Development of a prediction model for target positioning by using diaphragm waveforms extracted from CBCT projection images

PURPOSE: To develop a prediction model (PM) for target positioning using diaphragm waveforms extracted from CBCT projection images. METHODS: Nineteen patients with lung cancer underwent orthogonal rotational kV x‐ray imaging lasting 70 s. IR markers placed on their abdominal surfaces and an implanted gold marker located nearest to the tumor were considered as external surrogates and the target, respectively. Four different types of regression‐based PM were trained using surrogate motions and target positions for the first 60 s, as follows: Scenario A: Based on the clinical scenario, 3D target positions extracted from projection images were used as they were (PM(CL)). Scenario B: The short‐arc 4D‐CBCT waveform exhibiting eight target positions was obtained by averaging the target positions in Scenario A. The waveform was repeated for 60 s (W (4D‐CBCT)) by adapting to the respiratory phase of the external surrogate. W (4D‐CBCT) was used as the target positions (PM(4D‐CBCT)). Scenario C: The Amsterdam Shroud (AS) signal, which depicted the diaphragm motion in the superior–inferior direction was extracted from the orthogonal projection images. The amplitude and phase of W (4D‐CBCT) were corrected based on the AS signal. The AS‐corrected W (4D‐CBCT) was used as the target positions (PM(AS‐4D‐CBCT)). Scenario D: The AS signal was extracted from single projection images. Other processes were the same as in Scenario C. The prediction errors were calculated for the remaining 10 s. RESULTS: The 3D prediction error within 3 mm was 77.3% for PM(4D‐CBCT), which was 12.8% lower than that for PM(CL). Using the diaphragm waveforms, the percentage of errors within 3 mm improved by approximately 7% to 84.0%‐85.3% for PM(AS‐4D‐CBCT) in Scenarios C and D, respectively. Statistically significant differences were observed between the prediction errors of PM(4D‐CBCT) and PM(AS‐4D‐CBCT). CONCLUSION: PM(AS‐4D‐CBCT) outperformed PM(4D‐CBCT), proving the efficacy of the AS signal‐based correction. PM(AS‐4D‐CBCT) would make it possible to predict target positions from 4D‐CBCT images without gold markers.