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Basics of range <t>verification,</t> exemplarily shown for the voxel coordinates (x, y) = (70,59) in patient P3 (cf table 1). Left: β+-activity profiles obtained by MC simulation and in-beam PET measurement, normalized to the maximum, as well as the corresponding dose profile are shown. The blue lines denote the location of the activity maximum, the 50 % dose fall-off (vertically, left to right) and the 20 % activity limit (horizontally). Right: The profile difference Ddiff is visualized as function of the profile shift for different analysis starting depths zmin.
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Basics of range verification, exemplarily shown for the voxel coordinates (x, y) = (70,59) in patient P3 (cf table 1). Left: β+-activity profiles obtained by MC simulation and in-beam PET measurement, normalized to the maximum, as well as the corresponding dose profile are shown. The blue lines denote the location of the activity maximum, the 50 % dose fall-off (vertically, left to right) and the 20 % activity limit (horizontally). Right: The profile difference Ddiff is visualized as function of the profile shift for different analysis starting depths zmin.

Journal: Physics in medicine and biology

Article Title: Automation and uncertainty analysis of a method for in-vivo range verification in particle therapy

doi: 10.1088/0031-9155/59/19/5903

Figure Lengend Snippet: Basics of range verification, exemplarily shown for the voxel coordinates (x, y) = (70,59) in patient P3 (cf table 1). Left: β+-activity profiles obtained by MC simulation and in-beam PET measurement, normalized to the maximum, as well as the corresponding dose profile are shown. The blue lines denote the location of the activity maximum, the 50 % dose fall-off (vertically, left to right) and the 20 % activity limit (horizontally). Right: The profile difference Ddiff is visualized as function of the profile shift for different analysis starting depths zmin.

Article Snippet: In the following section, the basic principles of the range verification methods by ( Knopf et al. 2008 ) and ( Min et al. 2013 ) are reviewed, which are used in the development of the MLS approach and applied to the investigated data, respectively.

Techniques: Activity Assay

Range verification of the proton-irradiation induced activity in P7. (a) Exemplary sagittal planes of the simulation (top) and the offline PET measurement (bottom) are displayed. (b) The corresponding normalized activity depth profiles are shown together with the dose profile. The activity fall-off thresholds of 25 % and 50 % are marked by blue lines. (c) The MLS results (top) show only small deviations in most parts of the distribution compared to the MP (bottom) calculations.

Journal: Physics in medicine and biology

Article Title: Automation and uncertainty analysis of a method for in-vivo range verification in particle therapy

doi: 10.1088/0031-9155/59/19/5903

Figure Lengend Snippet: Range verification of the proton-irradiation induced activity in P7. (a) Exemplary sagittal planes of the simulation (top) and the offline PET measurement (bottom) are displayed. (b) The corresponding normalized activity depth profiles are shown together with the dose profile. The activity fall-off thresholds of 25 % and 50 % are marked by blue lines. (c) The MLS results (top) show only small deviations in most parts of the distribution compared to the MP (bottom) calculations.

Article Snippet: In the following section, the basic principles of the range verification methods by ( Knopf et al. 2008 ) and ( Min et al. 2013 ) are reviewed, which are used in the development of the MLS approach and applied to the investigated data, respectively.

Techniques: Irradiation, Activity Assay

Range verification with several offline measured activity distributions after different treatment fractions of P6. The most-likely shift for the analysis between M1 and M2 (a), M1 and M3 (b) as well as between M1 and M4 (c) is shown.

Journal: Physics in medicine and biology

Article Title: Automation and uncertainty analysis of a method for in-vivo range verification in particle therapy

doi: 10.1088/0031-9155/59/19/5903

Figure Lengend Snippet: Range verification with several offline measured activity distributions after different treatment fractions of P6. The most-likely shift for the analysis between M1 and M2 (a), M1 and M3 (b) as well as between M1 and M4 (c) is shown.

Article Snippet: In the following section, the basic principles of the range verification methods by ( Knopf et al. 2008 ) and ( Min et al. 2013 ) are reviewed, which are used in the development of the MLS approach and applied to the investigated data, respectively.

Techniques: Activity Assay