Purpose:
In‐vivo dose and beam range verification in proton therapy could play significant roles in proton treatment validation and improvements. Invivo beam range verification, in particular, could ...enable new treatment techniques one of which, for example, could be the use of anterior fields for prostate treatment instead of opposed lateral fields as in current practice. We have developed and commissioned an integrated system with hardware, software and workflow protocols, to provide a complete solution, simultaneously for both in‐vivo dosimetry and range verification for proton therapy.
Methods:
The system uses a matrix of diodes, up to 12 in total, but separable into three groups for flexibility in application. A special amplifier was developed to capture extremely small signals from very low proton beam current. The software was developed within iMagX, a general platform for image processing in radiation therapy applications. The range determination exploits the inherent relationship between the internal range modulation clock of the proton therapy system and the radiological depth at the point of measurement. The commissioning of the system, for in‐vivo dosimetry and for range verification was separately conducted using anthropomorphic phantom. EBT films and TLDs were used for dose comparisons and range scan of the beam distal fall‐off was used as ground truth for range verification.
Results:
For in‐vivo dose measurement, the results were in agreement with TLD and EBT films and were within 3% from treatment planning calculations. For range verification, a precision of 0.5mm is achieved in homogeneous phantoms, and a precision of 2mm for anthropomorphic pelvic phantom, except at points with significant range mixing.
Conclusion:
We completed the commissioning of our system for in‐vivo dosimetry and range verification in proton therapy. The results suggest that the system is ready for clinical trials on patient.
During the past years, many different registration methods have emerged. These usually lead to different results and one faces the problem of choosing the most appropriate. To mitigate this issue, ...several algorithms have been developed to include prior knowledge in order to force the registration to have a physical behavior. The use of most of these methods in daily practice is cumbersome because of the need to create data-specific meshes. This paper introduces a local convolutive filter in order to iteratively make the result of any registration method converge towards a linear elastic solution. This method was tested and validated on virtual data and on a real silicone rubber cube.
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