X-ray or gamma ray systems or devices – Specific application – Absorption
Reexamination Certificate
2001-03-15
2003-05-06
Dunn, Drew A. (Department: 2882)
X-ray or gamma ray systems or devices
Specific application
Absorption
C378S064000
Reexamination Certificate
active
06560311
ABSTRACT:
STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT
BACKGROUND OF THE INVENTION
The present invention relates generally to radiation therapy planning for the treatment of tumors and suitable for radiation therapy machines providing independent intensity modulated narrow beams of radiation.
Radiation therapy involves the treatment of tumorous tissue with high energy radiation according to a treatment plan. The treatment plan controls the radiation's placement and dose level so that the tumorous tissue receives a sufficient dose of radiation while the radiation to surrounding and adjacent non-tumorous tissue is minimal.
Intensity modulated radiation therapy (IMRT) treats a patient with multiple rays of radiation each of which may be independently controlled in intensity and/or energy. The rays are directed from different angles about the patient and combine to provide a desired dose pattern. Typically, the radiation source consists of either high-energy X-rays, electrons from certain linear accelerators, or gamma rays from highly focused radioisotopes such as Co
60
.
Methods of producing intensity modulated rays of radiation are well known in the art and include the stop and shoot method, (Xia, P., Verhey, L. J., “Multileaf Collimation Leaf Sequencing Algorithm for Intensity Modulated Beams with Multiple Static Segments,”
Medical Physics
, 25:1424-34 (1998)), the sliding window technique (Bortfeld, et al., “Realization and Verification of Three-Dimensional Conformal Radiotherapy With Modulated Fields,”
Int'l J. Radiat. Oncol. Biol. Phys
., 30:899-908 (1994)), intensity modulated arc therapy, (Yu, C. X., “Intensity-Modulated Arc Therapy With Dynamic Multileaf Collimation: An Alternative to Tomotherapy,”
Physics in Medicine & Biology
, 40:1435-49 (1995)), and sequential (axial) tomotherapy, (Carol, et al., “The Field-Matching Problem as it Applies to the Peacock Three Dimensional Conformal System for Intensity Modulation,”
Int'l J. Radiat. Oncol. Biol. Phys
., 34:183-87 (1996)).
One highly accurate IMRT method uses a planar fan beam which orbits the patient in the plane of the beam to treat a single slice of the patient at a time. Prior to reaching the patient, the fan beam is passed through a multileaf collimator (MLC) consisting of a series of opaque leaves. As the radiation source rotates around the patient, the tungsten leaves move into and out of the radiation beam modulating the intensity of individual rays of the fan beam.
An intensity value for each ray of the fan beam at each angle of the fan beam about the patient and for each slice of the patient is defined by a treatment sinogram. The treatment sinogram is prepared by a physician based on a dose map indicating the amount of radiation dose and its location throughout the patient.
Preparation of a treatment sinogram from a dose map is extremely complicated. Examples include simulated annealing (Langer M. And Morrill S., “A Comparison of Mixed Integer Programming and Fast Simulated Annealing For Optimized Beam Weights in Radiation Therapy,”
Medical Physics
, 23:957-64 (1996)), linear programming (Langer M. and Leong J., “Optimization of Beam Weights Under Dose-Volume Restrictions,
Int'l. J. Radiat. Oncol. Biol. Phys
., 13:1225-60 (1987)), non-linear programming (Bortfeld et al., “Methods of Image Reconstruction From Projections Applied to Conformal Radiotherapy”
Phys. Med. Biol
., 35:1423-34 (1990)), mixed-integer programming (Langer M. And Morrill S., “A Comparison of Mixed Integer Programing and Fast Simulated Annealing For Optimized Beam Weights in Radiation Therapy,”
Medical Physics
, 23:957-64 (1996)), and iterative filtered backprojection (Holmes et al., “An Iterative Filtered Backprojection Inverse Treatment Planning Algorithm for Tomotherapy,”
Int'l. J. Radiat. Oncol. Biol. Phys
., 32:1215-1225 (1995)). Another method is the “Dynamically Penalized Likelihood” method suggested by Llacer and described in U.S. Pat. No. 5,602,892.
Many of these methods place severe burdens on computer memory. For example, in tomotherapy applications, a medium sized radiation treatment plan will often involve storing intensities of over 91,000 rays of radiation. Tracking the dose provided by these rays may require storage of more than 2.7×10
11
dose elements.
BRIEF SUMMARY OF THE INVENTION
The present invention provides a method and apparatus for generating treatment sinograms from dose maps.
More specifically, the present invention provides a method for optimizing a radiation treatment plan for a radiotherapy machine providing independently controlled radiation along a plurality of rays j directed towards a patient to deliver dose D
i
d
=d
ij
w
j
to voxels i. In a first step, a prescribed total dose D
i
p
at the voxels i in a treatment area is received from a physician and a fluence w
j
value is assigned to each ray j. An actual total dose D
i
d
produced at each voxel i with the assigned fluence values w
j
is then calculated. The fluence values w
j
are then modified according to an update function of the prescribed dose D
i
p
and the actual dose D
i
d
without reference to the dose per energy fluence, d
ij
, delivered to each voxel by the given ray j. Finally the modified fluence values w
j
are used to control the radiotherapy machine.
Thus it is one object of the invention to provide a method of determining fluence values of multiple rays used in a radiation therapy session without the need to store partial dose values for each ray.
In one embodiment, the update function may be a ratio of the prescribed dose D
i
p
and the actual dose D
i
d
for each voxel i receiving radiation from the given ray j or for example:
w
j
(
k
+
1
)
=
w
j
k
∑
i
aD
i
p
∑
i
aD
i
d
k
where w
j
(k+1)
and w
j
k
are the fluence values before and after the modification of the fluence of the rays and a is a predetermined approximation of dose per magnitude of energy fluence, d
ij
.
Thus it is another object of the invention to provide a computationally simple method of modifying ray fluences such as may be rapidly executed on an electronic computer. By using an approximation of dose per energy fluence, d
ij
, or dose per any magnitude related to energy fluence, the above described problems of storing and calculating partial dose are avoided.
In an alternative embodiment, the update function may be a ratio of the prescribed dose D
i
p
and the actual dose D
i
d
for each voxel i receiving radiation from the given ray j or for example:
w
j
(
k
+
1
)
=
w
j
k
(
∏
i
n
D
i
p
)
1
n
(
∏
i
n
D
i
d
k
)
1
n
where w
j
(k+1)
and w
j
k
are the fluence values before and after the modification of step (d).
Thus it is another object of the invention to provide a function for modifying fluences of the rays to converge to produce the desired dose having no partial dose d
ij
term.
The foregoing and other objects and advantages of the invention will appear from the following description. In the description, reference is made to the accompanying drawings which form a part hereof and in which there is shown by way of illustration a preferred embodiment of the invention. Such embodiment does not necessary represent the full scope of the invention, however, and reference must be made to the claims herein for interpreting the scope of the invention.
REFERENCES:
patent: 5647663 (1997-07-01), Holmes
patent: 5782739 (1998-07-01), Criss et al.
patent: 6038283 (2000-03-01), Carol et al.
patent: 6393096 (2002-05-01), Carol et al.
patent: 6411675 (2002-06-01), Llacer
Sandham W.A. et al: “Conformal Therapy Using Maximum Entropy Optimization”, International Journal of Imaging Systems and Technology, US, Wiley and Sons, New York; vol. 6, No. 1, p. 80-90; XP000620336; ISSN: 0899-9457.
Gustaffson A. et al: “A Generalized Pencil Beam Algorithm for Optimization of Radiation Therapy”, Medical Physics, US, American Institute of Physics, New York; vol. 21, No. 3, p. 343-356; XP000435143; ISSN: 0094-2405.
Hoban Peter
Mackie Thomas R.
Olivera Gustavo H.
Reckwerdt Paul J.
Shepard David M.
Quarles & Brady LLP
Thomas Courtney
Wisconsin Alumni Research Foundation
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