IMRT: Treatment Planning and Dosimetry

1. IMRT: Treatment Planning and Dosimetry Nesrin Dogan, Ph.D Department of Radiation Oncology Virginia Commonwealth University Medical College of Virginia Hospitals Richmond, VA, USA

2. Fundamental Issues • Beam Modeling • Dose Calculation • Inverse Planning • IMRT QA

3. 1 cm 1 cm 1 cm 1 cm 1 cm 1 cm 1 cm 1 cm 1 cm 1 cm Beam Modeling • For small fields, minor uncertainties due to approximations in dose calculation models, methods for determining MLC leaf sequences and other factors may form a large fraction of dose delivered, and lead to inaccuracies in delivered dose. 10 cm

4. Beam Modeling, cont. • Dosimetric accuracy of the IMRT plan delivery depends on the accurate representation of • Accurate Beam Penumbra representation – MLC / collimator jaws. • Adequate characterization and accounting of transmission and scattering properties of MLC leaves. • Output factor for small field size. • Accuracy of dose calculation algorithm. • Approximations of leaf sequence generation algorithm. • Leaf positioning accuracy.

5. Penumbra • Need to be measured with microchamber, film or diode. • Subtle effects make a difference in IMRT. Beam model based on penumbra measured with 6 mm diameter chamber Beam model based on penumbra measured with film Courtesy of G. Ezzel, Ph.D., Mayo Clinic

6. ~1.5% ~12% ~1% ~2.5% MLC Leaf Characteristics • Inter- and intra-leaf transmission • Tongue-and-groove – can lead to under-dosages ~30% in a 2 mm wide region • Rounded tip

7. Radiation Field Offset for Rounded Leaf Ends • Offset for between the light and radiation field edge = ~0.6 mm Measuring the offset 0.6 is best, i.e. subtract 0.6 mm from MLC settings -> TPS should take care of this Courtesy of G. Ezzel, Ph.D., Mayo Clinic

8. MLC Leaf Transmission and Scattering • Leaf leakage • transmission • rounded leaf tip transmission • MLC scatter • Collimator scatter upstream from the MLC. • Leakage through closed opposing leaf pair for rounded ends ~20% - leaves should be parked under the jaw • Minimum gap between opposed leaves = 0.5 -0.6 mm to avoid collisions Leakage through leaf ~2% Leakage between neighboring leaf ~5% Courtesy of G. Ezzel, Ph.D., Mayo Clinic

9. Output Factor Small Fields Micro cham: 0.009cc PTW: 0.125cc Farmer:0.65cc D.A. Low et al. “Ionization chamber volume averaging effects in dynamic intensity modulated radiation therapy beams, Med.Phys.30(7): 1706-1711 (2003).

10. MLC and Small Fields • Output for small fields very dependent on MLC accuracy. • 10%/mm for 1 cm segment. Courtesy of G. Ezzel, Ph.D., Mayo Clinic

11. Which Detectors to Use? • Need to determine energy dependence and angular response. • Small field detectors required for small field characterization. • Sensitive to position • Detector should be smaller than homogeneous region of dose to be measured • Assess electrometer response.

12. Small 1-D Detectors Courtesy of Jean Moran, Ph.D, UofMichigan

13. EPID: DMLC measurements Predicted EPID Ion Chamber Overall: Good agreement + 10 MV 25 MV Discrepancies in the penumbra region (up to 10%) Pasma Med Phys 26: 2373-2378 (2376) 1999 Courtesy of Jean Moran, UofMichigan

14. Dose Calculation • Current IMRT systems use simplified dose calculations during plan optimization: e.g., pencil beam ->uses very simple heterogeneity corrections, causing significant dose errors (10% or more non-IMRT cases) • Final dose calculation is performed using a separate independent dose calculation that incorporate the influence of the MLC: e.g, convolution / superposition; more accurate than Pencil beam; however, inaccuracies persist under certain circumstances

15. Conventional dose algorithms can be inaccurate for • Small fields • Regions of dose gradients (radiation disequilibrium) • Heterogeneous conditions IMRT is typically delivered through a sequence of small static fields or with a dynamically moving aperture with a small width. Dose gradients are common place in IMRT fields. For such fields, assumptions used in conventional algorithms regarding scatter equilibrium and output factor variation with field size typically break down.

16. For IMRT • Significant fraction of the dose within targets and organs at risk is due to scattered or leakage radiation • calculated dose distributions have the greatest uncertainties due to approximations inherent in conventional methods of transforming intensities into MLC leaf sequences • Experimental checks of IMRT fields routinely shows discrepancies between the planned (desired) and actual.

17. Dose Calculation Algorithms Pencil Beam Superposition/Convolution Calculation Speed Monte Carlo Calculation Accuracy Courtesy: Jeff Siebers, VCU

18. Comparison of SC and MC Comparison of a) Superposition-Convolution (SC) and b) MC dose calculations

19. Comparison of PB and MC Pencil Beam Monte Carlo Pencil Beam Monte Carlo Pawlicki et al., Med Dosim, 26 157 (2001)

20. Comparison of SC and MC Slice 45 Superposition Slice 55 Slice 64 Superposition Superposition Monte Carlo Monte Carlo Monte Carlo

21. Consequences of Inaccuracy • Dose Prediction Error (DPE) • For a given intensity distribution, dose predicted differs from that actually delivered to the patient/phantom • Can be avoided by performing final calculation with accurate algorithm • Optimization Convergence Error (OCE) • Consequence of systematic error during optimization • Optimization with an inaccurate algorithm results in different intensities than those predicted by an accurate algorithm • Actual dose is not optimal, a better solution exists • Can be avoided by optimization with an accurate algorithm

22. DPE(same intensities) PB computed 68 Gy64 Gy60 Gy50 Gy40 Gy30 Gy SC computed Make sure your final dose calculation is with an accurate algorithm

23. OCE(different intensities) 68 Gy64 Gy60 Gy50 Gy40 Gy30 Gy SC optimization SC calc PB optimization SC calc

24. Leaf positions do not exist Optimization Create Leaf Sequence Leaf Sequencer Create Deliverable Intensities “Deliverable” Dose Calculation Deliverable Plan Conventional IMRT Optimization Process

25. Problems with Conventional IMRT process • Optimized plans are converted to deliverable plans through leaf-sequencing process that takes into account the limitations and effects (leakage/scatter) of the MLC • The idealized optimal plan is replaced with “deliverable” plan • Optimized and deliverable IMRT plans differ • Different intensity distributions • More complex the intensity distribution, the greater the deviation

26. Comparison of Isodoses a) An optimized intensity distribution b) A deliverable distribution using DMLC calculated using Convolution/Superposition algorithm

27. Initial Intensity (II(x,y)) 1 Create Leaf Sequence 7 Create Deliverable Intensities (ID(x,y)) 8 Compute Dose (DO) 2 6 Evaluate Plan Objective Adjust I(x,y) 3 Converged? 4 No Yes Optimized Intensity (IO(x,y)) and Dose DO = DD 5 Deliverable IMRT Optimization Process Leaf Sequencing combine optimization and delivery into one process Final dose is deliverable

28. Original SCopt Deliverable Plan SC MCopt (deliverable) MC of Deliverable Deliverable Optimization Head and Neck IMRT plan Deliverable optimization can restore original optimized plan

29. Heterogeneity Corrections w /Hetero • More important for IMRT than conventional treatments. • Heterogeneities may effect some beamlets more than others -> causing different localized dose differences. • The reliability of clinical experience with DVH prescriptions and results may be significantly compromised if heterogeneity corrections are not used (e.g., Lung). • Use AAPM Report No:85 Tissue Inhomogeneity Corrections for Megavoltage Photon Beams. • 4% - 10% error in relative e- density result in ~2% error in dose. w/o Hetero

30. Dose Grid • Size of the OARs. • Dose gradients near the • OARs. • Finer dose grids are • necessary for cases in • which high gradients are • needed. • Dose grid should be finer • than the size of the • beamlets or incident fluence • map so that the effects of • modulation are adequately • sampled.

31. What do we do about differences? • May need to adjust the beam model. • May need to live with it. • Take known deficiencies into account when evaluating plans • May be important for OARs.

32. Buildup Region • Important when target regions (PTV) extend into the buildup region. • Calculated doses are often inaccurate and lower than delivered doses. • Likely to cause hot spots in the target and elsewhere as a result of inverse planning engine fighting with the buildup effect – may cause excessive skin reactions and compromise the plan quality. • Bolus needs to be added if the target is in the buildup region: needs to be included during the scanning of patient.

33. Target and OARs • Definition of Target Volumes • GTV, CTV and PTV need to be explicitly defined • Consistent with the ICRU definitions (ICRU 50) • Definition of OARs • Planning OAR Volume (ICRU 62) • Need to • Use contrast-enhanced CTs • Image fusion (PET, MRI, preopt CTs, etc..)

34. Margins for Targets • IMRT does not inherently demand for tight target margins. • CTV to PTV margins depends on each individual patient and the patient immobilization / location techniques used. • Tight target margins can be achieved by improved imaging for planning, immobilization and image-guided verification.

35. Automatic CTV expansions • Automatic CTV expansions may unrealistically cross tissue boundaries. Realistic for CTV? Courtesy of G. Ezzel, Ph.D., Mayo Clinic

36. Margins for OARs • ICRU 62 recommendations suggest the use of margins for OARs. • Generate expanded OARs if it is possible. e.g.; CordExpand = Cord + 5 mm BrainstemExpand = Brainstem + 5 mm • Create “pseudo” structures to achieve sparing at the desired areas.

37. Defining Normal Tissues • Tissues to be spared need to be explicitly defined; e.g., oral mucosa when changing from parallel-opposed to IMRT. Oral mucosa - avoid Courtesy of G. Ezzel, Ph.D., Mayo Clinic

38. Avoidance tissue Target Gy 60 50 45 30 Gy 60 50 45 30 Nodes Spinal cord Avoidance tissue Courtesy of G. Ezzel, Ph.D., Mayo Clinic

39. Hot Spots Outside of Target Regions • Occurs in regions that are not contoured. Work-around • Create “Unspecified Tissue” Region and include in the optimization.

40. Defining OARs for Optimization • Create nonPTVOARs for organs overlapping with PTVs: NonPTVSmallBowell, NonPTVRectum, NonPTVBladder, etc.

41. Guidelines for Target Expansions Prostate CTV:Expand prostate by 0.5cm in all directions except posteriorly then + seminal vesicles (no expansion for seminal vesicles) Prostate PTV:Expand Prostate CTV by 0.5cm in all directions (3D expansion) Lymph Nodes CTV: Expand lymph nodes by 1.0 cm in anterior, posterior, right and left (2D expansion) with small bowel, bladder, rectum, bones, muscle, skin1cm and prostate PTV tissues being the limiting organs Lymph Nodes PTV: Expand Lymph Nodes CTV 0.5 cm in all directions (3D expansion) with only skin1cm and Prostate PTV as the limiting structures

42. Constraints • Required by the inverse planning process – dose or dose-volume constraints for all structures • A trial and error process to come up with the proper dose or dose-volume constraints. • Don’t ask the impossible – set realistic goals – improperly specified constraints will result in inferior plans. • Create site-specific protocols which can be used for similar cases.

45. General Principles for Beam Angle Selection

46. Beam ConfigurationsGeneral Principles • It is useful to minimize the number of beams for practical reasons • The minimum number of beams depends upon a complex combination of factors: • Shape and size of target volume • Locations, tolerances and tissue architecture of normal tissues • Prescription dose (higher doses would normally require more beams) • The optimum number may be determined for each class of radiotherapy problems by trial-and-error

47. Beam ConfigurationsGeneral Principles • If sufficient number of beams are used, the IMRT plan quality is relatively insensitive to beam angles • The computer should be able to adjust the weights of rays to make up for modest imperfections in beam placement • Beams may be placed at equiangular steps • The larger the number of beams, the better the IMRT plan • Rotational IMRT should be better • Non-coplanar beams should provide additional benefit

48. Beam ConfigurationsGeneral Principles • In general, if beam angles are optimized • the plan optimality should improve • the number of beams required for equivalent dose distribution is smaller than if beams are placed at equi-angular steps • Computer-aided optimization of the beam angles is a difficult and as yet inadequately solved problem • Extremely large number of plans need to be compared

49. Beam ConfigurationsGeneral Principles • Choose shortest path to irradiate target(s) • Avoid OARs • Keep large beam separation if it is possible • Beam angle may become important for tumors that are not centrally located. • It depends on the optimizer

50. H&N: 5 Beam 7 Beam 9 Beam 15 Beam