Upload
pierce-newman
View
230
Download
0
Tags:
Embed Size (px)
Citation preview
6. CLINICAL IMPLEMENTATION AND SBRT QUALITY ASSURANCE Patient Specific QAEquipment specific QAIn vivo DosimetryTG-142 and TG-101 guidelinesProcess assessmentClinical challenges
Jeffrey Barber, Medical PhysicistIAEA RAS6065, Singapore Dec 2012
2
Useful References
• AAPM TG-101 Report: SBRT• AAPM TG-142 Report: Medical Linac QA• AAPM TG-179 Report: CT-based IGRT QA
0.5mm gantry locus
2mm image
reg
2mm immob
movement
0.5mm kV-MV
1mm laser loc
2mm couch locus
2mm contouring variation
10mm target
respiratory motion
3% dose delivery
Quality Assurance
• Physicists should check individual parameters and combined processes
• If you check everything in isolation, how do you know what you are doing at the end
• TG-142 and TG-101 are guidelines. Lots of advice on how to do things, how to investigate and how to develop local protocol
• The future TG-100 proposes a different approach
QA Approach• Perks et al (2012) IJROBP 83 p1324 • Fault Mode Effects Analysis (FMEA) • Process Engineering concept used to
focus QA efforts on most practical problems
1. Map your processes (flowchart, tree, etc)
2. Give any foreseeable fault a weighted score• likelihood of Occurrence• Severity of fault• likelihood of being Detected
3. Then add QA processes to address the potential faults, with most effort focused on highest scores
QA Approach
8
QA Approach
• FMEA promises to increase the efficiency and effectiveness of the testing required
• But FMEA takes a lot of resources and time to set up
• Current guidelines are effective, if intensive
• Quality Assurance can be categorised as:• Equipment QA• Patient-specific QA
9
EQUIPMENT QA
Equipment QA
• TG-142 Daily
Equipment QA
• TG-142 Monthly
Equipment QA
• TG-142 Annual (1)
Equipment QA
• TG-142 Annual (2)
Equipment QA
• TG-142 MLC
Equipment QA
• TG-142 Imaging (1)
Equipment QA
• TG-142 Imaging (2)
17
Equipment QA
• ASTRO
Equipment QA
• TG-101
Equipment QA
• TG-101
Equipment QA
• TG-101
Equipment QA
• TG-101
Equipment QA – kV/MV coincidence
Room Lasers
Imaging Isocentre
Radiation Isocentre
Equipment QA – kV/MV coincidence
Room Lasers
Imaging Isocentre
Radiation Isocentre
Equipment QA – kV/MV coincidence
• Winston-Lutz type tests check centre points
Equipment QA – kV/MV coincidence
Sharpe et al, Med. Phys. 33, 136-144, 2006
Equipment QA – kV/MV coincidence
• Elekta: Planar images are uncorrected. Flexmap offset saved in DICOM header. 3D reconstructions include the correction.
• Varian: Flex is included in robotic arm so each image is corrected.
• If flex needs calibrating, it will be visible in the reconstructed images Bissonnette
Equipment QA – Daily Checks
• Daily IGRT QA1. Set up phantom with known offset2. Image, register, check offset is right3. Correct couch, re-image, check residual error4. Visually inspect the new phantom position
28
Equipment QA – Image Quality
Rings
Capping
Streaks
Motion
29
Equipment QA – Image Quality
• Most important Image Quality parameter is spatial accuracy and scaling
30
Equipment QA – Image Quality
• Most important Image Quality parameter is spatial accuracy and scaling
Machine QA – MLC Accuracy
• Using Picket Fence and Garden Fence beams• Film• EPID• Array Device
• Analysis is the hard part• How good is your eye?• How good is your image processing?• Lots of commercial solutions available
Machine QA – MLC Accuracy
33
PATIENT-SPECIFIC QA
Patient Specific QA
high doses+ small volumes+ complex beam arrangements+ moving structures= need for patient-specific QA
• Verify Dose
• Verify 3D Distribution
Patient Specific QA
• Verify Dose• Copy plan to phantom, recalculate, deliver to
chamber
• Chamber measurements ≤ 3% from planned dose
• Array devices and film can be calibrated to dose
Patient Specific QA
• Verify Distribution• Array devices (MapCheck, ArcCheck, Matrixx,
Octavius, Delta4, etc.)• Film• Gel?
• Use Record/Verify “QA Mode” deliver at true gantry angles.
• Analyse beams individually and as whole fraction.
Patient-Specific QA (Pre-Tx)• Using the Delta4 phantom we get psuedo-3D distribution of
points across the plan volume
• Two 2D planes of diodes form a cross
• Real plan > copy to phantom CT, recalc > measure > analyse
• Results are highly reproducible
Delta4 Results
Delta4 Results
• Halo distribution • TPS pumping dose in the
non-lateral-equilibrium regions
• Absolute dose max ~200% patient prescription• Difference of dose
absorption between high and low density mediums
Delta4 Results• Very similar results when measurements are repeated on same
day and different day reproducible delivery by MLC• Very similar results when measurements are repeated on
different linacs well matched and stable linacs
• Where to set tolerance for pass/fail?
Avg γ Pass 3mm DTA 2mm DTA 1mm DTA
Dose Diff 3% 100.0% 99.5% 93.1%
Dose Diff 2% 99.5% 96.0% 88.9%
Dose Diff 1% 97.9% 95.5% 77.5%
More QA Equipment
Tomas Kron, Peter MacCallum Cancer Centre
Patient-Specific QA (Post-Tx)
• Phantom measurements check one delivery, one time.
• Linac log files can be used to check actual treatment delivery mechanical parameters
• Combine this with IGRT and dose reconstruction/accumulation is possible
Patient-Specific QA (Post-Tx)• Elekta does not have dynalogs • But a record of mechanical parameters is sent to Mosaiq after delivery• A report can be generated and compared to the DICOM-RTPlan
In vivo Dosimetry
• TLD• OSLD• Diodes• MOSFETS• Radiochromic film squares
• “Ex vivo” Dosimetry• Transit Dosimetry via EPID• Per fraction beam fluence measurements
• Recommend checking in field and out of field
45
In vivo Dosimetry
46
PROCESS REVIEW
Process Evaluation
Process Evaluation
• MARGINPTV = 2.5Σ + 0.7σ
• Σ – st dev of sys errors• σ – st dev of random errors
• 2.5 and 0.7 come from 90% and 95% confidence intervals for Gaussian distributions, respectively.
• This margin has the 95% isodose line cover the CTV in 90% of patients
• Systematic errors contribute more than random errors to uncertainty
• 4DCT and IGRT should remove systematic error and reduce random error
Process Evaluation
Van Herk 2012
Process Evaluation
For a single patient:
• Systematic Error = mean offset
• Random Error = standard deviation
Chris Fox, Peter MacCallum
Process Evaluation
For a population of patients:
• Systematic Error = standard deviation of individual mean errors
• Random Error = Root-Mean-Sum of individual random errors
Chris Fox, Peter MacCallum
Litt
le S
igm
aBi
g Si
gma
52
Process Evaluation
• You can only collect statistics on what you image.
• If you want to know how accurate your IGRT is, you need another image after any couch shift
THANK YOUTomas KronSimon DownesSean White
53
54