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Comparative Study
. 2020 Jul;15(7):1147-1155.
doi: 10.1007/s11548-020-02149-4. Epub 2020 May 8.

Ultrasound 3D reconstruction of malignant masses in robotic-assisted partial nephrectomy using the PAF rail system: a comparison study

Chongyun Wang  1 , Charalampos Komninos  2 , Stephanie Andersen  3 , Claudia D'Ettorre  1 , George Dwyer  1 , Efthymios Maneas  1 , Philip Edwards  1 , Adrien Desjardins  1 , Agostino Stilli  4 , Danail Stoyanov  1
Affiliations
Comparative Study

Ultrasound 3D reconstruction of malignant masses in robotic-assisted partial nephrectomy using the PAF rail system: a comparison study

Chongyun Wang et al. Int J Comput Assist Radiol Surg. 2020 Jul.

Abstract

Purpose: In robotic-assisted partial nephrectomy (RAPN), the use of intraoperative ultrasound (IOUS) helps to localise and outline the tumours as well as the blood vessels within the kidney. The aim of this work is to evaluate the use of the pneumatically attachable flexible (PAF) rail system for US 3D reconstruction of malignant masses in RAPN. The PAF rail system is a novel device developed and previously presented by the authors to enable track-guided US scanning.

Methods: We present a comparison study between US 3D reconstruction of masses based on: the da Vinci Surgical System kinematics, single- and stereo-camera tracking of visual markers embedded on the probe. An US-realistic kidney phantom embedding a mass is used for testing. A new design for the US probe attachment to enhance the performance of the kinematic approach is presented. A feature extraction algorithm is proposed to detect the margins of the targeted mass in US images.

Results: To evaluate the performance of the investigated approaches the resulting 3D reconstructions have been compared to a CT scan of the phantom. The data collected indicates that single camera reconstruction outperformed the other approaches, reconstructing with a sub-millimetre accuracy the targeted mass.

Conclusions: This work demonstrates that the PAF rail system provides a reliable platform to enable accurate US 3D reconstruction of masses in RAPN procedures. The proposed system has also the potential to be employed in other surgical procedures such as hepatectomy or laparoscopic liver resection.

Keywords: 3D ultrasound; Laparoscopy; Soft robotics; Surgical robotics.

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Conflict of interest statement

The authors declare that they have no conflict of interest.

Figures

Fig. 1
Fig. 1
Pneumatically attachable flexible rails: overview of the system when used to guide a drop-in US probe for tumour margins outlining in RAPN procedures
Fig. 2
Fig. 2
Grasping comparison: a grasping configuration between the EndoWrist®PrograspTM Forceps gripper and the BK X12C4 drop-in US probe in standard clinical use and b when the custom connector for the PAF rail system is embedded
Fig. 3
Fig. 3
Experimental setup for phantom tests: the setup includes: the PVA kidney phantom embedding the targeted mass, the PAF rail system, the drop-in US probe BK X12C4 embedding the custom connector to enable mechanical coupling with the PAF rail system, the BK-5000 US cart to collect the US data, the da Vinci® Surgical System (I Generation) fitted with the EndoWrist®PrograspTM Forceps to drive the drop-in US probe and the EndoWrist® Large Needle Driver to position the PAF rail, the da Vinci® Research Kit to collect kinematic and video data, the Panasonic camera controller to collect the data from the stereo endoscope and the single-stage vacuum pump to supply the vacuum pressure to the PAF rail to enable suction between the suction cup and the phantom surface
Fig. 4
Fig. 4
Distribution of the positions of the tip of the end-effector (ProGrasp) mounted on the PSM (in Blue) and distribution of the calculated positions of the ceramic sphere (in Red) using the optimised transformation in the xy (a), xz (b) and yz (c) planes. Green circle is the real position of the ceramic sphere
Fig. 5
Fig. 5
Meshes of the targeted mass inside the kidney phantom plotted as point clouds built using CT data (a), ultrasound data based on DVRK kinematics data (b), single- (c) and stereo-camera (d) data based on visual markers tracking
See this image and copyright information in PMC

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