Design of a Drop-in EBI Sensor Probe for Abnormal Tissue Detection in Minimally Invasive Surgery

Click-on fluorescence detectors: using robotic surgical instruments to characterize molecular tissue aspects

Fluorescence imaging is increasingly being implemented in surgery. One of the drawbacks of its application is the need to switch back-and-forth between fluorescence- and white-light-imaging settings and not being able to dissect safely under fluorescence guidance. The aim of this study was to engineer 'click-on' fluorescence detectors that transform standard robotic instruments into molecular sensing devices that enable the surgeon to detect near-infrared (NIR) fluorescence in a white-light setting. This NIR-fluorescence detector setup was engineered to be press-fitted onto standard forceps instruments of the da Vinci robot. Following system characterization in a phantom setting (i.e., spectral properties, sensitivity and tissue signal attenuation), the performance with regard to different clinical indocyanine green (ICG) indications (e.g., angiography and lymphatic mapping) was determined via robotic surgery in pigs. To evaluate in-human applicability, the setup was also used for ICG-containing lymph node specimens from robotic prostate cancer surgery. The resulting Click-On device allowed for NIR ICG signal identification down to a concentration of 4.77 × 10^-6 mg/ml. The fully assembled system could be introduced through the trocar and grasping, and movement abilities of the instrument were preserved. During surgery, the system allowed for the identification of blood vessels and assessment of vascularization (i.e., bowel, bladder and kidney), as well as localization of pelvic lymph nodes. During human specimen evaluation, it was able to distinguish sentinel from non-sentinel lymph nodes. With this introduction of a NIR-fluorescence Click-On sensing detector, a next step is made towards using surgical instruments in the characterization of molecular tissue aspects.

Monopolar, bipolar, tripolar, and tetrapolar configurations in robot assisted electrical impedance scanning

OBJECTIVE

Tissue recognition is a critical process during a Robot-assisted minimally invasive surgery (RMIS) and it relies on the involvement of advanced sensing technology.

APPROACH

In this paper, the concept of Robot Assisted Electrical Impedance Sensing (RAEIS) is utilized and further developed aiming to sense the electrical bioimpedance of target tissue directly based on the existing robotic instruments and control strategy. Specifically, we present a new sensing configuration called pseudo-tetrapolar method. With the help of robotic control, we can achieve a similar configuration as traditional tetrapolar, and with better accuracy.

MAIN RESULTS

Five configurations including monopolar, bipolar, tripolar, tetrapolar and pseudo-tetrapolar are analyzed and compared through simulation experiments. Advantages and disadvantages of each configuration are thus discussed.

SIGNIFICANCE

This study investigates the measurement of tissue electrical property directly based on the existing robotic surgical instruments. Specifically, different sensing configurations can be realized through different connection and control strategies, making them suitable for different application scenarios.

Robot-Assisted Electrical Impedance Scanning system for 2D Electrical Impedance Tomography tissue inspection

The electrical impedance tomography (EIT) technology is an important medical imaging approach to show the electrical characteristics and the homogeneity of a tissue region noninvasively. Recently, this technology has been introduced to the Robot Assisted Minimally Invasive Surgery (RAMIS) for assisting the detection of surgical margin with relevant clinical benefits. Nevertheless, most EIT technologies are based on a fixed multiple-electrodes probe which limits the sensing flexibility and capability significantly. In this study, we present a method for acquiring the EIT measurements during a RAMIS procedure using two already existing robotic forceps as electrodes. The robot controls the forceps tips to a series of predefined positions for injecting excitation current and measuring electric potentials. Given the relative positions of electrodes and the measured electric potentials, the spatial distribution of electrical conductivity in a section view can be reconstructed. Realistic experiments are designed and conducted to simulate two tasks: subsurface abnormal tissue detection and surgical margin localization. According to the reconstructed images, the system is demonstrated to display the location of the abnormal tissue and the contrast of the tissues' conductivity with an accuracy suitable for clinical applications.