Instrumental tactile diagnostics in robot-assisted surgery

Abstract

BackgroundRobotic surgery has gained wide acceptance due to minimizing trauma in patients. However, the lack of tactile feedback is an essential limiting factor for the further expansion. In robotic surgery, feedback related to touch is currently kinesthetic, and it is mainly aimed at the minimization of force applied to tissues and organs. Design and implementation of diagnostic tactile feedback is still an open problem. We hypothesized that a sufficient tactile feedback in robot-assisted surgery can be provided by utilization of Medical Tactile Endosurgical Complex (MTEC), which is a novel specialized tool that is already commercially available in the Russian Federation. MTEC allows registration of tactile images by a mechanoreceptor, real-time visualization of these images, and reproduction of images via a tactile display.Materials and methodsNine elective surgeries were performed with da Vinci™ robotic system. An assistant performed tactile examination through an additional port under the guidance of a surgeon during revision of tissues. The operating surgeon sensed registered tactile data using a tactile display, and the assistant inspected the visualization of tactile data. First, surgeries where lesion boundaries were visually detectable were performed. The goal was to promote cooperation between the surgeon and the assistant and to train them in perception of the tactile feedback. Then, instrumental tactile diagnostics was utilized in case of visually undetectable boundaries.ResultsIn robot-assisted surgeries where lesion boundaries were not visually detectable, instrumental tactile diagnostics performed using MTEC provided valid identification and localization of lesions. The results of instrumental tactile diagnostics were concordant with the results of intraoperative ultrasound examination. However, in certain cases, for example, thoracoscopy, ultrasound examination is inapplicable, while MTEC-based tactile diagnostics can be efficiently utilized.ConclusionThe study proved that MTEC can be efficiently used in robot-assisted surgery allowing correct localization of visually undetectable lesions and visually undetectable boundaries of pathological changes of tissues.

Instrumental Mechanoreceptoric Palpation in Gastrointestinal Surgery

“…The MTEC is a complex consisting of tactile mechanoreceptors, a computer, and an optional tactile display [ 16 ]. A tactile mechanoreceptor registers tactile data via pressure sensors located in its operating head and wirelessly transmits the results to a computer.…”

“…A tactile mechanoreceptor registers tactile data via pressure sensors located in its operating head and wirelessly transmits the results to a computer. A computer processes raw data [ 17 ], performs real-time visualisation of tactile images [ 16 ], and reproduces tactile images on a tactile display, where images can be perceived simply with the use of a finger. Two versions of tactile mechanoreceptors are available ( Figure 1 ).…”

“…Detection and localisation of tumours using MTEC are based on identification of lesion boundaries, which produce heterogeneous tactile images. A press on a homogeneous area results in homogeneous tactile frames, while a press on a boundary results in highly contrasting tactile frames ( Figure 2 ; see also [ 16 , Figures 2 and 3]).…”

A Greedy Clustering Algorithm Based on Interval Pattern Concepts and the Problem of Optimal Box Positioning

“…MTEC allows intraoperative mechanoreceptor tactile examination of tissues and is already used in endoscopic surgery [14][15][16]. As methods for automated analysis of medical tactile images are still insufficient, validation results in particular and the developed clustering algorithm in general provide new opportunities for the medical domain applications.…”

NP-Hardness of the Problem of Optimal Box Positioning

“…The algorithm was inspired by the apparatus of maximum interval pattern concepts (see, e.g., [4,5]), a technique that allows one to select patterns from fuzzy contexts. This approach was successfully applied to the dataset of tactile images registered by the Medical Tactile Endosurgical Complex [6][7][8], which allows intraoperative tactile examination of tissues. Comparison of the proposed clustering approach with the conventional k-means clustering resulted in a statistically significant advantage of the proposed method over k-means in clustering quality.…”