [VerfasserIn]
• Verfasst von: Combs, Stephanie [VerfasserIn]
• Titel: Datenbankbasierte digitale retrospektive Auswertung von Patientenkollektiven in der Radioonkologie
• Verf.angabe: K.A. Kessel, D. Habermehl, C. Bohn, A. Jäger, R.O. Floca, L. Zhang, N. Bougatf, R. Bendl, J. Debus, S.E. Combs
• Umfang: 6 S.
• Fussnoten: Gesehen am 13.08.2018
• Titel Quelle: Enthalten in: Strahlentherapie und Onkologie
• Jahr Quelle: 2012
• Band/Heft Quelle: 188(2012), 12, S. 1119-1124
• ISSN Quelle: 1439-099X
• DOI: doi:10.1007/s00066-012-0214-0
• Datenträger: Online-Ressource
• Sprache: ger
• K10plus-PPN: 1578512190

Abstract

PurposeEspecially in the field of radiation oncology, handling a large variety of voluminous datasets from various information systems in different documentation styles efficiently is crucial for patient care and research. To date, conducting retrospective clinical analyses is rather difficult and time consuming. With the example of patients with pancreatic cancer treated with radio-chemotherapy, we performed a therapy evaluation by using an analysis system connected with a documentation system.Materials and methodsA total number of 783 patients have been documented into a professional, database-based documentation system. Information about radiation therapy, diagnostic images and dose distributions have been imported into the web-based system.ResultsFor 36 patients with disease progression after neoadjuvant chemoradiation, we designed and established an analysis workflow. After an automatic registration of the radiation plans with the follow-up images, the recurrence volumesare segmented manually. Based on these volumes the DVH (dose volume histogram) statistic is calculated, followed by the determination of the dose applied to the region of recurrence. All results are saved in the database and included in statistical calculations.ConclusionThe main goal of using an automatic analysis tool is to reduce time and effort conducting clinical analyses, especially with large patient groups. We showed a first approach and use of some existing tools, however manual interaction is still necessary. Further steps need to be taken to enhance automation. Already, it has become apparent that the benefits of digital data management and analysis lie in the central storage of data and reusability of the results. Therefore, we intend to adapt the analysis system to other types of tumors in radiation oncology.