COMPASS. Dr. Lutz Müller. AK IMRT Bamberg April D IMRT Verification in Patient Anatomy

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COMPASS 3D IMRT Verification in Patient Anatomy AK IMRT Bamberg April 2010 Dr. Lutz Müller

Patient-specific Verification? CT Treatment unit Gantry =0 Treatmt unit Patient couch X-ray beam Patient couch X-ray beam TPS 3D Dose Fields 3D Dose In Patient 3D Dose In Phant Targ. Vol/Dose/constraints disturbed Fields Resulting 3D Dose In Patient

Generations of electronic IMRT Dosimetry 1 st Single fields, perpendicular 2nd Homogeneous phantom, composite 3 rd COMPASS

2nd Generation This is a Piece of Plastic (and not a Human Being)

How to assess dose to the patient for IMRT? Invasive Method: place a film in the patient

What is? + + Detector Beam model Dose engine NOTE: all these elements are PART of COMPASS, not only the transmission detector

Compass: from Entrance Fluence to 3D Patient Dose DICOM plan Beam model Transmission Detector Real Fluence Dose engine CT

2 Detectors for COMPASS MatriXX Transmission Detector 1020 ion chambers Pre-treatment verification Verification of systematic errors Display of 3D dose distribution in patient anatomy 1600 ion chambers Pre-treatment + online verification Dose distribution measurement during patient treatment Systematic and random errors Display of 3D dose distribution in patient anatomy

2 detectors for COMPASS MatriXX Transmission

New Transmission Detector Wireless data transmission Battery operated Minimal clearance reduction

The Beam Model (RaySearch) A Beam Model... Is a virtual accelerator, which allows fluence and spectrum calculation from MU number and collimator settings In order to do so... The model needs to be commissioned, i.e. has to learn features of specific accelerator and energy

Commissioning of COMPASS

Auto Modelling Auto modelling function Affected parameters Target function Electron energy spectrum Electron spectrum parameters E and c, secondary electron source weights, direct electron source width and weight. Energy spectrum and output factor corrections Primary and flattening filter sources Photon energy spectrum and output factor corrections Primary and flattening filter photon sources: weight, widths, positions. Depth dose curves from zero depth Depth dose curves deeper than 1 cm 10 cm 10 cm field profiles for different depths. Beam profile corrections and off axis softening Beam profile corrections and off-axis softening Largest field x- and y-profiles for different depths. Output factor corrections Value of the output factor corrections Depth dose curves at the calibration point depth Note that for any given MLC position, it is assumed that the MLC-leaves and settings have the proper scale, so that their projected size onto the iso-center plane does not vary. If the projected size (or projected position) does not match the nominal values, this is regarded as a position calibration, and not as an off-set of the z-position.

Fluence Correction: 1. Residual Response Plan Measurement Comissioning Beam Model Factory calibration Fluence Detector comissioning MC Det. modelling Detector Model Predicted Response Measured Response Input User Factory

Response Prediction and Comparison

Dose engine (Collapsed Cone Superposition) A Dose Engine... Takes the incoming fluences Takes the CT Copyright philips Calculates the resulting dose distribution in patient anatomy

Planned vs. Reconstructed Dose

IMRT Quality Comparative Study DESIGN AND IMPLEMENTATION OF AN ANTHROPOMORPHIC QUALITY ASSURANCE PHANTOM FOR INTENSITY-MODULATED RADIATION THERAPY FOR THE RADIATION THERAPY ONCOLOGY GROUP ANDREA MOLINEU, M.S.,* DAVID S. FOLLOWILL, PH.D.,* PETER A. BALTER, PH.D.,*WILLIAM F. HANSON, PH.D.,* MICHAEL T. GILLIN, PH.D.,* M. SAIFUL HUQ, PH.D., AVRAHAM EISBRUCH, M.D., AND GEOFFREY S. IBBOTT, PH.D.* *Department of Radiation Physics, The University of Texas M. D. Anderson Cancer Center, Houston, TX; Department of Radiation Oncology, University of Pittsburgh Medical Center, Pittsburgh, PA; Department of Radiation Oncology,University of Michigan Medical Center, Ann Arbor, MI 7%/4mm ca. 30 % fail!

3rd Generation. Dose in the Patient Anatomy

Delivery Error 2mm Shift (Generation 2)

Delivery error in RPC phantom case Primary PTV Secondary PTV OAR: spinal cord Effect of 2mm y-shift on DVH

Collecting the Gantry Angle Information Starting with R2.0 Compass allows to track the gantry angle while measuring the treatment plan. Gravity-based Gantry Angle Sensor to be mounted on gantry.

Plane View

Response/control point (Plan vs. Measurement)

Statistical evaluation Pre-defined protocols can be applied Bulbus right Bulbus left PTV Chiasm Brain Lens

Report Export to e.g. EXCEL

Reporting and Archiving (India)

COMPASS Report

Data from Fujio Araki, Kumamoto university

Prostate Case 3 Film Film Film ERGO++ CPS Computed CPS Reconstructed Gamma 4/4 Gamma 4/4 Gamma 4/4 Data from Ramesh Boggula, Mannheim (submitted)

Para spinal Case 3 Film Film ERGO++ COMPASS Plan was computed on a inhomogeneous thorax phantom Data from Ramesh Boggula, Mannheim (submitted)

COMPASS vs. MONACO MC IMRT 5 Prostate Plans on Inhomogeneous Pelvic Phantom EDR 2 Film Data from Ramesh Boggula, Mannheim (to be published)

COMPASS Present and Future RTplan Transmission Det MatriXX Planning CT Reference Dose PET-CT (F)-MRT COMPASS 3 D Dos 2 D Dos On line 4 D Dos Cone Beam CT RTstruct Gating Log files Data Base

Integrated Imaging Systems Integrated Imaging System fraction-to fraction monitoring of organ position AND shape Data from X.A.Li et al., Medical Collegue of Wisconsin

CTV Volume and Shape change Data from X.A.Li et al., Medical Collegue of Wisconsin

Cone beam CT import CT CBCT

Variation due to bladder filling (fraction 4)

Initial manual countouring Draw a spline to help the algorithm finding the border of the bladder, especially where it is going outside of the higher quality image area.

Automatic adaptation

Rigid registration (Prostate) Adaptation of prostate is done in the same manner. Only rigid movements however since really hard to identify by grayscale. Need personal clinical knowledge to deform by your own.

3D ROI Adaptation All adaptation work on the full 3d volume description of the ROI s

Cumulative DVH Fraction 4 After all fractions Planned COMPASS

Commissioning & Validating COMPASS in a Clinical Environment Vanderbilt-Ingram Cancer Center Radiation Oncology Department Jostin Crass, M.S.

POLL QUESTION Raise your hand if your physician would understand this? 95% of Pixels with Gamma < 1.0

POLL QUESTION What about this? Or this? Measured Reconstructed

Validating COMPASS Validate our TPS Validate COMPASS computation algorithm Validate COMPASS prediction algorithm Validate COMPASS reconstruction algorithm

Validating COMPASS Validate COMPASS prediction algorithm Compare COMPASS predicted response to response measured on MatriXX Difference Histogram ~96% of the pixels are within ±1.5% Difference Compared Field by Field for complete validation

Validating COMPASS Validate COMPASS reconstruction algorithm

Validating COMPASS Validate COMPASS reconstruction algorithm

COMPASS Pros & Cons Cons Beam Modeling should be more automated and intuitive Improve documentation Need to integrate OmniPro IMRT functionality CT numbers add to another uncertainty category

COMPASS Pros & Cons Pros Intuitive GUI Simple Measurement Setup TRIGGER MODE is AWESOME Customizable Reports Dose Visualization Physician Friendly Analysis

A Novel 3D Approach to Rotational Verification Anees Dhabaan, Ph.D. Eric Elder, Ph.D. Department of Radiation Oncology

Method of Evaluating COMPASS Comparison Studies Between TPS, Film, MatriXX and COMPASS Film MatriXX COMPASS

Method of Evaluating COMPASS 1. Gafchromic Film Dosimetry 2. Conventional Chamber array (MatriXX) 3. TPS compared to Planar dose extracted from COMPASS indirectly measured dose

Plan on a phantom Planar Dose

Film vs. TPS Dose Difference Tolerance: 3% DTA Tolerance: 3 mm Max Gamma Index: 1.5 Min Gama Index: 0.00 Mean Gam1a Index: 0.36 Std Dev Gamma Index: 0.21 Total Pixels: 35784 Search Radius: 10 mm Number of Pixels> Gamma Index 1: 159(.44%)

MatriXX vs. TPS Total number of pixels: 40401 Minimum Signal: 0.00 Maximum Signal: 1.48 Average Signal: 0.19 Standard Deviation: 0.18 Pixels in Ranges: 0.00 to 1.00 : 40180 (=99.45%) 1.00 to 1.50 : 221 (=0.55%) Result: Gamma, 3.0%, 3.0 mm

COMPASS vs. TPS Total number of pixels: 263196 Minimum Signal: 0.00 Maximum Signal: 1.60 Average Signal: 0.30 Standard Deviation: 0.22 Pixels in Ranges: 0.00 to 1.00 : 261025 (=99.19%) 1.00 to 1.60 : 2144 (=0.81%) Result: Gamma, 3.0%, 3.0 mm

MatriXX vs. COMPASS Results 99% of pixels have gamma index <1.0 Gamma 3%, 3 mm

Clinical Example

Clinical Example - Coronal TPS Compass-indirectly measured dose

Clinical Example - Coronal

Clinical Example - Axial TPS Indirectly measured Dose Spinal Cord PTV Spinal cord PTV Heart R Lung Dose gamma

Clinical Example - Sagittal TPS Indirectly measured Dose Spinal cord PTV Heart R Lung Dose gamma

Conclusion Provides 3D dose distribution within patient anatomy allowing detailed evaluation of plan. Directly identifies discrepancies between plan and delivery. Independent verification of treatment planning system.

Verification and clinical introduction of a QA system* in head and neck IMRT *COMPASS (IBA Dosimetry) Continuous Online Monitoring PAtient Safety System Erik Korevaar Dept of Radiation Oncology University Medical Centre Groningen The Netherlands UMCG

Purpose 1. Clinical introduction of COMPASS 2. COMPASS QA results identify bad treatments as in standard (film based) QA? 3. Machine QA test correlates with patient IMRT QA? UMCG

Methods 1. MLC test geometries 2. Head and neck IMRT test cases 22 treatments on two twin accelerators Gamma index evaluation*: planned vs. delivered dose γ mean < 0.5 0.5-0.6 > 0.6 OK rejected *Low et al. Med. Phys. 25 (1998) UMCG

Dose [cgy] MLC geometry: Strip test 9 adjacent 1.8x20cm 2 MLC segments Film COMPASS 200 100 Film COMPASS 0 0 5 10 15 20 Y position [cm] UMCG

Head and neck IMRT case #1 Gamma index (3%/3mm) γ mean = 0.53 γ mean = 0.57 γ 1 hot area: measured > TPS 0 1 cold area: measured < TPS QA Film QA COMPASS UMCG

COMPASS QA vs Film QA Gamma index correlation COMPASS QA (γ mean ) 1.0 0.8 0.6 0.4 0.2 0.0 0 0.2 0.4 0.6 0.8 1 Film QA (γ mean ) UMCG

COMPASS QA vs Film QA Gamma index correlation COMPASS QA (γ mean ) 1.0 0.8 0.6 0.4 0.2 0.0 0 0.2 0.4 0.6 0.8 1 Film QA (γ mean ) UMCG

COMPASS QA vs Film QA Gamma index correlation COMPASS QA (γ mean ) 1.0 0.8 y = 0.95x R 2 = 0.86 0.6 Linac II 0.4 Linac I 0.2 0.0 0 0.2 0.4 0.6 0.8 1 Film QA (γ mean ) UMCG

COMPASS QA in patient CT TPS COMPASS γ mean = 0.33 TPS COMPASS γ mean = 0.57 DVH: spinal cord (green), planning target volumes (purple, red) Gamma index (orange: γ >1 ) UMCG

Conclusions COMPASS based QA agrees with film based QA Machine QA test correlates with patient QA In clinical use since February 2009 IMRT QA time reduced by half UMCG

Acknowledgements University Medical Center Groningen University of Groningen, Department of Radiation Oncology Groningen, The Netherlands D. Wauben, P.C. van der Hulst, J.A. Langendijk, A.A. van t Veld IBA Dosimetry GmbH Schwarzenbruck, Germany RaySearch Laboratories Stockholm, Sweden UMCG

Clinical Validation of COMPASS-System for Verification of Intensity Modulated Fields S. Heyden¹, M. Kretschmer¹, F. Würschmidt¹, L. Müller² ¹Radiologie & Radioonkologie im Struenseehaus, Hamburg- Altona ²IBA-Dosimetry, Schwarzenbruck

Materials and Methods Comissioning of COMPASS Determination of dosimetric base data for 6MV photon beam with a water phantom. The LINAC used was ONCOR Impression (Siemens). Validation of COMPASS Comparison of output factors, depth dose curves and lateral profiles vs. Base data for simple quadratic fields Similation of delivery errors by modification of planning data (photon energy variation, MLC and collimator positions). Clinical routine usage of COMPASS for 4 head-and-neck plans. The plans have been evaluated with COMPASS and compared to dose distributions from the planning system KonRad (Siemens) All measurements have been carried out using the ion chamber array MatriXX (IBA-Dosimetry), using a gantry holder.

Dose [a.u.] rel. Dosis Dev. Abweichung rel. to TPS in % [%] OF (normalized) Results Output factors It could be shown that results both for COMPASS recalculated plans as well for COMPASS measurement based reconstruction yielded good agreement with base data for output factors, lateral profiles and depth dose curves. 1,0 0,5 PDD 10x10cm² Basisdaten Bese data Compass- COMPASS Rekalkulation (recalc) Compass-Messung COMPASS (measured) 3,0 2,0 1,0 0,0-1,0-2,0 Bese data TPS-Masterplan COMPASS (recalc) COMPASS (measured) Field Field size size [cm] [cm] Abweichung PDD 10x10cmPDD 2 10x10cm² D COMPASS Compass-Rekalkulation (recalc) X COMPASS(measured) Compass-Messung 0,0 0 5 10 15 20 Tiefe in cm Depth [cm] -3,0 0 5 10 15 20 Tiefe in cm Depth [cm] Intentionally applied modifications to the plans have shown that leaf displacements down to ±1mm could be identified unambigously. A change in photon energy and collimator position could be detected for field sizes > 10x10cm². Leaf displacements for2x2cm², 5x5cm² und 10x10cm² fields. The arrows indicate the first appearance of the manipulated leaf

Results The comparison between COMPASS recalculated and measured dose distributions for target and OAR volumes for 6 MV head-and-neck plans shows good agreement with the TPS distributions, both for average doses and DVH slopes. Discrepancies were noticeable at transition areas to air cavities and are caused by different dose computation algorithms (KonRad=Pencil-Beam, COMPASS=Convolution-Superposition) COMPASS-recalculation vs. KonRad COMPASS-measurement vs. KonRad Tumor bed PTV Spinal cord Parotis Tumor bed PTV Spinal cord Parotis ROI KonRad Average dose [Gy] COMPASS recalculated Rel. Diff [%] Abs. Diff [Gy] Tumor bed 50.35 50.60-0.50-0.25 PTV 49.62 49.36 0.54 0.27 Parotis 44.85 44.80 0.10 0.05 Spinal cord 24.71 23.25 6.31 1.47 ROI KonRad Average dose [Gy] COMPASS measurement Rel. Diff [%] Abs. Diff [Gy] Tumor bed 50.35 50.24 0.21 0.11 PTV 49.62 49.18 0.65 0.32 Parotis 44.85 45.54-1.52-0.69 Spinal cord 24.71 24.09 2.61 0.63

Summary The dosimetric validation of COMPASS shows good agreement to the base data Leaf displacements in the dose difference plot can be identified unambiguously from ±1mm on Comparison with IMRT-plans shows good agreement for both average target doses and DVH slopes Time spent for plan QA (hybrid plan generation with KonRad, recalculation, measurement, evaluation) can be reduced from 3:30 h to about 1 h using COMPASS