CN104117151A - Optimization method of online self-adaption radiotherapy plan - Google Patents
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- 238000005457 optimization Methods 0.000 title claims abstract description 22
- 238000004422 calculation algorithm Methods 0.000 claims abstract description 71
- 238000011282 treatment Methods 0.000 claims abstract description 37
- 210000000056 organ Anatomy 0.000 claims abstract description 18
- 238000011404 fractionated radiotherapy Methods 0.000 claims description 26
- 210000003484 anatomy Anatomy 0.000 claims description 14
- 230000003068 static effect Effects 0.000 claims description 13
- 230000003044 adaptive effect Effects 0.000 claims description 12
- 238000000275 quality assurance Methods 0.000 claims description 8
- 230000005540 biological transmission Effects 0.000 claims description 6
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- 230000004048 modification Effects 0.000 claims description 4
- 238000012986 modification Methods 0.000 claims description 4
- 230000005855 radiation Effects 0.000 claims description 4
- 238000004364 calculation method Methods 0.000 claims description 3
- 230000009191 jumping Effects 0.000 claims description 3
- 238000002560 therapeutic procedure Methods 0.000 abstract description 7
- 230000004075 alteration Effects 0.000 abstract 1
- 206010028980 Neoplasm Diseases 0.000 description 5
- 238000002721 intensity-modulated radiation therapy Methods 0.000 description 4
- 230000006978 adaptation Effects 0.000 description 3
- 238000002591 computed tomography Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 230000002093 peripheral effect Effects 0.000 description 2
- 238000002600 positron emission tomography Methods 0.000 description 2
- 238000002604 ultrasonography Methods 0.000 description 2
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- 238000012790 confirmation Methods 0.000 description 1
- 230000007423 decrease Effects 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
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Abstract
The invention discloses an optimization method of an online self-adaption radiotherapy plan. The method comprises the steps of performing rigid registration and deformation registration on an image in a primary plan after a fractional guide image is input, so as to generate a target section and a fractional sketch outline which dangers organs; recalculating a dosage distribution and dosage volume histogram according to the parameters, fractional guide image and the fractional sketch outline in an original plan; judging whether the radiotherapy plan needs to be altered by combining the restriction of an original formula; combining a clinical requirement to perform rapid online alteration of the patient radiotherapy plan if needed, so as to generate the fractional guide image and perform an automatic radiotherapy plan quality guarantee. According to the optimization method provided by the invention, the optimization of the radiotherapy plan can be quickly finished at short time before every fractional therapy by comprehensively considering the change of a therapy in a patient treating process, based on a deformation rectification and dosage computational algorithm accelerated by a CPU (Central Processing Unit). Compared with an off-line self-adaption radiotherapy method based on a commercial treatment planning system, the optimization method is high in efficiency and meets clinical demands.
Description
Technical field
The present invention relates to the optimization method for the treatment of plan, be specifically related to a kind of optimization method of radiotherapy planning.
Background technology
Current tumour radiotherapy process is generally before treatment starts, and the location CT based on patient generates radiotherapy planning, then in therapeutic process subsequently, keeps radiotherapy planning constant, and patient is carried out to some interval procedures.Such treatment pattern does not consider that the anatomical structure of patient in therapeutic process changes, such as the variation of gross tumor volume and position, the variation of patient body profile, the variation of the full state of gastrointestinal and the surrounding causing jeopardize the variation of organ site etc., cause the dosage of the actual acceptance of patient to depart from doctor's prescribed dose, and then cause the decline of tumor control rate and the increase of normal structure complication probability.
When differences in patient is when great changes will take place, traditional self adaptation Therapeutic Method is usually used to revise radiocurable plan.Tradition self adaptation radiotherapy scans patient's location CT before by certain gradation in therapeutic process, then again delineate target area and the profile that jeopardizes organ by doctor, then pass through business treatment planning systems (Treatment Planning System by physics teacher or radiation supervisor, TPS) redesign and optimize treatment plan, and by the physics Shi Jinhang treatment plan quality assurance, the treatment of gradation after last treatment plan just can be used to.But the process that generates new treatment plan is the same with the original radiotherapy planning of design, the time is long, has incured loss through delay the treatment time of new plan, and need to drop into a lot of man power and materials, so also seldom adopted by hospital.
Therefore, make a general survey of the existing radiotherapy pattern in current home and abroad, radiotherapy based on traditional is not considered the variation of anatomical structure in patient process, therefore can not realize the therapeutic goal of expection, if do off-line adaptive radiation therapy based on business treatment planning systems, efficiency is low, takes time and effort, and is therefore difficult to be widely used clinically.
Summary of the invention
Goal of the invention: in order to overcome the deficiencies in the prior art, the invention provides a kind of online adaptive radiotherapy planning optimization method, make it possible to complete fast the optimization of whole treatment plan before each interval procedure starts, met well clinical needs.
Technical scheme: for solving the problems of the technologies described above, online adaptive radiotherapy planning optimization method provided by the invention, comprises the following steps:
1) import gradation navigational figure;
2) image rigid registration in gradation navigational figure and original radiotherapy planning;
3) the image deformation registration in gradation navigational figure and original radiotherapy planning;
4) generate and adjust target area and sketch outline (when inferior gradation sketches outline) with this gradation that jeopardizes organ, make its anatomical structure with gradation navigational figure consistent;
5) according to the image in gradation navigational figure and original radiotherapy planning, judge whether the variation of patient's anatomical structure exceedes change threshold, in this way, enter step 6); As no, preserve original radiotherapy planning as this fractionated radiotherapy plan (when inferior fractionated radiotherapy plan), finish;
6), according to the parameter in original radiotherapy planning, sketch outline and recalculate dose distribution (Dose Distribution) and dose volume histogram (Dose Volume Histogram, DVH) based on gradation navigational figure and this gradation;
7) determining step 6) whether the dose distribution that obtains and dose volume histogram meet original prescription constraint, as no, enters step 8); In this way, use original radiotherapy planning as this fractionated radiotherapy plan, finish;
8) this gradation generating based on step 4) sketches outline, and in conjunction with clinical requirement, carries out the quick online modification of patient's radiotherapy planning, generate this fractionated radiotherapy plan (when inferior fractionated radiotherapy plan), and carry out the automatic releasing treatment plan quality assurance (Quality Assurance, QA), finish.
Preferably, in described step 1), described gradation navigational figure comprises CT(Computed Tomography), Cone-Beam CT (Cone-Beam CT), ultrasonic (Ultrasound), PET(Positron Emission Tomography) or the image such as magnetic resonance (Magnetic Resonance, MR) at least one; In described step 3), calculate fast deformation vector field by deformable registration algorithm, and calculate the stressing conditions of each volume elements based on FEM (finite element) model, analyze the error of deformation vector field, the degree of accuracy of the image deformation registration in automatic check gradation navigational figure and original radiotherapy planning;
In described step 4), comprise the steps:
4.1) integrating step 1) the deformation vector field that obtains of the gradation navigational figure that obtains and step 3), based on target area in original scheme with jeopardize sketching outline of organ, generate initial gradation and sketch outline;
4.2) initial gradation is sketched outline with original scheme on sketch outline and contrast, modify in conjunction with clinical requirement, make its anatomical structure with gradation navigational figure consistent, thereby this gradation that generates target area and jeopardize organ sketches outline;
In described step 6), that the gradation navigational figure that the parameter of original radiotherapy planning, step 1) are obtained, this gradation that step 4) obtains sketch outline, recalculate dose distribution by fast dose computational algorithm, and then calculate dose volume histogram DVH;
In described step 8), comprise the steps:
8.1) in the time that original radiotherapy planning is static intensity modulating radiotherapy treatment planning (Static IMRT), this gradation obtaining based on step 4) sketches outline, use fast projection algorithm to obtain beam direction view (Beam Eye View along frame angle, BEV), revise and confirm multi-blade collimator (Multi-Leaf Collimator, the MLC) shape of the each Ziye of static intensity modulating radiotherapy treatment planning (Segment) according to beam direction view; In the time that original radiotherapy planning is the strong radiotherapy treatment planning of adjustment with volume (VMAT), this gradation obtaining based on step 4) sketches outline, use fast projection algorithm to obtain beam direction view along each control point, in conjunction with the blade maximum movement speed of multi-blade collimator, revise and confirm the multi-blade collimator shape of the each Ziye of the strong radiotherapy treatment planning of adjustment with volume according to beam direction view;
8.2) taking original radiotherapy planning dose volume histogram as reference, automatically adjust this gradation sketch outline in the weight of each organ, in conjunction with the impact of multi-blade collimator transmission photon and tongue and groove transmission photon, adopt fast dose computational algorithm to calculate the dose distribution of amended each Ziye;
8.3), in the time that original radiotherapy planning is static intensity modulating radiotherapy treatment planning (Static IMRT), adopt rapid optimizing algorithm to optimize the weight of each Ziye, i.e. the jumping figure of each Ziye (MU), the dose distribution of this fractionated radiotherapy plan after acquisition is optimized; In the time that original radiotherapy planning is the strong radiotherapy treatment planning of adjustment with volume (VMAT), adopt rapid optimizing algorithm to optimize the weight of each Ziye, obtain multi-blade collimator blade movement speed and accelerator close rate at interior radiotherapy accelerator machine radiation parameters, obtain the dose distribution of this fractionated radiotherapy plan after optimizing;
8.4), in conjunction with clinical requirement, generate this fractionated radiotherapy plan, when inferior fractionated radiotherapy plan;
8.5) adopt and be different from step 8.2) another kind of fast dose computational algorithm again carry out Rapid Dose Calculation, and with step 8.3) dose distribution that obtains carries out three-dimensional gamma index value and calculates assessment, judge whether gamma percent of pass is less than default gamma percent of pass threshold value, enter in this way step 8.1) recalculate, as otherwise finish.
Preferably, the change threshold in described step 5) is 30%.Can certainly be to set as required, as be 10%, 15%, 20% or 25%.
Preferably, the deformable registration algorithm in described step 3), described step 6), step 8.2) with step 8.5) in fast dose computational algorithm, described step 8.1) and step 8.3) in rapid optimizing algorithm, described step 8.5) in three-dimensional gamma index value calculate assessment by based on GPU, CPU or the realization of distributed cloud computing platform.
Preferably, the deformable registration algorithm of described step 3) is Demons algorithm or B-Spline algorithm; Described step 6), step 8.2) with step 8.5) in fast dose computational algorithm be convolution superposition algorithm or Monte carlo algorithm; Described step 8.1) in fast projection algorithm be Ray-Tracing algorithm; Described step 8.3) in rapid optimizing algorithm be Conjugate Gradient Barzilai-Borwein algorithm;
Preferably, described step 8.5) in default gamma percent of pass threshold value be 95%.Can certainly be to set as required, as be 96%, 97%, 98% or 99%.
Beneficial effect: the invention provides a kind of online adaptive radiotherapy planning optimization method, its by import after gradation navigational figure with original radiotherapy planning in image carry out Rigid Registration and deformable registration, generate target area and jeopardize organ when time gradation sketch outline, in the time that the variation of patient's anatomical structure exceedes change threshold, according to the parameter in original radiotherapy planning, gradation navigational figure and gradation that ought be inferior sketch outline recalculates dose distribution and dose volume histogram, in conjunction with original prescription constraint judge whether need to revise radiotherapy planning thereafter, in the time that dose distribution and dose volume histogram do not meet original prescription constraint, sketch outline the quick online modification that carries out patient's radiotherapy planning with clinical requirement in conjunction with this gradation, final generation when inferior fractionated radiotherapy plan, and carry out the automatic releasing treatment plan quality assurance.
This method invention is by the deformable registration and the Dose calculation algorithm that accelerate based on GPU, consider the variation of anatomical structure in patient process, and whole radiotherapy planning optimizing process can be completed within a few minutes after patient lies down on one's sick bed, can before starting, each interval procedure complete fast the optimization of whole radiotherapy planning.Than the off-line self adaptation radiotheraping method based on business treatment planning systems, efficiency of the present invention is high, saves time and human cost, has well met clinical needs, can be applicable clinically, has significant social meaning.
Brief description of the drawings
Fig. 1 is the flow chart of this method invention;
Fig. 2 is the flow chart of step 8) in this method invention.
Detailed description of the invention
Below in conjunction with embodiment, the present invention is described in further detail, and this implementation column does not form restriction to the present invention.
Original radiotherapy planning is, before certain course for the treatment of, certain interval procedure was carried out first or before, based on the image information of patient tumors and peripheral organs tissue thereof, to delineate the radiotherapy planning of confirmation through target area.Original prescription is constrained to a part for original radiotherapy planning.
First or before in certain interval procedure therapeutic process after carrying out, also will carry out interval procedure to patient, before such interval procedure (this interval procedure) is carried out, the present invention considers the variation of anatomical structure in patient process, original radiotherapy planning is optimized to generate this fractionated radiotherapy plan, the online adaptive radiotherapy planning optimization method that the present embodiment provides, as shown in Figure 1, it comprises the following steps:
1) import gradation navigational figure: described gradation navigational figure for this reason interval procedure carry out before the image information of patient tumors and peripheral organs tissue thereof, comprise CT(Computed Tomography), Cone-Beam CT (Cone-Beam CT), ultrasonic (Ultrasound, US), PET(Positron Emission Tomography) or the image such as magnetic resonance (Magnetic Resonance, MR) at least one;
2) image rigid registration in gradation navigational figure and original radiotherapy planning;
3) the image deformation registration in gradation navigational figure and original radiotherapy planning: calculate fast deformation vector field (Deformation Vector Field, DVF) by deformable registration algorithm, described deformable registration algorithm is Demons algorithm or B-Spline algorithm; And calculate the stressing conditions of each volume elements based on FEM (finite element) model (Finite Element Modeling, FEM), analyze the error of deformation vector field, the degree of accuracy of the image deformation registration in automatic check gradation navigational figure and original radiotherapy planning;
4) generate and adjust target area and sketch outline (when inferior gradation sketches outline) with this gradation that jeopardizes organ, make its anatomical structure with gradation navigational figure consistent, comprising:
4.1) integrating step 1) the deformation vector field that obtains of the gradation navigational figure that obtains and step 3), based on target area in original scheme with jeopardize sketching outline of organ, generate initial gradation and sketch outline;
4.2) initial gradation is sketched outline with original scheme on sketch outline and contrast, modify in conjunction with clinical requirement, make its anatomical structure with gradation navigational figure consistent, thereby this gradation that generates target area and jeopardize organ sketches outline;
5) according to the image in gradation navigational figure and original radiotherapy planning, judge whether the variation of patient's anatomical structure exceedes change threshold, in this way, enter step 6); As no, preserve original radiotherapy planning as this fractionated radiotherapy plan (when inferior fractionated radiotherapy plan), finish; Change threshold in step 5) is 30%.Can certainly be to set as required, as be 10%, 15%, 20% or 25%.
6) according to the parameter in original radiotherapy planning, sketch outline and recalculate dose distribution and dose volume histogram DVH based on gradation navigational figure and this gradation: the gradation navigational figure that the parameter of original radiotherapy planning, step 1) are obtained, this gradation that step 4) obtains sketch outline, recalculate dose distribution by fast dose computational algorithm, and then calculate dose volume histogram DVH; The fast dose computational algorithm that this place adopts is convolution superposition algorithm or Monte carlo algorithm;
7) judge whether to revise radiotherapy planning i.e. determining step 6 in conjunction with the constraint of original prescription) whether the dose distribution and the dose volume histogram that obtain meet original prescription constraint, as no, enters step 8); In this way, use original radiotherapy planning as this fractionated radiotherapy plan, finish;
8) this gradation generating based on step 4) sketches outline, in conjunction with clinical requirement, carry out the quick online modification of patient's radiotherapy planning, generate this fractionated radiotherapy plan (when inferior fractionated radiotherapy plan), and carry out automatic releasing treatment plan quality assurance (Quality Assurance, QA), as shown in Figure 2, step 8) comprises the steps:
8.1) in the time that original radiotherapy planning is static intensity modulating radiotherapy treatment planning (Static IMRT), this gradation obtaining based on step 4) sketches outline, use fast projection algorithm to obtain beam direction view (Beam Eye View along frame angle, BEV), revise and confirm multi-blade collimator (Multi-Leaf Collimator, the MLC) shape of the each Ziye of static intensity modulating radiotherapy treatment planning (Segment) according to beam direction view; In the time that original radiotherapy planning is the strong radiotherapy treatment planning of adjustment with volume (VMAT), this gradation obtaining based on step 4) sketches outline, along each control point, (Control Point) uses fast projection algorithm to obtain beam direction view, in conjunction with the blade maximum movement speed of multi-blade collimator, revise and confirm the multi-blade collimator shape of the each Ziye of the strong radiotherapy treatment planning of adjustment with volume according to beam direction view;
8.2) taking original radiotherapy planning dose volume histogram as reference, automatically adjust this gradation sketch outline in the weight of each organ, in conjunction with the impact of multi-blade collimator transmission photon and tongue and groove transmission photon, adopt fast dose computational algorithm to calculate the dose distribution of amended each Ziye;
8.3) in the time that original radiotherapy planning is static intensity modulating radiotherapy treatment planning (Static IMRT), adopt the weight of the each Ziye of Conjugate Gradient Barzilai-Borwein algorithm optimization, be the jumping figure (MU) of each Ziye, obtain the dose distribution of this fractionated radiotherapy plan after optimizing; In the time that original radiotherapy planning is the strong radiotherapy treatment planning of adjustment with volume (VMAT), also use the weight of the each Ziye of Conjugate Gradient Barzilai-Borwein algorithm optimization, obtain multi-blade collimator blade movement speed and accelerator close rate at interior radiotherapy accelerator machine radiation parameters, obtain the dose distribution of this fractionated radiotherapy plan after optimizing;
8.4), in conjunction with clinical requirement, generate this fractionated radiotherapy plan, when inferior fractionated radiotherapy plan;
8.5) carry out the automatic radiotherapy planning quality assurance, adopt and be different from step 8.2) another kind of fast dose computational algorithm again carry out Rapid Dose Calculation, and with step 8.3) dose distribution that obtains carries out three-dimensional gamma index value and calculates assessment, judge whether gamma percent of pass is less than default gamma percent of pass threshold value, enter in this way step 8.1) recalculate, as otherwise finish.Step 8.5) in default gamma percent of pass threshold value be 95%.Can certainly be to set as required, as be 96%, 97%, 98% or 99%.
Step 8.2 in the present embodiment) in fast dose computational algorithm be convolution superposition algorithm, step 8.5) in fast dose computational algorithm be Monte carlo algorithm; Can certainly be set as required: step 8.2) in fast dose computational algorithm be Monte carlo algorithm, step 8.5) in fast dose computational algorithm be convolution superposition algorithm.
Deformable registration algorithm in the present embodiment in step 3), step 6), step 8.2) with step 8.5) in fast dose computational algorithm, step 8.1) and step 8.3) in rapid optimizing algorithm, step 8.5) in three-dimensional gamma index value calculate assessment by based on GPU, CPU or the realization of distributed cloud computing platform.
Claims (6)
1. an online adaptive radiotherapy planning optimization method, is characterized in that comprising the following steps:
1) import gradation navigational figure;
2) image rigid registration in gradation navigational figure and original radiotherapy planning;
3) the image deformation registration in gradation navigational figure and original radiotherapy planning;
4) generate and adjust target area and sketch outline with this gradation that jeopardizes organ, make its anatomical structure with gradation navigational figure consistent;
5) according to the image in gradation navigational figure and original radiotherapy planning, judge whether the variation of patient's anatomical structure exceedes change threshold, in this way, enter step 6); As no, preserve original radiotherapy planning as this fractionated radiotherapy plan, finish;
6), according to the parameter in original radiotherapy planning, sketch outline and recalculate dose distribution and dose volume histogram based on gradation navigational figure and this gradation;
7) determining step 6) whether the dose distribution that obtains and dose volume histogram meet original prescription constraint, as no, enters step 8); In this way, use original radiotherapy planning as this fractionated radiotherapy plan, finish;
8) this gradation generating based on step 4) sketches outline, and in conjunction with clinical requirement, carries out the quick online modification of patient's radiotherapy planning, generates this fractionated radiotherapy plan and carries out the automatic releasing treatment plan quality assurance, finishes.
2. online adaptive radiotherapy planning optimization method according to claim 1, is characterized in that:
In described step 1), described gradation navigational figure comprises at least one in CT, Cone-Beam CT, ultrasonic, PET or magnetic resonance;
In described step 3), calculate fast deformation vector field by deformable registration algorithm, and calculate the stressing conditions of each volume elements based on FEM (finite element) model, analyze the error of deformation vector field, the degree of accuracy of the image deformation registration in automatic check gradation navigational figure and original radiotherapy planning;
In described step 4), comprise the steps:
4.1) integrating step 1) the deformation vector field that obtains of the gradation navigational figure that obtains and step 3), based on target area in original scheme with jeopardize sketching outline of organ, generate initial gradation and sketch outline;
4.2) initial gradation is sketched outline with original scheme on sketch outline and contrast, modify in conjunction with clinical requirement, make its anatomical structure with gradation navigational figure consistent, thereby this gradation that generates target area and jeopardize organ sketches outline;
In described step 6), be that the gradation navigational figure that the parameter of original radiotherapy planning, step 1) are obtained, this gradation that step 4) obtains sketch outline, recalculate dose distribution by fast dose computational algorithm, and then calculate dose volume histogram;
In described step 8), comprise the steps:
8.1) in the time that original radiotherapy planning is static intensity modulating radiotherapy treatment planning, this gradation obtaining based on step 4) sketches outline, use fast projection algorithm to obtain beam direction view along frame angle, revise and confirm the multi-blade collimator shape of the each Ziye of static intensity modulating radiotherapy treatment planning according to beam direction view; In the time that original radiotherapy planning is the strong radiotherapy treatment planning of adjustment with volume, this gradation obtaining based on step 4) sketches outline, use fast projection algorithm to obtain beam direction view along each control point, in conjunction with the blade maximum movement speed of multi-blade collimator, revise and confirm the multi-blade collimator shape of the each Ziye of the strong radiotherapy treatment planning of adjustment with volume according to beam direction view;
8.2) taking original radiotherapy planning dose volume histogram as reference, automatically adjust this gradation sketch outline in the weight of each organ, in conjunction with the impact of multi-blade collimator transmission photon and tongue and groove transmission photon, adopt fast dose computational algorithm to calculate the dose distribution of amended each Ziye;
8.3), in the time that original radiotherapy planning is static intensity modulating radiotherapy treatment planning, adopt rapid optimizing algorithm to optimize the weight of each Ziye, i.e. the jumping figure of each Ziye, the dose distribution of this fractionated radiotherapy plan after acquisition is optimized; In the time that original radiotherapy planning is the strong radiotherapy treatment planning of adjustment with volume, adopt rapid optimizing algorithm to optimize the weight of each Ziye, obtain multi-blade collimator blade movement speed and accelerator close rate at interior radiotherapy accelerator machine radiation parameters, obtain the dose distribution of this fractionated radiotherapy plan after optimizing;
8.4), in conjunction with clinical requirement, generate this fractionated radiotherapy plan;
8.5) adopt and be different from step 8.2) another kind of fast dose computational algorithm again carry out Rapid Dose Calculation, and with step 8.3) dose distribution that obtains carries out three-dimensional gamma index value and calculates assessment, judge whether gamma percent of pass is less than default gamma percent of pass threshold value, enter in this way step 8.1) recalculate, as otherwise finish.
3. online adaptive radiotherapy planning optimization method according to claim 1, is characterized in that: the change threshold in described step 5) is 10% or 15% or 20% or 25% or 30%.
4. online adaptive radiotherapy planning optimization method according to claim 2, is characterized in that: the deformable registration algorithm in described step 3), described step 6), step 8.2) with step 8.5) in fast dose computational algorithm, described step 8.1) fast projection algorithm and step 8.3) and in rapid optimizing algorithm, described step 8.5) in three-dimensional gamma index value computational algorithm by realizing based on GPU, CPU or distributed cloud computing platform.
5. online adaptive radiotherapy planning optimization method according to claim 2, is characterized in that: the deformable registration algorithm of described step 3) is Demons algorithm or B-Spline algorithm; Described step 6), step 8.2) with step 8.5) in fast dose computational algorithm be convolution superposition algorithm or Monte carlo algorithm; Described step 8.1) in fast projection algorithm be Ray-Tracing algorithm; Described step 8.3) in rapid optimizing algorithm be Conjugate Gradient Barzilai-Borwein algorithm.
6. online adaptive radiotherapy planning optimization method according to claim 2, is characterized in that: described step 8.5) in default gamma percent of pass threshold value be 95% or 96% or 97% or 98% or 99%.
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