Patent Description:
The use of energy to treat medical conditions comprises a known area of prior art endeavor. For example, radiation therapy comprises an important component of many treatment plans for reducing or eliminating unwanted tumors. Unfortunately, applied energy does not inherently discriminate between unwanted material and adjacent tissues, organs, or the like that are desired or even critical to continued survival of the patient. As a result, energy such as radiation is ordinarily applied in a carefully administered manner to at least attempt to restrict the energy to a given target volume. A so-called energy-based treatment plan often serves in the foregoing regards.

An energy-based treatment plan such as a radiation treatment plan typically comprises specified values for each of a variety of treatment-platform parameters during each of a plurality of sequential fields. Treatment plans for radiation treatment sessions are often generated through a so-called optimization process. As used herein, "optimization" will be understood to refer to improving a candidate treatment plan without necessarily ensuring that the optimized result is, in fact, the singular best solution. Such optimization often includes automatically adjusting one or more treatment parameters (often while observing one or more corresponding limits in these regards) and mathematically calculating a likely corresponding treatment result to identify a given set of treatment parameters that represent a good compromise between the desired therapeutic result and avoidance of undesired collateral effects.

Unfortunately, existing optimization techniques do not necessarily address all potential needs for all potential patients in all potential application settings. As one example in these regards, modulated proton scanning typically requires the optimization of so-called spot position and spot weights in order to obtain optimal dosing and dose rates. The automatic optimization of spot positions and weights, however, does not always produce satisfactory results.

It is possible to manually edit spot weights following optimization to improve anticipated results for a problematic region (or, alternatively, one can continue to use the optimization algorithm to add or change the optimization criteria in order to seek a better result). Prior art approaches in these regards, however, require recalculating the dose to thereby observe and assess the results of such modifications. Furthermore, such recalculations may be necessarily required multiple times in order to test/assess different possible adjustments to the plan. These approaches can require considerable time, sometimes requiring multiple hours. That expenditure of time can be at least inconvenient for both the patient and the technician(s)/physician(s), and as a result, a less than fully-suitable plan may be simply settled upon.

<CIT> discloses manipulation of an achievable dose distribution estimate deliverable by a radiation delivery apparatus for proposed treatment of a subject. One method comprises: determining a dose modification voxel for which it is desired to modify the dose value and a corresponding magnitude of desired dose modification; for each of a plurality of beams: (i) characterizing the beam as a two-dimensional array of beamlets, wherein each beamlet is associated with a corresponding intensity value and a ray line representing the projection of the beamlet into space; and (ii) identifying one or more dose-change beamlets which have associated ray lines that intersect the dose modification voxel; modifying the intensity values of at least one of the dose-change beamlets; and updating the achievable dose distribution estimate to account for the modified intensity values of the at least one of the dose-change beamlets.

In one aspect the present invention provides a method as defined in claim <NUM>. In another aspect the present invention provides an apparatus as defined in claim <NUM>. Optional features are specified in the dependent claims.

The above needs are at least partially met through provision of the method and apparatus to detect and respond to radiation treatment plan spot weight edits described in the following detailed description, particularly when studied in conjunction with the drawings, wherein:.

For example, the dimensions and/or relative positioning of some of the elements in the figures may be exaggerated relative to other elements to help to improve understanding of various embodiments of the present teachings. Also, common but well-understood elements that are useful or necessary in a commercially feasible embodiment are often not depicted in order to facilitate a less obstructed view of these various embodiments of the present teachings. Certain actions and/or steps may be described or depicted in a particular order of occurrence while those skilled in the art will understand that such specificity with respect to sequence is not actually required. The terms and expressions used herein have the ordinary technical meaning as is accorded to such terms and expressions by persons skilled in the technical field as set forth above except where different specific meanings have otherwise been set forth herein. The word "or" when used herein shall be interpreted as having a disjunctive construction rather than a conjunctive construction unless otherwise specifically indicated.

Generally speaking, these various embodiments serve to facilitate optimizing a patient treatment plan to administer therapeutic energy, such as a proton beam, to a particular patient.

By one approach, these teachings provide for optimizing a radiation treatment plan for a particular patient and providing corresponding resultant radiation dosing information. Such optimization can include, by one approach, calculating a corresponding influence matrix. Upon detecting at least one manual edit to at least one spot weight that corresponds to the radiation treatment plan, these teachings can provide for responsively generating new radiation dosing information in at least near real-time as a function of a corresponding influence matrix.

These teachings will accommodate various approaches to detecting such manual edits. By one approach, for example, a manual edit can be detected via a user interface when a user selects a region that includes a plurality of spots (using, for example, a cursor). By another approach, and as another example, a manual edit can be detected when a user selects individual spots.

By one approach, these teachings provide for generating the new radiation dosing information by multiplying the aforementioned influence matrix by the corresponding spot weights. The latter may comprise, for example, using vector multiplication.

These teachings are both flexible and practical in practice and will accommodate, for example, generating the new radiation dosing information by calculating a total radiation dose, calculating a dose rate, or both as desired.

These teaching accordingly support interactive dose modification in a treatment planning system. These teachings are highly flexible in terms of accommodating various approaches to how a user can interact with the treatment planning system. So configured, these teachings provide a simple and intuitive way to address problematic cases that the automatically optimized solution does not adequately address. Perhaps just as importantly, the corresponding results can be very quickly provided (for example, within <NUM> to <NUM> seconds as compared to, potentially, many hours required by many prior art approaches).

By permitting the user to see the results of their changes to spot weighting in at least near real-time, a given highly-effective radiation treatment plan can be more likely achieved in a practical application setting.

These and other benefits may become clearer upon making a thorough review and study of the following detailed description. Referring now to the drawings, and in particular to <FIG>, an illustrative apparatus <NUM> that is compatible with many of these teachings will first be presented.

In this particular example, the enabling apparatus <NUM> includes a control circuit <NUM>. Being a "circuit," the control circuit <NUM> therefore comprises structure that includes at least one (and typically many) electrically-conductive paths (such as paths comprised of a conductive metal such as copper or silver) that convey electricity in an ordered manner, which path(s) will also typically include corresponding electrical components (both passive (such as resistors and capacitors) and active (such as any of a variety of semiconductor-based devices) as appropriate) to permit the circuit to effect the control aspect of these teachings.

Such a control circuit <NUM> can comprise a fixed-purpose hard-wired hardware platform (including but not limited to an application-specific integrated circuit (ASIC) (which is an integrated circuit that is customized by design for a particular use, rather than intended for general-purpose use), a field-programmable gate array (FPGA), and the like) or can comprise a partially or wholly-programmable hardware platform (including but not limited to microcontrollers, microprocessors, and the like). These architectural options for such structures are well known and understood in the art and require no further description here. This control circuit <NUM> is configured (for example, by using corresponding programming as will be well understood by those skilled in the art) to carry out one or more of the steps, actions, and/or functions described herein.

The control circuit <NUM> operably couples to a memory <NUM>. This memory <NUM> may be integral to the control circuit <NUM> or can be physically discrete (in whole or in part) from the control circuit <NUM> as desired. This memory <NUM> can also be local with respect to the control circuit <NUM> (where, for example, both share a common circuit board, chassis, power supply, and/or housing) or can be partially or wholly remote with respect to the control circuit <NUM> (where, for example, the memory <NUM> is physically located in another facility, metropolitan area, or even country as compared to the control circuit <NUM>).

In addition to information such as radiation dosing information, this memory <NUM> can serve, for example, to non-transitorily store the computer instructions that, when executed by the control circuit <NUM>, cause the control circuit <NUM> to behave as described herein. (As used herein, this reference to "non-transitorily" will be understood to refer to a non-ephemeral state for the stored contents (and hence excludes when the stored contents merely constitute signals or waves) rather than volatility of the storage media itself and hence includes both non-volatile memory (such as read-only memory (ROM) as well as volatile memory (such as a dynamic random access memory (DRAM).

By one optional approach the control circuit <NUM> also operably couples to a user interface <NUM>. This user interface <NUM> can comprise any of a variety of user-input mechanisms (such as, but not limited to, keyboards and keypads, cursor-control devices, touch-sensitive displays, speech-recognition interfaces, gesture-recognition interfaces, and so forth) and/or user-output mechanisms (such as, but not limited to, visual displays, audio transducers, printers, and so forth) to facilitate receiving information and/or instructions from a user and/or providing information to a user.

If desired the control circuit <NUM> can also operably couple to a network interface (not shown). So configured the control circuit <NUM> can communicate with other elements (both within the apparatus <NUM> and external thereto) via the network interface. Network interfaces, including both wireless and non-wireless platforms, are well understood in the art and require no particular elaboration here.

By one approach, a computed tomography apparatus <NUM> and/or other imaging apparatus <NUM> as are known in the art can source some or all of any desired patient-related imaging information.

In this illustrative example the control circuit <NUM> is configured to ultimately output an optimized energy-based treatment plan <NUM> (such as, for example, an optimized radiation treatment plan). This energy-based treatment plan <NUM> typically comprises specified values for each of a variety of treatment-platform parameters during each of a plurality of sequential exposure fields. In this case the energy-based treatment plan <NUM> is generated through an optimization process. Various automated optimization processes specifically configured to generate such an energy-based treatment plan are known in the art. As the present teachings are not overly sensitive to any particular selections in these regards, further elaboration in these regards is not provided here except where particularly relevant to the details of this description.

By one approach the control circuit <NUM> can operably couple to an energy-based treatment platform <NUM> that is configured to deliver therapeutic energy <NUM> to a corresponding patient <NUM> in accordance with the optimized energy-based treatment plan <NUM>. These teachings are generally applicable for use with any of a wide variety of energy-based treatment platforms/apparatuses.

In a typical application setting the energy-based treatment platform <NUM> will include an energy source <NUM> such as a source of ionizing radiation, a source of microwave energy, a source of heat energy, and so forth. For the sake of an illustrative example, it will be presumed here that the energy source <NUM> is a source of protons that provides a beam of protons to irradiate diseased tissue.

By one approach this energy source <NUM> can be selectively moved via a gantry along an arcuate pathway (where the pathway encompasses, at least to some extent, the patient themselves during administration of the treatment). The arcuate pathway may comprise a complete or nearly complete circle as desired. By one approach the control circuit <NUM> controls the movement of the energy source <NUM> along that arcuate pathway, and may accordingly control when the energy source <NUM> starts moving, stops moving, accelerates, de-accelerates, and/or a velocity at which the energy source <NUM> travels along the arcuate pathway.

A typical energy-based treatment platform <NUM> may also include one or more support apparatuses <NUM> (such as a couch) to support the patient <NUM> during the treatment session, one or more patient fixation apparatuses <NUM>, a gantry or other movable mechanism to permit selective movement of the energy source <NUM>, and one or more energy-shaping apparatuses <NUM> (for example, beam-shaping apparatuses such as jaws, multi-leaf collimators, and so forth) to provide selective energy shaping and/or energy modulation as desired.

In a typical application setting, it is presumed herein that the patient support apparatus <NUM> is selectively controllable to move in any direction (i.e., any X, Y, or Z direction) during an energy-based treatment session by the control circuit <NUM>. As the foregoing elements and systems are well understood in the art, further elaboration in these regards is not provided here except where otherwise relevant to the description.

Referring now to <FIG>, a process <NUM> that can be carried out, for example, in conjunction with the above-described application setting (and more particularly via the aforementioned control circuit <NUM>) will be described.

At block <NUM>, this process <NUM> provides for optimizing a radiation treatment plan <NUM> for a particular patient <NUM> and providing corresponding resultant radiation dosing information. For the sake of an illustrative example, it will be presumed here that the radiation treatment plan <NUM> comprises a plan to administer scanning proton therapy.

It will also be presumed here that optimizing the radiation treatment plan <NUM> includes calculating a corresponding influence matrix. Influence matrices are known in the art. An influence matrix specifies how each spot affects the dose (and hence specifies the contribution of each spot). For the sake of an illustrative example, and referring momentarily to <FIG>, the depicted grid <NUM> corresponds to a two-dimensional patient comprising <NUM> x <NUM> voxels (two of which are denoted by reference <NUM>). The wedges <NUM> are proton beams or "spots," and the broken line <NUM> is the trajectory of an individual proton inside the patient. The stars (one of which is denoted by reference <NUM>) indicate collisions of the proton with particles in the medium where it loses and deposits some energy (where "dose" equals energy divided by local density).

Reference numeral <NUM> denotes the corresponding influence matrix. In this illustrative example the columns of the influence matrix each correspond to one spot and each row corresponds to one voxel. To form the influence matrix, the control circuit <NUM> simulates the trajectories of protons and adds all of their individual contributions to the influence matrix based on the spot the proton belongs to and the voxel where the dose is deposited.

Referring again to <FIG>, at block <NUM> the control circuit <NUM> detects at least one manual edit to at least one spot weight that corresponds to the radiation treatment plan <NUM>. (In the absence of detecting a trigger event, this process <NUM> can accommodate any of a variety of responses. Examples of responses can include temporal multitasking (pursuant to which the control circuit <NUM> conducts other tasks before returning to again monitor for a manual edit) as well as continually looping back to essentially continuously monitor for this trigger event. These teachings also accommodate supporting this detection activity via a real-time interrupt capability.

These teachings will accommodate various approaches to detecting a manual edit. By one approach, and referring momentarily to <FIG> and <FIG>, <FIG> depicts the user interface <NUM> presenting a scanned image that includes scanned imagery of the patient's treatment volume <NUM> along with other patient features and dosing information. <FIG> depicts a region <NUM> of the treatment volume <NUM> that the user has selected (using, for example, a cursor control and selection device such as a mouse or a touch screen display). This region <NUM> corresponds to and includes a plurality of spots. By this approach, the control circuit <NUM> detects that selection activity as a manual edit.

By another approach, and referring momentarily to <FIG> depicts the user interface <NUM> presenting some individual spots that correspond to the treatment volume <NUM>. <FIG> depicts, in turn, the user interface <NUM> presenting certain of the spots (generally denoted by reference <NUM>) that correspond to individual spots that were selected by the user. In all of these cases the user can select a corresponding weight for the selected spots. These teachings will accommodate other approaches to detecting a manual edit as desired.

Upon detecting this event, at block <NUM> the control circuit <NUM> responsively generates new radiation dosing information in at least near real-time as a function of a corresponding influence matrix. (As used herein, the expression "near real-time" shall be understood to mean within two seconds. If desired, longer processing times can be accommodated. For example, the foregoing generation (and display) of the information may necessarily occur with, say, five seconds, ten seconds, twenty seconds, thirty seconds, one minute, and so forth as desired. ) By one approach, to generate the new radiation dosing information the control circuit <NUM> calculates the dose by assigning the modified weight(s) (which may all be the same modified weight or different weights as desired) to the spots and multiplying the influence matrix with a vector of these spot weights. Calculating the dose this way is much faster than, for example, via simulating the dose deposition. These teachings will also facilitate determining how much each spot contributes to each voxel much faster than one would ordinarily find when using prior art approaches.

The so-generated new radiation dosing information can comprise, for example, a calculated total radiation dose, a calculated dose rate, or both as desired. Referring to <FIG>, the resultant calculated information can be presented graphically and/or alphanumerically by any means known in the art, such as but not limited to via the user interface <NUM>. If desired, the speed of presentation of such information can be at least partially facilitated by use of a graphics processing unit. In another approach, in lieu of the foregoing or in combination therewith, the dose space can be parsed into distinct regions and only the presentation of the affected regions need be updated to reflect the modified dosing.

This use of the influence matrix makes it both simple and intuitive to modify spot weights to thereby change dose distribution while also accommodating a very fast calculation of and presentation of the corresponding results to the user.

Claim 1:
A method comprising:
by a control circuit (<NUM>):
optimizing (<NUM>) a radiation treatment plan for a particular patient and providing corresponding resultant radiation dosing information;
detecting (<NUM>) at least one manual edit to at least one spot weight of the radiation treatment plan;
in response to detecting the at least one manual edit, generating new radiation dosing information;
characterized in that:
optimizing (<NUM>) the radiation treatment plan for the particular patient includes calculating an influence matrix (<NUM>) that specifies how each spot (<NUM>) affects the dose; and
the generating (<NUM>) of the new radiation dosing information is performed in at least near real-time as a function of the influence matrix (<NUM>) and comprises multiplying the influence matrix (<NUM>) by the at least one spot weight to allow a user to see the results of their changes to the at least one spot weight in at least near real-time.