CN201880220U - Auxiliary radiotherapy mattress system with function of image and breathing guidance - Google Patents

Auxiliary radiotherapy mattress system with function of image and breathing guidance Download PDF

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CN201880220U
CN201880220U CN2010205883272U CN201020588327U CN201880220U CN 201880220 U CN201880220 U CN 201880220U CN 2010205883272 U CN2010205883272 U CN 2010205883272U CN 201020588327 U CN201020588327 U CN 201020588327U CN 201880220 U CN201880220 U CN 201880220U
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breathing state
tumor
mattress
breathing
image
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刘宏
宋恩民
杨词慧
李琴
张祺
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Huazhong University of Science and Technology
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Huazhong University of Science and Technology
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Abstract

The utility model discloses an auxiliary radiotherapy mattress system with a function of image and breathing guidance, comprising a data processor, a breathing detector, an auxiliary motion mattress and an auxiliary motion mattress controller; the breathing detector sends the detected breathing state to the data processor; and the auxiliary motion mattress controller is connected with the data processor and the auxiliary motion mattress respectively. The auxiliary radiotherapy mattress system can be used in conjunction with traditional radiotherapy equipment so that the traditional radiotherapy equipment has the function of guiding radiotherapy by image. When in use, the relationship model of the breathing state and the tumor displacement is establishedon the basis of the synchronously collected breathing state sequence and tumor anatomy structure image sequence; the breathing state of the next moment can be predicted according to the current breathing state and the previous breathing state during the radiotherapy state; subsequently the predicted tumor displacement is calculated by the relationship model between the breathing state and the tumor displacement; furthermore, the position of a patient is adjusted in real time so that the tumor center is basically aligned to the focus point of the radiation source, thus reducing the harm of the radials on the normal tissues of the patient.

Description

The auxiliary radiation therapy bed mattress system of image and breathing guiding
Technical field
This utility model belongs to medical apparatus and instruments auxiliary treatment apparatus field, is specifically related to a kind of image and breathes the auxiliary radiation therapy bed mattress system of guiding.
Background technology
In the process of radiotherapy (radiotherapy), patient's respiratory movement meeting causes the variation of lung tumors position.In order to reduce the adverse effect that respiratory movement brings radiotherapy, traditional method is to enlarge the radiotherapy target area, and with the tumor of abundant covering campaign, but this can cause certain injury to normal structure.Occurred breathing (breath-hold) and respiration gate control (respiratory gating) technology of holding one's breath subsequently, promptly when patient holds one's breath or exhale air-breathing end, tumor region has been carried out radiotherapy, so that with as far as possible little tumor target area.Be called " Method and system for physiological gating of radiation therapy " american documentation literature (US6690965B1) as name, detect the well-regulated physiological movement of patient by optics or video image system, when motion surpasses a certain threshold value, just start gate-control signal, suspend the irradiation of radioactive source.But this method has strict requirement to patient's breathing state, needs patient's cooperation, and patient lies in time on the therapeutic bed and has greatly not to be to accept irradiation treatment, to make therapeutic equipment can not give full play to service efficiency.
Also there is patent documentation to propose the method for the relation between research breathing state and the knub position at this problem, be called " based on the image guiding and tracking method of prediction " (publication number is CN101428154A) and be called the patent documentation of " real-time tracking method for dynamic tumor " (publication number is CN101423198A) as name, quantize and analyze by tumor anatomical structure image and breathing state feature set input, set up the dependency of respiratory movement and tumor motion, and obtain the image and the breathing state feature of dynamic tumor in real time, by the breathing state feature after the prediction time-delay, determine the interval image sequence of corresponding tumor metamorphosis, itself and the dynamic tumor image that obtains are in real time mated and therefrom choose best tumor aspect graph, to realize motion tracking tumor.These two patent documentations come tracking of knub position by the registration of multiple image, calculate more consuming time, can not satisfy the requirement of real-time tracking tumor motion, in addition, this patent documentation is used for the radiotherapy process to how with the result of tracking of knub motion and does not provide effective method.
Also there is multiple Forecasting Methodology to can be used for breathing state and tumor motion are predicted at present, as " Adaptive switching circuits " (B.Widrow and M.E.Hoff, IRE Wescon Convention Record Part 4, pp.96-104,1960.) introduced a kind of Kalman (Kalman) wave filter in; " A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking; " (M.S.Arulampalam, S.Maskell, N.Gordon, and T.Clapp, IEEE Transactions on Signal Processing, vol.50, pp.174-188, Feb 2002.) lowest mean square (least mean square, LMS) sef-adapting filter proposed; Neural networks for pattern recognition (C.M.Bishop, New York:Oxford University Press, Inc., 1995.) has introduced artificial neural network (artificial neural network) method.These Forecasting Methodologies can be adjusted the parameter of forecast model in the process of prediction automatically.For the target detection in the image, template matching is a kind of method (referring to R.O.Duda and P.E.Hart, Pattern classification and scene analysis.New York:Wiley, 1973.) relatively more commonly used.For relationship modeling, method of least square is a kind of data fitting method commonly used (referring to O.Bretscher, Linear algebra with applications, 3rd ed.New York:Prentice Hall, 1995.).
For the detection of breathing, mainly contain at present pressure transducer method, inductance volume graphical method, critesistor method, by ecg information obtain, methods such as impedance spirography and infrared camera detection.As publication number is that the patent documentation of CN2885122Y discloses a kind of " photo-electric ventral breathing pick off ", and publication number is that the patent documentation of CN101212930 also discloses a kind of " device for detecting respiratory ", all can be used to detect the breathing state that obtains human body.
Termed image-guided radiotherapy (image-guided radiotherapy, IGRT) technology kinestate to tumor in the radiotherapy process carries out real-time tracking, dynamically adjust the position of radioactive source or patient's position according to the motion of tumor, make the focus of radioactive source and the center-aligned of tumor.The United States Patent (USP) that is called " Dynamic tracking of moving targets " (publication number is US20060074292) as name has been introduced the method that a kind of dynamic tumor is followed the tracks of radiotherapy, before treatment, utilize three-dimensional computed tomography (the three-dimensional computed tomography that gathers, 3D-CT) image sequence or other 3-D view are set up four-dimensional mathematical model, to determine the relation between tumor target and the anatomic region three-dimensional position, the tumor image that to gather in real time in the treatment and digital reconstruction radiotherapy image carry out registration, thereby finish the tracking and the real-time positioning of tumor target.This technical scheme also needs to obtain by image registration the position of tumor, can't satisfy the requirement of real-time tracking.The CyberKnife robot radiotherapy system that Accuray company produces, with X ray linear accelerator (linear accelerator, LINAC) be installed on the industrial robot arm, adopting two X line video cameras to monitor knub position in real time changes, and automatically positional information is sent to the robots arm, the robots arm can make it to prospective tumor by six-freedom degree reorientation x-ray.CyberKnife robot radiotherapy system has been applied to clinical at present.Existing IGRT equipment can reduce the influence of respiratory movement to radiotherapy to a certain extent, but these IGRT equipment price costlinesses, be 2 to 3 times of conventional radiotheraphy equipment price, only there is minority hospital to be equipped with IGRT equipment at present, in in recent years, most of hospital will continue to use legacy equipment and traditional method that the patient is carried out radiotherapy, even the hospital that has has been equipped with IGRT equipment, also can use traditional radiotherapy apparatus simultaneously.
Summary of the invention
The auxiliary radiation therapy bed mattress system that the purpose of this utility model is to propose a kind of image and breathes guiding, this system is used to be placed on the therapeutic bed of existing radiotherapy apparatus, can adjust in real time the position of bed board in the system, make the focus of radioactive source be positioned at the desired position all the time.。
The auxiliary radiation therapy bed mattress system of a kind of image that this utility model provides and breathing guiding is characterized in that this system comprises data processor, apnea detector, assisted movement mattress and assisted movement mattress controller;
Apnea detector is connected with the data processor news by wired or wireless mode; The assisted movement mattress is used to be placed on the therapeutic bed of existing radiotherapy apparatus; Assisted movement mattress controller is connected with data processor and assisted movement mattress respectively;
Data processor is used for the breathing state that apnea detector provides is handled, and calculates the required quantity of motion of assisted movement mattress, and offers assisted movement mattress controller; The motion of assisted movement mattress controller control assisted movement mattress.
This utility model system cooperates existing radiotherapy apparatus to use together, need not existing radiotherapy apparatus is transformed, and just can make its radiotherapy function with image guiding, thereby realizes only needing lower cost just can strengthen the purpose of the function of existing radiotherapy apparatus.This system can dope the displacement of tumor in real time, more exactly, and according to the tumor displacement of prediction the bed board position of assisted movement mattress is adjusted, and makes the focus of radioactive source be positioned at the desired position all the time.So just can be in use, make the center of tumor be in all the time the radioactive source focal position or near, thereby reduce patient's the suffered beam toxicity of normal structure.Simultaneously, breathing state that this system sets up the patient according to the breathing state and the tumor anatomical structure image of synchronous acquisition and the relation between the tumor displacement do not have special requirement to patient's breathing, therefore have good versatility.
Description of drawings
Fig. 1 is the structure chart of this utility model system;
Fig. 2 is the structural representation of a kind of specific embodiment of this utility model;
Fig. 3 is the scheme of installation of this utility model example;
Fig. 4 is the structural representation of the assisted movement mattress of this utility model example;
Fig. 5 is the apnea detector outside drawing of this utility model example;
Fig. 6 is the breathing state and the tumor displacement relation matched curve sketch map of this utility model example;
Fig. 7 is the actual breathing state and prediction breathing state sketch map of this utility model example;
Fig. 8 is the prediction tumor displacement diagram of this utility model example;
Description of reference numerals: 1-data processor; The 2-apnea detector; 3-assisted movement mattress; 4-assisted movement mattress controller; 5-image processing module, 6-breathing state and tumor displacement relation analysis module; 7-tumor displacement prediction module; The 8-motion-control module; 21-respiration detection box; 22-detects band; The 301-base plate; 302-first linear guides; The 303-slide block; The 304-motor mounting plate; The 305-first ball-screw supporting seat; The 306-second ball-screw supporting seat; The 307-ball-screw; 308-second linear guides; The 309-mobile platform; The 310-servomotor; The 311-shaft coupling; The 312-bed board.
The specific embodiment
Below in conjunction with accompanying drawing and example this utility model is described in further detail.
As shown in Figure 1, the auxiliary radiation therapy bed mattress system of the image of this utility model design and breathing guiding comprises data processor 1, apnea detector 2, assisted movement mattress 3 and assisted movement mattress controller 4;
Data processor 1 can be that computer or embedded device or other can carry out the device of computing, it is used for setting up the relational model between breathing state and the tumor displacement before radiotherapy, in the radiotherapy process, next breathing state is constantly predicted according to the breathing state that receives, calculate next prediction tumor displacement constantly according to next prediction breathing state and relational model between breathing state and the tumor displacement constantly, and calculate the quantity of motion of the bed board needs motion of assisted movement mattress 3 according to existing prediction tumor displacement data, send motion control instruction to assisted movement mattress controller 4, thereby realize patient's tumor center being alignd substantially with the radioactive source focus by breathing the position of the bed board of change assisted movement mattress indirectly.
Apnea detector 2 is any devices that can be used to detect patient's breathing state, this device is used to detect patient's breathing state, as thorax variation, abdominal part fluctuations, vital capacity, the motion of tabula mould, the motion of lung tissue etc., and when the relational model of setting up between breathing state and the tumor displacement and prediction during knub position, respectively breathing state is sent to data processor 1 by wired or wireless mode.
Assisted movement mattress 3 is used to be placed on the therapeutic bed of existing radiotherapy apparatus, and the patient overlies and accepts radiotherapy, and its bed board is moving on 1 or 2 or 3 directions under the control of assisted movement mattress controller 4, to change patient's position.
Assisted movement mattress controller 4 is used to receive the motion control instruction that data processor 1 sends, the bed board motion of control assisted movement mattress 3.
Now illustrate the specific design mode of software module in the data processor 1, it includes image processing module 5, breathing state and tumor displacement relation analysis module 6, tumor displacement prediction module 7 and motion-control module 8, and its structure as shown in Figure 2.
The tumor anatomical structure image is meant that computed tomography (CT) image or nuclear magnetic resonance, NMR (MR) image or positron emission computerized tomography (PET) image or x-ray image or ultrasound wave (US) image or other can reflect the image of the anatomical structure of tumor.During enforcement, offer data processor 1 after obtaining and arrange in chronological order by medical imaging devices.
Image processing module 5 is used for the good tumor anatomical structure image sequence I of arrangement in chronological order to 1 reception of data processor 1, I 2, Λ, I kHandle, from tumor anatomical structure image sequence I 1, I 2, Λ, I kIn determine the position of tumor to generate tumor displacement sequence D 1, D 2, Λ, D k, and with tumor displacement sequence D 1, D 2, Λ, D kOffer breathing state and tumor displacement relation analysis module 6, wherein k is the width of cloth number of the tumor anatomical structure image that receives when setting up the relational model of breathing state and tumor displacement.The concrete processing procedure of this module is:
(1) data processor 1 receives the tumor anatomical structure image sequence I that arranges in chronological order 1, I 2, Λ, I k, wherein, first width of cloth image I 1In the good tumor region of cropping is arranged;
(2) image processing module 5 calculates first width of cloth image I 1In the barycenter of tumor region, and with the position of this barycenter as first width of cloth image I 1The position P of middle tumor 1
(3) for all other image I of tumor anatomical structure image sequence 2, I 3, Λ, I k, image processing module 5 adopts method or other motion tracking method of template matching, in all other image I j(j=2,3, Λ detects the image-region the most similar to tumor region in k), and calculates the barycenter of each image-region, with the position of barycenter as image I jThe position P of middle tumor j
In template matching method, it generally is elder generation's given template (as the little image of a width of cloth or an image-region), in certain scope zone of image or image, search for zone then to given template the most similar (or the most approaching), the similar value of two image-regions calculates by a certain weighing criteria, the similar value maximum in certain the piece zone in template and image, just represent that template is the most similar to this piece zone, this piece zone is exactly the most similar image-region of being asked.
(4) with all knub position P 1And P jRespectively with first width of cloth image in knub position P 1Subtract each other, the result who obtains is arranged in chronological order, obtain tumor displacement sequence D 1, D 2, Λ, D k
Breathing state and tumor displacement relation analysis module 6 are used for the breathing state that data processor 1 receives is arranged in chronological order, form the first breathing state sequence A 1, A 2, Λ, A k, according to the first breathing state sequence A 1, A 2, Λ, A kWith the tumor displacement sequence D that receives 1, D 2, Λ, D k, the employing curve fitting algorithm is set up the relational model between breathing state and the tumor displacement, and this relational model is offered tumor displacement prediction module 7.
Because breathing state and tumor anatomical structure image are synchronous acquisition, thus the breathing state number of reception equate with the width of cloth number of tumor anatomical structure image, be k.Curve fitting algorithm can adopt method of least square, B batten or other fitting algorithms.
Tumor displacement prediction module 7 is used in breathing state prediction model parameters deterministic process the breathing state that data processor 1 receives being arranged in chronological order, forms the second breathing state sequence B 1, B 2, Λ, B m(the breathing state number that m receives when determining the parameter of breathing state forecast model) is then with the second breathing state sequence B 1, B 2, Λ, B mBe training dataset, determine the parameter of breathing state forecast model, and prediction patient m+1 breathing state constantly, m+1 prediction breathing state B ' constantly obtained M+1If i is used for when using this utility model system the moment that receives breathing state being counted, initial value is m+1, and each of back number constantly all adds 1 in front the moment number; In actual use, be used for according to i (i=m+1, m+2 ...) the breathing state B that constantly receives iWith i prediction breathing state B constantly i' between difference, the parameter of breathing state forecast model is adjusted, and prediction patient i+1 breathing state B ' constantly I+1According to i+1 prediction breathing state B ' constantly I+1With the relational model of breathing state and tumor displacement, calculate i+1 prediction tumor displacement D ' constantly I+1
Prediction patient's breathing state and parameter definite, that adjust the breathing state forecast model can adopt Kalman filter, minimum mean square self-adaption filter, artificial neural network or other Forecasting Methodology.
Motion-control module 8 is used for the i+1 prediction tumor displacement D constantly according to 7 predictions of tumor displacement prediction module I+1' with i prediction tumor displacement D constantly i' between deviation calculate the quantity of motion M that assisted movement mattress 3 needs motion I+1, send motion control instruction to assisted movement mattress controller 4 by data processor 1.
When this utility model system uses, set up earlier patient's breathing state and the relational model between the tumor displacement according to the following steps:
(1) uses an interior breathing state and tumor anatomical structure image of breathing cycle of apnea detector 2 and medical imaging devices synchronous acquisition patient, breathing state is sent to data processor 1 by wired or wireless mode, the tumor anatomical structure image is arranged in chronological order generated tumor anatomical structure image sequence I 1, I 2, Λ, I k, send to data processor 1 by wired or wireless mode.
(2) the tumor anatomical structure image sequence I of 5 pairs of data processors of image processing module, 1 reception 1, I 2, Λ, I kHandle, generate tumor displacement sequence D 1, D 2, Λ, D k, and with tumor displacement sequence D 1, D 2, Λ, D kOffer breathing state and tumor displacement relation analysis module 6.
(3) breathing state and tumor displacement relation analysis module 6 are arranged the breathing state that data processor 1 receives in chronological order, form the first breathing state sequence A 1, A 2, Λ, A k, according to the first breathing state sequence A 1, A 2, Λ, A kWith the tumor displacement sequence D that receives 1, D 2, Λ, D k, the employing curve fitting algorithm is set up the relational model between breathing state and the tumor displacement, and this relational model is offered tumor displacement prediction module 7.Curve fitting algorithm can adopt method of least square, B batten or other fitting algorithms.
Behind the relational model between the breathing state of setting up the patient and the tumor displacement, gather breathing state according to the following steps in advance, determine the parameter of breathing state forecast model:
(1) assisted movement mattress 3 is placed on the therapeutic bed of radiotherapy apparatus;
(2) patient lies low on assisted movement mattress 3, and the patient is put the position;
(3) adopt apnea detector 2 to gather the breathing state of at least one breathing cycle of patient, and breathing state is sent to data processor 1 by wired or wireless mode;
(4) tumor displacement prediction module 7 is arranged the breathing state that data processor 1 receives in chronological order, forms the second breathing state sequence B 1, B 2, Λ, B m, then with the second breathing state sequence B 1, B 2, Λ, B mBe training dataset, determine the parameter of breathing state forecast model, and prediction patient m+1 breathing state B ' constantly M+1, determine that the parameter of breathing state forecast model and prediction m+1 breathing state constantly can adopt Kalman filter, minimum mean square self-adaption filter, artificial neural network or other Forecasting Methodology.
After the parameter of having determined the breathing state forecast model, use this utility model system according to the following steps:
(1) passes through the breathing state B that apnea detector 2 detects patients in real time constantly at i (the i initial value is m+1) i, and with breathing state B iSend to data processor 1 by wired or wireless mode;
(2) tumor displacement prediction module 7 is according to the breathing state B of data processor 1 reception iI breathing state B ' constantly with prediction iBetween difference, the parameter of breathing state forecast model is adjusted;
(3) tumor displacement prediction module 7 is according to the breathing state B of data processor 1 reception i, l-1 breathing state B that constantly receives before I-l+1, B I-l+2, Λ, B I-1With the parameter of adjusting breathing state forecast model afterwards, prediction patient i+1 breathing state B ' constantly I+1, l is a constant here, the number of needed historical data during the expression prediction, and prediction patient's breathing state is identical with the method for the parameter of definite breathing state forecast model with the method that the parameter of adjusting the breathing state forecast model adopts;
(4) tumor displacement prediction module is according to the i+1 breathing state B ' constantly of prediction I+1With the relational model of breathing state and tumor displacement, calculate i+1 prediction tumor displacement D ' constantly I+1
(5) motion-control module 8 is according to i+1 prediction tumor displacement D ' constantly I+1With i prediction tumor displacement D ' constantly iBetween deviation calculate the quantity of motion M that assisted movement mattress 3 needs motion I+1, and in assisted movement mattress controller 4, send motion control instruction by data processor 1;
(6) assisted movement mattress controller 4 moves according to the bed board of the motion control instruction control assisted movement mattress 3 that receives, and the motion of tumor is compensated, thereby make i+1 align substantially with the radioactive source focus center of the intravital tumor of patient constantly;
(7) whether the time of judging radiotherapy finishes, if the time of radiotherapy does not arrive, then makes i=i+1, forwards (1) to and proceeds radiotherapy; Otherwise the radiotherapy process finishes.
Example:
In order to make technical problem to be solved in the utility model, technical scheme and beneficial effect clearer,, this utility model is described in further details below in conjunction with accompanying drawing and example.In this example, select computer as data processor 1.Apnea detector 2 can adopt existing various respiration detection pick off or checkout gear, also can adopt structure as shown in Figure 5, and it is made up of respiration detection box 21 and detection band tyre 22.Use this apnea detector to detect when breathing, will detect band tyre 22 and lie in detected person's chest, and with the detection band of respiration detection box 21 in be with and link to each other.Detect the band 22 inside testing agency motions that drive respiration detection box 21 along with detected person's chest respiratory movement in addition, respiration detection box 21 generates breathing state under the effect of inner testing agency motion, and breathing state is exported by wireless data interface.
As shown in Figure 3, Figure 4, assisted movement mattress 3 is made up of base plate 301, first linear guides 302, slide block 303, motor mounting plate 304, the first ball-screw supporting seat 305, the second ball-screw supporting seat 306, ball-screw 307, second linear guides 308, mobile platform 309, servomotor 310, shaft coupling 311, bed board 312.First linear guides 302, motor mounting plate 304, the first ball-screw supporting seat 305, the second ball-screw supporting seat 306 and second linear guides 308 are by being bolted on the base plate 301, slide block 303 links to each other with first linear guides 302, be used to support bed board 312, and on first linear guides 302, slide, ball-screw 307 is installed on the first ball-screw supporting seat 305 and the second ball-screw supporting seat 306 by bearing, be used for rotatablely moving of servomotor 310 become rectilinear motion, and driving mobile platform 309 moves, mobile platform 309 links to each other by the nut of bolt with ball-screw 307, and link to each other with slide block on second linear guides 308 by bolt, being used to drive bed board 312 moves, servomotor 310 is installed on the motor mounting plate 304 by bolt, its output shaft is by shaft coupling 311 and 307 coaxial linking to each other of ball-screw, bed board 312 is by being bolted on slide block 303 and the mobile platform 309 first linear guides 302, slide block 303 and bed board 312 are made by carbon fibre material.
Assisted movement mattress 3 can also adopt other multiple frame for movement design to realize, realizes as adopting rack-and-pinion drive mechanism and stepper motor driven mode.
Assisted movement mattress controller 4 is linked to each other with computer with servomotor 310 respectively by data wire, assisted movement mattress 3 is fixed on the therapeutic bed of radiotherapy apparatus.
Before the radiotherapy, gather tumor anatomical structure image sequence and breathing state sequence according to the following steps, set up patient's breathing state and the relational model between the tumor displacement, this example is selected x-ray image that the digital radiography machine the obtains tumor anatomical structure image as this example for use, select thorax to change as breathing state, select minimum mean square self-adaption filter as the breathing state Forecasting Methodology, select the method for least square conduct to set up the method for the relational model between breathing state and the tumor displacement:
(1) patient lies low on the therapeutic bed of digital radiography machine, with the detection band of apnea detector 2 22 chests that tie up to the patient in addition, and with the detection band of respiration detection box 21 in be with and link to each other, open the on and off switch of apnea detector 2 and digital radiography machine;
(2) use an interior x-ray image and breathing state of breathing cycle of digital radiography machine and apnea detector 2 synchronous acquisition patients, x-ray image is according to time sequence generated x-ray image I in the back 1, I 2, Λ, I k, send to computer by wired mode, wherein k is the width of cloth number of the x-ray image that receives when setting up the relational model of breathing state and tumor displacement, the respiration detection box of apnea detector 2 21 sends to computer with breathing state by wireless mode;
(3) the x-ray image sequence I of 5 pairs of computers receptions of image processing module 1, I 2, Λ, I kHandle, generate tumor displacement sequence D 1, D 2, Λ, D k, and with tumor displacement sequence D 1, D 2, Λ, D kOffer breathing state and tumor displacement relation analysis module 6;
(4) breathing state and tumor displacement relation analysis module 6 are arranged the breathing state that computer receives in chronological order, form the first breathing state sequence A 1, A 2, Λ, A k, then with the first breathing state sequence A 1, A 2, Λ, A kWith the tumor displacement sequence D that receives 1, D 2, Λ, D kBe mapped one by one in chronological order, be about to A i(i=1,2, Λ, k) and D iCorrespondence is again according to the first breathing state sequence A after the correspondence 1, A 2, Λ, A kWith the tumor displacement sequence D that receives 1, D 2, Λ, D k, adopt method of least square that the relational model between breathing state and the tumor displacement is carried out curve fitting, as shown in Figure 6, and this relational model offered tumor displacement prediction module 7.
Behind the relational model between the breathing state of having set up the patient and the tumor displacement, gather breathing state according to the following steps in advance, determine the parameter of breathing state forecast model:
(1) assisted movement mattress 3 is placed on the therapeutic bed of radiotherapy apparatus, with the detection band of apnea detector 2 22 chests that tie up to the patient in addition, and with the detection band of respiration detection box 21 in be with and link to each other, open the on and off switch of apnea detector 2; Allow the patient lie low on the bed board 33 of assisted movement mattress 3, the patient is put the position;
(2) adopt apnea detector 2 to gather the breathing state of at least 1 breathing cycle of patient, breathing state is sent to computer by wireless mode by the respiration detection box 21 of apnea detector 2;
(3) tumor displacement prediction module 7 is arranged the breathing state that computer receives in chronological order, forms the second breathing state sequence B 1, B 2, Λ, B m, then with the second breathing state sequence B 1, B 2, Λ, B mBe training dataset, adopt minimum mean square self-adaption filter to determine the parameter of breathing state forecast model, and prediction patient m+1 breathing state constantly, m+1 prediction breathing state B ' constantly obtained M+1
After the parameter of having determined the breathing state forecast model, use this utility model system according to the following steps:
(1) detects patient's breathing state B in real time by apnea detector 2 constantly at i i, and by the respiration detection box 21 of apnea detector 2 with breathing state B iSend to tumor displacement prediction module 7 in the computer by wireless mode;
(2) the breathing state B that receives constantly according to i of tumor displacement prediction module 7 iWith i prediction breathing state B ' constantly iBetween difference, adopt minimum mean square self-adaption filter that the parameter of breathing state forecast model is adjusted;
(3) tumor displacement prediction module 7 is according to the breathing state B that receives i, l-1 breathing state B that constantly receives before I-l+1, B I-l+2, Λ, B I-1With the parameter of adjusting breathing state forecast model afterwards, adopt minimum mean square self-adaption filter prediction patient i+1 breathing state B ' constantly I+1, the length of minimum mean square self-adaption filter equals l.The sketch map of actual breathing state and prediction breathing state as shown in Figure 7;
(4) tumor displacement prediction module 7 is according to i+1 prediction breathing state B ' constantly I+1With the relational model of breathing state and tumor displacement, calculate i+1 prediction tumor displacement D ' constantly I+1, its sketch map as shown in Figure 8;
(5) motion-control module 8 is according to i+1 prediction tumor displacement D ' constantly I+1With i prediction tumor displacement D ' constantly iBetween deviation calculate the quantity of motion M that assisted movement mattress 3 needs motion I+1, and send motion control instruction to assisted movement mattress controller 4 by data processor 1;
(6) assisted movement mattress controller 4 rotates according to the servomotor 310 in the motion control instruction control assisted movement mattress 3 that receives, servomotor 310 rotates the leading screw that orders about ball-screw 307 and rotates, the leading screw of ball-screw 307 rotates the nut that drives ball-screw 307 and moves, thereby driving mobile platform 309 moves, and the bed board 312 that links to each other with mobile platform 309 is moved, thereby adjust patient's position, motion to tumor compensates, make tumor the center with constantly align substantially at i+1 with the focus of radioactive source;
(7) whether the time of judging radiotherapy finishes, if the time of radiotherapy does not arrive, then makes i=i+1, forwards (1) to and proceeds radiotherapy; Otherwise the radiotherapy process finishes.
The above is a preferred embodiments of the present utility model, but this utility model should not be confined to the disclosed content of this example and accompanying drawing.So everyly do not break away from the equivalence of finishing under the spirit disclosed in the utility model or revise, all fall into the scope of this utility model protection.

Claims (2)

1. an image and breathe the auxiliary radiation therapy bed mattress system of guiding is characterized in that this system comprises data processor (1), apnea detector (2), assisted movement mattress (3) and assisted movement mattress controller (4);
Apnea detector (2) is connected with data processor (1) communication by wired or wireless mode; Assisted movement mattress (3) is used to be placed on the therapeutic bed of existing radiotherapy apparatus;
Assisted movement mattress controller (4) is connected with data processor (1) and assisted movement mattress (3) respectively;
Data processor (1) is used for the breathing state that apnea detector (2) provides is handled, and calculates the required quantity of motion of assisted movement mattress (3), and offers assisted movement mattress controller (4); The bed board motion of assisted movement mattress controller (4) control assisted movement mattress (3).
2. the auxiliary radiation therapy bed mattress system of image according to claim 1 and breathing guiding, it is characterized in that assisted movement mattress (3) comprises base plate (301), first, second linear guides (302,308), slide block (303), motor mounting plate (304), first, second ball-screw supporting seat (305,306), ball-screw (307), mobile platform (309), servomotor (310), shaft coupling (311) and bed board (312); First linear guides (302), motor mounting plate (304), the first ball-screw supporting seat (305), the second ball-screw supporting seat (306) and second linear guides (308) are fixed on the base plate (301), slide block (303) links to each other with first linear guides (302), be used to support bed board (312), and in upward slip of first linear guides (302), ball-screw (307) is installed on the first ball-screw supporting seat (305) and the second ball-screw supporting seat (306) by bearing, be used for rotatablely moving of servomotor (310) become rectilinear motion, and it is mobile to drive mobile platform (309), mobile platform (309) links to each other with the nut of ball-screw (307), and link to each other with slide block (303) on second linear guides (308), being used to drive bed board (312) moves, servomotor (310) is installed on the motor mounting plate (304), its output shaft is by shaft coupling (311) and coaxial linking to each other of ball-screw (307), bed board (312) is fixed on slide block (303) and the mobile platform (309), first linear guides (302), slide block (303) and bed board (312) are made by carbon fibre material.
CN2010205883272U 2010-11-02 2010-11-02 Auxiliary radiotherapy mattress system with function of image and breathing guidance Expired - Fee Related CN201880220U (en)

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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104258505A (en) * 2014-09-19 2015-01-07 西安交通大学医学院第一附属医院 Anthropomorphic phantom for tumor radiotherapy dosage individualized verification and building method and application thereof
CN112843493A (en) * 2019-11-12 2021-05-28 西安交通大学医学院第一附属医院 Ultrasonic guide radiotherapy assists patient to set a position and uses scanning device
CN114177545A (en) * 2022-01-17 2022-03-15 中国科学院合肥物质科学研究院 Non-contact respiratory rhythm monitoring device and method used in radiotherapy

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104258505A (en) * 2014-09-19 2015-01-07 西安交通大学医学院第一附属医院 Anthropomorphic phantom for tumor radiotherapy dosage individualized verification and building method and application thereof
CN104258505B (en) * 2014-09-19 2017-03-01 西安交通大学医学院第一附属医院 Tumour radiotherapy individuation of dosage checking anthropomorphic phantom and its foundation and application
CN112843493A (en) * 2019-11-12 2021-05-28 西安交通大学医学院第一附属医院 Ultrasonic guide radiotherapy assists patient to set a position and uses scanning device
CN114177545A (en) * 2022-01-17 2022-03-15 中国科学院合肥物质科学研究院 Non-contact respiratory rhythm monitoring device and method used in radiotherapy
CN114177545B (en) * 2022-01-17 2023-11-07 中国科学院合肥物质科学研究院 Contactless respiratory rhythm monitoring device and method for radiotherapy

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