Abstract
Purpose: X‐ray projections acquired with linac‐based scanners for 4d CBCT reconstruction are traditionally binned into breathing phases ‘after‐the‐fact’, i.e. after the image acquisition. This approach leads to an uneven spreading of projections over breathing phases, which compromises the image quality. We have therefore developed a novel approach based on actively triggered projections employing the forward‐predicted position of the tumor at the time of image acquisition. Methods: The prediction is based on a high‐frequency external motion sensor and uses linear regression to compensate for the effective latency of the external motion sensor and the x‐ray imaging chain (160 ms). An internal‐to‐external motion model is established from the first 40 images, by correlating the external chest‐wall displacement (AP) with the internal motion (SI) derived from the images (using an ‘Amsterdam shroud’). We used a lung phantom moving on a sinusoidal trajectory (15 mm SI amplitude) with a 3.5/5.0 s period. The AP motion (5 mm) was phase‐shifted by 13°. The gantry rotation times were adapted depending on the breathing period during prediction training (first 30 s). Results: The first 40–50 projections were acquired at 6.25 Hz to cover 1–2 breathing cycles. During post‐processing, these images were binned and used alongside the actively triggered frames. For the 4d CBCT mode, we were able to evenly spread the projections over all breathing phases. Motion‐induced artifacts were effectively mitigated and the tumor‐to‐lung contrast became more evenly distributed over the respiratory phases. We also demonstrated a quasi‐4d mode consisting of actively triggered peak‐exhale/peak‐inhale images only. By increasing the image frequency for the quasi‐4d mode, it was possible to reduce the gantry rotation to 2.5–3.5 min without compromising the number of projections. Conclusion: Our new approach to 4d CBCT imaging allows for active phase selection as opposed to the traditional retrospective phase binning.
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