Radiation therapy is a targeted cancer treatment that’s typically delivered over several weeks, using a plan that’s optimized on a CT scan taken before treatment begins. But during this time, the geometry of the tumour and the surrounding anatomy can vary, with different patients responding in different ways to the delivered radiation. To optimize treatment quality, such changes must be taken into consideration. And this is where adaptive radiotherapy comes into play.

Adaptive radiotherapy uses patient images taken throughout the course of treatment to update the initial plan and compensate for any anatomical variations. By adjusting the daily plan to match the patient’s daily anatomy, adaptive treatments ensure more precise, personalized and efficient radiotherapy, improving tumour control while reducing toxicity to healthy tissues.

The implementation of adaptive radiotherapy is continuing to expand, as technology developments enable adaptive treatments in additional tumour sites. And as more cancer centres worldwide choose this approach, there’s a need for flexible, innovative software to streamline this increasing clinical uptake.

Designed to meet these needs, RayStation – the treatment planning system from oncology software specialist RaySearch Laboratories – makes adaptive radiotherapy faster and easier to implement in clinical practice. The versatile and holistic RayStation software provides all of the tools required to support adaptive planning, today and into the future.

“We need to be fast, we need to be predictable and we need to be user friendly,” says Anna Lundin, technical product manager at RaySearch Laboratories.

Meeting the need for speed

Typically, adaptive radiotherapy uses the cone-beam CT (CBCT) images acquired for daily patient positioning to perform plan adaptation. For seamless implementation into the clinical workflow to fully reflect the daily anatomical changes, this procedure should be performed “online” with the patient on the treatment table, as opposed to an “offline” approach where plan adaptation occurs after the patient has left the treatment session. Such online adaptation, however, requires the ability to analyse patient scans and perform adaptive re-planning as rapidly as possible.

To fulfil the needs for streamlining all types of adaptive (online or offline) requirements, RayStation incorporates a package of advanced algorithms that perform key tasks, including segmentation, deformable registration, CBCT image enhancement and recontouring, all while the previously delivered dose is taken into consideration. By automating all of these steps, RayStation accelerates the replanning process to the speed needed for online adaptation, with the ability to create an adaptive plan in less than a minute.

Central to this process is RayStation’s dose tracking, which uses the daily images to calculate the actual dose delivered to the patient in each fraction. This ability to evaluate treatment progress, both on a daily basis and considering the estimated total dose, enables informed decisions as to whether to replan or not. The software’s flexible workflow allows users to perform daily dose tracking, compare plans with daily anatomical information against the original plans and adapt when needed.

“You can document trigger points for when adaptation is needed,” Lundin explains. “So you can evaluate whether the original plan is still good to go or whether you want to update or adapt the treatment plan to changes that have occurred.”

User friendly

Another challenge when implementing online adaptation is that its time constraints necessitate access to intuitive tools that enable quick decision making. “One of the big challenges with adaptive radiotherapy has been that a lot of the decision making and processes have been done on an ad hoc basis,” says Lundin. “We need to utilize the same protocol-based planning for adaptive as we do for standard treatment planning.”

As such, RaySearch Laboratories has focused on developing software that’s easy to use, efficient and accessible to a large proportion of clinical personnel. RayStation enables clinics to define and validate clinical procedures for a specific patient category in advance, eliminating the need to repeat this each time.

“By doing this, we let the clinicians focus on what they do best – taking responsibility for the clinical decisions – while RayStation focuses on providing all the data that they need to make that possible,” Lundin adds.

Versatile design

Lundin emphasizes that this accelerated adaptive replanning solution is built upon RayStation’s pre-existing comprehensive framework. “It’s not a parallel solution, it’s a progression,” she explains. “That means that all the tools that we have for robust optimization and evaluation, tools to assess biological effects, support for multiple treatment modalities – all that is also available when performing adaptive assessments and adaptive planning.”

This flexibility allows RayStation to support both photon- and ion-based treatments, as well as multiple imaging modalities. “We have built a framework that can be configured for each site and each clinical indication,” says Lundin. “We believe in giving users the freedom to select which techniques and which strategies to employ.”

We let the clinicians focus on what they do best – taking responsibility for the clinical decisions – while RayStation focuses on providing all the data that they need to make that possible

In particular, adaptive radiotherapy is gaining interest among the proton therapy community. For such highly conformal treatments, it’s even more important to regularly assess the actual delivered dose and ensure that the plan is updated to deliver the correct dose each day. “We have the first clinics using RayStation to perform adaptive proton treatments in an online fashion,” Lundin says.

It’s likely that we will also soon see the emergence of biologically adapted radiotherapy, in which treatments are adapted not just to the patient’s anatomy, but to the tumour’s biological characteristics and biological response. Here again, RayStation’s flexible and holistic architecture can support the replanning needs of this advanced treatment approach.

Predictable performance

Lundin points out that the progression towards online adaptation has been valuable for radiotherapy as a whole. “A lot of the improvements required to handle the time-critical procedures of online adaptive are of large benefit to all adaptive assessments,” she explains. “Fast and predictable replanning is crucial to allow us to treat more patients with greater specificity using less clinical resources. I see it as strictly necessary for online adaptive, but good for all.”

Artificial intelligence (AI) is not only a key component in enhancing the speed and consistency of treatment planning (with tools such as deep learning segmentation and planning), but also enables the handling of massive data sets, which in turn allows users to improve the treatment “intents” that they prescribe.

Learning more about how the delivered dose correlates with clinical outcome provides important feedback on the performance and effectiveness of current adaptive processes. This will help optimize and personalize future treatments and, ultimately, make the adaptive treatments more predictable and effective as a whole.

Lundin explains that full automation is the only way to generate the large amount of data in the predictable and consistent manner required for such treatment advancements, noting that it is not possible to achieve this manually.

RayStation’s ability to preconfigure and automate all of the steps needed for daily dose assessment enables these larger-scale dose follow-up clinical studies. The treatment data can be combined with patient outcomes, with AI employed to gain insight into how to best design treatments or predict how a tumour will respond to therapy.

“I look forward to seeing more outcome-related studies of adaptive radiotherapy, so we can learn from each other and have more general recommendations, as has been done in the field of standard radiotherapy planning,” says Lundin. “We need to learn and we need to improve. I think that is what adaptive is all about – to adapt each person’s treatment, but also adapt the processes that we use.”

Future evolution

Looking to the future, adaptive radiotherapy is expected to evolve rapidly, bolstered by ongoing advances in imaging techniques and increasing data processing speeds. RayStation’s machine learning-based segmentation and plan optimization algorithms will continue to play a central role in supporting this evolution, with AI making treatment adaptations more precise, personalized and efficient, enhancing the overall effectiveness of cancer treatment.

“RaySearch, with the foundation that we have in optimization and advancing treatment planning and workflows, is very well equipped to take on the challenges of these future developments,” Lundin adds. “We are looking forward to the improvements to come and determined to meet the expectations with our holistic software.”

• Get to know RaySearch’s oncology information system, RayCare, and explore the role it plays in adaptive radiotherapy.

The post Fast and predictable: RayStation meets the needs of online adaptive radiotherapy appeared first on Physics World.

Brain tumours are notoriously difficult to treat, resisting conventional treatments such as radiation therapy, where the deliverable dose is limited by normal tissue tolerance. To better protect healthy tissues, researchers are turning to microbeam radiation therapy (MRT), which uses spatially fractionated beams to spare normal tissue while effectively killing cancer cells.

MRT is delivered using arrays of ultrahigh-dose rate synchrotron X-ray beams tens of microns wide (high-dose peaks) and spaced hundreds of microns apart (low-dose valleys). A research team from the Centre for Medical Radiation Physics at the University of Wollongong in Australia has now demonstrated that combining MRT with targeted radiosensitizers – such as nanoparticles or anti-cancer drugs – can further boost treatment efficacy, reporting their findings in Cancers.

“MRT is famous for its healthy tissue-sparing capabilities with good tumour control, whilst radiosensitizers are known for their ability to deliver targeted dose enhancement to cancer,” explains first author Michael Valceski. “Combining these modalities just made sense, with their synergy providing the potential for the best of both worlds.”

Enhancement effects

Valceski and colleagues combined MRT with thulium oxide nanoparticles, the chemotherapy drug methotrexate and the radiosensitizer iododeoxyuridine (IUdR). They examined the response of monolayers of rodent brain cancer cells to various therapy combinations. They also compared conventional broadbeam orthovoltage X-ray irradiation with synchrotron broadbeam X-rays and synchrotron MRT.

Synchrotron irradiations were performed on the Imaging and Medical Beamline at the ANSTO Australian Synchrotron, using ultrahigh dose rates of 74.1 Gy/s for broadbeam irradiation and 50.3 Gy/s for MRT. The peak-to-valley dose ratio (PVDR, used to characterize an MRT field) of this set-up was measured as 8.9.

Using a clonogenic assay to measure cell survival, the team observed that synchrotron-based irradiation enhanced cell killing compared with conventional irradiation at the same 5 Gy dose (for MRT this is the valley dose, the peaks experience 8.9 times higher dose), demonstrating the increased cell-killing effect of these ultrahigh-dose rate X-rays.

Adding radiosensitizers further increased the impact of synchrotron broadbeam irradiation, with DNA-localized IUdR killing more cells than cytoplasm-localized nanoparticles. Methotrexate, meanwhile, halved cell survival compared with conventional irradiation.

The team observed that at 5 Gy, MRT showed equivalent cell killing to synchrotron broadbeam irradiation. Valceski explains that this demonstrates MRT’s tissue-sparing potential, by showing how MRT can maintain treatment efficacy while simultaneously protecting healthy cells.

MRT also showed enhanced cell killing when combined with radiosensitizers, with the greatest effect seen for IUdR and IUdR plus methotrexate. This local dose enhancement, attributed to the DNA localization of IUdR, could further improve the tissue-sparing capabilities of MRT by enabling a lower per-fraction dose to reduce patient exposure whilst maintaining tumour control.

Imaging valleys and peaks

To link the biological effects with the physical collimation of MRT, the researchers performed confocal microscopy (at the Fluorescence Analysis Facility in Molecular Horizons, University of Wollongong) to investigate DNA damage following treatment at 0.5 and 5 Gy. Twenty minutes after irradiation, they imaged fixed cells to visualize double-strand DNA breaks (DSBs), as shown by γH2AX foci (representing a nuclear DSB site).

The images verified that the cells’ biological responses corresponded with the MRT beam patterns, with the 400 µm microbeam spacing clearly seen in all treated cells, both with and without radiosensitizers.

In the 0.5 Gy images, the microbeam tracks were consistent in width, while the 5 Gy MRT tracks were wider as DNA damage spread from peaks into the valleys. This radiation roll-off was also seen with IUdR and IUdR plus methotrexate, with numerous bright foci visible in the valleys, demonstrating dose enhancement and improved cancer-killing with these radiosensitizers.

The researchers also analysed the MRT beam profiles using the γH2AX foci intensity across the images. Cells treated with radiosensitizers had broadened peaks, with the largest effect seen with the nanoparticles. As nanoparticles can be designed to target tumours, this broadening (roughly 30%) can be used to increase the radiation dose to cancer cells in nearby valleys.

“Peak broadening adds a novel benefit to radiosensitizer-enhanced MRT. The widening of the peaks in the presence of nanoparticles could potentially ‘engulf’ the entire cancer, and only the cancer, whilst normal tissues without nanoparticles retain the protection of MRT tissue sparing,” Valceski explains. “This opens up the potential for MRT radiosurgery, something our research team has previously investigated.”

Finally, the researchers used γH2AX foci data for each peak and valley to determine a biological PVDR. The biological PDVR values matched the physical PVDR of 8.9, confirming for the first time a direct relationship between physical dose delivered and DSBs induced in the cancer cells. They note that adding radiosensitizers generally lowered the biological PVDRs from the physical value, likely due to additional DSBs induced in the valleys.

The next step will be to perform preclinical studies of MRT. “Trials to assess the efficacy of this multimodal therapy in treating aggressive cancers in vivo are key, especially given the theragnostic potential of nanoparticles for image-guided treatment and precision planning, as well as cancer-specific dose enhancement,” senior author Moeava Tehei tells Physics World. “Considering the radiosurgical potential of stereotactic, radiosensitizer-enhanced MRT fractions, we can foresee a revolutionary multimodal technique with curative potential in the near future.”

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