Abstract: The present application provides an initial, or first, packed arc setup to be compared with predefined arc setup constraints. These predefined arc setup constraints constrain at least one or more of the number of patient table angles per target volume, the number of times the gantry moves along one arc per table angle, the sum of gantry span per metastasis over all arcs, and the minimum table span. Based on the result of the comparison between the packed first arc setup with the predefined arc setup constraints, a second arc setup is automatically suggested. The automatically suggested second arc setup may then be compared with the first arc setup by calculating a score for both setups. Several iterations of such a method can be carried out based on the comparison between an arc setup and the following, subsequent arc setup in the iteration.

Abstract: A ceramic core (40) for an investment casting process (80) including a subsurface internal channel (50) for the introduction of leachate (98) to improve the effectiveness of a leaching process used to remove the core (94) from a cast alloy component (100). The subsurface internal channel may be completely hollow, or it may include one or more ribs (54). The core may be formed (82) using a 3D printing process wherein a carrier material (68) is deposited in a central region of the channel for the purpose of supporting an overlying layer (62) of core material, with the carrier material later being removed to reveal the hollow internal channel (52).

Abstract: Disclosed is a computer-implemented method of determining a treatment plan, encompassing acquiring patient image data, acquiring target data describing targets, acquiring position data describing control points which define one or more arcs, and determining target projection data which describes outlines of the target in a beam's-eye view. Margin data is acquired. For the outlines, margins are applied to determine auxiliary outlines. Beam shaping device data is determined describing configurations of the collimator leaves so that irradiation of the auxiliary outlines is enabled. Based on these configurations, the irradiation amount is simulated for voxels of the patient image data. Constraints to be fulfilled by the treatment plan may be set. Configurations of blockings, arc-weights and margins are proposed. Only different combinations of these parameters are proposed while additional possible parameters are neglected. An optimization algorithm is used to minimize an objective function.

Abstract: The present application provides an initial, or first, packed arc setup to be compared with predefined arc setup constraints. These predefined arc setup constraints constrain at least one or more of the number of patient table angles per target volume, the number of times the gantry moves along one arc per table angle, the sum of gantry span per metastasis over all arcs, and the minimum table span. Based on the result of the comparison between the first packed arc setup with the predefined arc setup constraints, a second arc setup is automatically suggested. The automatically suggested second arc setup may then be compared with the first arc setup by calculating a score for both setups. Several iterations of such a method can be carried out based on the comparison between an arc setup and the following, subsequent arc setup in the iteration.

Abstract: A ceramic core (40) for an investment casting process (80) including a subsurface internal channel (50) for the introduction of leachate (98) to improve the effectiveness of a leaching process used to remove the core (94) from a cast alloy component (100). The subsurface internal channel may be completely hollow, or it may include one or more ribs (54). The core may be formed (82) using a 3D printing process wherein a carrier material (68) is deposited in a central region of the channel for the purpose of supporting an overlying layer (62) of core material, with the carrier material later being removed to reveal the hollow internal channel (52).

Abstract: Disclosed is a computer-implemented method of determining a treatment plan, encompassing acquiring patient image data, acquiring target data describing targets, acquiring position data describing control points which define one or more arcs, and determining target projection data which describes outlines of the target in a beam's-eye view. Margin data is acquired. For the outlines, margins are applied to determine auxiliary outlines. Beam shaping device data is determined describing configurations of the collimator leaves so that irradiation of the auxiliary outlines is enabled. Based on these configurations, the irradiation amount is simulated for voxels of the patient image data. Constraints to be fulfilled by the treatment plan may be set. Configurations of blockings, arc-weights and margins are proposed. Only different combinations of these parameters are proposed while additional possible parameters are neglected. An optimization algorithm is used to minimize an objective function.

Abstract: A computer-implemented medical method of irradiation treatment planning is provided. Therein, an initial coverage volume for a planning target volume, which is to be irradiated in an irradiation treatment with a prescribed dose, is provided. Further, at least one constraint indicative of an allowed dose for an organ at risk is provided. Applying an initial irradiation treatment plan, an organ dose deposited in at least a partial volume of the organ at risk is calculated. Based on comparing the organ dose to the at least one constraint, an amount of violation is determined. Taking into account the determined amount of violation, a reduction coverage volume is calculated for the planning target volume and a virtual planning object is generated based on changing a volume of the organ at risk, such that an overlap region of the virtual planning object and the planning target volume corresponds to the reduction coverage volume.

Abstract: The present application provides an initial, or first, packed arc setup to be compared with predefined arc setup constraints. These predefined arc setup constraints at least constrain the number of patient table angles per target volume, constrain the number of times the gantry moves along one arc per table angle, constraint the sum of gantry span per metastasis over all arcs, and constrain the minimum table span. Based on the result of the comparison between the first packed arc setup with the predefined arc setup constraints, a second arc setup is automatically suggested. The automatically suggested second arc setup may then be compared with the first one by calculating a score for both setups. Several iterations of such a method can be carried out based on the comparison between an arc setup and the following, subsequent arc setup in the iteration.

Abstract: The present application provides an initial, or first, packed arc setup to be compared with predefined arc setup constraints. These predefined arc setup constraints at least constrain the number of patient table angles per target volume, constrain the number of times the gantry moves along one arc per table angle, constraint the sum of gantry span per metastasis over all arcs, and constrain the minimum table span. Based on the result of the comparison between the first packed arc setup with the predefined arc setup constraints a second arc setup is automatically suggested. The automatically suggested second arc setup may then be compared with the first one by calculating a score for both setups. Several iterations of such a method can be carried out based on the comparison between an arc setup and the following, subsequent arc setup in the iteration.

Abstract: Disclosed is a computer-implemented method of determining a treatment plan, encompassing acquiring patient image data, acquiring target data describing targets, acquiring position data describing control points which define one or more arcs, and determining target projection data which describes outlines of the target in a beam's-eye view. Margin data is acquired. For the outlines, margins are applied to determine auxiliary outlines. Beam shaping device data is determined describing configurations of the collimator leaves so that irradiation of the auxiliary outlines is enabled. Based on these configurations, the irradiation amount is simulated for voxels of the patient image data. Constraints to be fulfilled by the treatment plan may be set. Configurations of blockings, arc-weights and margins are proposed. Only different combinations of these parameters are proposed while additional possible parameters are neglected. An optimization algorithm is used to minimize an objective function.

Abstract: Disclosed is a method for determining an irradiation trajectory for the movement of a treatment device for irradiating an anatomical structure with ionising treatment radiation, the method comprising steps of acquiring medical image data describing a medical image of the anatomical structure; determining, based on the medical image data, image concavity data; acquiring predetermined concavity data; determining, based on the image concavity data and the predetermined concavity data, partition data; determining, based on the medical image data, partition boundary data; and determining, based on the partition boundary data, irradiation trajectory data.

Abstract: A computer-implemented medical method of irradiation treatment planning is provided. Therein, an initial coverage volume (118) for a planning target volume (116), which is to be irradiated in an irradiation treatment with a prescribed dose, is provided. Further, at least one constraint (106, 110) indicative of an allowed dose for an organ at risk (120) is provided. Applying an initial irradiation treatment plan, an organ dose deposited in at least a partial volume of the organ at risk (120) is calculated. Based on comparing the organ dose to the at least one constraint (106, 110), an amount of violation is determined. Taking into account the determined amount of violation, a reduction coverage volume is calculated for the planning target volume (116) and a virtual planning object (122) is generated based on changing a volume of the organ at risk (120), such that an overlap region (124) of the virtual planning object (122) and the planning target volume (116) corresponds to the reduction coverage volume.

Abstract: Disclosed is a computer-implemented medical data processing method for determining a dose distribution for use in a medical procedure involving irradiation of an anatomical structure of a patient's body with ionizing radiation. A processor acquires medical image data describing a medical image of the anatomical structure. The processor acquires dose distribution data describing an irradiation dose distribution spatially defined in the reference system of the medical image of the anatomical structure. Prioritization data is determined that describes, for each image unit of the medical image describing non-target tissue, a priority of that image unit for consideration during an optimization of the irradiation dose distribution described by the dose distribution data.

Abstract: Disclosed is a computer-implemented medical data processing method for determining a dose distribution for use in a medical procedure involving irradiation of an anatomical structure of a patient's body with ionising radiation. A processor acquires medical image data describing a medical image of the anatomical structure. The processor acquires dose distribution data describing an irradiation dose distribution spatially defined in the reference system of the medical image of the anatomical structure. Prioritization data is determined that describes, for each image unit of the medical image describing non-target tissue, a priority of that image unit for consideration during an optimization of the irradiation dose distribution described by the dose distribution data.

Abstract: Disclosed is a method for determining an irradiation trajectory for the movement of a treatment device for irradiating an anatomical structure with ionising treatment radiation, the method comprising steps of acquiring medical image data describing a medical image of the anatomical structure; determining, based on the medical image data, image concavity data; acquiring predetermined concavity data; determining, based on the image concavity data and the predetermined concavity data, partition data; determining, based on the medical image data, partition boundary data; and determining, based on the partition boundary data, irradiation trajectory data.