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

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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 trackingmethod 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 millimeterwide 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 "cigarshaped" 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.

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N’Djin, W. A., Chapelon, J. Y., & Melodelima, D. (2015). 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. PLoS ONE, 10(9). https://doi.org/10.1371/journal.pone.0137317

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