With MR-linacs, radiation therapy clinics can monitor and account for organ motion by imaging a patient and modifying their treatment plan while the patient is on the treatment table. This type of radiation therapy, called adaptive radiotherapy, delivers the same prescription dose in each treatment fraction. Researchers at the University Hospital of Zurich (USZ) are among several groups that have studied how to optimize the amount of dose delivered to a patient in each fraction – an approach they’ve dubbed adaptive fractionation.
Traditionally, clinicians have accounted for inter-fraction motion with treatment margins and by adjusting contours. Jan Unkelbach, a professor of medical physics research at USZ, says that when USZ installed an MR-linac in 2019, he wanted to push the boundaries of adaptive radiotherapy. In treatments of abdominal lesions, the USZ clinic observes inter-fraction motion on the order of a few millimetres, which can compromise tumour coverage and is accounted for using current adaptive radiotherapy techniques.
“We wanted to make use of the new imaging information that the MR-linac gives us every day, and we wanted to pursue something that goes beyond adaptive radiotherapy as performed in the clinics today,” Unkelbach says. “Adaptive fractionation is one approach to exploit inter-fraction motion rather than only compensating for it.”
The researchers say that they take advantage of inter-fraction motion by upscaling or downscaling the prescribed dose on each day’s treatment plan. A patient receiving adaptive fractionation treatments would be prescribed a larger radiation dose on days when the separation between a tumour and organs-at-risk (OARs) is large. Correspondingly, they would receive a smaller radiation dose on days with smaller tumour–OAR separation.
One of the challenges of adaptive fractionation is that while clinicians know the inter-fraction motion on a given day and the dose that has been delivered so far, they don’t know what will happen on subsequent days and fractions.
“This is exactly the big problem we tried to solve by using methods from the field of stochastic optimal control. By using patients from the same population [in our studies], we can model what we expect to see in the future, and we can compute this optimal dose based on the probability distribution of future organ and tumour anatomy,” explains Yoel Pérez Haas, previously a graduate student in Unkelbach’s group when he led their first adaptive fractionation studies.
The algorithm developed by the researchers assumes that a classic biologically equivalent dose (BED) model can be extended to an adaptive fractionation application, and that cumulative BED at the end of treatment is given by the sum of BED values in individual fractions. Parameters of the probability distribution are updated in each fraction following a patient’s daily MRI scan.
Pérez Haas used the algorithm to retrospectively analyse 16 five-fraction abdominal stereotactic body radiotherapy (SBRT) treatments delivered on the MR-linac system. Inter-fraction motion was modelled by sparing factors that describe how much dose a dose-limiting organ receives compared with the tumour and which the researchers used to adjust prescription dose on a fraction-by-fraction basis. BED metrics were used to quantify benefits to escalating tumour dose on a large separation day and suggest improvements over standard fractionation.
The researchers’ preliminary results suggest that only a few patients might show enough motion to significantly benefit from adaptive fractionation. But integrating adaptive fractionation into clinical workflows is worthwhile if it improves treatment outcomes in even a small number of patients, Unkelbach says.
Is the MR-linac the future of adaptive radiotherapy?
Important issues remain to be addressed. For example, patients who would have benefited most from the group’s adaptive fractionation scheme would have received larger doses of radiation in a single fraction (more than 20 Gy) than clinicians would be comfortable delivering. The researchers’ algorithm also does not account for uncertainties in dose delivery. It’s also not yet known how patients who might benefit from adaptive fractionation would be identified.
The researchers are currently exploring ways to identify such patients, and they are extending their algorithm to include clinical constraints, including the maximum and minimum dose that can be delivered in a single fraction. They are also conducting a larger retrospective study to see if their results hold in a larger cohort.
For more information, read the study in .