Knowledge-based spatial dose metrics and methods to generate beam orientations in radiotherapy

1. A method executed on a computing device, the method for estimating a dose and developing a radiation therapy plan, the method comprising:

executing, with a processor of the computing device, a dose distribution planning tool stored as programming code in a computer-readable medium of the computing device, wherein said executing comprises:

subdividing a representation of a volume of interest into a first plurality of voxels;

determining a first distance between an origin of a first planned radiation field of a radiation beam and a first voxel of the first plurality of voxels that is traversed by the first planned radiation field;

computing a first metric based on the first distance, a prescription dose associated with a target volume outside the volume of interest, and a first field parameter; and

evaluating the first metric and determining a beam orientation for delivering the prescription dose to the target volume, wherein said determining a beam orientation comprises including the first planned radiation field in the radiation therapy plan if the first metric satisfies a dose constraint for the volume of interest.

2. The method of claim 1 , wherein a fanline of the first planned radiation field traverses the first voxel and the target volume.

3. The method of claim 1 , wherein the first field parameter comprises a strength parameter corresponding to a nominal energy level of the first planned radiation field.

4. The method of claim 1 , wherein the volume of interest corresponds to an organ at risk with respect to the radiation therapy plan.

5. The method of claim 1 , wherein the first metric represents a discrete contribution at the first voxel to an estimated dose received by the volume of interest.

6. The method of claim 1 , further comprising:

determining a plurality of distances, each of which is associated with the first planned radiation field and a respective voxel of the first plurality of voxels, the plurality of distances including the first distance;

computing a plurality of metrics based on the plurality of distances, one or more plan parameters associated with one or more target volumes traversed by the first planned radiation field, and the first field parameter, the one or more plan parameters including the first plan parameter; and

summing the plurality of metrics corresponding to the first plurality of voxels, the plurality of metrics including the first metric.

7. The method of claim 6 , wherein the summation of the plurality of metrics represents an estimated dose received by the volume of interest from the first planned radiation field.

8. The method of claim 1 , further comprising:

computing a second metric based on the first distance, a second plan parameter associated with a second target volume traversed by a fanline of the first planned radiation field that traverses the first voxel, and the first field parameter, wherein the second plan parameter comprises a second prescription dose associated with the second target volume; and

summing the first metric and the second metric, wherein the resulting summation represents an estimated dose received by the first voxel from the first planned radiation field.

9. The method of claim 1 , further comprising:

determining a second distance between an origin of a second planned radiation field of a radiation beam and the first voxel; and

computing a second metric based on the second distance, the prescription dose, and a second field parameter, wherein the first field parameter comprises a strength parameter corresponding to a nominal energy level of the first planned radiation field, and wherein the second field parameter comprises a strength parameter corresponding to a nominal energy level of the second planned radiation field.

10. The method of claim 1 , further comprising:

subdividing a representation of a second volume of interest into a second plurality of voxels;

determining a plurality of distances, each of which is associated with the first planned radiation field and a respective voxel of the second plurality of voxels;

computing a plurality of metrics based on the plurality of distances, one or more plan parameters associated with one or more target volumes traversed by the first planned radiation field, and the first field parameter; and

summing the plurality of metrics corresponding to the second plurality of voxels.

11. The method of claim 1 , wherein said evaluating comprises:

generating a plurality of normal vectors that emanate from a plurality of points on a surface of a representation of the target volume and extend to a body surface;

quantifying a dose fall-off curve along each of the normal vectors based on the radiation therapy plan;

grouping a subset of the plurality of normal vectors based on the volume of interest;

determining a mean dose fall-off curve for the volume of interest based on the subset; and

deriving a dose-volume histogram for the volume of interest based on the mean dose fall-off curve and a mean distance between the target volume and the volume of interest.

12. The method of claim 11 , wherein said quantifying the dose fall-off curve along each of the normal vectors comprises accessing stored patient results associated with historical therapy plans.

13. The method of claim 11 , further comprising:

for each normal vector of the normal vectors, computing a dose gradient based on the dose fall-off curve along said each normal vector;

for said each normal vector of the normal vectors, projecting the dose gradient for said each normal vector along a plane that is orthogonal to said each normal vector to produce projected dose gradients;

generating a preference matrix on the surface of a sphere based on the projected dose gradients; and

determining preferred beam orientations based on the preference matrix.

14. The method of claim 11 , further comprising:

computing a dose gradient corresponding to each of the normal vectors based on the dose fall-off curve along each of the normal vectors;

constructing a boundary around the target volume based on dose gradients resulting from said computing; and

evaluating a sensitivity of the beam orientation with respect to a target volume motion based on the boundary.