Cover Imaging for Physicists
|
ESTRO Course Book |
1 |
|
Imaging for Physicists |
1 |
|
13 – 17 September, 2015 |
1 |
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Leiden, The Netherlands |
1 |
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L02 MRI Physics; Basic Principles - Malinen |
7 |
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MRI physics - basic principles |
7 |
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Background |
8 |
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Nuclear magnetic moment |
9 |
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Magnetic moment and spin |
10 |
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Quantized nuclear spin |
11 |
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Unpaired nucleons, spin and g |
12 |
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Potential energy in magnetic field |
13 |
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Magnetic resonance |
14 |
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Magnetic resonance |
15 |
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Macroscopic considerations |
16 |
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Macroscopic magnetization |
17 |
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Bloch equations |
18 |
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Spin precession (new slide) |
19 |
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Spin precession |
20 |
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Introducing the RF field |
21 |
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Flip angle |
22 |
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T1 relaxation |
23 |
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T2 relaxation |
24 |
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T2 relaxation cont’d |
25 |
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Relaxation |
26 |
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Relaxation dynamics |
27 |
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Relaxation dynamics and contrast |
28 |
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Detection |
29 |
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Free induction decay |
30 |
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Summary |
31 |
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Thank you for your attention! |
32 |
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L03 MRI Physics; Contrast Formation - Nyholm |
33 |
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MRI physics: Contrast formation |
33 |
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Precession |
34 |
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Flip |
35 |
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Relaxation |
36 |
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T1 relaxation |
37 |
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T2 relaxation |
38 |
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T2* relaxation |
39 |
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Slide Number 8 |
40 |
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Spin-Echo sequence |
41 |
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T2 contrast |
42 |
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Slide Number 11 |
43 |
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T2 contrast |
44 |
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ExamplesT2 Contrast |
45 |
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T1 contrast |
46 |
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T1 Contrast |
47 |
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Slide Number 16 |
48 |
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T1 contrast |
49 |
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ExamplesT1 contrast |
50 |
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Inversion-recovery (IR) |
51 |
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Slide Number 20 |
52 |
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IR |
53 |
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IR |
54 |
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Summary |
55 |
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Proton contrast |
56 |
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Turbo spin echoFast spin echo |
57 |
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Gradient echo (T2*) |
58 |
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Gradient echo |
59 |
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What kind of contrast? |
60 |
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Different contrasts |
61 |
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Why is it often difficult to see gold markers in T2w spin echo sequences of the prostate? |
62 |
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Slide Number 32 |
63 |
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Summary again |
64 |
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Slide Number 34 |
65 |
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L04 MRI Physics; Space Encoding - Liney |
66 |
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MRI Physics: Space Encoding |
66 |
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Introduction |
67 |
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Spin Echo Sequence |
68 |
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Fourier Transform (FT) |
69 |
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Fourier Transform (FT) |
70 |
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FT Pairs |
71 |
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FT Pairs |
72 |
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Gradients |
73 |
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Slice Selection |
74 |
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Slice Selection |
75 |
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Slice Selection |
76 |
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Slice Selection |
77 |
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Slice Selection |
78 |
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Frequency Encoding |
79 |
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Phase Encoding |
80 |
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Phase Encoding |
81 |
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Phase Encoding |
82 |
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Phase Encoding |
83 |
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Slide Number 19 |
84 |
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Slide Number 20 |
85 |
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Slide Number 21 |
86 |
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Faster unchanged slower |
87 |
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Phase Encoding |
88 |
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Spin Echo Sequence |
89 |
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Spin Echo Sequence |
90 |
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Spin Echo Sequence |
91 |
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Scan Time |
92 |
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Multi-Slice Imaging |
93 |
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‘3D’ MRI |
94 |
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What is k-space? |
95 |
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What is k-space? |
96 |
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What is k-space? |
97 |
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k-space |
98 |
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k-space |
99 |
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k-space |
100 |
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k-space |
101 |
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k-space trajectories |
102 |
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k-space trajectories |
103 |
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Partial k-space |
104 |
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L05 MRiPhysics; Equipment - Liney |
105 |
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MRI Physics: Equipment |
105 |
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Installation of New Scanner |
106 |
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RF Cage |
107 |
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RF Cage Construction |
108 |
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Slide Number 5 |
109 |
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The Inner Controlled Area |
110 |
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Cabinet (Equipment) Room |
111 |
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MRI Equipment: Overview |
112 |
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Patient Bore |
113 |
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Example Specifications |
114 |
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Example Specifications |
115 |
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Magnet |
116 |
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Slide Number 13 |
117 |
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Static Field (B0) |
118 |
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Superconductors |
119 |
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Homogeneity |
120 |
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Shim Demo |
121 |
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Slide Number 18 |
122 |
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Fringe (stray) Field |
123 |
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Slide Number 20 |
124 |
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Slide Number 21 |
125 |
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Slide Number 22 |
126 |
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Gradients (db/dt) |
127 |
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Gradients |
128 |
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Gradients |
129 |
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Gradients |
130 |
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Peripheral Nerve Stimulation (PNS) |
131 |
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RF Coils (B1) |
132 |
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RF Chain |
133 |
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RF Coils: Signal Characteristics |
134 |
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RF Coil Designs |
135 |
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RF Coils |
136 |
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Coil Arrays |
137 |
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Quadrature Coils |
138 |
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RF Coils: Other |
139 |
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B1 Uniformity |
140 |
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Dielectric Effect |
141 |
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RT Specific Equipment |
142 |
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RT Planning Scans |
143 |
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Dedicated System (MR Simulator) |
144 |
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Slide Number 41 |
145 |
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The Future |
146 |
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L06 PET Physics; Basic Principles - Thorwarth |
147 |
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Positron Emission Tomography Physics - Basic Principles |
147 |
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Molecular Imaging with Positron Emission Tomography (PET) |
148 |
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Basic principle of PET |
149 |
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Slide Number 4 |
150 |
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State-of-the-art PET/CT Designs |
151 |
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PET/CT |
152 |
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Slide Number 7 |
153 |
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Slide Number 8 |
154 |
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2D-/3D-PET |
155 |
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2D/3D-PET acquisition |
156 |
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Axial Sensitivity |
157 |
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Image Formation |
158 |
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Radiation detection |
159 |
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Properties of scintillaton detectors applied in PET |
160 |
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Photo-multiplier tubes (PMTs) |
161 |
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Detector Designs used in PET |
162 |
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Detector Designs used in PET |
163 |
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Timing Resolution and Coincidence Detection |
164 |
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Question: Timing Resolution |
165 |
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Answer: Timing Resolution |
166 |
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Time-of-flight (TOF) PET |
167 |
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Question: Time-of-flight |
168 |
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Question: Time-of-flight |
169 |
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Detected Events in PET |
170 |
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Prompt Events |
171 |
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Prompt Events (II) |
172 |
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Performance of PET Systems |
173 |
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Performance of PET Systems:Spatial Resolution |
174 |
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Performance of PET Systems: Energy Resolution |
175 |
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Performance of PET Systems:Count Rate Performance |
176 |
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Performance of PET Systems: Scatter Fraction |
177 |
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Performance of PET Systems: Scatter Fraction |
178 |
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Summary |
179 |
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Literature |
180 |
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L07 MRI Geometrical Artifacts I - van der Heide |
181 |
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Slide Number 1 |
181 |
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Artifacts in MRI |
182 |
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Artifacts in MRI |
183 |
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Outline |
184 |
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Origin of various artifacts |
185 |
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Imaging artifact |
186 |
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Sampling the MR signal |
187 |
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Sampling the MR signal |
188 |
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Resolve aliasing by increasing sampling frequency |
189 |
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Field Of View covers entire object: no fold-over |
190 |
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Question: field of view |
191 |
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Field Of View covers entire object: no fold-over |
192 |
|
FOV too small: fold-over |
193 |
|
How to suppress fold-over artifacts? |
194 |
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How to suppress fold-over artifacts? |
195 |
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How to suppress fold-over artifacts? |
196 |
|
Saturate signal from outside FOV |
197 |
|
Imaging artifact |
198 |
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Imaging artifact |
199 |
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Truncation errors (ringing) |
200 |
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How to avoid truncation errors (Ringing) |
201 |
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Sampling of k-space |
202 |
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Sampling of k-space |
203 |
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Sampling k-space in practice |
204 |
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Position encoding in a spin-echo sequence |
205 |
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Slice selection: transversal |
206 |
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Phase encoding |
207 |
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Phase encoding |
208 |
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Phase encoding |
209 |
|
Phase encoding |
210 |
|
Frequency encoding (read-out) |
211 |
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Frequency encoding (read-out) |
212 |
|
Position encoding in a spin-echo sequence |
213 |
|
A spin-echo sequence in k-space |
214 |
|
A spin-echo sequence in k-space |
215 |
|
A spin-echo sequence in k-space |
216 |
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Phase evolution |
217 |
|
Phase evolution |
218 |
|
A spin-echo sequence in k-space |
219 |
|
Do we really sample k-space the way we think we do? |
220 |
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Imperfections of B0 and gradient fields |
221 |
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Non-linear gradients cause position distortions |
222 |
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Magnetic susceptibility |
223 |
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Erroneous sampling of k-space |
225 |
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Position errors: slice selection |
226 |
|
Distortion of phase evolution |
227 |
|
Impact on geometrical accuracy |
228 |
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Impact on geometrical accuracy |
229 |
|
Result: geometrical distortion in spin-echo imaging |
230 |
|
Question: water-fat shift |
231 |
|
Result: geometrical distortion in spin-echo imaging |
232 |
|
Distortions in a Gradient Echo sequence |
233 |
|
Dephasing due to static field inhomogeneities |
234 |
|
Rephasing in a Spin Echo sequence |
235 |
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Continued dephasing in a Gradient Echo sequence |
236 |
|
Phantom experiments |
237 |
|
Dephasing effects increase with TE in gradient echo imaging |
238 |
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Dephasing effects increase with TE in gradient echo imaging |
239 |
|
Summary 1 |
240 |
|
Outline lecture 2 |
241 |
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L08 MRI Geometrical Artifacts II - van der Heide |
242 |
|
Slide Number 1 |
242 |
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Many reasons for artifacts |
243 |
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Many reasons for artifacts |
244 |
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Many reasons for artifacts |
245 |
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Outline lecture 2 |
246 |
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Homogeneity of the main magnetic field |
247 |
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Gradient fields |
248 |
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Correction of imperfect B0 and gradient fields |
249 |
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Phantoms |
250 |
|
Design of a phantom for field-error measurements |
251 |
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Setup of experiments to characterize magnetic field inhomogeneity and gradient non-linearity |
252 |
|
Distortion mapping |
253 |
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Continuous or stepped table measurement |
254 |
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Gradient corrections |
255 |
|
System measurements |
256 |
|
Slide Number 16 |
257 |
|
Magnetic susceptibility |
258 |
|
Susceptibility artifacts |
259 |
|
Susceptibility artifacts |
260 |
|
Susceptibility artifacts |
261 |
|
Calculation of field distortions |
262 |
|
Susceptibility artifact in read-out direction |
263 |
|
Shimming |
264 |
|
B0 mapping |
265 |
|
B0 mapping |
266 |
|
Examples of artifacts |
267 |
|
Example from clinical practice. What is wrong? |
268 |
|
CT scan of same patient |
269 |
|
Patient with hip prosthesis |
270 |
|
Patient with hip prosthesis |
271 |
|
Susceptibility artifact |
272 |
|
Water-Fat Shift |
273 |
|
Water-fat shift |
275 |
|
Water-fat shift |
276 |
|
Question: motion artifacts |
277 |
|
Motion artifacts |
278 |
|
Motion artifacts |
279 |
|
What to do about it? |
280 |
|
Motion correction with a Propeller sequence |
281 |
|
Propeller sequence: Eye movement |
282 |
|
bSSFP artifact |
283 |
|
bSSFP artifact |
284 |
|
EPI artifacts |
285 |
|
EPI artifact |
286 |
|
Geometrical artifacts |
287 |
|
Practical consequences |
288 |
|
Practical consequences |
289 |
|
Slide Number 49 |
290 |
|
Summary 1 |
291 |
|
Summary 2 |
292 |
|
Slide Number 52 |
293 |
|
Acknowledgments |
294 |
|
L09_PET Physics; Image Reconstruction, Contouring - Thorwarth |
295 |
|
Slide Number 1 |
295 |
|
PET Image Formation |
296 |
|
Random Correction |
297 |
|
Normalization |
298 |
|
Slide Number 5 |
299 |
|
Scatter Correction |
300 |
|
Improved image quality due to random and scatter correction |
301 |
|
Attenuation Correction |
302 |
|
CT-based attenuation correction |
303 |
|
Slide Number 10 |
304 |
|
…and their consequences |
305 |
|
Slide Number 12 |
306 |
|
4D-PET/CT vs. 3D-PET/CT |
307 |
|
Image Reconstruction |
308 |
|
Analogue to CT reconstruction: Filtered Backprojection |
309 |
|
Fourier Slice Theorem |
310 |
|
Filtered Backprojection (FBP) |
311 |
|
Filtered Backprojection FBP |
312 |
|
Filtered Backprojection |
313 |
|
Iterative reconstruction: ML-EM |
314 |
|
ML-EM: noisy data introduce instabilities |
315 |
|
OSEM (ordered subset EM) |
316 |
|
Slide Number 23 |
317 |
|
3D Iterative Reconstruction |
318 |
|
Time-of-Flight (TOF) PET |
319 |
|
Resolution Modeling - PSF |
320 |
|
Iterative reconstruction with resolution modeling |
321 |
|
Improvement of PET/CT Image Quality |
322 |
|
Summary: Reconstruction |
323 |
|
Quantitative analysis of PET images |
324 |
|
Slide Number 31 |
325 |
|
Absolute Thresholding |
326 |
|
Relative Thresholding |
327 |
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Iterative Thresholding |
328 |
|
Source-to-Background Algorithms |
329 |
|
Comparison of different contouring approaches |
330 |
|
Gradient-based auto-contouring |
331 |
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Gradient-based auto-segmentation |
332 |
|
Gradient-based segmentation improves target volume definition in NSCLC |
333 |
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Activity Recovery, Partial Volume Effect:The Smaller the Volume, the Darker it Appears |
334 |
|
Influence of PET reconstruction |
335 |
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Effect of reconstruction on PET-based contouring |
336 |
|
Comparison of auto-contouring methods with „intelligent“ manual delineation |
337 |
|
EARL: Standardization of clinical PET scanners |
338 |
|
Slide Number 45 |
339 |
|
Summary / Conclusion |
340 |
|
Literature |
341 |
|
L10 Applications; MRI in Brain - Menard |
342 |
|
Applications: MRI in Brain |
342 |
|
Goal – MRI Simulation |
343 |
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Slide Number 3 |
344 |
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Slide Number 4 |
345 |
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Slide Number 5 |
346 |
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Slide Number 6 |
347 |
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Tissue Contrast |
348 |
|
Imaging Coils |
349 |
|
MR-only simulationMR imaging of cortical bone with Ultra-short TE |
350 |
|
Delineation – Visible Tumor |
351 |
|
Delineation – MRSI |
352 |
|
MRSI – Predicting Site of Recurrence |
353 |
|
Slide Number 13 |
354 |
|
FA map for CTV delineation |
355 |
|
Slide Number 15 |
356 |
|
b=3000 s/mm2 DW |
357 |
|
Optic Radiation – SRS Injury |
358 |
|
DTI – OAR Sparing |
359 |
|
Atlas-based Segmentation |
360 |
|
Stereotactic Reference - Deviation |
361 |
|
Displacement of IAC |
362 |
|
Stereotactic Reference Deviation (T2) |
363 |
|
Stereotactic Reference Deviation (T1) |
364 |
|
3T: Patient vs. Phantom |
365 |
|
Phantom: Internal Deviation (3T) |
366 |
|
Slide Number 26 |
367 |
|
Hemorhagic Metastasis |
368 |
|
Slide Number 28 |
369 |
|
Example – Clinical readout-segmented-DWI at 3 T |
370 |
|
Geometry – Key Points |
371 |
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Slide Number 31 |
372 |
|
Tumor Geometry ROC for 2y OS |
373 |
|
MRSI – Predicting Response |
374 |
|
Slide Number 34 |
375 |
|
ADC Response |
376 |
|
ADC Dynamics |
377 |
|
ADC Response vs Tumor Growth Rate |
378 |
|
Slide Number 38 |
379 |
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Slide Number 39 |
380 |
|
Slide Number 40 |
381 |
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Diffusion Abnormality Index |
382 |
|
Voxel Correspondence |
383 |
|
Slide Number 43 |
384 |
|
DTI in RT |
385 |
|
Parametric Response Map |
386 |
|
Radionecrosis - Structure |
387 |
|
Radionecrosis - DSC |
388 |
|
Acknowledgements |
389 |
|
L11 Functional Imagin MRI - Liney |
390 |
|
Functional Techniques in MRI |
390 |
|
Slide Number 2 |
391 |
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MRI: Functional techniques |
392 |
|
Slide Number 4 |
393 |
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Techniques of (RT) Interest |
394 |
|
Slide Number 6 |
395 |
|
fMRI protocol |
396 |
|
Slide Number 8 |
397 |
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Slide Number 9 |
398 |
|
MR Spectroscopy |
399 |
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The MR Spectrum |
400 |
|
Spectroscopic Imaging (MRSI) |
401 |
|
Slide Number 13 |
402 |
|
Slide Number 14 |
403 |
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Slide Number 15 |
404 |
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Slide Number 16 |
405 |
|
Slide Number 17 |
406 |
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Slide Number 18 |
407 |
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Slide Number 19 |
408 |
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Slide Number 20 |
409 |
|
DWI |
410 |
|
Slide Number 22 |
411 |
|
Distortions* |
412 |
|
Example |
413 |
|
Slide Number 25 |
414 |
|
Multi-Parameteric MRI (mpMRI) |
415 |
|
Slide Number 27 |
416 |
|
Slide Number 28 |
417 |
|
Intra-fraction Motion in Cine-MRI |
418 |
|
Inter-fraction Motion in Cine-MRI |
419 |
|
Spin Tagging |
420 |
|
Future |
421 |
|
L12 Applications; MRI in Gynaecology RT - Dirix |
422 |
|
Slide Number 1 |
422 |
|
Cervical cancer |
423 |
|
MRI in radiotherapy for cervical cancer |
424 |
|
MRI features |
425 |
|
1. T-staging: normal anatomy |
426 |
|
Cervical anatomy: MRI features |
427 |
|
FIGO I (confined to uterus) |
428 |
|
FIGO II (beyond uterus) |
429 |
|
ACRIN 6651 – GOG 183 |
430 |
|
ACRIN 6651 – GOG 183: PMI |
431 |
|
T2: excluding PMI |
432 |
|
Slide Number 12 |
433 |
|
DWI to predict PMI |
434 |
|
FIGO III (locally advanced) |
435 |
|
FIGO IV (adjacent organs) |
436 |
|
2. N-staging: pelvic disease |
437 |
|
ACRIN 6651 – GOG 183: LNI |
438 |
|
Pelvic LN staging: is PET(-CT) superior? |
439 |
|
Pelvic LN staging: added value of DWI (1) |
440 |
|
Pelvic LN staging: added value of DWI (2) |
441 |
|
Slide Number 21 |
442 |
|
PAO LN staging: is PET(-CT) superior? |
443 |
|
PAO LN: surgical staging remains gold standard |
444 |
|
Conclusion: MRI is superior to CT for LR staging |
445 |
|
Slide Number 25 |
446 |
|
EBRT = MRI-guided, organ-sparing IMRT |
447 |
|
MRI-guided IMRT: GTV delineation |
448 |
|
PET/MRI for GTV |
449 |
|
Correlation between SUVmax & ADCmin |
450 |
|
MRI-guided IMRT: CTV delineation |
451 |
|
MRI-guided IMRT: consensus guidelines |
452 |
|
MRI-guided IMRT: consensus guidelines |
453 |
|
Currently: VMAT |
454 |
|
Based on PET-CT |
455 |
|
And MRI |
456 |
|
MRI-guided IMRT: PTV delineation |
457 |
|
MRI-guided IMRT: organ motion (1) |
458 |
|
MRI-guided IMRT: organ motion (2) |
459 |
|
MRI-guided IMRT: organ motion (3) |
460 |
|
Individualized (non)adaptive IMRT |
461 |
|
Margin/plan of the day (MoD) |
462 |
|
MRI-guided IMRT: what about LN? |
463 |
|
MRI-guided IMRT: tumor shrinkage |
464 |
|
4. BT boost: advantages |
465 |
|
BT boost: ICRU reference dose points (1) |
466 |
|
BT boost: ICRU reference dose points (2) |
467 |
|
MRI-guided, 3D BT |
468 |
|
MRI-guided, 3D BT: advantages |
469 |
|
MRI-guided BT: GEC-ESTRO target definitions (1) |
470 |
|
MRI-guided BT: GEC-ESTRO target definitions (2) |
471 |
|
MRI-guided BT: GEC-ESTRO target definitions (3) |
472 |
|
MRI-guided BT: GEC-ESTRO protocol recommendations |
473 |
|
MRI-guided BT: GEC-ESTRO protocol recommendations |
474 |
|
MRI-guided BT: GEC-ESTRO EQD2 spreadsheet |
475 |
|
MRI-guided BT: Leuven protocol (1) |
476 |
|
MRI-guided BT: Leuven protocol (2) |
477 |
|
MRI-guided BT: manual optimization |
478 |
|
MRI-guided BT: when things go wrong… |
479 |
|
MRI-guided BT: Vienna experience (1) |
480 |
|
MRI-guided BT: Vienna experience (2) |
481 |
|
MRI-guided BT: Nordic experience |
482 |
|
MRI-guided BT: Leuven experience |
483 |
|
MRI-guided BT: EMBRACE trial (1) |
484 |
|
MRI-guided BT: EMBRACE trial (2) |
485 |
|
5. Response assessment: T2w MRI |
486 |
|
5. Response assessment: functional imaging |
487 |
|
5. Response assessment: DWI |
488 |
|
5. Response assessment: PET/MRI |
489 |
|
Conclusion: MRI = crucial for |
490 |
|
Thank you |
491 |
|
L13_ Applciation; MRI in Prostate - Menard |
492 |
|
Applications: MRI in Prostate |
492 |
|
Slide Number 2 |
493 |
|
MRI – Target Delineation |
494 |
|
MRI Integration Improves Prostate Delineation Accuracy? |
495 |
|
Learning Curve |
496 |
|
Autosegmentation |
497 |
|
Smaller CTV |
498 |
|
Slide Number 8 |
499 |
|
Slide Number 9 |
500 |
|
Better Outcomes? |
501 |
|
Reducing PTV margin |
502 |
|
Rectum Bladder |
503 |
|
How To: An Approach |
504 |
|
CT-MRI Registration |
505 |
|
Image Registration |
506 |
|
Motion and Image Quality |
507 |
|
Result Position accuracy - Simulation |
508 |
|
TGSE |
509 |
|
Slide Number 19 |
510 |
|
Deformable Registration |
511 |
|
Pelvis |
512 |
|
Slide Number 22 |
513 |
|
Slide Number 23 |
514 |
|
Slide Number 24 |
515 |
|
Atlas-based Electron Density Maps |
516 |
|
Paradigm Shift |
517 |
|
Slide Number 27 |
518 |
|
Slide Number 28 |
519 |
|
Slide Number 29 |
520 |
|
Diffusion Imaging - Geometry |
521 |
|
Cancer is Not Confided to the Prostate Gland |
522 |
|
Independent Predictive Factor |
523 |
|
ECE and Brachytherapy |
524 |
|
Local Failure |
525 |
|
Impact on CTV delineation |
526 |
|
Volume of Tumor Burden on MRI and Radiotherapy Outcomes |
527 |
|
Slide Number 37 |
528 |
|
Slide Number 38 |
529 |
|
Slide Number 39 |
530 |
|
Slide Number 40 |
531 |
|
Impact of cell density |
532 |
|
Slide Number 42 |
533 |
|
Slide Number 43 |
534 |
|
Contouring Variability |
535 |
|
Probability Maps – Path Validation |
536 |
|
Neo-adjuvant Hormones |
537 |
|
Slide Number 47 |
538 |
|
Dosimetry Literature |
539 |
|
Systematic Review – Tumor Boost |
540 |
|
Systematic Review |
541 |
|
Caution in De-escalation |
542 |
|
MRI - GEC/ESTRO 2005 → 2013 |
543 |
|
Slide Number 53 |
544 |
|
Registration to CT |
545 |
|
Slide Number 55 |
546 |
|
Slide Number 56 |
547 |
|
Slide Number 57 |
548 |
|
Image Acquisition |
549 |
|
Slide Number 59 |
550 |
|
Needle Guidance – Anterior Tumours |
551 |
|
Slide Number 61 |
552 |
|
Conclusions |
553 |
|
LN spead |
554 |
|
LNs – MRL vs PET |
555 |
|
DWI – LN imaging |
556 |
|
bDFS according to MRI findings |
557 |
|
bDFS according to dose to macroscopic recurrence |
558 |
|
Target Geometry (Deformation) – Prostate |
559 |
|
Early Response - Endogenous |
560 |
|
Early Response – Contrast Kinetics |
561 |
|
Acknowledgements |
562 |
|
L14 Applications; MRI Guided RT for H&N - Dirix |
563 |
|
Slide Number 1 |
563 |
|
MRI in radiotherapy for HNC |
564 |
|
Head and neck cancer (HNC) |
565 |
|
Current standard: concomitant CRT |
566 |
|
Towards a higher conformality |
567 |
|
1. GTV delineation becomes critical |
568 |
|
Is imaging reliable? |
569 |
|
Radiation oncologists live inside Plato’s cave |
570 |
|
Large intra/inter-observer variability |
571 |
|
Slide Number 10 |
572 |
|
Slide Number 11 |
573 |
|
Slide Number 12 |
574 |
|
MRI for nasopharyngeal cancer (NPC) |
575 |
|
MRI for sinonasal cancer (SNC) |
576 |
|
MRI for all base of skull tumors! |
577 |
|
MRI for oropharyngeal cancer (OPC) |
578 |
|
MRI for hypopharyngo-laryngeal cancer (1) |
579 |
|
Slide Number 18 |
580 |
|
Slide Number 19 |
581 |
|
Caution with FDG-PET for GTV delineation |
582 |
|
2. Highly conformal RT: LN staging is crucial |
583 |
|
FDG-PET |
584 |
|
Slide Number 23 |
585 |
|
Apparent Diffusion Coefficient (ADC) |
586 |
|
Apparent Diffusion Coefficient (ADC) |
587 |
|
Slide Number 26 |
588 |
|
Slide Number 27 |
589 |
|
Results (1) |
590 |
|
Results (2) |
591 |
|
Clinical example of DWI for LN staging |
592 |
|
Similar results at Maastricht University |
593 |
|
All reported results for ADC-based nodal staging |
594 |
|
Towards dose de-escalation on the elective neck? |
595 |
|
Significantly less dysphagia, clinical outcome expected |
596 |
|
3. Early response assessment |
597 |
|
Slide Number 36 |
598 |
|
Slide Number 37 |
599 |
|
Slide Number 38 |
600 |
|
Slide Number 39 |
601 |
|
Slide Number 40 |
602 |
|
Slide Number 41 |
603 |
|
Slide Number 42 |
604 |
|
Clinical example of DWI for response assessment (1) |
605 |
|
Clinical example of DWI for response assessment (2) |
606 |
|
Clinical example of DWI for response assessment (3) |
607 |
|
Slide Number 46 |
608 |
|
Slide Number 47 |
609 |
|
Slide Number 48 |
610 |
|
Slide Number 49 |
611 |
|
Slide Number 50 |
612 |
|
Slide Number 51 |
613 |
|
Slide Number 52 |
614 |
|
Slide Number 53 |
615 |
|
Slide Number 54 |
616 |
|
Slide Number 55 |
617 |
|
FDG-PET & DWI contain different info |
618 |
|
Pathology validation study |
619 |
|
Pathology validation study |
620 |
|
Pathology validation study |
621 |
|
Association between ADC and pathology (1) |
622 |
|
Association between ADC and pathology (2) |
623 |
|
All reported results for DWI & response assessment |
624 |
|
Initial Ktrans predicts outcome |
625 |
|
Repeated imaging during RT |
626 |
|
5. DWI during follow-up |
627 |
|
Clinical example of DWI during follow-up |
628 |
|
Slide Number 67 |
629 |
|
7. Organ-sparing |
630 |
|
DWI: non-invasive evaluation of salivary gland function |
631 |
|
6. Pitfalls of DWI |
632 |
|
Slide Number 71 |
633 |
|
Slide Number 72 |
634 |
|
Slide Number 73 |
635 |
|
Slide Number 74 |
636 |
|
Slide Number 75 |
637 |
|
L15-16 CT Physics 3D and 4D Imanging & Advanced Applications - Geleijns |
638 |
|
CT PhysicsAdvanced CT Applications3D and 4D CT imaging |
638 |
|
Modern CT scanners |
639 |
|
Projection radiography, chest |
640 |
|
Computed tomography, chest |
641 |
|
Normal display of CT images |
642 |
|
State of the art: very fast, excellent image quality |
643 |
|
State of the art: excellent 4D image quality |
644 |
|
Advanced Computed Tomography |
645 |
|
Slide Number 9 |
646 |
|
Slide Number 10 |
647 |
|
Computed tomography was originally known as the "EMI scan“ 1973 |
648 |
|
Slide Number 12 |
649 |
|
Slide Number 13 |
650 |
|
Slide Number 14 |
651 |
|
Acquisition geometry …. |
652 |
|
Acquisition geometry …. |
653 |
|
Acquisition geometry …. |
654 |
|
Multisource (and multi slice) CT: three x-ray tubes and three detector arcs United States Patent April 1980 |
655 |
|
Multisource (and multi slice) CT: three x-ray tubes and three detector arcs United States Patent April 1980 |
656 |
|
Multisource (and multi slice) CT: three x-ray tubes and three detector arcs United States Patent April 1980 |
657 |
|
Dynamic Spatial Reconstructor 198014 x-ray tubes and 14 image intensifiers |
658 |
|
Helical scanning: continuous rotation of the x-ray source and continuous translation of the patient. United States Patent, December, 1986. |
659 |
|
Helical scanning: continuous rotation of the x-ray source and continuous translation of the patient. United States Patent, December, 1986. |
660 |
|
Advanced Computed Tomography |
661 |
|
64 detector row scanner in 2004, e.g. 64 x 0.5 mm = 32 mm. |
662 |
|
Helical dual source CT scanner in 2005: two x-ray tubes, two multislice detectors. |
663 |
|
Axial 320 detector row volume CT in 2007. Patient translation is not required for coverage of entire organs. |
664 |
|
320 slice (cone beam) CT in 2007 |
665 |
|
320 x 0.5 mm detector, 160 mm coverage |
666 |
|
Cone beam (FPD) CT for 3D mammography, diagnosis of breast cancer |
667 |
|
Mucinous adenocarcinoma (arrowheads) with partial rim enhancement (arrow) in a 46-year-old woman: a. postcontrast transverse, b. precontrast coronal, and c. postcontrast coronal breast CT |
668 |
|
3D imaging in the cath-lab |
669 |
|
3D imaging in the cath-lab |
670 |
|
Cone beam (FPD) CT mounted on a LinacKilovoltage imaging, 30-60 seconds |
671 |
|
Axial coverage or Field Of View |
672 |
|
Axial coverage or Field Of View |
673 |
|
Minimal required rotation angle |
674 |
|
Slide Number 38 |
675 |
|
Slide Number 39 |
676 |
|
Slide Number 40 |
677 |
|
Center: 180 degree rotation is sufficient |
678 |
|
Periphery: is a 180 degree rotation sufficient? |
679 |
|
Periphery: is a 180 degree rotation sufficient? |
680 |
|
Periphery: is a 180 degree rotation sufficient? |
681 |
|
Periphery: a 180 degree rotation is not sufficient! |
682 |
|
Periphery: a 180 degree plus fan angle rotation is sufficient! |
683 |
|
Dual source CT improves temporal resolution with a factor two |
684 |
|
Rotation speed, diagnostic CT scanners rotate fast |
685 |
|
Diagnostic CT scanners have “better” detectors |
686 |
|
XVI at LUMC - 2012 |
687 |
|
XVI at LUMC - 2012 |
688 |
|
Advanced Computed Tomography |
689 |
|
Slide Number 53 |
690 |
|
Slide Number 54 |
691 |
|
Slide Number 55 |
692 |
|
Single axial, 8 mm |
693 |
|
Sinogram space |
694 |
|
Sinogram space |
695 |
|
Slide Number 59 |
696 |
|
Slide Number 60 |
697 |
|
Slide Number 61 |
698 |
|
Slide Number 62 |
699 |
|
A better solution for CT reconstruction is to use a filtered backprojection |
700 |
|
Image reconstruction by adding (filtered) backprojectionsof many views/angles |
701 |
|
Image reconstruction by adding (filtered) backprojectionsof many views/angles |
702 |
|
Image reconstruction by adding (filtered) backprojectionsof many views/angles |
703 |
|
Slide Number 67 |
704 |
|
Backprojection, not filtered |
705 |
|
Slide Number 69 |
706 |
|
Backprojection, not filtered |
707 |
|
The mathematical operations of a filtered backprojection consist of four steps. |
708 |
|
Slide Number 72 |
709 |
|
The mathematical operations of a filtered backprojection consist of four steps. |
710 |
|
Slide Number 74 |
711 |
|
The mathematical operations of a filtered backprojection consist of four steps. |
712 |
|
Slide Number 76 |
713 |
|
The mathematical operations of a filtered backprojection consist of four steps. |
714 |
|
Filtered backprojection |
715 |
|
Backprojection vs filtered backprojection |
716 |
|
Filtered backprojection |
717 |
|
Slide Number 81 |
718 |
|
Filtered backprojection |
719 |
|
Filtered backprojection |
720 |
|
Filtered backprojection |
721 |
|
Filtered backprojection |
722 |
|
Band limited window functions in the frequency domain and corresponding kernels in the spatial domain |
723 |
|
Reconstruction filter |
724 |
|
Reconstruction filter |
725 |
|
Filtered backprojection, is there more? |
726 |
|
Slide Number 90 |
727 |
|
Statistical reconstruction methods in X-ray CT |
728 |
|
Introduction |
729 |
|
Evolution of reconstruction in CT |
730 |
|
Filtered backprojection with iterative noise reduction |
731 |
|
Adaptive Iterative Dose Reduction (AIDR) |
732 |
|
Example: Adaptive Iterative Dose Reduction (AIDR) |
733 |
|
Adaptive Iterative Dose Reduction Result 1 |
734 |
|
Adaptive Iterative Dose Reduction Result 2 |
735 |
|
Adaptive Iterative Dose Reduction Result 3 |
736 |
|
Statistical denoising |
737 |
|
Iterative reconstruction methods in X-ray CT |
738 |
|
Iterative reconstruction methods in X-ray CT |
739 |
|
Iterative reconstruction methods in X-ray CT |
740 |
|
Results (Noise) |
741 |
|
Slide Number 105 |
742 |
|
Advanced Computed Tomography |
743 |
|
With a fast CT scanner and advanced reconstruction … |
744 |
|
… you get crystal sharp images in cardiac CT. |
745 |
|
Freezing of motion of organs in CT |
746 |
|
Freezing of motion in CT |
747 |
|
Freezing of motion in CT |
748 |
|
Freezing of motion of organs in CT |
749 |
|
The ECG is recorded, cardiac CT scan |
750 |
|
Freezing of motion of organs in CT |
751 |
|
Freezing of motion of organs in CT |
752 |
|
Synchronization |
753 |
|
Slide Number 117 |
754 |
|
Retrospective ECG gate(d) reconstruction |
755 |
|
Synchronization |
756 |
|
Triggered, during the acquisition |
757 |
|
Prospective ECG triggered acquisition |
758 |
|
Prospective respiratory triggered acquisition |
759 |
|
4D visualization of the chest |
760 |
|
Dynamic axial images of the chest at two levels |
761 |
|
Advanced Computed Tomography |
762 |
|
State of the art: excellent 4D image quality |
763 |
|
Four-dimensional DSA MDCT of Bone Sarcoma Vascularization (Case 1) |
764 |
|
Four-dimensional DSA MDCT of Bone Sarcoma Vascularization (Case 1) |
765 |
|
Results (Case 1) |
766 |
|
Results (Case 1) |
767 |
|
Results (Case 1) |
768 |
|
Computed Tomography |
769 |
|
CT brain perfusion |
770 |
|
CT perfusion |
771 |
|
CT perfusion |
772 |
|
Slide Number 136 |
773 |
|
Slide Number 137 |
774 |
|
CT perfusion |
775 |
|
Slide Number 139 |
776 |
|
Example: 4D Liver Perfusion Protocol |
777 |
|
Why Perfusion CT |
778 |
|
Clinical examples |
779 |
|
Slide Number 143 |
780 |
|
Slide Number 144 |
781 |
|
Advanced Computed Tomography |
782 |
|
Dual Energy or Spectral CT |
783 |
|
Dual Energy or Spectral CT |
784 |
|
Dual Energy or Spectral CT scanners |
785 |
|
G.N. Hounsfield, BJR, 1973, Description of system |
786 |
|
Dual Energy or Spectral CT |
787 |
|
Dual energy is based on the photoelectric effect! |
788 |
|
Dual Energy or Spectral CT |
789 |
|
Dual Energy or Spectral CT principles |
790 |
|
Rapid switching of the tube voltage (2000 Hz) |
791 |
|
Rapid switching of the tube voltage (2000 Hz) |
792 |
|
Rapid switching of the tube voltage (5000 Hz) |
793 |
|
Dual layer detector |
794 |
|
Dual layer detector |
795 |
|
Dual layer detector |
796 |
|
Dual source |
797 |
|
Dual source |
798 |
|
Dual source |
799 |
|
Dual Spin |
800 |
|
Dual energy, Spin-Spin |
801 |
|
Dual Spin |
802 |
|
Extra: dual energy, helical at low pitch (< 0.5) |
803 |
|
Dual Energy CT, optimisation of kV, mA and filtration |
804 |
|
|
805 |
|
Dual Energy or Spectral CT |
806 |
|
Slide Number 170 |
807 |
|
Dual energy in digital chest radiography |
808 |
|
Dual energy CT in the raw data domain (transmission) |
809 |
|
Dual Energy or Spectral CT |
810 |
|
Spectral CT applications |
811 |
|
Treatment planning |
812 |
|
Virtual unenhanced imaging |
813 |
|
Slide Number 185 |
814 |
|
Slide Number 186 |
815 |
|
Further reading … |
816 |
|
Further reading … |
817 |
|
CT delivers excellent 3D image quality (appeared on Dutch TV) |
818 |
|
Slide Number 190 |
819 |
|
L17 PET Tracers and Applications - Thorwarth |
820 |
|
Positron Emission TomographyTracers and applications |
820 |
|
Possibilities for Functional Imaging in Radiotherapy |
821 |
|
Radionuclides for diagnostic applications |
822 |
|
Production of radionuclides in a nuclear reactor |
823 |
|
… in the cyclotron |
824 |
|
… in the radionuclide generator |
825 |
|
[18F]FDG for target delineation and LN staging |
826 |
|
FDG PET/CT improves consistency of GTV delineation in NSCLC |
827 |
|
FDG PET/CT improves consistency of GTV delineation in NSCLC |
828 |
|
Slide Number 10 |
829 |
|
Response Prediction by Quantitative Assessment of Glucose Use |
830 |
|
Therapy monitoring with FDG-PET in HNC |
831 |
|
Treatment Monitoring with FDG PET |
832 |
|
[11C]MET / [18F]FET / [18F]FLT for Brain Lesions |
833 |
|
Dynamic Imaging: [18F]-FET PETStaging by Tracer Kinetics |
834 |
|
Proliferation Imaging with [18F]FLT PET |
835 |
|
Imaging Cellular Proliferation during RT |
836 |
|
Dose Painting Hypothesis I:Direct Dose at Tumour Cell Foci |
837 |
|
FLT PET does not discriminate between reactive and metastatic lymph nodes |
838 |
|
From Functional Imaging to Dose Painting |
839 |
|
Hypoxia Imaging with [18F]FMISO |
840 |
|
Hypoxia PET Imaging with FMISO |
841 |
|
Hypoxia PET Imaging with FAZA |
842 |
|
Hypoxia Imaging with DCE-MRI |
843 |
|
Dose Painting Hypotheses II:direct Dose at Insensitive Cells |
844 |
|
Dose Painting based on dynamic FMISO PET: Phase II trial in Tübingen |
845 |
|
Slide Number 27 |
846 |
|
Slide Number 28 |
847 |
|
Baseline dyn. FMISO PET is prognostic for loco-regional control |
848 |
|
FDG PET based dose painting study in lung cancer |
849 |
|
New multimodality imaging perspective: Combined PET/MRI |
850 |
|
PET/CT vs. PET/MR: PET performance |
851 |
|
PET/CT vs. PET/MR: practical aspects |
852 |
|
Limitations of combined PET/MR |
853 |
|
Future prospects: Hypoxia imaging using PET/MRI |
854 |
|
Summary / Conclusion |
855 |
|
L18 Guidelines for PET Imaging in RT - Thorwarth |
856 |
|
Recommendations for the integration of FDG PET/CT into radiotherapy treatment planning |
856 |
|
Slide Number 2 |
857 |
|
Potential of PET in radiotherapy (RT) treatment planning (TP) |
858 |
|
PET in RT TP |
859 |
|
Practical recommendations for using PET/CT in RT |
860 |
|
1. PET/CT hardware |
861 |
|
1. PET/CT Hardware |
862 |
|
2. Quality control, calibration |
863 |
|
2a. QC of the CT system |
864 |
|
2b. QC of the PET system |
865 |
|
2c. PET/CT alignment |
866 |
|
2d. RT specific QC aspects |
867 |
|
2. Quality control, calibration |
868 |
|
3. Data acquisition and reconstruction |
869 |
|
3a. Image acquisition techniques (thorax scans) |
870 |
|
3b. PET image reconstruction |
871 |
|
3b. PET image reconstruction |
872 |
|
3b. PET image reconstruction |
873 |
|
3. PET data acquisition and image reconstruction |
874 |
|
4. Data transfer / treatment planning system (TPS) |
875 |
|
4. Data transfer / TPS |
876 |
|
5. Image fusion / registration |
877 |
|
5. Image fusion / registration |
878 |
|
5. Image fusion / registration |
879 |
|
6. Image contouring |
880 |
|
6. Image contouring |
881 |
|
6. Image contouring |
882 |
|
7. Patient set-up / staff training |
883 |
|
7b. Radiation exposure |
884 |
|
7. Patient set-up and staff training |
885 |
|
Conclusion |
886 |
|
Acknowledgments |
887 |
|
L19 Dynamic PET and CT Imaging - Malinen |
888 |
|
Dynamic CT and PET |
888 |
|
Background |
889 |
|
Dynamic CT |
890 |
|
Iodinated contrast agents |
891 |
|
Vessel leakiness in tumors |
892 |
|
Tissue distribution |
893 |
|
Temporal uptake characteristics |
894 |
|
Compartmental modeling |
895 |
|
1-compartment model |
896 |
|
1-compartment model |
897 |
|
Interpreting Ktrans |
898 |
|
Case study: DCECT of lymphoma patients |
899 |
|
Dynamic image series, overlay |
900 |
|
Identifying the artery |
901 |
|
Voxel-by-voxel analysis |
902 |
|
Parametric maps |
903 |
|
Impact of AIF |
904 |
|
Clinical significance – cervical cancer |
905 |
|
DCE + gene expression …. (new slide) |
906 |
|
Reproducibility…. (new slide) |
907 |
|
Dynamic FDG-PET |
908 |
|
DICOM header |
909 |
|
Tissue distribution |
910 |
|
Dynamic FDG-PET |
911 |
|
Temporal characteristics |
912 |
|
Perfusion imaging |
913 |
|
Dogs; DPET and DCECT 1 min p.i. |
914 |
|
2-compartment modeling |
915 |
|
2-compartment modeling |
916 |
|
Model analysis |
917 |
|
Application |
918 |
|
Thank you for your attention! |
919 |
|
L20 MR Safety - Nyhololm |
920 |
|
Health risks associated with MR |
920 |
|
Mechanical risks |
921 |
|
Accidents |
922 |
|
Heating |
923 |
|
Displacement and Heating |
924 |
|
Medical inplants |
925 |
|
Do you see the artifact? |
926 |
|
How do you think that WHO classify E-M exposure? |
927 |
|
Long and short term effects |
928 |
|
WHO grades |
929 |
|
Slide Number 11 |
930 |
|
Health risk(static fields) |
931 |
|
Local survey of problems |
932 |
|
Slide Number 14 |
933 |
|
Health risksLow frequency magnetic fields |
934 |
|
Peripheral nerve excitation |
935 |
|
Slide Number 17 |
936 |
|
Radio frequent fields |
937 |
|
Whole body heating |
938 |
|
Burn injuries |
939 |
|
Lack of knowleadge |
940 |
|
Thank you! |
941 |
|
L21 MRI Physics; Fast Scanning, Colume Sequences - Liney |
942 |
|
MRI Physics: Fast Scanning, Volume Sequences |
942 |
|
Introduction |
943 |
|
How Do We Go Faster? |
944 |
|
Some ‘Fast’ Terminology? |
945 |
|
Ultra-fast Imaging |
946 |
|
Slide Number 6 |
947 |
|
Spin-echoes… |
948 |
|
Segmented k-space |
949 |
|
Fast Spin Echo (Turbo Spin Echo) |
950 |
|
FSE (TSE) |
951 |
|
Slide Number 11 |
952 |
|
Partial k-Space |
953 |
|
ssFSE and HASTE |
954 |
|
Driven Equilibrium |
955 |
|
Echo Planar Imaging (EPI) |
956 |
|
EPI |
957 |
|
EPI |
958 |
|
Slide Number 18 |
959 |
|
GRASE |
960 |
|
GRASE (TGSE) |
961 |
|
Slide Number 21 |
962 |
|
Gradient-echoes… |
963 |
|
Slide Number 23 |
964 |
|
Slide Number 24 |
965 |
|
Slide Number 25 |
966 |
|
Steady-State Sequences |
967 |
|
Slide Number 27 |
968 |
|
Slide Number 28 |
969 |
|
Slide Number 29 |
970 |
|
Gradient-Speed Limit |
971 |
|
Parallel Imaging = ‘Coil Encoding’ |
972 |
|
Slide Number 32 |
973 |
|
Multi-Coil Arrays |
974 |
|
Parallel Imaging |
975 |
|
Parallel Imaging |
976 |
|
SENSE |
977 |
|
Slide Number 37 |
978 |
|
Slide Number 38 |
979 |
|
Slide Number 39 |
980 |
|
SENSE |
981 |
|
mSENSE |
982 |
|
SMASH |
983 |
|
Slide Number 43 |
984 |
|
Slide Number 44 |
985 |
|
Key-hole Imaging |
986 |
|
Key-hole Imaging |
987 |
|
Slide Number 47 |
988 |
|
Recent Developments |
989 |
|
Pulse sequences in this talk |
990 |
|
Slide Number 50 |
991 |
|
L22 In-Room Imaging CT and MRI - Nyholm |
992 |
|
In-room imaging and MR planning |
992 |
|
Overview of the lecture |
993 |
|
Imaging in radiotherapy |
994 |
|
Workflow |
995 |
|
Why is MR needed in radiotherapy |
996 |
|
CT/MR workflow |
997 |
|
ProblemRegistration |
998 |
|
Switch from CT based to MR based workflow |
999 |
|
How? |
1000 |
|
MR signal |
1001 |
|
Manual segmentation and bulk densities |
1002 |
|
Manual segmentation and bulk densities |
1003 |
|
Registration based |
1004 |
|
Registration based |
1005 |
|
Automatic segmentation and bulk densities |
1006 |
|
Automatic segmentation and bulk densities |
1007 |
|
Direct voxel-vise conversion |
1008 |
|
MR signal |
1009 |
|
Slide Number 19 |
1010 |
|
Slide Number 20 |
1011 |
|
Slide Number 21 |
1012 |
|
How to esstimate the HU? |
1013 |
|
Voxel by voxel esstimation |
1014 |
|
Slide Number 24 |
1015 |
|
Slide Number 25 |
1016 |
|
Slide Number 26 |
1017 |
|
Slide Number 27 |
1018 |
|
Workflow |
1019 |
|
Imaging in the treatment room |
1020 |
|
Cone beam CT |
1021 |
|
Cone beam CT |
1022 |
|
Comparison CBCT and CT |
1023 |
|
Scatter artifacts in CBCT |
1024 |
|
Slide Number 34 |
1025 |
|
Dealing with scatter |
1026 |
|
Slide Number 36 |
1027 |
|
Correction |
1028 |
|
Dealing with scatter |
1029 |
|
Scatter reduction with grid |
1030 |
|
Other artifacts |
1031 |
|
QA of CBCT |
1032 |
|
Clinical application |
1033 |
|
Accelerator in magnetic field |
1034 |
|
Accelerator in magnetic field |
1035 |
|
Accelerator in magnetic field |
1036 |
|
Principal of active shielding |
1037 |
|
Principal of active shielding |
1038 |
|
RF from linac disturbing the MR |
1039 |
|
Dosimetry with magnetic field |
1040 |
|
Dosimetry with magnetic field |
1041 |
|
Dosimetry with magnetic field |
1042 |
|
Potential with MR guided radiotherapy |
1043 |
|
Potential with MR guided radiotherapy |
1044 |
|
When to do what |
1045 |
|
Thank you! |
1046 |
|
L23 Applications; CT and PET for RTof Lung - van der Heide |
1047 |
|
Advanced Imaging for PhysicistsApplication of CT and PET for radiotherapy of lung cancer |
1047 |
|
Imaging for radiotherapy of lung cancer |
1048 |
|
CT imaging for radiotherapy of lung cancer |
1049 |
|
CT imaging for radiotherapy of lung cancer |
1050 |
|
CT imaging for radiotherapy of lung cancer |
1051 |
|
PET and SPECT for radiotherapy of lung cancer |
1052 |
|
MRI is not commonly used for lung cancer |
1053 |
|
FDG-PET improves accuracy of staging in non-small cell lung cancer |
1054 |
|
FDG-PET improves accuracy of staging innon-small cell lung cancer |
1055 |
|
Sensitivity and specificity of mediastinal lymph node staging |
1056 |
|
PET has a high (>90%) negative predictive value in mediastinal lymph node staging |
1057 |
|
PET staging in small-cell lung cancer |
1058 |
|
FDG-PET has impact on treatment strategy |
1059 |
|
Selective mediastinal irradiation |
1060 |
|
Monitoring volume changes during treatment |
1061 |
|
Imaging of recurrences, follow-up |
1062 |
|
Imaging of recurrences, follow-up |
1063 |
|
Limitations of PET for staging of lung cancer |
1064 |
|
PET(-CT) for staging of lung cancer |
1065 |
|
Improved consistency of GTV delineation |
1066 |
|
Improved consistency of GTV delineation |
1067 |
|
Improved consistency of GTV delineation |
1068 |
|
Different methods for tumor delineation on PET produce very different results |
1069 |
|
Auto-contouring algorithms improve consistency |
1070 |
|
Impact of FDG-PET on definition of PTV |
1071 |
|
Validation of PET contouring algorithms with pathology is essential |
1072 |
|
3D validation of contouring with pathology |
1073 |
|
PET and CT registration: planning CT and CT of the PET-CT |
1074 |
|
PET and CT registration:planning CT and CT of the PET-CT |
1075 |
|
how well are the PET and CT in a PET-CT registered? |
1076 |
|
Tumor motion during regular breathing |
1077 |
|
4D PET-CT |
1078 |
|
4D PET-CT |
1079 |
|
Attenuation correction for 4D PET |
1080 |
|
Attenuation correction for 4D PET |
1081 |
|
Attenuation correction for 4D PET |
1082 |
|
Making a PET-CT for radiotherapy |
1083 |
|
Target definition on a 4D CT scan |
1084 |
|
Target definition on a 4D CT scan |
1085 |
|
Internal Target Volume (ITV) |
1086 |
|
Internal Target Volume (ITV) |
1087 |
|
Internal Target Volume (ITV) |
1088 |
|
Maximum exhale phase |
1089 |
|
Maximum exhale phase |
1090 |
|
Maximum exhale phase |
1091 |
|
Mid-Ventilation scan |
1092 |
|
Mid-Ventilation scan |
1093 |
|
Mid-Ventilation scan |
1094 |
|
Different PTV STRATEGIES |
1095 |
|
Different PTV STRATEGIES |
1096 |
|
Impact of motion on dose |
1097 |
|
Impact of tumor motion on dose distribution |
1098 |
|
Impact of tumor motion on accumulated dose is very small |
1099 |
|
From 4D CT to 3D Planning CT |
1100 |
|
CT based Mid-Position PET |
1101 |
|
From 4D PET to 3D Planning PET |
1102 |
|
From 4D PET to 3D Planning PET |
1103 |
|
Use of in-room imaging for position verification |
1104 |
|
Baseline shifts |
1105 |
|
Intra-fraction displacement of bone and tumor |
1106 |
|
SBRT Lung protocol at NKI-AVL |
1107 |
|
SBRT lung: first scan (4 min for 4D) |
1108 |
|
SBRT lung: matched on bone |
1109 |
|
SBRT lung: matched on tumor |
1110 |
|
Geometrical uncertainties |
1111 |
|
Geometrical uncertainties |
1112 |
|
Margins versus amplitude |
1113 |
|
Summary |
1114 |
|
Summary |
1115 |
|
Acknowledgment |
1116 |