connectivity by design.

Preventive maintenance is vital in radiotherapy to reduce costs, optimize machine performance and provide optimal care. It is enabled by ‘connectivity by design’. This ensures clinical and technological compatibility and information exchange within and between devices.



  • interoperability opens the gate to the inclusion of predictive maintenance strategies in system software
  • these strategies have huge cost-saving potential
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software as a solution.

Radiotherapy ranks among the most computerized and technologically advanced medical disciplines. This field deploys highly complex radiation equipment for high precision treatment of patient malignancies. Optimal treatment requires many components and devices to work in concert, such as the beam production system, the dose delivery system, motion systems, a safety system and a patient positioning system.

As a consequence of this complexity, especially in proton or light-ion therapy, a large and highly skilled staff has to be available 24/7 to monitor the system and prevent machine downtime. However, despite this labor-intensive operation, a proton beam system still has typically a 3 to 5% downtime. These machine ‘interrupts’ result in treatment delays with all the stress for patient and staff that comes with it. They also lead to workload problems through the necessity of rescheduling.

Connectivity by design and smart software can minimize this by storing, sharing analyzing and predicting the system’s performance, asking for novel algorithms and data analytics fed with accurate and high-quality data in the device context.


finding the sweet spot.

It may thus be worthwhile to include a preventive maintenance strategy in the software. A machine performance check during daily initialization might prevent breakdown and analysis of the data could hint at long-term specification issues building up. Deep learning of wear and tear patterns could support and refine this insight into the system’s condition. Advanced and future software capabilities include real-time performance checking and cloud-based (big) data collection for breakdown detection in a global installed base.


Jan-Willem Doosje

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All of these options start with the detection of deviations that give rise to scheduling the maintenance. This shouldn’t be done too early, as in that case costly components will be replaced unnecessarily. The challenge is to find the sweet spot that reduces costs and downtime and simultaneously offers logistics benefits. If carried out well, considerable savings in for instance support staff costs might be attained.