An Ultrasound Image-Based Dynamic Fusion Modeling Method for Predicting the Quantitative Impact of In Vivo Liver Motion on Intraoperative HIFU Therapies: Investigations in a Porcine Model

Abstract

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 = 0.20Hz, magnitude >13mm). Elastic liver motions due to cardiovascular activity, although negligible, were detectable near millimeter-wide sus-hepatic veins (f = 0.96Hz, magnitude <1mm). 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.

Intraoperative HIFU Ablation of the Pancreas Using a Toroidal Transducer in a Porcine Model. The First Step towards a Clinical Treatment of Locally Advanced Pancreatic Cancer

“…For example, the discovery of metastatic disease (mainly liver metastases and peritoneal carcinomatosis) clearly precludes local treatment and illustrates the need for an intra-operative treatment. For these reasons the HIFU device used in this study was developed for intraoperative used as the one we developed for liver tumors [ 18 , 53 ]. The size of the ablation can be adapted to constrain related to the organ using electronic focalization [ 54 ].…”

Real-time 3D ultrasound based motion tracking for the treatment of mobile organs with MR-guided high-intensity focused ultrasound

“…$2 mm at -6 dB in the direction transverse to the axis of propagation). Thereby, HIFU focus has to be steered in real-time to follow the targeted tissue position in order to deposit heat at the desired location, reduce the treatment time and improve the safety of the procedure [5] by avoiding overheating the surrounding tissues [6].…”

Impact of cavitation on lesion formation induced by high intensity focused ultrasound

“…One solution to improve the safety of HIFU is introducing some effective and accurate monitoring method, such as ultrasound image-guidance [12][13][14][15][16][17][18] and MRI-guidance. [19][20][21][22][23] However, there still exist some problems, like time delay for the MRI image system and low image resolution of the ultrasound system.…”