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El. knyga: Contemporary IMRT: Developing Physics and Clinical Implementation

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The most important radiotherapy modality used today, intensity modulated radiation therapy (IMRT), is the most technologically advanced radiotherapy cancer treatment available, rapidly replacing conformal and three-dimensional techniques. Because of these changes, oncologists and radiotherapists need up-to-date information gathered by physicists and engineers. Focusing on new developments and the preliminary clinical implementation, Contemporary IMRT: Developing Physics and Clinical Implementation discusses the relationship between these advances and applications.

Capturing contemporary technological advances, the book reviews modern applications of IMRT and shows how IMRT is used now and how it will be used in the future. The book begins with a historical background of IMRT as well as a discussion of the current state of IMRT. It also covers technical solutions that have been commercialized, such as the sliding window technique, step-and-shoot, tomotherapy, and the Cyberknife. The final chapter explores imaging developments and new planning methods, including gradient-descent and split modulation.

Covering recent advancements in IMRT and showing how these techniques and devices have been implemented, Contemporary IMRT: Developing Physics and Clinical Implementation provides state-of-the-art findings for oncologists, radiotherapists, radiographers, physicists, and engineers.
Preface and acknowledgments xv
1 Intensity-modulated radiation therapy (IMRT): General statements and points of debate 1(17)
1.1 Observations on IMRT at the current time
1(9)
1.2 Criticism of the philosophy of IMRT
10(8)
2 Developments in rotation IMRT and tomotherapy 18(21)
2.1 NOMOS MIMiC tomotherapy
18(8)
2.1.1 Technology history
18(3)
2.1.2 Matchline concerns and solutions
21(2)
2.1.3 Energy considerations
23(1)
2.1.4 Concerns about increased treatment time
24(1)
2.1.5 Machine features
25(1)
2.2 University of Wisconsin machine for tomotherapy
26(9)
2.2.1 Development history
26(2)
2.2.2 Generation and use of megavoltage computed tomography (MVCT) images
28(5)
2.2.3 Clinical application
33(1)
2.2.4 Commissioning issues
34(1)
2.2.5 Verification of MIMIC and University of Wisconsin tomotherapy
35(1)
2.3 Tomotherapy using a 60Co source
35(2)
2.4 Tomotherapy with an MLC
37(1)
2.5 Summary
38(1)
3 Developments in IMRT using a multileaf collimator (MLC) (physics) 39(122)
3.1 New sequencers/interpreters
46(20)
3.1.1 General; dynamic IMRT sequencers with hard MLC constraints on leaves and jaws
46(1)
3.1.2 Sequencing multiple-static MLC fields-clusters
47(3)
3.1.3 Non-uniform spatial and fluence steps
50(1)
3.1.4 Minimizing the number of segments
51(2)
3.1.5 IMFAST
53(1)
3.1.6 The best interpreter ever?
53(3)
3.1.7 Sequencers exploiting MLC rotation
56(2)
3.1.8 Comparison of dynamic MLC (dMLC) and multiple static field (MSF) techniques
58(3)
3.1.9 Varian MLC and HELIOS planning system
61(1)
3.1.10 Developments in Elekta IMRT
62(1)
3.1.11 Other interpreters
63(3)
3.1.12 The effect of removing the flattening filter
66(1)
3.2 Radiation leakage and accounting for machine effects in IMRT delivery
66(8)
3.2.1 General leakage issues
66(2)
3.2.2 Factoring in delivery physics
68(1)
3.2.2.1 Measurement and prediction of leakage and scatter
68(2)
3.2.2.2 Using leakage and scatter knowledge in the MSF-MLC technique
70(3)
3.2.3 The effect of rounded leaf ends: light-field to radiation-field discrepancy in IMRT
73(1)
3.3 Dose calculation for IMRT
74(3)
3.3.1 Application of colour theory
75(1)
3.3.2 Penumbra sharpening for IMRT
76(1)
3.3.3 MU verification
76(1)
3.4 Features of MLC delivery of IMRT
77(7)
3.4.1 Large-field IMRT-splitting the delivery
77(1)
3.4.2 Tongue-and-groove effect
77(3)
3.4.3 Leaf-speed limitations
80(1)
3.4.4 Stability of accelerator and delivery of a small number of MUs and small fieldsizes
81(3)
3.5 Dynamic arc therapy
84(2)
3.6 Combining step-and-shoot and dynamic delivery for dMLC
86(3)
3.7 IMAT-technical issues
89(6)
3.7.1 IMAT in clinical use
92(2)
3.7.2 IMAT modified to aperture-modulated-arc therapy (AMAT)
94(1)
3.8 New ideas related to the dMLC technique
95(1)
3.9 Compensators and comparisons of compensator and MLC-based IMRT
96(81)
3.9.1 Do we need the MLC for IMRT?
96(1)
3.9.2 Use of compensators for IMRT
97(8)
3.9.3 Comparison of compensator and MLC-based IMRT
105(1)
3.10 Optimum width of leaves for an MLC
106(1)
3.11 MicroMLCs for IMRT
107(9)
3.11.1 Siemens (virtual) microMLC
107(1)
3.11.2 Varian (virtual) MLC
108(1)
3.11.3 Elekta (virtual) microMLC and microMLC
108(1)
3.11.4 Radionics microMLC
109(1)
3.11.5 BrainLAB microMLC
110(1)
3.11.6 DKFZ-originating microMLCs
111(1)
3.11.6.1 The MRC systems GMBH/Siemens 'Moduleaf'
111(1)
3.11.6.2 New DKFZ microMLC
112(1)
3.11.7 3DLine microMLC
112(1)
3.11.8 Comparison and use of microMLCs
112(3)
3.11.9 Multi-level MLC
115(1)
3.12 Increasing the spatial resolution of a conventional MLC
116(4)
3.13 Verification of MLC-delivered IMRT
120(32)
3.13.1 Electronic-portal-imager-based IMRT verification
120(4)
3.13.2 Other EPID designs
124(1)
3.13.3 Technical aspects of EPID imaging for IMRT
124(1)
3.13.4 Extraction of anatomical images from portal images generated during IMRT
125(1)
3.13.5 Blocking-tray-level measurement
126(1)
3.13.6 The two-level MLC
127(2)
3.13.7 Water-beam-imaging system (WBIS)
129(2)
3.13.8 Integrated portal fluence and portal dosimetry
131(1)
3.13.9 IMRT verification phantom measurements
132(6)
3.13.10 Verification by software techniques
138(3)
3.13.11 Comparison of delivered modulated fluence profile with plan-predicted modulated profile
141(2)
3.13.12 Verification of canine and human IMRT using in-vivo dosimetry
143(1)
3.13.13 Polyacrylamide gel (PAG) dosimetry for IMRT verification
144(1)
3.13.13.1 Review
144(1)
3.13.13.2 PAG readout techniques
145(2)
3.13.13.3 Use of PAGs for IMRT verification
147(3)
3.13.13.4 New PAGs
150(1)
3.13.14 Film as an IMRT dosimeter
150(2)
3.14 Quality assurance (QA) of MLC delivery
152(7)
3.14.1 Average leaf-pair opening (ALPO)
152(1)
3.14.2 Routine QA of MLC leaf movement
153(5)
3.14.3 Modelling the effects of MLC error
158(1)
3.15 Summary
159(2)
4 Developments in IMRT not using an MI,C 161(18)
4.1 The Cyberknife
161(7)
4.2 The design of the shuttling MLC (SMLC)
168(1)
4.3 IMRT with the 'jaws-plus-mask' technique
169(5)
4.4 The variable aperture collimator (VAC)
174(2)
4.5 One-dimensional IMRT
176(1)
4.6 Summary
177(2)
5 Clinical IMRT-evidence-based medicine? 179(51)
5.1 IMRT of the prostate showing measurable clinical benefit
183(4)
5.2 Comparison of treatment techniques for the prostate
187(5)
5.3 Royal Marsden NHS Foundation Trust pelvic and other IMRT
192(5)
5.4 Comparison of IMRT with conformal radiotherapy (CFRT) for complex shaped tumours
197(2)
5.5 IMRT for whole-pelvic and gynaecological radiotherapy
199(2)
5.6 Head-and-neck IMRT
201(10)
5.6.1 Thyroid IMRT
202(1)
5.6.2 Nasopharynx IMRT
203(1)
5.6.3 Oropharynx IMRT
204(1)
5.6.4 Oropharynx and nasopharynx IMRT
205(1)
5.6.5 Larynx IMRT
205(1)
5.6.6 Evidence for parotid sparing
206(3)
5.6.7 Meningioma IMRT
209(1)
5.6.8 Paediatric medulloblastoma IMRT
210(1)
5.6.9 Ethmoid cancer IMRT
210(1)
5.6.10 Other studies reported
210(1)
5.7 Breast IMRT
211(11)
5.7.1 Breast IMRT at William Beaumont Hospital
211(3)
5.7.2 Other reports of techniques using small top-up fields
214(2)
5.7.3 EPID-based techniques for breast IMRT
216(2)
5.7.4 Modified wedge technique
218(1)
5.7.5 Breast IMRT in combination with use of respiration gating
218(1)
5.7.6 Comparison of IMRT delivery techniques for the breast
218(2)
5.7.7 Reduced complications observed following breast IMRT
220(2)
5.7.8 Combination of IMRT with charged-particle irradiation
222(1)
5.8 Bladder IMRT at the Christie Hospital
222(2)
5.9 Lung cancer IMRT
224(1)
5.10 Scalp IMRT
225(2)
5.11 Other clinical IMRT reports-various tumour sites
227(1)
5.12 Summary
228(2)
6 3D planning for CFRT and IMRT: Developments in imaging for planning and for assisting therapy 230(149)
6.1 Challenges to IMRT and inverse planning
230(1)
6.2 Determination of the GTV, CTV and PTV; the influence of 3D medical imaging
231(19)
6.2.1 General comments on inhomogeneous dose to the PTV and image-guided planning
231(1)
6.2.2 Interobserver variability in target-volume definition
231(1)
6.2.3 Margin definition
232(2)
6.2.4 Use of magnetic resonance for treatment planning
234(1)
6.2.4.1 Distortion correction
234(2)
6.2.4.2 Use of contrast agents
236(1)
6.2.4.3 Planning based on MR images alone
237(1)
6.2.4.4 Coregistered CT and MR planning
237(3)
6.2.4.5 Increased protection of structures
240(1)
6.2.4.6 Monitoring the response to radiotherapy via MRI
241(1)
6.2.5 Use of functional information from SPECT and PET for treatment planning
242(1)
6.2.5.1 Generalities and prostate imaging
242(2)
6.2.5.2 Head-and-neck imaging
244(2)
6.2.5.3 Lung imaging
246(1)
6.2.5.4 Para-aortic lymph node (PALN) imaging
247(1)
6.2.5.5 Combined PET-CT scanning
248(1)
6.2.5.6 Imaging to overcome breathing-motion effects
248(2)
6.2.6 Use of pathology specimens to compare with GTV and PTV
250(1)
6.3 New inverse-planning methods for IMRT
250(28)
6.3.1 Gradient-descent inverse planning
251(1)
6.3.2 Simulated annealing inverse planning
251(1)
6.3.3 Equivalent-uniform-dose-based inverse planning
251(1)
6.3.4 Maximum entropy inverse planning
252(1)
6.3.5 Genetic algorithms
253(1)
6.3.6 Single-step inverse planning
254(1)
6.3.7 Simulated particle dynamics
255(2)
6.3.8 Optimization of surrogate parameters in beam space
257(2)
6.3.9 Comparison of inverse-planning techniques
259(2)
6.3.10 Features and comparison of commercial planning algorithms
261(1)
6.3.11 Dependences of IMRT plans on target geometry
262(1)
6.3.12 Multiple local minima and the global minimum in optimization
263(3)
6.3.13 Sampling the dose matrix for IMRT optimization speed-up
266(3)
6.3.14 Creating a uniform PTV dose in IMRT; cost tuning
269(1)
6.3.15 Importance factors
269(2)
6.3.15.1 Voxel-dependent IFs
271(2)
6.3.16 Biological and physical optimization
273(2)
6.3.17 Pareto optimal IMRT
275(1)
6.3.18 Combined CFRT and IMRT
275(1)
6.3.19 Split modulation
276(2)
6.3.20 Summary on inverse-planning techniques
278(1)
6.4 New forward-planning methods for IMRT; direct aperture optimization
278(10)
6.4.1 Segmental inverse planning at Thomas Jefferson University (TJU)
279(1)
6.4.2 Aperture-based planning at the University of Ghent
280(4)
6.4.3 Direct aperture optimization (DAO) at the University of Maryland
284(2)
6.4.4 DAO wobbling the MLC leaf positions
286(1)
6.4.5 Other forward-planning studies
286(1)
6.4.6 Summary on aperture-based IMRT
287(1)
6.5 Smoothing IMBs
288(7)
6.5.1 Smoothing techniques from the Royal Marsden NHS Foundation Trust
288(1)
6.5.2 Smoothing techniques from the University of Virginia
288(2)
6.5.3 Smoothing technique from the Memorial Sloan Kettering Cancer Institute
290(1)
6.5.4 Smoothing technique from the University of Tubingen
290(2)
6.5.5 Smoothing technique in the Nucletron PLATO TPS
292(1)
6.5.6 Smoothing technique at the Thomas Jefferson University
292(1)
6.5.7 Smoothing techniques at University of Maryland
292(1)
6.5.8 Smoothing techniques at University of California, San Francisco
293(1)
6.5.9 Smoothing techniques at Sichuan University, China
293(1)
6.5.10 Summary on smoothing
294(1)
6.6 Incorporating MLC equipment constraints in inverse planning
295(1)
6.7 Beam direction optimization
296(9)
6.8 Monte Carlo dose calculation
305(12)
6.8.1 The debate over the usefulness of Monte Carlo dose-calculation techniques
305(2)
6.8.2 Determination of photon spectrum and phase space data for Monte Carlo calculations
307(1)
6.8.3 Comparison of Monte Carlo and pencil-beam calculations
307(3)
6.8.4 MCDOSE
310(2)
6.8.5 Speeding up Monte Carlo dose calculations
312(1)
6.8.6 Monte Carlo calculation accuracy and error
313(1)
6.8.7 Application to the dMLC technique
313(2)
6.8.8 Monte Carlo calculations in tomotherapy
315(1)
6.8.9 Monte Carlo calculations of IMAT
315(1)
6.8.10 Other reports on Monte Carlo dosimetry
316(1)
6.9 Energy in IMRT
317(2)
6.10 Measuring and accounting for patient/tumour movement
319(49)
6.10.1 General review
319(1)
6.10.2 Some observations of the effects of movement
320(1)
6.10.3 Optical imaging for movement correction
321(1)
6.10.3.1 Breast movement
323(1)
6.10.4 X-ray imaging of position
323(1)
6.10.4.1 Intrafraction and interfraction prostate movement measurements
323(1)
6.10.4.2 Intrafraction and interfraction lung movement measurements
327(2)
6.10.5 Ultrasound measurement of position
329(1)
6.10.5.1 The NOMOS BAT
331(1)
6.10.5.2 Other ultrasound systems developed
335(2)
6.10.6 Magnetic monitoring of position
337(1)
6.10.7 Gating
337(1)
6.10.7.1 Gating based on optical measurements of surface markers
337(1)
6.10.7.2 Gating based on x-ray fluoroscopic measurements
339(1)
6.10.7.3 Imaging and therapy gated by respiration monitor
341(1)
6.10.7.4 Measurements using oscillating phantoms
343(1)
6.10.7.5 Evidence against the need for gating
345(1)
6.10.8 Robotic feedback
346(1)
6.10.9 Held-breath self-gating
347(1)
6.10.10 Intervention for immobilization
348(1)
6.10.11 Active breathing control
348(3)
6.10.12 Calculating the effect of tissue movement
351(1)
6.10.12.1 Incorporating movement knowledge into the inverse planning itself
351(1)
6.10.12.2 Use of multiple CT datasets and adaptive IMRT
352(7)
6.10.12.3 Modelling the effect of intrafraction movement
359(8)
6.10.12.4 Modelling set-up inaccuracy
367(1)
6.10.12.5 Modelling the movement of OARs
368(1)
6.11 Megavoltage CT (MVCT) and kilovoltage CT (kVCT) for position verification
368(6)
6.11.1 MVCT
368(4)
6.11.2 Flat-panel imaging for kVCT
372(2)
6.12 MRI and IMRT simultaneously
374(2)
6.13 IMRT using mixed photons and electrons
376(3)
Epilogue 379(3)
References 382(82)
Index 464


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