To date, conducting retrospective clinical analyses is rather difficult and time consuming. Especially in radiation oncology, handling voluminous datasets from various information systems and different documentation styles efficiently is crucial for patient care and research. With the example of patients with pancreatic cancer treated with radio-chemotherapy, we performed a therapy evaluation by using analysis tools connected with a documentation system. A total number of 783 patients have been documented into a professional, web-based documentation system. Information about radiation therapy, diagnostic images and dose distributions have been imported. For patients with disease progression after neoadjuvant chemoradiation, we designed and established an analysis workflow. After automatic registration of the radiation plans with the follow-up images, the recurrence volumes are 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 stored in the database and included in statistical calculations. The main goal of using an automatic evaluation system 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 evaluation system to other types of tumors in radiation oncology.
Conducting clinical studies is rather difficult because of the large variety of voluminous datasets, different documentation
styles, and various information systems, especially in radiation oncology. In this paper, we describe
our development of a web-based documentation system with first approaches of automatic statistical analyses
for transnational and multicenter clinical studies in particle therapy. It is possible to have immediate access
to all patient information and exchange, store, process, and visualize text data, all types of DICOM images,
especially DICOM RT, and any other multimedia data. Accessing the documentation system and submitting
clinical data is possible for internal and external users (e.g. referring physicians from abroad, who are seeking
the new technique of particle therapy for their patients). Thereby, security and privacy protection is ensured
with the encrypted https protocol, client certificates, and an application gateway. Furthermore, all data can be
pseudonymized. Integrated into the existing hospital environment, patient data is imported via various interfaces
over HL7-messages and DICOM. Several further features replace manual input wherever possible and ensure data
quality and entirety. With a form generator, studies can be individually designed to fit specific needs. By including
all treated patients (also non-study patients), we gain the possibility for overall large-scale, retrospective
analyses. Having recently begun documentation of our first six clinical studies, it has become apparent that the
benefits lie in the simplification of research work, better study analyses quality and ultimately, the improvement
of treatment concepts by evaluating the effectiveness of particle therapy.
An approach for active noise and vibration control for systems subject to periodic disturbances with time-varying fundamental frequency is presented. The motivation is active compensation of engine-induced noise in automobiles, where the fundamental frequency (engine firing frequency) goes from 7 Hz (idle, 800 rpm) to 50 Hz (6000 rpm) and the frequency (engine speed) is available. In this new approach, an observer for an input disturbance is designed based on a disturbance model containing all frequencies to be cancelled. The disturbance-model part of the observer is time-varying since the current frequency is measured and fed into this part. Based on this frequency measurement, an observer gain is selected from a set of pre-computed gains. The approach is non-adaptive, and the frequency is a scheduling variable. Theoretical issues of the algorithm (observer design) are discussed and real-time results obtained with an active control system in a vehicle are presented. These results show a major reduction of the interior sound pressure level in the vehicle.