A method (900, 1000) for radiation treatment planning, the method (900, 1000) comprising: receiving a set of clinical goals wherein at least a first clinical goal in the set of clinical goals is expressed with reference to a threshold isodose surface corresponding to a threshold dose; defining a cost function having a cost function component corresponding to each clinical goal in the set of clinical goals, wherein a first cost function component corresponding to the first clinical goal is defined based directly on the threshold isodose surface; computing, for each treatment plan in a set of candidate treatment plans, the cost function and a cost function gradient having a gradient element corresponding to each cost function component, wherein for the first cost function component, computing the gradient element includes: identifying a set of voxels of interest, wherein the set of voxels of interest includes at least some voxels that are intersected by the threshold isodose surface; computing, for each voxel of interest, a gradient of a dose distribution; and determining, for each voxel of interest, a local contribution to the gradient element based at least in part on the gradient of the dose distribution; performing a cost function minimization using the cost function and the cost function gradient; and generating an optimized treatment plan based on a result of the cost function minimization; wherein: identifying the set of voxels of interest for a particular candidate treatment plan in the set of candidate treatment plans includes: computing a dose distribution for the particular candidate treatment plan using a dose prediction model, the dose distribution including a dose at each of a plurality of lattice points, the plurality of lattice points defining a set of voxels having corner points at adjacent lattice points; and identifying, as a voxel of interest, any voxel in the set of voxels for which at least one corner point has a dose greater than the threshold dose and at least one corner point has a dose less than the threshold dose. receiving a set of clinical goals wherein at least a first clinical goal in the set of clinical goals is expressed with reference to a threshold isodose surface corresponding to a threshold dose; defining a cost function having a cost function component corresponding to each clinical goal in the set of clinical goals, wherein a first cost function component corresponding to the first clinical goal is defined based directly on the threshold isodose surface; computing, for each treatment plan in a set of candidate treatment plans, the cost function and a cost function gradient having a gradient element corresponding to each cost function component, wherein for the first cost function component, computing the gradient element includes: identifying a set of voxels of interest, wherein the set of voxels of interest includes at least some voxels that are intersected by the threshold isodose surface; computing, for each voxel of interest, a gradient of a dose distribution; and determining, for each voxel of interest, a local contribution to the gradient element based at least in part on the gradient of the dose distribution; identifying a set of voxels of interest, wherein the set of voxels of interest includes at least some voxels that are intersected by the threshold isodose surface; computing, for each voxel of interest, a gradient of a dose distribution; and determining, for each voxel of interest, a local contribution to the gradient element based at least in part on the gradient of the dose distribution; performing a cost function minimization using the cost function and the cost function gradient; and generating an optimized treatment plan based on a result of the cost function minimization; wherein: identifying the set of voxels of interest for a particular candidate treatment plan in the set of candidate treatment plans includes: computing a dose distribution for the particular candidate treatment plan using a dose prediction model, the dose distribution including a dose at each of a plurality of lattice points, the plurality of lattice points defining a set of voxels having corner points at adjacent lattice points; and identifying, as a voxel of interest, any voxel in the set of voxels for which at least one corner point has a dose greater than the threshold dose and at least one corner point has a dose less than the threshold dose. computing a dose distribution for the particular candidate treatment plan using a dose prediction model, the dose distribution including a dose at each of a plurality of lattice points, the plurality of lattice points defining a set of voxels having corner points at adjacent lattice points; and identifying, as a voxel of interest, any voxel in the set of voxels for which at least one corner point has a dose greater than the threshold dose and at least one corner point has a dose less than the threshold dose.