METHOD TO DETERMINE A PATIENT DOSE DISTRIBUTION AND CORRESPONDING RADIATION DOSIMETRY APPARATUS

Abstract

In a method to determine a patient (radiation) dose distribution (13), it is provided to calculate, from a measured signal (7) of a detector (6) placed behind a region of interest, a dose distribution (11) for a patient-shaped water equivalent phantom (12) and to compute from this a patient dose distribution (13) that takes into account inhomogeneities of a matter distribution of the patient (4).

Claims

1. A method to determine a patient dose distribution (13) by an external radiation beam (5), the method comprising: measuring radiation by a detector (6) during or prior to therapy or after therapy; applying an algorithm to convert a measured signal (7) of the detector into a dose distribution (11) for a patient-shaped water equivalent phantom (12) in a first step (18); and converting the dose distribution (11) for the patient-shaped water equivalent phantom (12) in a second step into the patient dose distribution (13) by applying a correction (14) based on an inhomogeneous matter distribution of the patient (4).

2. The method according to claim 1, further comprising measuring the measured after traversing the patient (4) to reconstruct the patient dose distribution (13) delivered during therapy.

3. The method according to claim 1, further comprising measuring the radiation free in air to determine the patient dose distribution (13) prior to therapy or after therapy.

4. The method according to claim 1, wherein the algorithm to determine the dose distribution (11) of the patient-shaped water equivalent phantom (12) is based on calibration data taken from measurements using a water equivalent substance.

5. The method according to claim 1, wherein a radiation propagation algorithm is used that calculates from a measured signal (7) which is lower dimensional a higher dimensional dose distribution (11, 13).

6. The method according to claim 1, further comprising accumulating an angle-wise propagated dose distribution of the patient-shaped water equivalent phantom (12) for several consecutive incident radiation beam (5) angles (φ), per beam, per control point, per arc, or for a sum of all said arcs or said angles or said beams.

7. The method according to claim 1, wherein the inhomogeneous matter distribution contains a density distribution information of the patient (4).

8. The method according to claim 1, further comprising calculating the inhomogeneity correction (14) per incident radiation beam (5) angle (φ), for several consecutive ones of the incident radiation beam angles (φ), per beam, per control point, per arc, or for a sum of all said arcs or said angles or said beams using an amount of incident radiation.

9. The method according to claim 1, further comprising calculating the patient dose distribution (13) per incident radiation beam (5) angles (φ), for several consecutive ones of the incident radiation beam angles (φ), per beam, per control point, per arc, or for a sum of all said arcs or said angles or said beams.

10. The method according to claim 1, wherein at least one of: a) an amount of incident radiation is generated for each incident radiation beam (5) angle (φ) according to a treatment plan orb) the treatment plan contains data of at least one of a cross section or an intensity of the incident radiation beam (5).

11. The method according to claim 1, further comprising comparing the patient dose distribution (15) to a planned patient dose distribution (17) according to a treatment plan.

12. The method according to claim 1, wherein at least one of a CT, daily CBCT, MR data of a patient (4), or treatment planning data is used in at least one of the first step or the second step.

13. The method according to claim 1, wherein at least one of a 0D, 1D, or 2D detector (6) is used.

14. A radiation dosimetry apparatus (20) configured to perform the method according to claim 1.

15. The method according to claim 4, wherein the measurements are taken using photon beams of therapeutically relevant and/or MeV energies.

16. The method according to claim 5, wherein the radiation propagation algorithm is a back-projection (10) or forward-projection (21) algorithm.

17. The method according to claim 13, wherein the detector (6) is an electronic portal imaging device.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The invention will now be described in more detail with reference to a specific example. However, the invention is by no means limited to that example. Other working examples of the invention are conceivable, in particular through a combination of the features of one claim with the features of some of the claims or with various features of the example.

[0042] In particular, it is shown in

[0043] FIG. 1 a schematic view of the various steps of a method according to the invention,

[0044] FIG. 2 a detailed view of the left box of FIG. 1,

[0045] FIG. 3 a detailed view of the center box of FIG. 1,

[0046] FIG. 4 a detailed view of the right box of FIG. 1,

[0047] FIG. 5 a schematic view showing a calculation of an in aqua correction IAC for conversion of a measured signal into a in aqua dose,

[0048] FIG. 6 a schematic view showing a calculation of a dose inhomogeneity correction DIC based on the inhomogeneous matter distribution of the patient,

[0049] FIG. 7 an alternative to FIG. 3, starting from STEP C of FIG. 1,

[0050] FIG. 8 an alternative to FIG. 4, starting from STEP F′ of FIG. 7, and

[0051] FIG. 9 an alternative arrangement of a detector.

DETAILED DESCRIPTION

[0052] FIG. 1 shows a gantry 1 having a radiation source 2, a couch 3 for a patient 4. The radiation source 2 may be rotated about an axis parallel to the patient 4 to position the radiation source 2 in various gantry angles φ relative to the patient 4.

[0053] The radiation source 2 generates a radiation beam 5 that is disseminated towards the patient 4 according to a treatment plan. The treatment plan can, for example, define an intensity and/or a cross-section and/or energy of a radiation beam for various gantry angles φ.

[0054] Opposite the radiation source 2 there is a detector 6, e.g. a 2D detector like an EPID (Electronic Portal Imaging Device), for detecting an amount of radiation traversing the patient 4. In case of verification before or after patient treatment, the radiation traverses air.

[0055] In other examples, the detector may be adapted to record lower dimensional or higher dimensional signals.

[0056] The detector 6 in FIG. 1 produces a measured signal 7 that has to be converted, by means of detector-specific data, into a measured dose 8. The measured dose 8 in this example is a 2D field of data.

[0057] The detector 6 and a computation unit (not shown) to carry out at least first and second steps described below for a radiation dosimetry apparatus 20.

[0058] Using the incident angle or gantry angle φ, treatment planning information and the density information of the patient (e.g. CT data), an in aqua dose 9 is calculated for all gantry angles cp. It may be said that the in aqua dose 9 is the dose, for the measured dose 8, that would have been obtained had the patient 4 consisted of a water equivalent matter.

[0059] In particular, as an example but not limiting, the primary portal dose distribution Pr.sub.i,j.sup.EPID (the measured dose 8) is converted into the in aqua primary portal dose distribution Pr.sub.i,j.sup.EPID_IA (in aqua dose 9), the equivalent primary portal dose distribution that would be measured behind the water-filled patient. This is achieved by applying an in aqua correction IAC.sub.i,j which is defined as the ratio between the primary EPID dose transmission T.sub.i,j.sup.CT calculated with the water-filled patient and the patient CT data sets (cf. FIG. 5):

[00001]$\begin{array}{cc}P{r}_{i,j}^{\mathrm{EPID}\_\mathrm{IA}}=P{r}_{i,j}^{\mathrm{EPID}}.Math.{\mathrm{IAC}}_{i,j}=P{r}_{i,j}^{\mathrm{EPID}}.Math.\frac{T_{i,j}^{\mathrm{CT},\mathrm{water}}}{T_{i,j}^{\mathrm{CT},\mathrm{patient}}}& \left(1\right)\end{array}$

[0060] The indices i,j denote pixel position on the 2D detector, which is in this example an electronic portal imaging device.

[0061] The in aqua correction factor IAC.sub.i,j ‘removes’ the effect that patient inhomogeneities have on the primary dose detected at EPID level. T.sub.i,j.sup.CT is calculated using the radiological thickness of the patient t the linear attenuation coefficient of water for a specific beam energy μ and the beam hardening coefficient σ as shown in Eq. (2):

[00002]$\begin{array}{cc}{T}_{i,j}^{CT}=e^{\left(-\mu .Math.t_{\mathrm{ij}}^{\mathrm{radiol}}+\sigma .Math.{\left(t_{\mathrm{ij}}^{\mathrm{radiol}}\right)}^2\right)}& \left(2\right)\end{array}$

[0062] The radiological thickness may be computed using properly oriented and/or aligned CT data or other density distribution information of the patient 4.

[0063] Then, a back-projection 10 algorithm (as an example of a radiation propagation algorithm) uses the in aqua primary portal dose distribution Pr.sub.i,j.sup.EPID_IA to reconstruct (for all gantry angles φ) the delivered dose to the water-filled patient D.sub.i,j,k.sup.EPID_IA or dose distribution 11 for the patient-shaped water equivalent phantom 12.

[0064] Here, the back-projection 10 algorithm may be based on calibration data taken from measurements using photon beams of therapeutically relevant MeV energies using a water equivalent substance.

[0065] This concludes a first step 18 of the method.

[0066] From FIG. 1, it can be seen that the first step 18 comprises (sub)steps A through D.

[0067] In a second step 19, in particular in a substep E, the dose distribution 11 for the (hypothetical) patient-shaped water equivalent phantom 12 is converted into patient dose distribution 13, for instance by applying a voxel-by-voxel dose inhomogeneity correction DIC.sub.i,j,k:

[00003]$\begin{array}{cc}{D}_{i,j,k}^{\mathrm{EPID}\_\mathrm{IA}\_\mathrm{DIC}}=D_{i,j,k}^{\mathrm{EPID}\_\mathrm{IA}}.Math.{\mathrm{DIC}}_{i,j,k}=D_{i,j,k}^{\mathrm{EPID}\_\mathrm{IA}}.Math.\frac{D_{i,j,k}^{\mathrm{MC},\mathrm{patient}}}{D_{i,j,k}^{\mathrm{MC},\mathrm{water}}}& \left(3\right)\end{array}$

[0068] The indices i,j,k denote points in a 3D region.

[0069] The correction is defined as the ratio between patient and water-filled patient dose calculations, as schematically shown in FIG. 6.

[0070] In this example, the Monte Carlo (MC) dose engine SciMoCa of Radialogica LLC, Missouri, USA was used for dose calculation. Other dose engines that are suitable to calculate the dose for inhomogeneous matter distributions accurately may be used as well.

[0071] Dose inhomogeneity correction DIC tensors were calculated in this example for each beam in IMRT (Intensity Modulated Radiation Therapy) and 3DCRT (3D Conformal Radiation Therapy) plans and for each arc in VMAT (Volumetric Arc Therapy) plans and applied accordingly.

[0072] Turning back to FIG. 4, an accumulated patient dose distribution D.sub.i,j,k.sup.EPID_IA_DIC is computed by summing over all beam patient dose distributions in case of IMRT and 3DCRT and all arc patient dose distributions in case of VMAT.

[0073] The accumulated patient dose distribution as well as the patient dose distributions per beam/arc may be compared, in a computer-assisted comparison 16, to the corresponding accumulated dose distribution and/or the corresponding beam/arc dose distributions 17 from a treatment plan.

[0074] It can be seen from the figures that the measured signal 7, the measured dose 8 and the in aqua dose 9 are 2D data fields corresponding to 2D measurements, while dose distributions 11, 13, 15, and 17 after the back-projection 10 comprise 3D data fields corresponding to spatial dose distributions.

[0075] Hence, the back-projection 10 generates a higher dimensional data field from a lower dimensional one, in particular through a simulation or computation of the course of incident radiation. For this, a physical model of the radiation process can be used.

[0076] In general, the physical method or computation algorithm is adapted to measurements using photon beams of therapeutically relevant, viz. at MeV energies.

[0077] In other examples, detectors that generate data fields of dimensionality below 2 or above 2 will be used.

[0078] In another example, the method as described above is performed without a patient 4 on the couch 3. In other words, the measured signal 7 of the detector 6 corresponds to the interaction of the incident beam 5 with air.

[0079] This will allow to reconstruct a dose distribution 11 for the patient-shaped water equivalent phantom 12 as described above.

[0080] The resulting patient dose distribution 15 may be used to verify a planned dose distribution 17 prior to therapy or after therapy.

[0081] FIG. 7 shows an alternative example of a method according to the invention. The diagram of FIG. 7 may be thought of as setting in at STEP C in FIG. 1, thereby replacing the box of FIG. 2. Structurally or functionally similar or identical elements will be denoted by reference numerals as in FIGS. 1 and 2. Thus, explanations given in the context of FIGS. 1 and 2 are applicable to FIG. 7 as well.

[0082] FIG. 7 differs from FIG. 2 in that, in a substep E′, the dose distribution 11 for the (hypothetical) patient-shaped water equivalent phantom 12 is summed, or accumulated, over a beam, e.g. for IMRT/3DCRT type therapies, or over an arc, e.g. for VMAT type therapies, before, in a substep F′, dose inhomogeneity corrections DIC.sub.i,j,k will be applied.

[0083] In other words, therefore, D.sub.i,j,k.sup.EPID_IA(φ) was accumulated, in this example, per arc for VMAT plans and per beam with respect to IMRT or 3DCRT plans.

[0084] To this end, the dose inhomogeneity corrections have been computed for a beam or an arc, respectively, such that, for example, an angular resolution of the dose inhomogeneity correction DIC.sub.i,j,k matches an angular resolution of the accumulated dose distribution D.sub.i,j,k.sup.EPID_IA(arc).

[0085] Correspondingly, FIG. 8 shows a variant of FIG. 3 that follows substep F′ of FIG. 7. It can be seen that a comparison of measured dose distributions to a treatment plan 17 can be performed per beam or per arc, depending on the type of therapy, or for total accumulated values over all beams or arcs.

[0086] FIG. 9 shows a schematic view of an alternative example for a radiation dosimetry apparatus 20. Again, structurally and/or functionally identical or similar elements are denoted as in FIGS. 1 and 2. Thus, explanations given to FIGS. 1 and 2 may be read together with FIG. 9 as well. The arrangement of FIG. 9 may, for example, replace the one of FIGS. 1 and 2.

[0087] The arrangement of FIG. 9 differs from FIGS. 1 and 2 in that, inter alia, the detector 6 is located between radiation source 2 and patient 4.

[0088] Thus, substep D in FIG. 1, 2 or 7 will not be carried out by a back-projection 10 but by a forward-projection 21 (cf. FIGS. 1 and 7, where forward-projection 21 may replace or complement back-projection 10).

[0089] In a method to determine a patient (radiation) dose distribution 13, it is proposed to calculate, from a measured signal 7 of a detector 6 placed behind a region of interest, a dose distribution 11 for a patient-shaped water equivalent phantom 12 and to compute from this a patient dose distribution 13 that takes into account inhomogeneities of a matter distribution of the patient 4.

LIST OF REFERENCE NUMERALS

[0090] 1 gantry [0091] 2 radiation source [0092] 3 couch [0093] 4 patient [0094] 5 radiation beam [0095] 6 detector [0096] 7 measured signal [0097] 8 measured dose [0098] 9 in aqua dose [0099] 10 back-projection [0100] 11 dose distribution for the patient-shaped water equivalent phantom [0101] 12 patient-shaped water equivalent phantom [0102] 13 patient dose distribution [0103] 14 (inhomogeneity) correction [0104] 15 accumulated patient dose distribution [0105] 16 comparison [0106] 17 planned dose distribution [0107] 18 first step [0108] 19 second step [0109] 20 radiation dosimetry apparatus [0110] 21 forward-projection