Strategy for accurate liver intervention by an optical tracking system

Abstract

Image-guided navigation for radiofrequency ablation of liver tumors requires the accurate guidance of needle insertion into a tumor target. The main challenge of image-guided navigation for radiofrequency ablation of liver tumors is the occurrence of liver deformations caused by respiratory motion. This study reports a strategy of real-time automatic registration to track custom fiducial markers glued onto the surface of a patient's abdomen to find the respiratory phase, in which the static preoperative CT is performed. Custom fiducial markers are designed. Real-time automatic registration method consists of the automatic localization of custom fiducial markers in the patient and image spaces. The fiducial registration error is calculated in real time and indicates if the current respiratory phase corresponds to the phase of the static preoperative CT. To demonstrate the feasibility of the proposed strategy, a liver simulator is constructed and two volunteers are involved in the preliminary experiments. An ex-vivo porcine liver model is employed to further verify the strategy for liver intervention. Experimental results demonstrate that real-time automatic registration method is rapid, accurate, and feasible for capturing the respiratory phase from which the static preoperative CT anatomical model is generated by tracking the movement of the skin-adhered custom fiducial markers.

Keywords: (120.3890) Medical optics instrumentation; (170.0170) Medical optics and biotechnology.

Fig. 1

Scheme for navigating the placement of the puncture needle. (a) Prior to the intervention, a set of custom fiducial markers is glued onto the surface of the liver simulator. A CT scan is then acquired, and the custom fiducial markers are automatically localized in the image space. Finally, the respiratory controlling system functions to make the liver simulator generate respiratory movement. During the experiments, custom fiducial markers are continuously localized by an optical tracking system. The real-time calculation of FRE is continuously performed to find the respiratory phase corresponding to the preoperative CT scan in a respiratory cycle. A robotic arm is used to hold the puncture needle and touch the target points. (b) Diagram of the respiratory movement of the liver simulator.

Fig. 2

Workflow of detecting retroreflective spheres in the patient space and stereo matching of two subpixel sets from the left and right images to compute 3D coordinates with an optical tracking system. In the middle sub-figure of the bottom line, the blue circle represents the retroreflective sphere center searched in the compressed image; the red cross represents the retroreflective sphere center searched in the original image.

Fig. 3

Workflow of the automatic extraction of retroreflective sphere centers in the image space. (a) Three-dimension reconstruction model of the liver simulator built from the CT image data set. (b) 3D reconstruction after applying two band-pass threshold values $T_{low}$ and $T_{high}$ and implementing erosion and dilation operations. (c) The right pedestals are obtained after comparing their volumes with that of the pedestal model. (d) The point cloud of pedestal model sampled from the surface of the pedestal model. (e) Image after the ICP algorithm is implemented to register the point cloud sampled from the 3D pedestal model surface to one of the pedestals searched in the image space. (f) Retroreflective spheres are labeled with gray balls.

Fig. 4

(a) Nine custom fiducial markers are glued onto the surface of the liver simulator in the patient space. (b) 3D reconstruction model of the liver simulator in the image space.

Fig. 5

Representative setup with a volunteer, where the nine custom fiducial markers are glued onto the skin surface of the volunteer’s abdomen in the patient space. The optical tracking system tracks the fiducial markers in real time.

Fig. 6

Intervention result assessment on ex-vivo porcine liver model. The localization of the needle tip and target are defined in image space using the image processing system. The 3D distances between the needle tip and target points are computed for each run. The unit of blue grid marks is centimeter.

Fig. 7

Curves of absolute displacement errors of all nine custom fiducial markers change over time in Configuration 1 for 1 min. The green curve represents the maximum displacement of the nine markers; the red curve represents the minimum displacement of the nine markers; and the blue curve represents the averaged displacement of the nine markers. The black dash line called inspiratory phase line indicates that the current phase is inspiratory phase when the value of displacement is lower than this line. The points of three displacements in the middle of dotted box indicate the expiratory phase. The different displacements are recorded for (a) the liver simulator and (b) the volunteers.

Fig. 8

FRE change over time in Configuration 1 for 1 min. The black dash line called inspiratory phase line indicates that the current phase is inspiratory phase when the value of FRE is lower than this line. The phases of curve pointed by purple narrows indicate the expiratory phases. The curve of FRE is recorded for (a) the liver simulator and (b) the volunteers.

Fig. 9

Measured TRE values in different regions for the automatic registrations in the expiratory phase in liver simulator. For all boxplots, the central line mark represents the median TRE; the box represents the 25th and 75th percentiles; the small square within the boxplot represents the averaged TRE; and the whiskers indicate the range in TRE.

Fig. 10

Comparison of measured TRE values in different configurations for the automatic registration in the expiratory phase in liver simulator. For all boxplots, the central mark represents the median TRE; the box represents the 25th and 75th percentiles; the small square within the boxplot represents the averaged TRE; and the whiskers indicate the range in TRE.