A new lease of AI radiotherapy software highlights how automated contouring is becoming part of routine cancer care across hospitals.
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An oncology institute in Ljubljana plans to lease artificial intelligence software that automatically maps organs-at-risk and lymph node regions on CT and MR scans, aiming to sharpen the quality and consistency of radiotherapy planning and aligning with a broader move towards AI-assisted imaging in clinical care.
On 10th December 2025, ONKOLOŠKI INŠTITUT LJUBLJANA published a contract notice for the Lease of Radiotherapy Software Licenses.
The notice describes a plan to lease artificial intelligence software licences for automatic delineation of organs-at-risk and lymph node areas on CT and MR images. The goal is to enhance radiation therapy planning.
Delineation – drawing precise contours around critical organs and nodal regions on imaging studies – is a central, labour-intensive stage in radiotherapy planning. Automating this step with AI is intended to:
The choice to lease software licences, rather than opt for a one-off purchase, suggests the institute wants sustained access to updated tools and vendor support as part of day-to-day clinical workflows. While the notice does not specify duration or value, the focus on radiotherapy planning indicates that the system is expected to sit close to the core of treatment operations rather than remain a peripheral pilot.
The Ljubljana initiative sits within a wider pattern of healthcare providers weaving AI into imaging-heavy parts of the cancer pathway, from early detection to treatment planning.
In lung cancer, several buyers have recently turned to AI to support the sheer volume and complexity of thoracic imaging:
Beyond lung imaging, authorities are starting to standardise AI support across broader radiology workloads. In September 2025, the Dirección General de Gestión Económica, Contratación e Infraestructuras de la Conselleria de Sanidad signalled plans to supply and configure AI Software for Radiological Diagnosis of thoracic and bone lesions, with a clear emphasis on integration with existing health systems, regulatory compliance, and training and support.
Radiotherapy departments are also investing in software to refine dose calculation and targeting, complementing the manual skills of clinicians. Several recent procurements highlight this:
Taken together, these projects show imaging AI and advanced planning tools spreading along the cancer care continuum: supporting early detection on low-dose CT scans, guiding radiologists through complex chest imaging, and now, in Ljubljana, tackling the detailed contouring that underpins radiotherapy planning.
AI is also beginning to appear alongside other high-tech interventions. In December 2025, SPITALUL DE URGENTA AL MAI "PROF. DR. DIMITRIE GEROTA" BUCURESTI launched a procurement for Medical Equipment Acquisition within an "AI-Assisted Robotic and Laparoscopic Surgery System" project, including an automated histological slide scanning system for pathology. This underlines how AI-enabled imaging and analysis are being linked across radiology, radiotherapy and pathology laboratories.
The Ljubljana notice is notable not just for its AI focus but also for its commercial structure. The institute plans to lease, rather than buy, the radiotherapy software licences.
Leasing models for imaging and related technologies are becoming more common. They can give hospitals predictable costs, access to upgrades and bundled maintenance, while allowing technology to be refreshed as clinical needs and software capabilities evolve.
Recent notices show this pattern across different types of equipment:
In this context, the decision by the oncology institute in Ljubljana to lease AI radiotherapy contouring software looks aligned with a wider shift. Rather than treating digital tools as static capital assets, buyers are increasingly procuring them as services, with expectations around continual updates, integration support and maintenance built into the contract.
Introducing AI into radiotherapy planning is not only a technical task. It also touches workflows, skills and governance. Although the Ljubljana notice focuses on the software’s core function of automatic delineation, parallel procurements in imaging and oncology point to the likely implementation challenges.
Many imaging projects now explicitly include staff training and change management. In August 2025, Oblastní nemocnice Mladá Boleslav tendered for a Computing Tomography System that included disassembly of the existing device, staff training and warranty services. In November 2025, VšĮ Vilniaus universiteto ligoninė Santaros klinikos sought a Computer Tomograph and Injector, again bundling delivery, installation, disposal of packaging and staff training.
Software upgrades show similar concerns. The September 2025 notice from „SPETSIALIZIRANA BOLNITSA ZA AKTIVNO LECHENIE NA ONKOLOGICHNI ZABOLYAVANIYA „PROF. D-R MARIN MUSHMOV“ EOOD for a CT Medical Imaging System Upgrade includes upgraded software and hardware with staff training and enhancements to processing capabilities.
Other notices stress interoperability from the outset. The AI radiological diagnosis project by the Conselleria de Sanidad, for instance, calls for integration with existing health systems and ongoing support. For the Ljubljana radiotherapy software, similar issues are likely to dominate implementation: ensuring the AI-generated contours fit into existing planning systems, validating performance against clinical standards, and training clinicians and medical physicists to use and scrutinise the outputs.
Hardware investments in radiotherapy also underline the need for coherent planning. Procurements such as Sansia Oy’s June 2025 notice for Radiotherapy Equipment Procurement (including a new linear accelerator and surface detection system) and the August 2025 notice from Centre Hospitalier Universitaire Dinant Godinne for Radiotherapy Equipment Supply and Maintenance show departments upgrading both machines and associated systems. The Ljubljana AI contouring project will need to sit alongside such equipment strategies, ensuring planning software, imaging hardware and treatment units work as a coherent whole.
The contract notice from ONKOLOŠKI INŠTITUT LJUBLJANA marks another step in bringing AI closer to the heart of cancer treatment. Automatic delineation of organs-at-risk and lymph node regions on CT and MR images could reshape how quickly and consistently radiotherapy plans are prepared.
Key points to watch will include which supplier can meet the institute’s needs, how the leased software is integrated with existing imaging and planning platforms, and how radiotherapy teams adapt their workflows and oversight to incorporate AI-generated contours. With multiple hospitals and health authorities now procuring AI tools for screening, diagnosis and treatment planning, this project will be followed closely by those considering similar moves in radiotherapy and beyond.
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