为了使用从CBCT投影图像中提取出的膈波形开发目标定位的预测模型（PM），采用了19例肺癌患者进行了70秒的正交旋转kV X射线成像。将放置在其腹部表面上的IR标记和位于肿瘤最近位置的植入金标记分别视为外部替代物和目标。首先60秒内使用替代运动和目标位置训练了四种不同类型的基于回归的PM，如下：情景A：基于临床情况，使用从投影图像中提取的3D目标位置（PMCL）。情景B：通过对情景A中的目标位置进行平均，获得了展现八个目标位置的短弧4D-CBCT波形。该波形通过适应外部替代物的呼吸相在60秒内重复（W4D-CBCT）。W4D-CBCT被用作目标位置（PM4D-CBCT）。情景C：从正交投影图中提取了描绘膈运动的阿姆斯特丹披风（AS）信号，该信号在上下方向上。根据AS信号对W4D-CBCT的振幅和相位进行了校正。经过AS校正的W4D-CBCT被用作目标位置（PMAS-4D-CBCT）。情景D：从单个投影图中提取了AS信号。其它过程与情景C相同。计算剩余10秒内的预测误差。对于PM4D-CBCT，3D预测误差在3mm内为77.3%，比PMCL降低了12.8%。使用膈波形，误差在3mm内的百分比在情景C和D中分别提高了约7%，达到84.0%-85.3%的PMAS-4D-CBCT。预测误差的统计学上具有显著差异，PM4D-CBCT和PMAS-4D-CBCT之间。PMAS-4D-CBCT优于PM4D-CBCT，证明了基于AS信号的校正的有效性。PMAS-4D-CBCT可以在没有金标记的4D-CBCT图像中预测目标位置。© 2023 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, LLC on behalf of The American Association of Physicists in Medicine.

To develop a prediction model (PM) for target positioning using diaphragm waveforms extracted from CBCT projection images.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 (PMCL ). 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 (W4D-CBCT ) by adapting to the respiratory phase of the external surrogate. W4D-CBCT was used as the target positions (PM4D-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 W4D-CBCT were corrected based on the AS signal. The AS-corrected W4D-CBCT was used as the target positions (PMAS-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.The 3D prediction error within 3 mm was 77.3% for PM4D-CBCT , which was 12.8% lower than that for PMCL . Using the diaphragm waveforms, the percentage of errors within 3 mm improved by approximately 7% to 84.0%-85.3% for PMAS-4D-CBCT in Scenarios C and D, respectively. Statistically significant differences were observed between the prediction errors of PM4D-CBCT and PMAS-4D-CBCT .PMAS-4D-CBCT outperformed PM4D-CBCT , proving the efficacy of the AS signal-based correction. PMAS-4D-CBCT would make it possible to predict target positions from 4D-CBCT images without gold markers.© 2023 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, LLC on behalf of The American Association of Physicists in Medicine.