CN104984481A - Method and system for carrying out on-line compensation on tumor motion generated by breathing - Google Patents

Abstract

The invention provides a method and a system for carrying out on-line compensation on tumor motion generated by breathing. The method comprises the steps of: obtaining real-time motion information of a tumor through a plurality of position sensors, wherein the plurality of position sensors are arranged inside the tumor; decomposing the real-time motion of the tumor into baseline drift motion and breathing fluctuating motion according to the real-time motion information; carrying out position prediction on the baseline drift motion and the breathing fluctuating motion after a preset time period so as to obtain baseline prediction data and fluctuating prediction data; and carrying out compensation respectively on the baseline drift motion and the breathing fluctuating motion according to the baseline prediction data and the fluctuating prediction data. By adopting the method provided by the invention, real-time on-line compensation can be carried out on the tumor motion generated by breathing, and precise and highly-efficient radiation treatment is further realized.

Description

The tumor motion breathing generation is carried out to the method and system of online compensation

Technical field

The present invention relates to technical field of medical equipment, particularly a kind of tumor motion to breathing generation carries out the method and system of online compensation.

Background technology

Radiotherapy treats one of Main Means of tumor as current, and the precision that its ray is delivered directly has influence on the safety of therapeutic effect and patient.In radiation therapy process, due to the breathing of patient, tumor (especially the tumor in thoracic cavity and abdominal cavity) can produce motion by a relatively large margin, greatly reduces radiocurable precision.

Such as, respiratory movement causes lung tumors motion can reach 14mm, 3mm and 12mm in the abdomen back of the body, side and head foot direction; The motion amplitude of liver's tumor in three directions is caused to reach 12mm, 9mm and 26mm.

In radiotherapy, reply breathing causes the means of tumor motion to mainly contain at present:

1. expand target area mode: according to the range of movement of tumor, the target area of irradiation is expanded to the border of tumor motion, to ensure that ray can be irradiated to tumor in whole respiratory.But this mode makes roentgenization scope strengthen, can damage the healthy organ of surrounding, and all actual positions of tumor in Patients During Radiotherapy cannot be obtained when Target delineations.

2. respiration gate control mode: make the shot cycle of beam synchronous with the breathing cycle by monitoring respiratory movement, only opens beam and carries out radiotherapy, thus reduce tumor displacement in the radiotherapy period in a certain specific phase of breathing.But this gating technology owing to only opening ray in limited breathing phases, thus greatly reduce emission efficiency.

3. dark air-breathing breath-holding techniques: determine the state residing for breathing by monitoring total lung capacity, the stage of holding one's breath after patient deeply breathes carries out radiotherapy.The same with gate mode, dark air-breathing breath-holding techniques only opens ray at limited breathing phases, and reduce the efficiency of radiotherapy, meanwhile, when patient per holds one's breath, the position of tumor also can change, and has the people of about 50% can not adopt dark air-breathing breath-holding techniques.

4. utilize mechanical arm to realize breathing compensation in real time: gamma knife is achieved and detected in real time by body surface and body internal labeling thing simultaneously, and compensates the tumor motion breathed and produce with robot movement.But the mode of this real-Time Compensation is only applicable to the frame for movement of mechanical arm with accelerator, and general radiotherapy apparatus cannot use.

In addition, due to the restriction of multi-leaf optical grating dynamic property (speed, acceleration), multi-leaf optical grating cannot the motion of real-time tracking tumor, does not therefore up to the present also have to utilize multi-leaf optical grating to the method for breathing the tumor motion caused and carry out real-time online compensation.

Summary of the invention

The present invention is intended to solve one of technical problem in above-mentioned correlation technique at least to a certain extent.

For this reason, one object of the present invention is to propose a kind ofly to carry out the method for online compensation to breathing the tumor motion produced, and the method can carry out real-time online compensation to breathing the tumor motion produced, so realize accurately, radiotherapy efficiently.

Another object of the present invention is to provide a kind of tumor motion to breathing generation to carry out the system of online compensation.

To achieve these goals, the embodiment of first aspect present invention proposes a kind of method that tumor motion to breathing generation carries out online compensation, comprise the following steps: the real time kinematics information being obtained tumor by multiple position sensor, wherein said multiple position sensor is arranged on inside tumor; According to described real time kinematics information, the real time kinematics of described tumor is decomposed into baseline drift campaign and breathing undulatory motion; Respectively the position prediction after the scheduled time is carried out to described baseline drift campaign and described breathing undulatory motion, to obtain baseline prediction data and fluctuating prediction data; And respectively described baseline drift campaign and breathing undulatory motion are compensated according to described baseline prediction data and described fluctuating prediction data.

According to the method for the tumor motion breathing generation being carried out to online compensation of the embodiment of the present invention, first the multiple position sensors by being arranged on inside tumor obtain the real time kinematics information of tumor, and accordingly the real time kinematics of tumor be decomposed into baseline drift campaign and breathe undulatory motion, and respectively the position prediction after the ticket reserving time is carried out to baseline drift campaign and breathing undulatory motion, last basis predicts the outcome and compensates baseline drift campaign and breathing undulatory motion respectively.Therefore, the method can to breathe produce tumor motion carry out real-time online compensation, and then can realize accurately, radiotherapy efficiently.

In addition, the method that the tumor motion to breathing generation according to the above embodiment of the present invention carries out online compensation can also have following additional technical characteristic:

In some instances, described according to described baseline prediction data and fluctuating prediction data respectively to described baseline drift campaign with breathe undulatory motion and compensate, comprising further: described baseline prediction data is sent to therapeutic bed controller, moving by controlling therapeutic bed the compensation carrying out baseline drift campaign; Described fluctuating prediction data is sent to multi-leaf optical grating controller, and compensate described breathing undulatory motion to control multi-leaf optical grating, wherein said multi-leaf optical grating controller is driven by linear electric motors.

In some instances, wherein, by the Kalman filter of constant acceleration model, position prediction is carried out to described baseline drift campaign.

In some instances, wherein, by Finite State Model, position prediction is carried out to described breathing undulatory motion, described breathing undulatory motion comprises linear condition, nonlinear state and irregular status, wherein described breathing undulatory motion is carried out to the position prediction of Preset Time, comprise further: judge the state that described breathing undulatory motion is current; The position prediction of described breathing undulatory motion is carried out according to described current state.

In some instances, wherein, judge that the formula of the state that described breathing undulatory motion is current is:

For linear condition and nonlinear state/irregular status:

$d_{\mathrm{\ρ}}\left(t_k\right)=\frac{{\mathrm{\ρ}}_{\mathrm{xy}}\left(t_k\right)-{\mathrm{\ρ}}_{\mathrm{xy}}\left(t_{k-1}\right)}{\mathrm{dt}},$

Wherein, d _ρ(t _k) be t _kthe linearly dependent coefficient variable gradient in moment, ρ _xy(t _k), ρ _xy(t _k-1) be respectively t _kmoment and t _k-1the linearly dependent coefficient in moment, dt is t _kmoment and t _k-1moment time difference; For irregular status and nonlinear state:

$\mathrm{PE}\left(t_k\right)=\frac{{\∫}_0^{f_t}{S}_{t_k}\left(f\right)\mathrm{df}}{{\∫}_0^{+\∞}{S}_{t_k}\left(f\right)\mathrm{df}},$

Wherein, PE (t _k) be t _kmoment gets breath data medium and low frequency energy accounting, parameter T is for arriving t _kmoment is the time span that section nonlinear state is lasting here, and X (f) is then the Fourier transformation result of signal in this section of time span.

Embodiment still provides of second aspect present invention a kind ofly carries out the system of online compensation to breathing the tumor motion produced, and comprising: multiple position sensor, described multiple position sensor is arranged on inside tumor, for obtaining the real time kinematics information of described tumor; Real-time controller, described real-time controller is used for, according to described real time kinematics information, the real time kinematics of described tumor is decomposed into baseline drift campaign and breathing undulatory motion; Position prediction module, described position prediction module carries out the position prediction after the scheduled time to described baseline drift campaign and described breathing undulatory motion respectively, to obtain baseline prediction data and fluctuating prediction data; And compensating controller, described compensating controller is used for compensating described baseline drift campaign and breathing undulatory motion respectively according to described baseline prediction data and described fluctuating prediction data.

According to the system of the tumor motion breathing generation being carried out to online compensation of the embodiment of the present invention, first the multiple position sensors by being arranged on inside tumor obtain the real time kinematics information of tumor, and accordingly the real time kinematics of tumor be decomposed into baseline drift campaign and breathe undulatory motion, and respectively the position prediction after the ticket reserving time is carried out to baseline drift campaign and breathing undulatory motion, last basis predicts the outcome and compensates baseline drift campaign and breathing undulatory motion respectively.Therefore, this system can carry out real-time online compensation to breathing the tumor motion produced, so can realize accurately, radiotherapy efficiently, and this system structure is simple, easy to operate.

In addition, the system that the tumor motion to breathing generation according to the above embodiment of the present invention carries out online compensation can also have following additional technical characteristic:

In some instances, described compensating controller comprises therapeutic bed controller and multi-leaf optical grating controller, and described therapeutic bed controller is used for controlling therapeutic bed according to baseline prediction data and moves the compensation carrying out baseline drift campaign; Described multi-leaf optical grating controller is for receiving described fluctuating prediction data, and compensate described breathing undulatory motion to control multi-leaf optical grating, wherein said multi-leaf optical grating controller is driven by linear electric motors.

In some instances, wherein, described position prediction module carries out position prediction by the Kalman filter of constant acceleration model to described baseline drift campaign.

In some instances, wherein, described position prediction module carries out position prediction by Finite State Model to described breathing undulatory motion, described breathing undulatory motion comprises linear condition, nonlinear state and irregular status, wherein, described position prediction module also for judging the state that described breathing undulatory motion is current, and carries out the position prediction of described breathing undulatory motion according to described current state.

In some instances, wherein, judge that the formula of the state that described breathing undulatory motion is current is:

For linear condition and nonlinear state/irregular status:

$d_{\mathrm{\ρ}}\left(t_k\right)=\frac{{\mathrm{\ρ}}_{\mathrm{xy}}\left(t_k\right)-{\mathrm{\ρ}}_{\mathrm{xy}}\left(t_{k-1}\right)}{\mathrm{dt}},$

Wherein, d _ρ(t _k) be t _kthe linearly dependent coefficient variable gradient in moment, ρ _xy(t _k), ρ _xy(t _k-1) be respectively t _kmoment and t _k-1the linearly dependent coefficient in moment, dt is t _kmoment and t _k-1moment time difference;

For irregular status and nonlinear state:

$\mathrm{PE}\left(t_k\right)=\frac{{\∫}_0^{f_t}{S}_{t_k}\left(f\right)\mathrm{df}}{{\∫}_0^{+\∞}{S}_{t_k}\left(f\right)\mathrm{df}},$

Wherein, PE (t _k) be t _kmoment gets breath data medium and low frequency energy accounting, parameter T is for arriving t _kmoment is the time span that section nonlinear state is lasting here, and X (f) is then the Fourier transformation result of signal in this section of time span.

Additional aspect of the present invention and advantage will part provide in the following description, and part will become obvious from the following description, or be recognized by practice of the present invention.

Accompanying drawing explanation

Above-mentioned and/or additional aspect of the present invention and advantage will become obvious and easy understand from accompanying drawing below combining to the description of embodiment, wherein:

Fig. 1 is the flow chart according to an embodiment of the invention tumor motion breathing generation being carried out to the method for online compensation;

Fig. 2 is the schematic flow sheet in accordance with another embodiment of the present invention tumor motion breathing generation being carried out to the method for online compensation;

Fig. 3 is the layout schematic diagram of the multiple position sensors according to the present invention's specific embodiment;

Fig. 4 is the schematic diagram according to an embodiment of the invention tumor real time kinematics being decomposed into baseline drift campaign and breathing undulatory motion;

Fig. 5 is the schematic flow sheet of the position prediction breathing undulatory motion according to an embodiment of the invention;

Fig. 6 is the state demarcation schematic diagram breathing undulatory motion according to an embodiment of the invention; And

Fig. 7 is the structured flowchart according to an embodiment of the invention tumor motion breathing generation being carried out to the system of online compensation.

Detailed description of the invention

Be described below in detail embodiments of the invention, the example of described embodiment is shown in the drawings, and wherein same or similar label represents same or similar element or has element that is identical or similar functions from start to finish.Being exemplary below by the embodiment be described with reference to the drawings, only for explaining the present invention, and can not limitation of the present invention being interpreted as.

Below in conjunction with accompanying drawing, the method and system of the tumor motion breathing generation being carried out to online compensation according to the embodiment of the present invention are described.

Fig. 1 is the flow chart according to an embodiment of the invention tumor motion breathing generation being carried out to the method for online compensation.Fig. 2 is the schematic flow sheet that the tumor motion breathing generation in accordance with another embodiment of the present invention carries out the method for online compensation.Shown in composition graphs 1 and Fig. 2, the method comprises the following steps:

Step S101, obtained the real time kinematics information of tumor by multiple position sensor, wherein multiple position sensor is arranged on inside tumor.

In specific implementation process, before step S101, such as shown in Fig. 2, first user needs to select therapeutic modality (such as: conformal therapy mode, step and shoot, sliding window etc.), and from server, obtain the treatment plan of the patient that will treat, thus initial launched field shape can be calculated, i.e. the position of each blade of multi-leaf optical grating.

In concrete example, as shown in Figure 3, for three position sensors, the distributing position of multiple position sensor in tumor is described.As shown in Figure 3, namely be uniformly distributed around tumor center during the transducer arrangements of position as far as possible, and the triangle formed is as far as possible large, distribution as the sensor 1 in Fig. 3, sensor 2 and sensor 3 is illustrated, and then the real time kinematics of tumor in three translation directions and three rotation directions can be obtained by these 3 equally distributed position sensors, also can obtain the real time kinematics information of tumor on six-freedom degree, there is very high real-time.

Step S102, is decomposed into baseline drift campaign and breathing undulatory motion according to real time kinematics information by the real time kinematics of tumor.In other words, namely according to the real time kinematics information of the tumor obtained in step S101, and then the real time kinematics of tumor be decomposed into baseline drift campaign and breathe undulatory motion two parts, such as, shown in Fig. 4, this ensure that the precision of prediction.More specifically, the real time kinematics of tumor is decomposed into baseline drift campaign and breathes undulatory motion calculation procedure as follows:

First, the period tau of current breathing state is obtained ₀, and:

$F\left(\mathrm{\τ}\right)=\underset{t=t_0-\mathrm{Ndt}}{\overset{t_0}{\mathrm{\Σ}}}|P\left(t\right)-P(t-\mathrm{\τ})|,$

F(τ ₀)＝min F(τ)

Wherein, P (t) is the amplitude of tumor motion in respiratory, period tau ₀f (τ) is made to get minimum.

Then, the meansigma methods of getting 3 doubling times as the value calculating moment breathing average baselining, then breathes baseline expression formula is:

${\tilde{B}}_0=\underset{t=t_0-{3\mathrm{\τ}}_0}{\overset{t_0}{\mathrm{\Σ}}}\frac{P\left(t\right)}{{3\mathrm{\τ}}_0}.$

Finally, with original breath signal deduct level and smooth after the data obtained point of breathing baseline be to breathe and rise and fall.

Step S103, carries out the position prediction after the scheduled time, to obtain baseline prediction data and fluctuating prediction data to baseline drift campaign and breathing undulatory motion respectively.Wherein, in one embodiment of the invention, as shown in Figure 5, such as, by the Kalman filter of constant acceleration model, position prediction is carried out to described baseline drift campaign.By Finite State Model, position prediction is carried out to breathing undulatory motion, breathing undulatory motion is decomposed into linear condition, nonlinear state and irregular status three kinds, such as, shown in Fig. 6.Therefore, when carrying out the position prediction after Preset Time to breathing undulatory motion, first will judge to breathe the current residing state of undulatory motion, then current according to breathing undulatory motion state carries out the position prediction breathing undulatory motion.

More specifically, such as, the judgment basis breathing the various states of undulatory motion is as follows:

Basis for estimation between linear condition and nonlinear state/irregular status is the variable gradient of linearly dependent coefficient, is expressed as:

$d_{\mathrm{\ρ}}\left(t_k\right)=\frac{{\mathrm{\ρ}}_{\mathrm{xy}}\left(t_k\right)-{\mathrm{\ρ}}_{\mathrm{xy}}\left(t_{k-1}\right)}{\mathrm{dt}},$

Wherein, d _ρ(t _k) be t _kthe linearly dependent coefficient variable gradient in moment, ρ _xy(t _k), ρ _xy(t _k-1) be respectively t _kmoment and t _k-1the linearly dependent coefficient in moment, dt is t _kmoment and t _k-1moment time difference.

Basis for estimation between irregular status and nonlinear state is low frequency energy accounting, is expressed as:

$\mathrm{PE}\left(t_k\right)=\frac{{\∫}_0^{f_t}{S}_{t_k}\left(f\right)\mathrm{df}}{{\∫}_0^{+\∞}{S}_{t_k}\left(f\right)\mathrm{df}},$

Wherein, PE (t _k) be t _kmoment gets breath data medium and low frequency energy accounting, parameter T is for arriving t _kmoment is the time span that section nonlinear state is lasting here, and X (f) is then the Fourier transformation result of signal in this section of time span.

Step S104, compensates baseline drift campaign and breathing undulatory motion respectively according to baseline prediction data and fluctuating prediction data.Specifically, baseline prediction data is sent to therapeutic bed controller, slowly mobile with the compensation carrying out baseline drift campaign by controlling therapeutic bed; Fluctuating prediction data is sent to multi-leaf optical grating controller, to control multi-leaf optical grating, breathing undulatory motion is compensated, wherein multi-leaf optical grating controller is driven by linear electric motors, make multi-leaf optical grating speed and acceleration very large, therefore, when carrying out the compensation of breathing undulatory motion, real-time and the accuracy of tracking can be ensured.

Further, after step s 104, if treatment not yet completes, then repeated execution of steps S101 to step S104 is until treated.

To sum up, according to the method for the tumor motion breathing generation being carried out to online compensation of the embodiment of the present invention, first the multiple position sensors by being arranged on inside tumor obtain the real time kinematics information of tumor, and accordingly the real time kinematics of tumor be decomposed into baseline drift campaign and breathe undulatory motion, and respectively the position prediction after the ticket reserving time is carried out to baseline drift campaign and breathing undulatory motion, last basis predicts the outcome and compensates baseline drift campaign and breathing undulatory motion respectively.Therefore, the method can carry out real-time online compensation to breathing the tumor motion produced, and then can realize accurate, radiotherapy efficiently.

Further embodiment of the present invention additionally provides the system that a kind of tumor motion to breathing generation carries out online compensation.

Fig. 7 is the structured flowchart according to an embodiment of the invention tumor motion breathing generation being carried out to the system of online compensation.As shown in Figure 7, this system 100 comprises: multiple position sensor 110, real-time controller 120, position prediction module 130 and compensating controller 140.

Particularly, multiple position sensor 110 is arranged on inside tumor, for obtaining the real time kinematics information of tumor.

Real-time controller 120 is for being decomposed into baseline drift campaign and breathing undulatory motion according to real time kinematics information by the real time kinematics of tumor.In some instances, the real time kinematics of tumor is decomposed into baseline drift campaign and breathes undulatory motion calculation procedure as follows:

First, the period tau of current breathing state is obtained ₀, and:

$F\left(\mathrm{\τ}\right)=\underset{t=t_0-\mathrm{Ndt}}{\overset{t_0}{\mathrm{\Σ}}}|P\left(t\right)-P(t-\mathrm{\τ})|$

$F\left({\mathrm{\&tau;}}_0\right)=\underset{0<\mathrm{\&tau;}<9f}{\min }F\left(\mathrm{\&tau;}\right),$

Wherein, P (t) for claiming the amplitude of tumor motion in respiratory, period tau ₀f (τ) is made to get minimum.

Then, the meansigma methods of getting 3 doubling times as the value calculating moment breathing average baselining, then breathes baseline expression formula is:

${\tilde{B}}_0=\underset{t=t_0-{3\mathrm{\&tau;}}_0}{\overset{t_0}{\mathrm{\&Sigma;}}}\frac{P\left(t\right)}{{3\mathrm{\&tau;}}_0}.$

Finally, with original breath signal deduct level and smooth after the data obtained point of breathing baseline be to breathe and rise and fall.

Position prediction module 130 carries out the position prediction after the scheduled time, to obtain baseline prediction data and fluctuating prediction data to baseline drift campaign and breathing undulatory motion respectively.In some instances, such as, position prediction module 130 carries out position prediction by the Kalman filter of constant acceleration model to baseline drift campaign.Position prediction module 130 carries out position prediction by Finite State Model to breathing undulatory motion, breathes undulatory motion and comprises linear condition, nonlinear state and irregular status.Therefore, to breathe undulatory motion carry out Preset Time after position prediction time, position prediction module 130 also breathes the current residing state of undulatory motion for judging, and carries out according to current state the position prediction breathing undulatory motion.Wherein, in one embodiment of the invention, judge that the formula breathing the current state of undulatory motion is:

Basis for estimation between linear condition and nonlinear state/irregular status is the variable gradient of linearly dependent coefficient, is expressed as:

$d_{\mathrm{\&rho;}}\left(t_k\right)=\frac{{\mathrm{\&rho;}}_{\mathrm{xy}}\left(t_k\right)-{\mathrm{\&rho;}}_{\mathrm{xy}}\left(t_{k-1}\right)}{\mathrm{dt}},$

Wherein, d _ρ(t _k) be t _kthe linearly dependent coefficient variable gradient in moment, ρ _xy(t _k), ρ _xy(t _k-1) be respectively t _kmoment and t _k-1the linearly dependent coefficient in moment, dt is t _kmoment and t _k-1moment time difference.

Basis for estimation between irregular status and nonlinear state is low frequency energy accounting, is expressed as:

$\mathrm{PE}\left(t_k\right)=\frac{{\&Integral;}_0^{f_t}{S}_{t_k}\left(f\right)\mathrm{df}}{{\&Integral;}_0^{+\&infin;}{S}_{t_k}\left(f\right)\mathrm{df}},$

Wherein, PE (t _k) be t _kmoment gets breath data medium and low frequency energy accounting, parameter T is for arriving t _kmoment is the time span that section nonlinear state is lasting here, and X (f) is then the Fourier transformation result of signal in this section of time span.

Compensating controller 140 is for compensating baseline drift campaign and breathing undulatory motion respectively according to baseline prediction data and fluctuating prediction data.Further, such as, compensating controller 140 comprises therapeutic bed controller 141 and multi-leaf optical grating controller 142 (not shown), and wherein, therapeutic bed controller 141 is slowly mobile with the compensation carrying out baseline drift campaign for controlling therapeutic bed according to baseline prediction data.Multi-leaf optical grating controller 142 is for receiving fluctuating prediction data, to control multi-leaf optical grating, breathing undulatory motion is compensated, wherein multi-leaf optical grating controller is driven by linear electric motors, make multi-leaf optical grating speed and acceleration very large, therefore, when carrying out the compensation of breathing undulatory motion, real-time and the accuracy of tracking can be ensured.

It should be noted that, the detailed description of the invention of the detailed description of the invention of this system 100 and the method for the above embodiment of the present invention is similar, and therefore, the concrete exemplary description for this system 100 refers to the description part to method, for reducing redundancy, repeat no more herein.

To sum up, according to the system of the tumor motion breathing generation being carried out to online compensation of the embodiment of the present invention, first the multiple position sensors by being arranged on inside tumor obtain the real time kinematics information of tumor, and accordingly the real time kinematics of tumor be decomposed into baseline drift campaign and breathe undulatory motion, and respectively the position prediction after the ticket reserving time is carried out to baseline drift campaign and breathing undulatory motion, last basis predicts the outcome and compensates baseline drift campaign and breathing undulatory motion respectively.Therefore, this system can carry out real-time online compensation to breathing the tumor motion produced, and then can realize accurate, radiotherapy efficiently, and this system structure is simple, easy to operate.

In describing the invention, it will be appreciated that, term " " center ", " longitudinal direction ", " transverse direction ", " length ", " width ", " thickness ", " on ", D score, " front ", " afterwards ", " left side ", " right side ", " vertically ", " level ", " top ", " end " " interior ", " outward ", " clockwise ", " counterclockwise ", " axis ", " radial direction ", orientation or the position relationship of the instruction such as " circumference " are based on orientation shown in the drawings or position relationship, only the present invention for convenience of description and simplified characterization, instead of indicate or imply that the device of indication or element must have specific orientation, with specific azimuth configuration and operation, therefore limitation of the present invention can not be interpreted as.

In addition, term " first ", " second " only for describing object, and can not be interpreted as instruction or hint relative importance or imply the quantity indicating indicated technical characteristic.Thus, be limited with " first ", the feature of " second " can express or impliedly comprise at least one this feature.In describing the invention, the implication of " multiple " is at least two, such as two, three etc., unless otherwise expressly limited specifically.

In the present invention, unless otherwise clearly defined and limited, the term such as term " installation ", " being connected ", " connection ", " fixing " should be interpreted broadly, and such as, can be fixedly connected with, also can be removably connect, or integral; Can be mechanical connection, also can be electrical connection; Can be directly be connected, also indirectly can be connected by intermediary, can be the connection of two element internals or the interaction relationship of two elements, unless otherwise clear and definite restriction.For the ordinary skill in the art, above-mentioned term concrete meaning in the present invention can be understood as the case may be.

In the present invention, unless otherwise clearly defined and limited, fisrt feature second feature " on " or D score can be that the first and second features directly contact, or the first and second features are by intermediary mediate contact.And, fisrt feature second feature " on ", " top " and " above " but fisrt feature directly over second feature or oblique upper, or only represent that fisrt feature level height is higher than second feature.Fisrt feature second feature " under ", " below " and " below " can be fisrt feature immediately below second feature or tiltedly below, or only represent that fisrt feature level height is less than second feature.

In the description of this description, specific features, structure, material or feature that the description of reference term " embodiment ", " some embodiments ", " example ", " concrete example " or " some examples " etc. means to describe in conjunction with this embodiment or example are contained at least one embodiment of the present invention or example.In this manual, to the schematic representation of above-mentioned term not must for be identical embodiment or example.And the specific features of description, structure, material or feature can combine in one or more embodiment in office or example in an appropriate manner.In addition, when not conflicting, the feature of the different embodiment described in this description or example and different embodiment or example can carry out combining and combining by those skilled in the art.

Although illustrate and describe embodiments of the invention above, be understandable that, above-described embodiment is exemplary, can not be interpreted as limitation of the present invention, and those of ordinary skill in the art can change above-described embodiment within the scope of the invention, revises, replace and modification.

Claims (10)

1. the tumor motion breathing generation is carried out to a method for online compensation, it is characterized in that, comprise the following steps:

Obtained the real time kinematics information of tumor by multiple position sensor, wherein said multiple position sensor is arranged on inside tumor;

According to described real time kinematics information, the real time kinematics of described tumor is decomposed into baseline drift campaign and breathing undulatory motion;

Respectively the position prediction after the scheduled time is carried out to described baseline drift campaign and described breathing undulatory motion, to obtain baseline prediction data and fluctuating prediction data; And

Respectively described baseline drift campaign and breathing undulatory motion are compensated according to described baseline prediction data and described fluctuating prediction data.

2. as claimed in claim 1 the tumor motion breathing generation is carried out to the method for online compensation, it is characterized in that, described according to described baseline prediction data and fluctuating prediction data respectively to described baseline drift campaign with breathe undulatory motion and compensate, comprise further:

Described baseline prediction data being sent to therapeutic bed controller, moving by controlling therapeutic bed the compensation carrying out baseline drift campaign;

Described fluctuating prediction data is sent to multi-leaf optical grating controller, and compensate described breathing undulatory motion to control multi-leaf optical grating, wherein said multi-leaf optical grating controller is driven by linear electric motors.

3. as claimed in claim 1 the tumor motion breathing generation is carried out to the method for online compensation, it is characterized in that, wherein, by the Kalman filter of constant acceleration model, position prediction is carried out to described baseline drift campaign.

4. as claimed in claim 1 the tumor motion breathing generation is carried out to the method for online compensation, it is characterized in that, wherein, by Finite State Model, position prediction is carried out to described breathing undulatory motion, described breathing undulatory motion comprises linear condition, nonlinear state and irregular status, wherein

Position prediction after Preset Time is carried out to described breathing undulatory motion, comprises further:

Judge the state that described breathing undulatory motion is current;

The position prediction of described breathing undulatory motion is carried out according to described current state.

5. as claimed in claim 4 the tumor motion breathing generation is carried out to the method for online compensation, it is characterized in that, wherein, judge that the formula of the state that described breathing undulatory motion is current is:

For linear condition and nonlinear state/irregular status:

$d_{\mathrm{\&rho;}}\left(t_k\right)=\frac{{\mathrm{\&rho;}}_{\mathrm{xy}}\left(t_k\right)-{\mathrm{\&rho;}}_{\mathrm{xy}}\left(t_{k-1}\right)}{\mathrm{dt}},$

Wherein, d _ρ(t _k) be t _kthe linearly dependent coefficient variable gradient in moment, ρ _xy(t _k), ρ _xy(t _k-1) be respectively t _kmoment and t _k-1the linearly dependent coefficient in moment, dt is t _kmoment and t _k-1moment time difference;

For irregular status and nonlinear state:

$\mathrm{PE}\left(t_k\right)=\frac{{\&Integral;}_0^{f_l}{S}_{t_k}\left(f\right)\mathrm{df}}{{\&Integral;}_0^{+\&infin;}{S}_{t_k}\left(f\right)\mathrm{df}},$

Wherein, PE (t _k) be t _kmoment gets breath data medium and low frequency energy accounting, parameter T is for arriving t _kmoment is the time span that section nonlinear state is lasting here, and X (f) is then the Fourier transformation result of signal in this section of time span.

6. the tumor motion breathing generation is carried out to a system for online compensation, it is characterized in that, comprising:

Multiple position sensor, described multiple position sensor is arranged on inside tumor, for obtaining the real time kinematics information of described tumor;

Real-time controller, described real-time controller is used for, according to described real time kinematics information, the real time kinematics of described tumor is decomposed into baseline drift campaign and breathing undulatory motion;

Position prediction module, described position prediction module carries out the position prediction after the scheduled time to described baseline drift campaign and described breathing undulatory motion respectively, to obtain baseline prediction data and fluctuating prediction data; And

Compensating controller, described compensating controller is used for compensating described baseline drift campaign and breathing undulatory motion respectively according to described baseline prediction data and described fluctuating prediction data.

7. the tumor motion to breathing generation according to claim 6 carries out the system of online compensation, and it is characterized in that, described compensating controller comprises therapeutic bed controller and multi-leaf optical grating controller, wherein,

Described therapeutic bed controller is used for controlling therapeutic bed according to baseline prediction data and moves the compensation carrying out baseline drift campaign;

Described multi-leaf optical grating controller is for receiving described fluctuating prediction data, and compensate described breathing undulatory motion to control multi-leaf optical grating, wherein said multi-leaf optical grating controller is driven by linear electric motors.

8. as claimed in claim 6 the tumor motion breathing generation is carried out to the system of online compensation, it is characterized in that, wherein, described position prediction module carries out position prediction by the Kalman filter of constant acceleration model to described baseline drift campaign.

9. as claimed in claim 6 the tumor motion breathing generation is carried out to the system of online compensation, it is characterized in that, wherein, described position prediction module carries out position prediction by Finite State Model to described breathing undulatory motion, described breathing undulatory motion comprises linear condition, nonlinear state and irregular status, wherein

Described position prediction module also for judging the state that described breathing undulatory motion is current, and carries out the position prediction of described breathing undulatory motion according to described current state.

10. as claimed in claim 9 the tumor motion breathing generation is carried out to the system of online compensation, it is characterized in that, wherein, judge that the formula of the state that described breathing undulatory motion is current is:

For linear condition and nonlinear state/irregular status:

$d_{\mathrm{\&rho;}}\left(t_k\right)=\frac{{\mathrm{\&rho;}}_{\mathrm{xy}}\left(t_k\right)-{\mathrm{\&rho;}}_{\mathrm{xy}}\left(t_{k-1}\right)}{\mathrm{dt}},$

Wherein, d _ρ(t _k) be t _kthe linearly dependent coefficient variable gradient in moment, ρ _xy(t _k), ρ _xy(t _k-1) be respectively t _kmoment and t _k-1the linearly dependent coefficient in moment, dt is t _kmoment and t _k-1moment time difference; For irregular status and nonlinear state:

$\mathrm{PE}\left(t_k\right)=\frac{{\&Integral;}_0^{f_l}{S}_{t_k}\left(f\right)\mathrm{df}}{{\&Integral;}_0^{+\&infin;}{S}_{t_k}\left(f\right)\mathrm{df}},$

Wherein, PE (t _k) be t _kmoment gets breath data medium and low frequency energy accounting, parameter T is for arriving t _kmoment is the time span that section nonlinear state is lasting here, and X (f) is then the Fourier transformation result of signal in this section of time span.