EORTC Radiation Oncology Group quality assurance platform: establishment of a digital central review facility.

OBJECTIVE: Quality assurance (QA) in clinical trials is essential to ensure treatment is safely and effectively delivered. As QA requirements have increased in complexity in parallel with evolution of radiation therapy (RT) delivery, a need to facilitate digital data exchange emerged. Our objective is to present the platform developed for the integration and standardization of QART activities across all EORTC trials involving RT. METHODS: The following essential requirements were identified: secure and easy access without on-site software installation; integration within the existing EORTC clinical remote data capture system; and the ability to both customize the platform to specific studies and adapt to future needs. After retrospective testing within several clinical trials, the platform was introduced in phases to participating sites and QART study reviewers. RESULTS: The resulting QA platform, integrating RT analysis software installed at EORTC Headquarters, permits timely, secure, and fully digital central DICOM-RT based data review. Participating sites submit data through a standard secure upload webpage. Supplemental information is submitted in parallel through web-based forms. An internal quality check by the QART office verifies data consistency, formatting, and anonymization. QART reviewers have remote access through a terminal server. Reviewers evaluate submissions for protocol compliance through an online evaluation matrix. Comments are collected by the coordinating centre and institutions are informed of the results. CONCLUSIONS: This web-based central review platform facilitates rapid, extensive, and prospective QART review. This reduces the risk that trial outcomes are compromised through inadequate radiotherapy and facilitates correlation of results with clinical outcomes.

Quality assurance in road traffic analyses in Switzerland.

Swiss laboratories performing toxicological road traffic analyses have been authorized for many years by the Swiss Federal Roads Office (FEDRO). In 2003 FEDRO signed a contract with the Swiss Society of Legal Medicine (SSLM) to organize the complete quality management concerning road traffic analyses. For this purpose a multidisciplinary working group was established under the name of "road traffic commission (RTC)". RTC has to organize external quality control, to interpret the results of these controls, to perform audits in the laboratories and to report all results to FEDRO. Furthermore the working group can be mandated for special tasks by FEDRO. As an independent organization the Swiss Center for Quality Control (CSCQ) in Geneva manages the external quality controls in the laboratory over the past years. All tested drugs and psychoactive substances are listed in a federal instruction. The so-called 'zero tolerance substances' (THC, morphine, cocaine, amphetamine, methamphetamine, MDMA and MDEA) and their metabolites have to be tested once a year, all other substances (benzodiazepines, zolpidem, phenobarbital, etc.) periodically. Results over the last years show that all laboratories are generally within the confidence interval of +/-30% of the mean value. In cases of non-conformities measures have to be taken immediately and reported to the working group. External audits are performed triennially but accredited laboratories can combine this audit with the approval of the Swiss Accreditation Service (SAS). During the audits a special checklist filled in by the laboratory director is assessed. Non-conformities have to be corrected. During the process of establishing a new legislation, RTC had an opportunity of advising FEDRO. In collaboration with FEDRO, RTC and hence SSLM can work actively on improving of quality assurance in road traffic toxicological analyses, and has an opportunity to bring its professional requests to the federal authorities.

Multi-modal distraction: insights from children's limited attention.

How does the multi-sensory nature of stimuli influence information processing? Cognitive systems with limited selective attention can elucidate these processes. Six-year-olds, 11-year-olds and 20-year-olds engaged in a visual search task that required them to detect a pre-defined coloured shape under conditions of low or high visual perceptual load. On each trial, a peripheral distractor that could be either compatible or incompatible with the current target colour was presented either visually, auditorily or audiovisually. Unlike unimodal distractors, audiovisual distractors elicited reliable compatibility effects across the two levels of load in adults and in the older children, but high visual load significantly reduced distraction for all children, especially the youngest participants. This study provides the first demonstration that multi-sensory distraction has powerful effects on selective attention: Adults and older children alike allocate attention to potentially relevant information across multiple senses. However, poorer attentional resources can, paradoxically, shield the youngest children from the deleterious effects of multi-sensory distraction. Furthermore, we highlight how developmental research can enrich the understanding of distinct mechanisms controlling adult selective attention in multi-sensory environments.

Multi-modal Change Detection, Application to the Detection of Flooded Areas: Outcome of the 2009-2010 data fusion contest

The 2009-2010 Data Fusion Contest organized by the Data Fusion Technical Committee of the IEEE Geoscience and Remote Sensing Society was focused on the detection of flooded areas using multi-temporal and multi-modal images. Both high spatial resolution optical and synthetic aperture radar data were provided. The goal was not only to identify the best algorithms (in terms of accuracy), but also to investigate the further improvement derived from decision fusion. This paper presents the four awarded algorithms and the conclusions of the contest, investigating both supervised and unsupervised methods and the use of multi-modal data for flood detection. Interestingly, a simple unsupervised change detection method provided similar accuracy as supervised approaches, and a digital elevation model-based predictive method yielded a comparable projected change detection map without using post-event data.