1. QA for the Radiotherapy
Salih Arican, M.Sc.

2. Quality Assurance Why do we need (IMRT) QA?
Do I really need to do QA for each IMRT patient?
If I use an independent Monitor Unit calculation program do I still need QA for each Patient?
Will I still need do IMRT QA after we’ve treated 500 patients?
If I expand my monthly machine QA can I eliminate IMRT QA for each patient?

3. What’s the Worst that Could Happen?
Least
Patient Death
Severe Complication
Bad administration
Major Treatment Deviation
Minor Treatment Deviation
Litigation
Lost Revenue

4. FDA Adverse Event Report (06/16/2004):
Patient Overdosed by 13.8%
Patient subsequently died as a
result of complications related
to the mistreatment

5. FDA Adverse Event Report (04/07/2005) :
Medical center reported that between 2004 and pts received radiation approx 52% in excess of their prescribed dose
The excess radiation was a result of a calculation error by the medical center physicist during calibration
This incident has been recognized/identified as "human error"

6. FDA Adverse Event Report (04/22/2005)
Prostate IMRT patient treated to a higher dose than prescribed
Reported as Medical Physics user error

7. The overall accuracy
of (IMRT) treatment
depends on …

8. Reasons for errors Patient Positioning Organ Motion
Delivery errors
TPS commissioning
TPS algorithm weaknesses
Organ Motion
Patient Positioning

9. Mechanical accuracy of LINAC
• Gantry
Collimator
isocenter

10. Explanations for Failures
Minimum # of occurrences
incorrect output factors in TPS 1
incorrect PDD in TPS
Software error
inadequacies in beam modeling at leaf ends (Cadman, et al; PMB 2002) 14
not adjusting MU to account for dose differences measured with ion chamber 3
errors in couch indexing with Peacock system
2 mm tolerence on MLC leaf position
setup errors 7
target malfunction

11. No compromise with accuracy
What is the Optimal Tool?
Reliable and
Cost-effective QA
No compromise with accuracy
Save time for setup, measuring, and analysis
Versatility to use
Less need for human resource
Excellent spatial
resolution
provide
3-D data

12. QA for IMRT: 4 Levels
Pre-Clinical verification of IMRT treatment (patient related)
Verification of fluence maps, individual IMRT fields on water phantom
IMRT delivery specific QA
Basic QA (LINAC, MLC) 4 3 2 1

13. (IMRT) – QA Plan

14. Routine QA of the delivery system
Does the radiation delivered have:
The correct energy?
The correct place?
The correct dose?
The correct intensity?
The correct time? 14 14

15. Beam Stability: Flatness,Symmetry
Stability of flatness and symmetry affects dose rate for small fields directed off the central axis.

16. Beam Stability: Dose Rate
With IMRT delivery, there is the potential for short irradiation times (MUs).
Dose rate stability influences the
treatment precision.

17. Linac-QA: Dose Rate

18. Linac-QA: Dose / Pulse

19. Linac-QA: Beam Start-Up

20. Linac-QA: Beam Position  Stabilization Time

21. LINAC-QA: Dose delivery8)
286,7 6)
355,2
15)
85,0
18)
10,0 7)
335,1 5)
392,0 4)
423,9 3)
459,3 2)
515,3
13)
124,5
16)
47,6
11)
196,9 9)
257,0
12)
147,4
10)
216,1
14)
79,3
17)
7,7
Planned dose value pattern (18 steps, dose values in cGy)

22. + = Multiple Beam ‘Segments’ Resultant IMRT
Each with a Different MLC Shape
Resultant IMRT
Beam Intensity Map + =

23. Measured
Calculated

24. MLC QA - check the influence of gravity

25. MLC Delivery Error at Gantry 90 deg
Individual segments
Gantry 90 deg
After error analysis & correction
leaf positioning failure!

26. Error in jaw position: Plan measured difference Profiles __ Y1
jaw displaced by
1.8 mm

27. Leaf position uncertainties
Beam widths of 1 cm, uncertainties of a few tenths of a millimeter in leaf position can cause dose uncertainties of several percent.
e.g. 0.5mm  >5%

28. MLC QA: Accuracy of relative MLC leaf position
Leaf positioning accuracy:
MLC pairs form a narrow slot moving across the field, stopping and reaccelerating at predefined positions (garden fence technique)

29. Regular Pattern
(golden standard)

30. Regular Pattern
Measured Pattern

31. 1.0 mm 0.5 mm 1.0 mm 0.9 mm 0.8 mm 0.7 mm 0.6 mm 0.5 mm 0.4 mm 0.3 mm

32. Leaf speed accuracy
The accuracy of dynamic MLC delivery depends on the accuracy with which the
speed of each leaf is controlled.

33. MLC QA – Leaf Speed Test
Leaf pairs form gaps moving with different speed
Delivery with beam interrupts

34. Leaf transmission characteristic
The transmission characteristics (leakage) of the MLC are important for IMRT because the leaves shadow the treatment area for a large fraction of the delivered MU.

35. All Leaves Closed Completely
Radiation Leaks through between Leaves and Across Ends
Interleaf
Transmission
Leaf End
Collimator Covers Field Up to Outermost Leaf
Leaks between Sides Reduced with Backup Collimator
Treatment Field
Collimator Jaw

36. Transmission (Leakage) Check

38. Patient-specific Verification ?
What is missing :
Does the plan give correct dose distribution ?
Does it fulfill the therapeutic requirements ?
What is the influence of inter-fraction variation ?
In case of 2D verification
What is the influence of revealed discrepancies on the dose distribution?

39. Pre-Treatment Verification
Field oriented Plan oriented
Gantry =0° X -
Rotating Gantry

40. Comparison of predicted and measured MLC-Shapes
Inverse Back-Projection
Leaf Sequencer
Delivered 3D-Dose- Distribution
RTPS:Desired D-Dose- Distribution
RTPS:Desired Fluence-Map
Leaf- & Gantry sequence
Deliveredfluence
MC-2
MC-SW
ArcCHECK

41. Patient-Specific validation of treatment plans
Inverse
Back-Projection
Delivery
System
Treatment
Planning
MLC
Segmentation
2D-Array
/3D-Array
Delivered Fluence

43. Predicted: --------Measured:
Measured fluence map
comparison
Predicted: Measured:
Predicted fluence map

44. DICOM_RT DOSE plan: Beam1: G=210 C=180 segments=20

45. Plan oriented verification with 2D-Array

46. Beam 1: Gantry 210 degree
Beam 2: Gantry 260 degree
Beam 3: Gantry 310 degree
Beam 4: Gantry 0 degree
Beam 7: Gantry 150 degree
Beam 5: Gantry 50 degree
Beam 6: Gantry 100 degree

47. Measured (composite) Beam 1 … Beam 7:

48. IMRT-Composite field verification (MC-SW): Pass-rate: 97.5 %
Measured Calculated
IMRT-Composite field verification (MC-SW): Pass-rate: 97.5 %

49. Discussions – Information Weight
0º: beam is normal to the array and all information is weighted equally
90º: 2D reduced to 1D, most information is lost
Other angles: variable weights
Dosimetric information is over or under-weighted based on beam angle and field size 0º
90º

50. Plan oriented verification with ArcCHECK

51. ArcCHECK in action

52. VARIAN RapidArc Inselspital Bern-Switzerland
Arc-1: Pass-Rate: 98%; Gamma: 3mm/3%

53. RD-Oxford Cancer Center H&N. dcm converted in AC_PLAN
RD-Oxford Cancer Center H&N.dcm converted in AC_PLAN.txt RD-Oxford Cancer Center H&N.dcm converted in AC_PLAN.txt imported
as 2D composite plan
The difference is clear: Cold-spot value at the gantry angle x1 degree might be balanced with hot-spot value at the gantry angle degree x2. That effect can't be seen in composite analysis result but with ArcCHECK measured and unrolled fields!

54. Film dosimetry: Plan oriented workflow
1. Planning of IMRT cycle for patient with RTPS
2. Planning of same IMRT cycle but now
with Body Phantom
3. Exposure of film in Body Phantom to IMRT cycle
5. Import of planned and measured data
in analysis SW
4. Development and digitization of exposed film
6. Comparison of planned versus measured dose

55. Film
The choise of film is very important. But even more important is the calibration of the film and the stability of the film processing environment and chemistry

56. Quantity
Calculation
Measurement
3D-Dose Distribution
Apply Plan to Phantom. Calculate 3D-Dose Distribution
Put Films in the Phantom. Process, Scan, Calibrate Films. Compose 3D-Dose Distribution
2D-Dose/Fluence
Calculate Fluence Pattern or 2-D Dose Distribution
Film, 2D-Array, 3D-Array
Leaf Positions
MLC QA
Leaf Positions from TPS
Film, 2D-Array, 3D-Array,
MU/Dose Check
Dose in a reference Point
Ion-Chamber/Electrometer
Penumbra measurement
Needed for TPS
Set-up
Small Ion Chamber or Diode (SFD) in 3D-Phantom

57. Conclusions
Quality assurance reduces uncertainties and errors in dosimetry, treatment planning, equipment performance, treatment delivery, etc., thereby improving dosimetric and geometric accuracy and the precision of dose delivery.

58. Conclusions
Quality assurance not only reduces the likelihood of accidents and errors
occurring, it also increases the probability that they will be recognized and rectified sooner if they do occur, thereby reducing their consequences for patient treatment.

59. Conclusions
Quality assurance allows a reliable comparison of results among
different radiotherapy centers, ensuring a more uniform and accurate dosimetry and treatment delivery.

60. Conclusions
Improved technology and more complex treatments in modern radiotherapy
can only be fully exploited if a high level of accuracy and
consistency is achieved.

61. Thank you,
Questions?