Towards online patient imaging during helical radiotherapy

Area of Science:

• Medical Physics
• Radiotherapy Technology
• Image Analysis

Background:

• Exit-detector data in helical radiation therapy are typically used for delivery verification and dose reconstruction.
• The dual use of the radiation source for both imaging and treatment presents an opportunity to explore alternative data applications.

Purpose of the Study:

• To investigate the feasibility of using exit-detector raw data for imaging purposes in helical radiation therapy.
• To explore clinical applications such as retrospective daily setup verification and inter-fractional setup error detection.

Main Methods:

• Exit-detector raw data were acquired from the treatment machine's onboard computer and analyzed using Python.
• Object contours were defined by applying a logarithmic function to the ratio of sinograms (with and without the object).
• Setup variations were detected by applying the same function to exit-detector sinograms from different treatment deliveries.

Main Results:

• Object contours were well-defined by secondary radiation and validated with the imaging beam.
• No internal structures were discernible due to primary radiation interference.
• Setup variation detection sensitivity reached 2 mm, limited by exit-detector resolution.

Conclusions:

• Exit-detector data from helical radiation therapy contain valuable photon exit fluence maps.
• These maps can be utilized for contour definition and patient alignment verification without the need for image reconstruction.
• This approach offers a potential method for retrospective setup verification and error detection in radiotherapy.