(19) United States
`(12) Patent Application Publication (10) Pub. No.: US 2004/0071261 A1
`(43) Pub. Date:
`Apr. 15, 2004
`Earl et al.
`
`US 20040071261A1
`
`(54)
`
`(75)
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`(73)
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`(21)
`(22)
`
`NOVEL METHOD FOR THE PLANNING
`AND DELIVERY OF RADIATION THERAPY
`
`Inventors: Matt A. Earl, Columbia, MD (US);
`David M. Shepard, Severn, MD (US);
`Xinsheng Yu, Clarksville, MD (US)
`
`Related US. Application Data
`
`(60) Provisional application No. 60/338,118, ?led on Dec.
`3, 2001.
`
`Publication Classi?cation
`
`Correspondence Address:
`SUGHRUE MION, PLLC
`2100 Pennsylvania Avenue, NW
`Washington, DC 20037-3213 (US)
`
`Assignee: UNIVERSITY OF MARYLAND AT
`BALTIMORE
`
`Appl. No.
`:
`
`10/308,090
`
`Filed:
`
`Dec. 3, 2002
`
`(51) Int. Cl.7 ..................................................... .. A61N 5/10
`(52) US. Cl. .............................................................. .. 378/65
`
`(57)
`
`ABSTRACT
`
`A neW optimization method for generating treatment plans
`for radiation oncology is described and claimed. This neW
`method Works for intensity modulated radiation therapy
`(IMRT), intensity modulated arc therapy (IMAT), and
`hybrid IMRT.
`
`Choose
`
`IMAT
`
`Fixed field and Hybrid
`
`6
`
`2617 Select number and rang 2
`
`of arcs
`
`"
`
`7
`
`V
`
`62b L
`
`Approximate art into
`
`series of discrete angles
`
`66
`
`L
`
`Assign initial aperture
`shape for each beam
`direction and calculate
`doie .nd value 0‘
`objective function
`
`1
`
`Filter an aperture L r
`' or weight based on some
`selection procedure
`l
`
`Does the change
`satisfy constraints
`de?ned in step 64
`
`No
`
`68
`
`Hybrid
`
`1
`Select number of delivery
`angles and number of
`apertuns from each angle
`
`72
`
`63
`
`r Fixed field
`
`Divide each field into a grid of
`, discrete pencil beams and
`calculate the dose contribution
`from each
`
`4
`
`Dg‘iide upon
`cllnlcal
`objectives
`
`‘
`
`De?ne geome?c
`constrainu for delivery
`mode and linac
`
`kiss K/M
`
`Is optimization
`?nished?
`
`Calculate new dose
`resulting from change
`and calculate objective
`function based on new
`dose
`
`Accept: or reject
`change based an
`optimization method
`
`Page 1 of 10
`
`Elekta Exhibit 1003
`
`

`
`Patent Application Publication Apr. 15, 2004 Sheet 1 0f 3
`
`US 2004/0071261 A1
`
`1
`
`626 L
`
`Select number and rang :
`of arcs
`
`l MAT
`
`Fixed field and Hybrid
`
`Hybrid
`
`l
`Select: number of delivery 4) 72
`angles and number of
`aperhir? from each angle
`63
`D
`lFixed field
`
`62b L
`
`Appruximah art into
`
`series of discrete angles
`
`Divide each ?eld intn a grid of
`discrete pencil beams and
`calculate the dose contribution
`from each
`
`l
`De?ne georretn'c
`constraints for delivery
`mode and linac
`
`66
`Assign initial aperlaul'e
`17 shape for each beam
`Decide upon
`directlon and calculate ‘- clinical
`dose and value of
`objectives
`objective function
`
`l
`
`67A
`
`Alter an aperture shape
`’ or weight based on some
`selection procedure
`l
`
`NO
`
`68
`
`Does the change
`satisfy constraints
`de?ned in step 64
`
`Calculate new dose
`resulting from change
`and calculate objective
`function based on new
`dose
`
`Is optimization
`?nished?
`
`If")
`
`'
`
`Accept: or rveiect
`change based on
`optimiza?on method
`
`Fig. 1 (NOTE CORRECTION BEING SENT BY FAX)
`
`Figure 2
`
`Page 2 of 10
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`

`
`Patent Application Publication Apr. 15, 2004 Sheet 2 0f 3
`
`US 2004/0071261 A1
`
`iure -
`
`Page 3 of 10
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`

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`Patent Application Publication Apr. 15, 2004 Sheet 3 0f 3
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`US 2004/0071261 A1
`
`v 33E
`
`435.3
`
`04 2
`
`Q5
`
`WUA
`
`sway/n
`
`Z < .E
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`Page 4 of 10
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`

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`US 2004/0071261 A1
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`Apr. 15, 2004
`
`NOVEL METHOD FOR THE PLANNING AND
`DELIVERY OF RADIATION THERAPY
`
`adverse complications can arise in the patient being treated
`because of irradiation of normal structures.
`
`[0001] This is a non-provisional application claiming
`domestic priority from Provisional Application No. 60/338,
`118, ?led on Dec. 3, 2001.
`
`[0002] A computer listing of a program according to an
`exemplary embodiment of the invention is submitted here
`With in a CD-ROM as an Appendix to this application. The
`contents of the CD-ROM are incorporated by reference. The
`computer program is subject to copyright protection.
`
`[0003] This invention Was made With the support of the
`US. government under Grant Number R29CA66075
`aWarded by NIH. The US. government has certain rights in
`this invention.
`
`BACKGROUND OF THE INVENTION
`
`[0004] 1. Field of the Invention
`
`[0005] The present invention relates to a computeriZed
`method for the planning and delivery of radiation therapy. In
`particular, it is a computeriZed method that determines the
`optimal radiation treatment plan for a patient using speci?ed
`clinical objectives.
`
`[0006] 2. Description of Related Art
`
`[0007] Radiation therapy, in general, is the use of ioniZing
`radiation for the treatment of disease. The most common use
`is in the treatment of cancer. The goal of radiation therapy
`for cancer is to destroy any diseased cells While minimiZing
`the damage to healthy tissue. One device for delivering the
`radiation to a patient is With a linear accelerator, a machine
`that generates a high-energy beam of radiation that can be
`controlled and directed onto speci?ed locations. Linear
`accelerators are sometimes equipped With a multi-leaf col
`limator (MLC), a device that shapes each individual beam of
`radiation.
`
`[0008] Prior art treatment planning for conventional can
`cer radiation treatment is often performed With the aid of
`three-dimensional patient images acquired using a computed
`tomography (CT) scanner. Using the three-dimensional
`patient images, the radiation oncologist pinpoints the loca
`tion of the tumor and any surrounding sensitive structures.
`Using the information provided by the radiation oncologist,
`a treatment planner devises the con?guration of radiation
`beams that Will deliver the desired radiation dose to the
`patient. The parameters that need to be determined by the
`treatment planner include the beam energies, beam orienta
`tions, and ?eld shapes. (Levitt et. al., “Technological Basis
`for Radiation Therapy: Clinical Applications”, 3rd Ed., Lip
`pincott, William & Wilkins (1999)) Using a trial-and-ertor
`approach, the treatment planner determines an acceptable
`con?guration of the various parameters that meets the clini
`cal goals speci?ed by the radiation oncologist. This
`approach is called “forward-planning” because a human
`being determines the parameters that produce the best treat
`ment plan. (Levitt, et. al.)
`
`[0009] Prior art treatment planning uses a “forWard-plan
`ning” technique for conventional cancer radiation treatment
`by shaping the radiation ?eld. HoWever, shaping the radia
`tion ?eld alone restricts one’s ability to shape the volume of
`the high radiation dose to conform to the tumor. As a result,
`
`[0010] Arecent development in radiation therapy is inten
`sity-modulated radiotherapy (IMRT) in Which the intensity
`of the radiation delivered is modulated Within each ?eld
`delivered. (Webb, “The Physics of Conformal Radio
`therapy”, Institute of Physics Publishing, Bristol (1997))
`The purpose of IMRT is to sculpt the radiation dose distri
`bution so that it maximiZes the radiation dose to the tumor
`While maintaining the radiation dose to normal structures
`Within some pre-speci?ed tolerance. (Webb) In IMRT,
`highly conformal dose distributions can be achieved through
`the delivery of optimiZed non-uniform radiation beam inten
`sities from each beam angle. Successful delivery of IMRT
`can alloW for an escalation of the tumor dose and may
`enhance local tumor control. The dosimetric advantages of
`IMRT can also be used to provide a reduced probability of
`normal tissue complications.
`
`[0011] Because of the complexity of the treatment plans
`for IMRT, an automated system is required to determine the
`intensity maps that produce the optimal radiation dose
`distribution. In contrast to prior art “forWard planning”
`techniques, this approach is termed “inverse-planning”
`because the automated system determines the parameters
`that produce the optimal radiation treatment plan. (Webb)
`[0012] Currently available IMRT delivery techniques
`include ?xed ?eld beam delivery (IMRT) and intensity
`modulated arc therapy (IMAT). When radiation is delivered
`With ?xed beam angles, a series of beam shapes are deliv
`ered at each beam angle either dynamically, Where the leaves
`of the MLC move during irradiation, or in a step-and-shoot
`fashion, Where the radiation is paused during the movement
`of MLC leaves. (Convery and Rosenbloom (1992), Bortfeld
`et al (1994), Yu, Symons et al (1995);Boyer AL, and Yu
`C.X.; (1999);) In contrast, IMAT uses multiple overlapping
`arcs of radiation in order to produce intensity modulation.
`(Yu, C.X. (1995); Yu et al (2002))
`[0013] The complexity of IMRT and IMAT is such that
`treatment plans cannot be produced through a manual trial
`and error approach. Instead, one must employ an automated
`treatment planning system. Furthermore, current automated
`planning tools are not capable of producing optimiZed plans
`for IMAT.
`
`[0014] Current inverse-planning algorithms for IMRT use
`a tWo-step approach (Boyer and Yu 1999). In the ?rst step,
`the portal that de?nes the radiation beam’s eye vieW (BEV)
`for each radiation beam angle is divided into a set number
`of ?nite-siZed pencil beams. The radiation dose for each of
`these pencil beams is then calculated and the corresponding
`beam intensities are subsequently optimiZed subject to pre
`speci?ed treatment goals. The second step uses the radiation
`intensity maps from each beam angle and translates the
`radiation intensity maps into a set of deliverable aperture
`shapes. During the optimiZation of the radiation intensity
`maps, the delivery constraints imposed by the design of
`various components of the linear accelerator are not taken
`into account resulting in treatment plans that are often
`complex and inef?cient to deliver.
`
`[0015] The tWo step approach used by current inverse
`planning algorithms is unable to generate treatment plans for
`IMAT. With IMAT, the radiation is delivered While the
`
`Page 5 of 10
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`

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`US 2004/0071261 A1
`
`Apr. 15, 2004
`
`gantry rotates continuously. Current inverse-planning algo
`rithms fail to take the gantry’s continuous movement into
`account. One feature of IMAT treatment plans is that the
`aperture shapes for adjacent angles Within an arc must not
`differ signi?cantly. This constraint exists because there are
`limitations on the speed at Which the leaves of the multileaf
`collimator can travel. This constraint makes it dif?cult to
`translate the radiation intensity maps into a set of deliverable
`arcs.
`
`[0016] This invention is an inverse-planning method that
`does not require the current tWo-step approach used for
`IMRT treatment planning. This invention alloWs for the
`planning for either IMRT, IMAT, or a neW type of intensity
`modulated radiotherapy Which comprises a combination of
`IMRT and IMAT. This combination of IMRT and IMAT
`represents a hybrid approach to IMRT. Hybrid IMRT pro
`vides the ability to incorporate into each treatment plan the
`dosimetric advantages of both IMRT and IMAT. For
`example, the rotational nature of IMAT can be used to
`dissipate the deposition of radiation dose to normal tissue
`While the ?xed ?eld capabilities of IMRT alloW for a high
`degree of modulation from any particular beam angle.
`
`SUMMARY OF THE INVENTION
`
`[0017] It is the purpose of this invention to enable a single
`planning system to plan for different modes of IMRT deliv
`ery and to simplify the planning and delivery of IMRT.
`Instead of optimiZing the intensity distributions of the beams
`and then converting them to deliverable MLC ?eld shapes,
`this invention directly optimiZes the shapes and the corre
`sponding Weights of the apertures. The combination of these
`optimally Weighted apertures at every beam angle creates
`highly modulated beam intensity distributions for achieving
`the clinical objectives of the treatment plan. In the process
`of optimiZing the ?eld shapes, all delivery constraints are
`considered. For instance, ?xed-?eld delivery Would have
`constraints imposed by the MLC. Rotational delivery Would
`have additional constraints imposed by the speed of the
`gantry rotation and speed of the MLC leaves.
`
`[0018] For ?xed-?eld delivery, the user speci?es the num
`ber of beams and their angles, the beam energies, and the
`number of apertures per beam angle. For rotational delivery,
`the user speci?es the number and range of the arcs. The
`goals of the treatment plan are determined and then quan
`ti?ed With an objective function, Which can be of dose
`volume based, biological, or of other forms.
`
`[0019] For each delivery angle, the maximum extent of the
`beam aperture is determined based on the beam’s eye vieW
`of the target With suf?cient margins. This beam is then
`divided into a grid of small beamlets called pencil beams.
`The dose distribution from each of these pencil beams is
`calculated using any conventional dose calculation method
`and stored on an appropriate medium, such as a hard drive.
`At the start of the optimiZation, all apertures in the same
`beam direction are set to the same shape as the maximum
`extent of the beam. These apertures are then optimiZed by an
`optimiZation algorithm. The optimiZation process generally
`involves modifying the shape or Weight of the apertures,
`determining if the modi?cation violates the delivery con
`straints, and, ?nally, accepting and rejecting such modi?ca
`tions based on the rules of the optimiZation. For each
`modi?cation, a neW dose distribution computed based upon
`
`the modi?ed aperture shapes or Weights. While simulated
`annealing lends itself Well to the optimiZation method, other
`optimiZation techniques could also be used.
`
`[0020] The output of the algorithm is a set of deliverable
`apertures and their Weights, Which can be transferred to the
`control system of a linear accelerator and delivered to a
`patient. Because of the feature of pre-speci?cation of the
`number of angles and apertures, the user controls the com
`plexity of the treatment plan. Because the invention can
`incorporate the delivery constraints for each particular linac
`and MLC, it can be used in conjunction With any commer
`cially available linear accelerator.
`
`BRIEF DESCRIPTION OF THE DRAWINGS
`
`[0021] FIG. 1 shoWs the How chart for direct aperture
`optimiZation.
`[0022] FIG. 2 illustrates three aperture shapes determined
`using direct aperture optimiZation.
`
`[0023] FIG. 3 illustrates the intensity map for three aper
`ture shapes determined using direct aperture optimiZation;
`
`[0024] FIG. 4 illustrates an apparatus according to an
`embodiment of the invention.
`
`DETAILED DESCRIPTION OF THE
`INVENTION
`
`[0025] Referring to FIG. 4, a linear accelerator (linac) 1
`Which is a device capable of controlled delivery of radiation
`to a patient in need of radiation therapy. The radiation exits
`through the end of the treatment head Which is mounted on
`the gantry (not shoWn). In some linacs, the treatment head is
`equipped With a multi-leaf collimator (MLC) Which shapes
`the radiation ?eld. A linac has a control unit in a housing. A
`linac has a gantry Which can rotate about a horiZontal axis
`H of rotation around the patient Who is lying on the bed. A
`linac emits a beam of radiation Which is aimed at the patient.
`The beam of radiation can be photons, electrons, or any
`other type of radiation used for therapy.
`
`[0026] During treatment, the radiation beam is directed on
`a part of the treatment area on the patient. The gantry can
`rotate about a horiZontal axis of rotation; thus alloWing for
`a change in the angle of treatment.
`
`[0027] A MLC has multiple thin leafs Which can be made
`of tungsten alloy or other heavy materials stacked in tWo
`opposing banks MLCl, MLC2. For one MLC the leaves are
`usually identical in Width, range of travel, and restrictions in
`relation to the other leaves in the same bank or opposing
`banks. MLC leaf restrictions can be characteriZed as static
`constraints and dynamic constraints. Static constraints can
`include, but are not limited to, the maximum distance
`betWeen the most forWard position and the most backWard
`position of any leaf in one bank and the minimum distance
`betWeen opposing leaves in opposing banks. HoWever, it is
`understood that different MLC’s can have Widths ranging
`from 2 mm to 12 mm, range of travel ranging from 1 cm to
`over 32 cm, and different restrictions. Dynamic constraints
`include, but not limited to, the speed of leaf travel, the
`acceleration and deceleration. These static and dynamic
`geometric constraints determine the kind of aperture shapes
`that a particular MLC can form.
`
`Page 6 of 10
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`US 2004/0071261 A1
`
`Apr. 15, 2004
`
`[0028] Within a linac and in addition to the MLC, a beam
`shielding device SLD is provided in the path of radiation
`beam to supplement the MLC in shaping the radiation ?elds.
`The beam shielding device includes a plurality of opposing
`plates. In one embodiment, additional pairs of plates are
`arranged perpendicular to the opposing plates. The opposing
`plates move With respect to the plate axis by a drive unit to
`change the siZe of the irradiated ?eld. The drive unit includes
`an electric motor Which is coupled to the opposing plates and
`Which is controlled by a motor controller. Position sensors
`are also coupled to the opposing plates, respectively for
`sensing their positions. The plate arrangement may alterna
`tively include a multi-leaf collimator (MLC) having many
`radiation blocking leaves.
`
`[0029] In an MLC, there are opposing banks of leaves.
`Each opposing leaf is attached to a drive unit. The drive units
`drive the leaves, in and out of the treatment ?eld, thus
`creating the desired ?eld shape. The MLC leaves, are
`relatively narroW, and cast a shadoW of about 0.5 cm to 1.0
`cm onto the treatment area. The position of the leaves of the
`MLC de?nes the aperture shape for a treatment.
`
`[0030] The intensity of a beam refers to the amount of
`radiation that accumulates at a speci?c location of the
`treatment portal de?ned by the linac.
`
`[0031] A longer radiation exposure time for a speci?c
`location in the treatment portal corresponds to a higher
`radiation intensity. If the MLC opening is ?xed during the
`entire duration of treatment, all locations in the treatment
`portal Would receive approximately the same amount of
`radiation, and there Would be no intensity modulation. A
`modulated intensity radiation ?eld occurs When the MLC
`opening changes such that different locations of the treat
`ment portal are exposed for different durations.
`
`[0032] The motor controller is part of the Linac Control
`System (LCS) that also contains a dosimetry system. The
`dosimetry system measures the output of the radiation beam
`With a measuring chamber MC and reports to the Linac
`Control System (LCS) the amount of radiation being deliv
`ered at any given time. The LCS coordinates radiation
`delivery and MLC leaf movement in order to achieve the
`desired intensity patterns. The LCS controls execution of the
`prescription generated by the present invention and trans
`ferred to the linac control system from the treatment plan
`ning system. During delivery, the MLC leaves move in order
`to achieve the desired treatment.
`
`[0033] During treatment planning, a user is alloWed to set
`the mode of treatment including IMRT or IMAT or a hybrid
`thereof, and to provide other treatment parameters such as
`the orientations of beams, ranges of arcs, the number of
`apertures per beam angle and/or the number of arcs. Using
`the invention described herein, the planning system auto
`matically optimiZes the shape and Weightings of the aper
`tures to best meet the objectives of the treatment The end
`product of the treatment planning process is a treatment plan
`that meets the dosimetric requirements speci?ed by the
`physician. Once a treatment plan is approved by the physi
`cian, the treatment planning system Will generate a prescrip
`tion, Which speci?es the proper coordination betWeen radia
`tion delivery and MLC leaf movements. The prescription,
`therefore, translates the treatment plan into the computer
`language understood by the Linac Control System (LCS)
`and programs the linac for the treatment delivery. The
`
`prescription of conventional treatments can be entered
`manually using a keyboard or other input type of device. For
`IMRT delivery, because of the complexity of the prescrip
`tion, prescriptions are normally entered via digital media,
`such as a diskette or CD, or a netWork link, or any other
`input type of device. At a given time during the delivery of
`radiation to a patient, the LCS is receiving information on
`dose delivery from the dose control unit. The LCS also
`receives information in real-time from the MLC position
`sensors. The LCS compares the dose delivery information
`from both the MLC controller and the dosimetry system
`controller With the prescription. Depending on the result of
`the comparison, the LCS may respond in a variety of
`manners. For example, the LCS may send a signal to the
`beam triggering system to pause the radiation so that the
`MLC can advance to the proper location.
`
`[0034] The present invention covers the method of plan
`ning and delivery of the radiation treatment plan for IMRT,
`IMAT, and hybrid IMRT. The treatment planning procedure
`is performed on a treatment planning system Which is
`distinct from the LCS, so that the treatment planning system
`can generate IMRT treatment plans for all commercially
`available linacs and MLC’s. Prior art IMRT planning inven
`tions can only plan for ?xed-?eld IMRT delivery but not
`IMAT or hybrid IMRT (US. Pat. No. 6,240,161 (Siochi);
`US. Pat. No. 6,260,005 (Yang, et al.)) and there is no
`distinct separation betWeen the treatment planning system
`and the LCS.
`
`[0035] Direct aperture optimiZation (DAO) Which is
`described herein optimiZes the position of the MLC leaves,
`thus optimiZing the aperture shapes, and optimiZes each
`aperture shape’s corresponding intensity based on the treat
`ment goals for a speci?c patient. With DAO, the geometric
`constraints of a MLC associated With either IMRT, IMAT, or
`hybrid IMRT are incorporated during the optimiZation pro
`cess, thereby permitting the development of a treatment plan
`for IMRT, IMAT, and hybrid IMRT in one system. DAO is
`an improvement over prior arts optimiZation methods
`because in the prior art methods each system is dedicated to
`only gantry-?xed IMRT. Inverse planning for IMAT and
`hybrid IMRT Was not possible With prior arts. Another
`distinguishing feature of DAO is that all of the geometric
`constraints imposed by the treatment unit are incorporated
`into the optimiZation. Examples of geometric constraints for
`the MLC and linac include, but are not limited to, the dose
`rate, gantry speed, and minimal amount of radiation that can
`be delivered With acceptable accuracy.
`
`[0036] FIG. 1 shoWs a How chart of the DAO procedure.
`In a ?rst step 60, the mode of delivery is selected. The modes
`of delivery include IMRT, IMAT, or hybrid IMRT. If ?xed
`?eld IMRT or hybrid IMRT is selected, in a step 61, the user
`must select the delivery angles and the number of apertures
`assigned to each angle. Then one proceeds to step 62a if one
`selected hybrid IMRT in a step 60. OtherWise, if one selected
`?xed ?eld IMRT in a step 60, then one proceeds immediately
`to a step 63. If the user selects IMAT in a step 60, then the
`user proceeds immediately to step 62a.
`
`[0037] In a step 62a, one must select the number of arcs
`and the range for each arc. After the consideration factors
`(the delivery angles and number of apertures assigned to
`each angle for DIRT or the number of arcs and range for
`each arc for IMAT) are entered, in a step 62b, the treatment
`
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`Apr. 15, 2004
`
`planning system automatically calculates evenly spaced
`radiation beams to approximate the range of rotation of the
`gantry. Hybrid IMRT required both steps 61 and 62 to
`account for the combined use of ?xed ?eld and arced
`delivery.
`[0038] In a step 63, each ?eld is divided into a grid of
`discrete pencil beams and the dose distribution for each
`pencil beam is computed. The MLC delivery constraints for
`?xed ?eld delivery are determined in a step 64. For rotation
`delivery in a step 64, the constraints associated With rota
`tional delivery are also determined to ensure not only
`coordination of MLC movement With radiation delivery, but
`also the synchroniZation of radiation delivery and gantry
`rotation.
`
`[0039] In a step 65, the user de?nes the clinical objectives
`of the treatment plan. These clinical objectives are used to
`score the quality of the treatment plan throughout the
`optimiZation process. The treatment plan quality can be
`scored by an objective function that reduces the treatment
`plan into a single numerical value. The objective function
`can be, by Way of example only, a least-square dose differ
`ence objective betWeen the desired dose and the achieved
`dose. The objective function can also be based on dose
`volume histograms (DVH) or biological based parameters.
`
`[0040] The optimiZation process begins in a step 66,
`Where the treatment planning system assigns an initial
`aperture shape for each beam angle. In the preferred embodi
`ment, the radiation beam’s eye vieW of the target for each
`beam angle is used for the starting point, but any aperture
`shape for each beam angle can be used. The treatment
`planning system also assigns a relative Weight (intensity) to
`each aperture shape. In addition, the treatment planning
`system calculates the radiation dose, the radiation dose
`distribution, and the dose distribution quality (objective
`function).
`[0041] After obtaining an initial score for the dose distri
`bution quality of the plan, the treatment planning system, in
`a step 67, modi?es an optimiZation variable. The optimiZa
`tion variables that the treatment planning system considers
`include, but are not limited to, the positions of the MLC
`leaves used to shape each aperture for each beam angle, and
`the relative Weight (intensity) of each aperture shape
`assigned to each aperture. A stochastic or deterministic
`approach can be used to determine the variable for modi?
`cation and the siZe of the modi?cation.
`
`[0042] Prior to calculating the neW dose distribution and
`objective function resulting from the modi?cation of the
`optimiZation variable in a step 67, the treatment planning
`system determines, in a step 68, if one or more geometric
`constraints is violated by the modi?cation. Examples of
`geometric constraints include, but are not limited to, the
`MLC leaf positions for the particular linear accelerator, the
`linac gantry speed, the dose rate, and MLC leaf travel speed.
`If the proposed modi?ed aperture shape or intensity violates
`any of geometric constraints, the treatment planning system
`rejects the modi?ed aperture shape and returns to a step 67.
`
`[0043] If none of the geometric constraints is violated in a
`step 68, then the treatment planning system calculates the
`radiation dose applied to the treatment area as a result of the
`modi?cation. The value of the objective function is calcu
`lated from the neW radiation dose, and the dose distribution
`
`quality is compared to the dose distribution quality prior to
`the modi?cation. If the value of the objective function
`changed in the desired direction, the treatment planning
`system accepts the proposed modi?cation of the aperture
`shape. If the radiation dose and dose distribution quality are
`not Within acceptable ranges or the objective function
`changes in the undesirable direction, the treatment planning
`system either accept or rejects the proposed modi?cation of
`the aperture shapes based on a series of pre-set rules and
`returns to a step 67.
`
`[0044] In the preferred embodiment of this invention, a
`simulated annealing algorithm is used in steps 67 through 70
`to determine the optimal aperture shapes and corresponding
`Weights. The optimiZation algorithm randomly selects a
`variable from the set of variables considered in the optimi
`Zation process, i.e., the MLC leaf positions and the Weights
`of the aperture shape. For the selected variable, a change of
`random siZe is sampled from a probability distribution. For
`instance, a Gaussian distribution could be used. In addition,
`the shape of the curve could change With successive iteration
`of the procedure. For instance, the Width of the Gaussian plot
`could decrease according to some schedule such as in
`Formula (1):
`
`wiisslttecgi
`10 (n
`+1)
`
`(l)
`
`[0045] Where A is the initial Gaussian Width, nsucc is the
`number of successful iterations, and TstepO quanti?es the rate
`of cooling. Although the above schedule is speci?c, any
`schedule can be used. For instance, the step siZe could be
`constant throughout the optimiZation. The goal of this inven
`tion is to achieve the optimal aperture shape for each beam
`angle as quickly as possible. Decreasing the amplitude of
`change as the optimiZation progresses alloWs coarse samples
`in the beginning and ?ne-tuning at the end of the optimiZa
`tion process.
`[0046] Other types of optimiZation algorithms can be used
`in this invention such as conjugate gradient or genetic
`algorithms.
`[0047] Based on pre-de?ned termination criteria Which are
`dictated by the optimiZation algorithm, the treatment plan
`ning system Will cease the optimiZation process in step 71.
`The plan With the optimal value of the objective function is
`deemed the optimal plan. This optimum treatment plan is a
`set of deliverable aperture shapes and the intensities asso
`ciated With each aperture shape. Monitor units are units of
`radiation output from a linac.
`
`[0048] In a step 72, the treatment planning system pro
`vides the optimum treatment plan and ?nal radiation dose
`distribution to a user for revieW by displaying the optimum
`treatment plan on a display screen, or printing it out using a
`printer, or placing it on some other user interface Which is
`knoWn in the art ?eld.
`
`[0049] In an optional step 73, the ?nal radiation dose
`distribution resulting from the optimum treatment plan is
`optionally revieWed and approved by a user capable for
`revieWing such information.
`[0050] In a step 74, after optional revieW and approval, the
`optimum treatment plan is transferred from the treatment
`
`Page 8 of 10
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`

`
`US 2004/0071261 A1
`
`Apr. 15, 2004
`
`planning system performing the direct aperture optimization
`to the LCS in the form of a Prescription ?le. The optimal
`treatment plan is loaded onto the LCS via a diskette, a
`computer netWork link, or any other means knoWn in the art
`?eld capable of transferring data betWeen tWo distinct com
`puters. This invention alloWs the direct aperture optimiZa
`tion information to be transmitted from the treatment plan
`ning system located at one site to the linac control system
`(LCS) located at a different site.
`
`[0051] Because the treatment planning system is distinct
`from the linac control system (LCS), one can optimiZe
`several different treatment plans for different types of linear
`accelerators in succession or concurrently.
`
`[0052] FIG. 2 illustrates three aperture shapes obtained by
`using the DAO of this invention assigned to a radiation beam
`direction. As compared With the aperture shapes obtained
`from a typical leaf sequencing step using the prior art
`treatment planning programs, the exposed area of each
`aperture shape is signi?cantly increased, resulting in greater
`ef?ciency in delivery.
`
`[0053] FIG. 3 illustrates the intensity distribution created
`With the three apertures shoWn in FIG. 2. Theoretically, the
`number of intensity levels, N, resulting from n apertures can
`be expressed as: N=2“—1. For example, With three aperture
`shapes per beam, seven intensity levels can be created.
`Moreover, because each intensity level is a free-?oating
`percentage of the maximum intensity as compared to ?xed
`percentage of the maximum intensity in the previous arts of
`IMRT planning, the seven intensity levels created by over
`lapping directly optimiZed apertures give more ?exibility to
`the planning system in creating optimal treatment plans. In
`the prior art IMRT treatment planning, an intensity pattern
`containing 7 intensity levels Would require 15 to 30 aper
`tures to realiZe, resulting in very inef?cient treatment deliv
`ery. Moreover, When such large number of apertures is used,
`the aperture shapes are generally small, requiring very high
`accuracy in the positions of the MLC leaves. As the result,
`quality assurance efforts must be intensi?ed to l