Abstract: A method of radiotherapy treatment planning for particle-based arc treatment comprises the steps of determining (S11; S21) an initial set of candidate energy layers, performing a calculation on the initial set, determining (S13; S23), based on the outcome of said calculation, at least one additional energy layer to produce an expanded candidate layer set, wherein the at least one additional energy layer involves an energy level that has not previously been used adding (S14; S24) the at least one additional energy to the initial set, to produce an expanded candidate energy layer set optimizing (S16; S26) a radiotherapy treatment plan based on the expanded candidate layer set.

Abstract: An estimated or predicted dose for radiotherapy treatment may be generated based on a partial dose map including dose information only for one or more regions of interest within a treatment site, by use of a properly trained machine learning system such as a U-Net or a V-Net. Said partial dose map typically set to fulfil clinical goals. A method of training such a machine learning system is also disclosed.

Abstract: A computer-implemented method for generating a radiation therapy treatment plan for a volume of a patient, the method comprising: receiving an image of the volume; receiving at least one dose-distribution-derived function configured to provide a value as an output based on, as input, at least part of a dose distribution defined relative to the image; receiving a first probability distribution and at least a second, different, probability distribution, the first and at least second probability distributions; defining a multi-criteria optimization problem comprising at least a first objective function based on the at least one dose-distribution-derived function, the first probability distribution and a loss function; and a second objective function based on the at least one dose-distribution-derived function, the second probability distribution and the loss function; and performing a multi-criteria optimization process based on the at least two objective functions to generate at least two output treatment plans

Abstract: A radiotherapy treatment planning method for achieving a FLASH radiotherapy treatment plan involves optimizing the plan using an optimization problem that has been designed to maximize the part of the irradiation that will be delivered under FLASH conditions, in particular to an organ at risk, to minimize the damage to the organ at risk.

Abstract: A computer based method of obtaining a 3D image of a part of a patient's body is disclosed, based on a fraction image having a limited field-of-view and extending the field of view with information from an image of the patient's outline, obtained from a surface scan of the patient. Anatomical data from the planning image are preferably used to fill in the outline image, by means of a contour-guided deformable registration between the planning image and contour.

Abstract: It is provided a method for generating a plurality of treatment plans for radiation therapy, each treatment plan specifying weights for a plurality of geometrically defined fluence elements. Each weight defines an amount of radiation fluence, to thereby provide radiation dose to a target volume. The method is performed in a treatment planning system and comprises the steps of: generating a first set of treatment plans; determining a subset of the fluence elements, based on the first set of treatment plans; and generating a second set of at least two treatment plans, wherein the treatment plans only contain weights for the subset of fluence elements.