Abstract: An initial, relatively coarse arrangement of spots in a target volume and a respective dose distribution per spot are accessed from memory or determined. If the dose distributions of neighboring spots do not satisfy a similarity criterion, then a new set of spots with finer spacing is determined for the regions that include dissimilar spots (e.g., spots are added between the dissimilar spots), and spot dose distributions are determined for the new spot arrangement. The process is repeated until the similarity criterion is satisfied for all or a threshold number of spots or until a minimum spot spacing is reached. The final arrangement of spots and dose distributions for the spots can be stored. During subsequent optimization of a treatment plan based on the final arrangement of spots, a dose distribution for a point that is between the spots can be determined by interpolating the dose distributions of nearby spots.

Abstract: A system and method for acquiring magnetic resonance (MR) images, with an MR system, of tissue proximal to a target treatment region in a patient, the tissue including a non-spatially uniform subcutaneous fat layer; in a computer comprising a hardware-based processor, automatically determining a thickness of the subcutaneous fat layer using a trained neural network, the neural network trained using manually-segmented MR images from previous patients; in the computer, automatically adjusting a treatment parameter based on the thickness of the subcutaneous fat layer; and delivering thermal therapy to the target treatment region with a high-intensity focused ultrasound system based on the adjusted treatment parameter.

Abstract: A system and method for acquiring magnetic resonance (MR) images, with an MR system, of tissue proximal to a target treatment region in a patient, the tissue including a non-spatially uniform subcutaneous fat layer; in a computer comprising a hardware-based processor, automatically determining a thickness of the subcutaneous fat layer using a trained neural network, the neural network trained using manually-segmented MR images from previous patients; in the computer, automatically adjusting a treatment parameter based on the thickness of the subcutaneous fat layer; and delivering thermal therapy to the target treatment region with a high-intensity focused ultrasound system based on the adjusted treatment parameter.