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Quality Assurance for Treatment Planning Systems PTCOG Educational Session
May 19th 2010
Oliver Jäkel
Heidelberg Ion Beam Therapy Centerand
German Cancer Research Center, Heidelberg
Page 3 Oliver Jäkel Medical Physics
IntroductionInternational recommendations; common sources of errors; vendor and user responsibility; legal aspects; risk analysis
Framework of QAQA and QC; acceptance tests; commissioning; periodic QA; uncertainty, deviation and tolerance; documentation;
Tools and MethodsSystem verification; software checks; measurements; Monte Carlo algorithms; analysis of results;
Typical test proceduresSoftware and data base; data transfer; generation of control parameters; imaging QA; geometrical and dosimetrical tests on dose distributions; radiobiological issues;
Conclusions
Outline
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Fatal Errors in TPIntroduction
621 mistakes in NY state 2001-2009:At average 2 mistakes contributing
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Intro: RecommendationsIAEA TRS No.430, 2004: Commissioning and Quality
Assurance of Computerized Planning Systems forRadiation Treatment of Cancer
IAEA-TECDOC-1540, 2007: Specification andAcceptance Testing of Radiotherapy Treatment PlanningSystemsIAEA-TECDOC-1583, 2008: Commissioning of
Radiotherapy Treatment Planning Systems -Testing for Typical External Beam Treatment Techniques
AAPM Report 55, TG 23: Radiation treatment planning dosimetry verification,1995
Van Dyk J et al. Commissioning and quality assurance of treatment planning computers. IJROBP 26, p261, 1993Fraas B, et al. AAPM TG 53: Quality assurance for
clinical radiotherapy treatment planning. Med. Phys. 25: p.1773, 1998
Jacky J, White CP, IJROBP 18:253.Testing a 3-D radiation therapy planning program (1990)
Page 6 Oliver Jäkel Medical Physics
IAEA: Lessons Learned from Accidental Exposures in Radiotherapy, Safety Reports Series No. 17, IAEA, Vienna (2000).
Intro: Common Sources of Error
Inconsistent/incorrect basic dataInsufficient understanding of TPS
Incorrect calculation of open/wedged fields
Calc. error after change of TP Confusion of fractional dose vs.
total doseMisunderstanding of complex TP
given verbally
lack of documentation and verification
Inadequate commissioningInsufficient understanding of
the TPSIncomplete validation
Lack of an independent check of the treatment planLack of effective procedures
Most TP errors can be summarized by a lack of:Education, Verification, Documentation, Communication.
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Intro: vendor responsibility Accurate specifications outlining system capabilities,
algorithms (incl. capabilities and limitations)
Detailed system documentation (system design, dose normalization, MU calculations)
User training: (1) basic training
(2) commissioning process
(3) system management
(4) implementation of a QA program
Detailed information regarding software updates, program alterations
Clear communication regarding bugs, error reporting
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Intro: legal aspectsIntro: User responsibility
Define responsible physicist for supervision and management (incl. installation, acceptance, commissioning and QA)
Implementation of acceptance, commissioning and QA process
Record keeping associated with acceptance, commissioning, QA
User training / staff education: clinical use of TPS and its output(!)
Implementation, commissioning, QA of software upgrades incl. documentation
Ongoing communication with the vendor regarding software bugs and updates
Ongoing communication with the users of the output of the TPS esp. regarding limitations and bugs.
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Intl. Recommendations (IAEA TecDoc 1040 QA in RT, ICRU)European directives (e.g. Medical Device Directive)AAPM (TG 24), ESTRO (Booklet No 4)
National radiation protection regulationGuidelines for medical application of radiationNational and International standards (ISO, IEC), e.g.:
DIN 6870-1: Quality management system in medical radiology Part 1: Radiotherapy
IEC 62083: Medical electrical equipment - Requirements for the safety of radiotherapy treatment planning systems
Intro: Legal Aspects of QA
There are few detailed and hard requirementsThe user always has to define a specific QA program
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Identify, characterize, and assess potential risks Assess the vulnerability of critical elements to specific risksQuantify the risk (expected consequences of specific events)
Prioritize risk reduction measures based on a strategy
Intro: Risk Analysis
ProbabilityF: Frequent IIa IIb IIIE: Probable IIa IIb
D: Sometimes IIaC: hardly
conceivable IIa IIb IIb
B: very unlikely IIa IIa
A: : inconceivable I
0 1 2 3 4None Irrelevant Small Critical Fatal
Effects
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Framework: QA and QCQuality assurance: All planned and systematic actions necessary to provide confidence that a product will satisfy given requirements for quality.
Quality Control:The regulatory process through which the actual quality performance ismeasured, compared with existing standards, and the actions necessary tokeep or regain conformance with the standards.
The QC process:(a) the definition of a specification; (b) the measurement of performance associated with that specification;(c) the comparison of the measurement with the specification; (d) the possible action steps required if the measurement falls outside the specification.
As part of step (d), one needs to define what is an acceptable deviation(a tolerance) from the known standard.
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Assessment of clinical needs
Framework: Implementation of a TPS
Selection and purchase
Installation
Commissioning
Periodic and patient specific QA
Acceptance test
Training
Clinical use
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Acceptance testAssure that the specifications of a product and safety standards are fulfilled (radiation and electrical hazards)
CommissioningCharacterization of the equipment's performance over the whole range of possible operation following acceptance incl. the preparation of procedures, protocols, instructions, data for clinical service.It includes development of procedures and QC tests and training.
Periodic QAProcedures which are performed regularly and which allow to assess, if the initial requirements are still fulfilled; may involve different procedures than during commissioning;
Patient specific QAProcedures performed on patient specific treatment plan or equipment.
Framework
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Framework: Uncertainty, deviation and tolerance
Deviation: Difference between a measured or calculated value and a reference value.Deviations will depend on many factors:
position in the beam, complexity of phantom and treatment plandose calculation algorithm
Tolerance:Range of acceptability beyond which corrective action is required; Tolerances are always specific for a certain facility and application.Uncertainty: The uncertainty of a measured value has to be included in the tolerance or (preferred) may be added later;
Typically: accuracy of algorithms, beam delivery, beam properties, CT data, dosimetry
Error:Deviation of a quantity obtained through an incorrect procedure; A result maybe within the tolerance although an error was made
Page 15 Oliver Jäkel Medical Physics
Dose measurements (Ion chamber, film, etc)Setup of phantomsBeam delivery (esp. in scanning, field homogeneity, stability)Dose calculation algorithmApproximations of the beam modelGeometric parameters (acc. of readings, instruments) Differences between commissioning and constancy checks
Sources of uncertainty
Example: How to separate beam delivery from TPS:Commissioning: Measure dose and compare with TP-dose
Defines reference for TP and DosimetryTP Periodic checks: Repeat calculation & compare w. safety copy Dosimrtry check: Repeat measurement & compare w. old data
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Tools and Methods: Steps in QC
1. Definition of the specifications (performance and test characteristics)
2. Definition of tolerances (incl. uncertainties)3. Definition of tests via
- System verification- Software checks- Dosimetric measurements- Monte Carlo simulations
4. Performing tests and Comparison w. specs5. Possible Action steps if outside tolerance
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G4
Mon
te C
arlo Xi
O
1 Gy(RBE)3 Gy(RBE)5 Gy(RBE)7 Gy(RBE)9 Gy(RBE)
11 Gy(RBE)13 Gy(RBE)15 Gy(RBE)17 Gy(RBE)
Range
MC versus TPS dose for passive delivery @ MGHPaganetti et al, Phys. Med. Biol. 53, 2008
Findings (29 fields): differences between TPS (PB-Alg.) and MC especially near the end of range + difference dose-to-water vs. dose-to-tissue
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Bone slab
Water slab
Water slab
Bone slab
Underdosage up to ~20%, consistent withdosimetric finding in water phantom
Courtesy of F. Sommerer et al, HIT
FLUKA recalculation of treatment plan
MC vs. TPS for lateral inhomogeneityTPS plan
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MC for individual treatment plans
FLUKA
TPS (TRiP)
Test proton plan:TPS (with inputFLUKA-generatedDatabase) vs MC
Courtesy of Parodi K., Sommerer F.,Unholtz D.,Brons S.
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Monte Carlo simulations are extremely powerful
They will immediately show differences as compared to TPS
A Monte Carlo is not automatically giving correct results, although its algorithms may be more accurate than the TPS
Monte Carlo requires much more information as input (cross sections, HU-LUT for all materials)
QA for a Monte Carlo may be very complicated:- Documentation of the Code, User Manual - Version control and change management- Benchmarking of code- Control of input parameters (cross sections etc.)
Cautions
Very few (if any) certified codes for p-RT exists!Clinical decisions should drawn very carefully!
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Examples of Test procedures @ HITSoftware & data base:Versioning, data base, data transfer, PACS- archive Machine interface & control parametersCalc. energies, ranges, field size, spot positions, fluence optimization Imaging QA Data transfer, HU-checks, geometrical image checks (distortions, scales, contrast), stereotactic tests, DRRGeometrical tests on dose distributionsField size, depth modulation, lateral and distal
gradientsDosimetrical tests on dose distributionsHomogeneous phantom (water, different angles)Depth inhomogeneities (slab phantom)Lateral inhomogeneities (slabs)Irregular inhom. Phantom (Alderson)
Radiobiological issuesCheck p-RBE, recalculate standard plans
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Courtesy of S. Klemm
Plans of different complexityDefined measurement positions:
1 High Dose2 Plateau3 Lateral Gradient4 Distal Gradient
Tolerances @ HIT:
3
214
3
21
3
4
3
Dosimetric tests in a water phantom
Regular Target: Max. dev : 5% Mean. dev : 3%*Relative to maximum dose
max,i
max
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3
ddd 1H @ HIT
Checks on the data base for treatment planning
To measure or not to measure ?
TPS: - check if input=output- check machine control file- check consistency
Beam delivery: measure!
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Empirical range calculation from CT numbers
Range relative to water
CT number
Tissue equivalent phantomsReal tissue measurements
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Imaging-QA: Possible distortions of CT numbers
Contrast agent in CT mean shift (25 pat.): 18 HUmax shifts: 36 HU Errors in range < 1.6 %
Reconstruction filters redistribution of HU numbersErrors in range < 3 %
Filter: AH50AH90
Dedicated imaging protocols and imaging QA required
Page 6 Oliver Jäkel Medical Physics
Dose distribution carbon ions
PET-Measurement
Patient with Chondrosarcoma of skull base
PET for Range verification ?
PET is not routinely used for formal QA at GSI/HIT
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Courtesy of B. Ackermann
Field geometry: IC in water vs. Films
Lateral
0.00
20.00
40.00
60.00
80.00
100.00
120.00
-60.00 -40.00 -20.00 0.00 20.00 40.00 60.00
lateral position in mm
D/D
(max
)
Measurement lateral rightTPS lateral rightMeasurement lateral leftTPS lateral left
Commissioing: Ion chambers
Periodic QA: films
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Dosimetric Checks of dose calculation
Measurement equipment for commissioningWater Phantom PTW Freiburg24 PinPoint chamber array connected to a MP3 controller2 12-channel Multidos dosimeters
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Dosimetric Verification of treatment plans for commissioing and patient specific QA
Data-acquisition in the TPSVx Verification Mode in TPS (Syngo PT Planning)Dose calculation in waterfor each PinPoint-ChamberCalculated dose [cGy]Gradient information [Gy/mm]
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Tolerance for dose verification @ HIT
12
Regular Target:Max. dev. < 5% Mean. Dev. : < 3%
Irregular/complex Target: Max. dev: < 7% Mean. dev: < 5 %
max,i
max
max,i
max
Tolerances include dosimetric uncertainties!
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MC application to active beam delivery @ HITFLUKA dose calculations of scanned fields for comparison withmeasurements and TPS calculation to support TPS-commissioning
Meas.: ICs in water phantom + data acquisition system from C. Karger (DKFZ)
FLUKA: ~ 108 p out of 4.4 1010
irradiated
Parodi, Mairani,Brons, HIT to be published
eye view Along depth Along depth
Protons
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Radiobiological QA: Verification with cell samplesMitaroff A et al, Rad. Env. Biophys. 1998
Measurements for validation of the model and TPS.
No biological QA routinely used for formal QA at HIT.
Page 13 Oliver Jäkel Medical Physics
MC for biological dose calculations @ GSI / HITFLUKA interfaced during runtime with the Local-Effect-Model (M. Scholz et al, GSI) used by TPS @ GSI / HIT
FLUKATRiP98Exp data
-TPS (TRiP98): biological planning and optimization for CHO cellsFLUKA-LEM: forward calculation of the optimized plan
Exp. Data and TPS calculations: Krämer et al, PMB 48 (2003) 2063MC Calculations: A. Mairani et al, Book of Abstract EW-MCTP, Cardiff,
2009; submitted to PMB
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Radiobiological QA @ HIT
No real biological QATest only constancy of algorithmsBenchmark of new algorithm vs. old algorithm Check input in data base
Courtesy of C. Karger
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Carefully analyze the clinical needsWrite down performance characteristicsDefine test characteristics, tolerances, actionsDefine how to test
(SOPs for commissioing and periodic QA)
Analyze uncertainties (SOP) Document all results Summarize findings for the users
Conclusion