Institute for Medical Engineering, Otto-von-Guericke University, Magdeburg, Germany; Forschungscampus STIMULATE, Otto-von-Guericke University, Magdeburg, Germany.
Institute for Medical Engineering, Otto-von-Guericke University, Magdeburg, Germany; Forschungscampus STIMULATE, Otto-von-Guericke University, Magdeburg, Germany.
Comput Biol Med. 2024 Mar;171:108199. doi: 10.1016/j.compbiomed.2024.108199. Epub 2024 Feb 20.
Traditional navigational bronchoscopy procedures rely on preprocedural computed tomography (CT) and intraoperative chest radiography and cone-beam CT (CBCT) to biopsy peripheral lung lesions. This navigational approach is challenging due to the projective nature of radiography, and the high radiation dose, long imaging time, and large footprints of CBCT. Digital tomosynthesis (DTS) is considered an attractive alternative combining the advantages of radiography and CBCT. Only the depth resolution cannot match a full CBCT image due to the limited angle acquisition. To address this issue, preoperative CT is a good auxiliary in guiding bronchoscopy interventions. Nevertheless, CT-to-body divergence caused by anatomic changes and respiratory motion, hinders the effective use of CT imaging. To mitigate CT-to-body divergence, we propose a novel deformable 3D/3D CT-to-DTS registration algorithm employing a multistage, multiresolution approach and using affine and elastic B-spline transformation models with bone and lung mask images. A multiresolution strategy with a Gaussian image pyramid and a multigrid strategy within the B-spline model are applied. The normalized correlation coefficient is included in the cost function for the affine model and a multimetric weighted cost function is used for the B-spline model, with weights determined heuristically. Tested on simulated and real patient bronchoscopy data, the algorithm yields promising results. Assessed qualitatively by visual inspection and quantitatively by computing the Dice coefficient (DC) and the average symmetric surface distance (ASSD), the algorithm achieves mean DC of 0.82±0.05 and 0.74±0.05, and mean ASSD of 0.65±0.29mm and 0.93±0.43mm for simulated and real data, respectively. This algorithm lays the groundwork for CT-aided intraoperative DTS imaging in image-guided bronchoscopy interventions with future studies focusing on automated metric weight setting.
传统的导航支气管镜检查程序依赖于术前计算机断层扫描 (CT) 和术中胸部 X 光和锥形束 CT (CBCT) 来对周围肺病变进行活检。由于 X 光的投影性质,以及 CBCT 的高辐射剂量、长成像时间和大脚印,这种导航方法具有挑战性。数字断层合成 (DTS) 被认为是一种有吸引力的替代方法,结合了 X 光和 CBCT 的优点。由于采集角度有限,仅深度分辨率无法与完整的 CBCT 图像匹配。为了解决这个问题,术前 CT 是指导支气管镜介入的良好辅助手段。然而,由于解剖变化和呼吸运动导致的 CT 与身体的发散,阻碍了 CT 成像的有效利用。为了减轻 CT 与身体的发散,我们提出了一种新颖的可变形 3D/3D CT 到 DTS 配准算法,该算法采用多阶段、多分辨率方法,并使用带有骨骼和肺掩码图像的仿射和弹性 B 样条变换模型。应用了具有高斯图像金字塔的多分辨率策略和 B 样条模型内的多网格策略。仿射模型的代价函数中包含归一化相关系数,B 样条模型使用多度量加权代价函数,权重通过启发式确定。在模拟和真实患者支气管镜数据上进行测试,该算法取得了有希望的结果。通过视觉检查进行定性评估,并通过计算骰子系数 (DC) 和平均对称表面距离 (ASSD) 进行定量评估,该算法在模拟和真实数据上分别实现了平均 DC 为 0.82±0.05 和 0.74±0.05,平均 ASSD 为 0.65±0.29mm 和 0.93±0.43mm。该算法为 CT 辅助术中 DTS 成像在图像引导支气管镜介入中奠定了基础,未来的研究将重点关注自动度量权重设置。