N'Djin W Apoutou, Chapelon Jean-Yves, Melodelima David
LabTAU, Inserm U1032, Institut National de la Santé et de la Recherche Médicale, Lyon, France; Université Claude Bernard Lyon 1, Lyon, France.
PLoS One. 2015 Sep 23;10(9):e0137317. doi: 10.1371/journal.pone.0137317. eCollection 2015.
Organ motion is a key component in the treatment of abdominal tumors by High Intensity Focused Ultrasound (HIFU), since it may influence the safety, efficacy and treatment time. Here we report the development in a porcine model of an Ultrasound (US) image-based dynamic fusion modeling method for predicting the effect of in vivo motion on intraoperative HIFU treatments performed in the liver in conjunction with surgery. A speckle tracking method was used on US images to quantify in vivo liver motions occurring intraoperatively during breathing and apnea. A fusion modeling of HIFU treatments was implemented by merging dynamic in vivo motion data in a numerical modeling of HIFU treatments. Two HIFU strategies were studied: a spherical focusing delivering 49 juxtapositions of 5-second HIFU exposures and a toroidal focusing using 1 single 40-second HIFU exposure. Liver motions during breathing were spatially homogenous and could be approximated to a rigid motion mainly encountered in the cranial-caudal direction (f = 0.20 Hz, magnitude > 13 mm). Elastic liver motions due to cardiovascular activity, although negligible, were detectable near millimeter-wide sus-hepatic veins (f = 0.96 Hz, magnitude < 1 mm). The fusion modeling quantified the deleterious effects of respiratory motions on the size and homogeneity of a standard "cigar-shaped" millimetric lesion usually predicted after a 5-second single spherical HIFU exposure in stationary tissues (Dice Similarity Coefficient: DSC < 45%). This method assessed the ability to enlarge HIFU ablations during respiration, either by juxtaposing "cigar-shaped" lesions with spherical HIFU exposures, or by generating one large single lesion with toroidal HIFU exposures (DSC > 75%). Fusion modeling predictions were preliminarily validated in vivo and showed the potential of using a long-duration toroidal HIFU exposure to accelerate the ablation process during breathing (from 0.5 to 6 cm3 · min(-1)). To improve HIFU treatment control, dynamic fusion modeling may be interesting for assessing numerically focusing strategies and motion compensation techniques in more realistic conditions.
器官运动是高强度聚焦超声（HIFU）治疗腹部肿瘤的关键因素，因为它可能会影响治疗的安全性、有效性和治疗时间。在此，我们报告了一种基于超声（US）图像的动态融合建模方法在猪模型中的进展，该方法用于预测体内运动对肝脏手术中进行的术中HIFU治疗效果的影响。在超声图像上使用斑点跟踪方法来量化术中呼吸和呼吸暂停期间肝脏的体内运动。通过将体内动态运动数据合并到HIFU治疗的数值模型中，实现了HIFU治疗的融合建模。研究了两种HIFU策略：一种是球形聚焦，进行49次5秒HIFU照射的并列；另一种是环形聚焦，使用1次40秒的HIFU照射。呼吸期间肝脏运动在空间上是均匀的，并且可以近似为主要在头-尾方向上遇到的刚性运动（频率f = 0.20 Hz，幅度> 13 mm）。尽管可以忽略不计，但在毫米级的肝下静脉附近可检测到由于心血管活动引起的弹性肝脏运动（频率f = 0.96 Hz，幅度< 1 mm）。融合建模量化了呼吸运动对通常在静止组织中单次5秒球形HIFU照射后预测的标准“雪茄形”毫米级病变的大小和均匀性的有害影响（骰子相似系数：DSC < 45%）。该方法评估了在呼吸期间扩大HIFU消融范围的能力，方法是通过将“雪茄形”病变与球形HIFU照射并列，或者通过环形HIFU照射产生一个大的单一病变（DSC > 75%）。融合建模预测在体内得到了初步验证，并显示了使用长时间环形HIFU照射在呼吸期间加速消融过程的潜力（从0.5至6 cm³·min⁻¹）。为了改善HIFU治疗控制，动态融合建模对于在更现实的条件下评估数值聚焦策略和运动补偿技术可能是有意义的。
