Robotic Tissue Sampling for Safe Post-Mortem Biopsy in Infectious Corpses

Abstract

In pathology and legal medicine, the histopathological and microbiological analysis of tissue samples from infected deceased is a valuable information for developing treatment strategies during a pandemic such as COVID-19. However, a conventional autopsy carries the risk of disease transmission and may be rejected by relatives. We propose minimally invasive biopsy with robot assistance under CT guidance to minimize the risk of disease transmission during tissue sampling and to improve accuracy. A flexible robotic system for biopsy sampling is presented, which is applied to human corpses placed inside protective body bags. An automatic planning and decision system estimates optimal insertion point. Heat maps projected onto the segmented skin visualize the distance and angle of insertions and estimate the minimum cost of a puncture while avoiding bone collisions. Further, we test multiple insertion paths concerning feasibility and collisions. A custom end effector is designed for inserting needles and extracting tissue samples under robotic guidance. Our robotic post-mortem biopsy (RPMB) system is evaluated in a study during the COVID-19 pandemic on 20 corpses and 10 tissue targets, 5 of them being infected with SARS-CoV-2. The mean planning time including robot path planning is 5.72±1.67 s. Mean needle placement accuracy is 7.19±4.22 mm.

Minimally Invasive Tissue Sampling via Post Mortem Ultrasound: A Feasible Tool (Not Only) in Infectious Diseases—A Case Report

“…Due to lesser contact with contagious material compared to a conventional autopsy, the risk of infections for medical staff is reduced. We were further able to establish a MITS protocol using post mortem CT instead of ultrasound and were successful in the first attempts of robotic tissue samplings to minimize the infectious hazards once more [ 26 ].…”

Quantifying Passive Biomechanical Stability Using an Industrial Robot: Development and Experimental Validation of a Task Space Motion Framework

“…Let ( ω, θ) be an axis-angle pair, where ω ∈ R 3 is the unit vector representing axis of rotation, and θ ∈ R is the angle to rotate about ω. The conversion of the axis-angle rotation to matrix form is expressed as shown in (1), where s = sin(θ), c = cos(θ), d = 1 − cos(θ) and ω = ω1 ω2 ω3…”

“…Despite their name, they have long been used for non-industrial purposes in healthcare, including research and development within medicine and biomechanics. Such applications can be post-mortem tissue collection [1] or biopsy [2], osteoporotic hip augmentation [3], assistance in laparoscopic hysterectomy [4], or automated robotic ultrasound imaging [5]. In these applications, the robots assist surgeons with their high durability, precision and accuracy.…”

Proximity-Based Haptic Feedback for Collaborative Robotic Needle Insertion

“…We consider robot-assisted needle insertions in the context of epidural anesthesia. CT-guided robotic needle insertions have shown promising results for soft tissue biopsy sampling [7]. In epidural anesthesia, external image guidance is challenging and tissue deformation as well as patient movement make a fully automated needle placement difficult.…”