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.
Highlights
Treatment safety and accuracy when using High Intensity Focused Ultrasound (HIFU) can be challenged by organ motions, during breathing [1,2,3,4]
The present paper presents a US image-based dynamic fusion modeling method which enables numerical modeling of the effects of in vivo real liver motions on the size, shape and location of thermal lesions induced during intraoperative USgHIFU treatments
Correction coefficients could be applied post-operatively to compensate for drifts and the relevance of the magnitude displacement detected was verified visually by comparing the displacement of a contrasted structure and that of an overlaid search region (SR) window moving virtually according to the tracking data on the US images
Summary
Treatment safety and accuracy when using High Intensity Focused Ultrasound (HIFU) can be challenged by organ motions, during breathing [1,2,3,4]. In order to avoid liver motions from interfering with treatment targeting and monitoring, some previous preclinical studies have highlighted the interest of using a “breath-hold” protocol by applying intermittent apnea during HIFU exposures [11,12,13]. In surgery (resection) and in procedures involving thermal ablation with physical agents, localized tumors must be ablated entirely with safety negative margins in order to ensure treatment efficacy. These margins are critical to prevent the risk of local recurrence and were shown to increase overall patient survival rates [14,15]. Allowing respiratory activity during HIFU treatments may be important for optimizing treatment performances, safety and enhancing post-treatment recovery
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