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

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±167s. Mean needle placement accuracy is 7.19± 422mm.

Development and Validation of a Novel Calibration Methodology and Control Approach for Robot-Aided Transcranial Magnetic Stimulation (TMS)

OBJECTIVE

This article presents the development and validation of a new robotic system for Transcranial Magnetic Stimulation (TMS), characterized by a new control approach, and an ad-hoc calibration methodology, specifically devised for the TMS application.

METHODS

The robotic TMS platform is composed of a 7 dof manipulator, controlled by an impedance control, and a camera-based neuronavigation system. The proposed calibration method was optimized on the workspace useful for the specific TMS application (spherical shell around the subject's head), and tested on three different hand-eye and robot-world calibration algorithms. The platform functionality was tested on six healthy subjects during a real TMS procedure, over the left primary motor cortex.

RESULTS

employing our method significantly decreases ( ) the calibration error by 34% for the position and 19% for the orientation. The robotic TMS platform achieved greater orientation accuracy than the expert operators, significantly reducing orientation errors by 46% ( ). No significant differences were found in the position errors and in the amplitude of the motor evoked potentials (MEPs) between the robot-aided TMS and the expert operators.

CONCLUSION

The proposed calibration represents a valid method to significantly reduce the calibration errors in robot-aided TMS applications. Results showed the efficacy of the proposed platform (including the control algorithm) in administering a real TMS procedure, achieving better coil positioning than expert operators, and similar results in terms of MEPs.

SIGNIFICANCE

This article spotlights how to improve the performance of a robotic TMS platform, providing a reproducible and low-cost alternative to the few devices commercially available.

Needle placement accuracy in CT-guided robotic post mortem biopsy

Forensic autopsies include a thorough examination of the corpse to detect the source or alleged manner of death as well as to estimate the time since death. However, a full autopsy may be not feasible due to limited time, cost or ethical objections by relatives. Hence, we propose an automated minimal invasive needle biopsy system with a robotic arm, which does not require any online calibrations during a procedure. The proposed system can be easily integrated into the workflow of a forensic biopsy since the robot can be flexibly positioned relative to the corpse. With our proposed system, we performed needle insertions into wax phantoms and livers of two corpses and achieved an accuracy of 4.34 ± 1.27 mm and 10.81 ± 4.44 mm respectively.

Non-orthogonal one-step calibration method for robotized transcranial magnetic stimulation

BACKGROUND

Robotized transcranial magnetic stimulation (TMS) combines the benefits of neuro-navigation with automation and provides a precision brain stimulation method. Since the coil will normally remain unmounted between different clinical uses, hand/eye calibration and coil calibration are required before each experiment. Today, these two steps are still separate: hand/eye calibration is performed using methods proposed by Tsai/Lenz or Floris Ernst, and then the coil calibration is carried out based on the traditional TMS experimental step. The process is complex and time-consuming, and traditional coil calibration using a handheld probe is susceptible to greater calibration error.

METHODS

A novel one-step calibration method has been developed to confirm hand/eye and coil calibration results by formulating a matrix equation system and estimating its solution. Hand/eye calibration and coil calibration are performed to confirm the pose relationships of the marker/end effector 'X', probe/end effector 'Y', and robot/world 'Z'. First, the coil is fixed on the end effector of the robot. During the one-step calibration process, a marker is mounted on the top of the coil and a calibration probe is fixed at the actual effective position of the coil. Next, the robot end effector is moved to a series of random positions 'A', the tracking data of marker 'B' and probe 'C' is obtained correspondingly. Then, a matrix equation system AX = ZB and AY = ZC can be acquired, and it is computed using a least-squares approach. Finally, the calibration probe is removed after calibration, while the marker remains fixed to the coil during the TMS experiment. The methods were evaluated based on simulation data and on experimental data from an optical tracking device. We compared our methods with two classical methods: the QR24 method proposed by Floris Ernst and the handheld coil calibration method.

RESULTS

The new methods outperform the QR24 method in the aspect of translational accuracy and performs similarly in the aspect of rotational accuracy, the total translational error decreased more than fifty percent. The new approach also outperforms traditional handheld coil calibration of navigated TMS systems, the total translational error decreased three- to fourfold, and the rotational error decreased six- to eightfold. Furthermore, the convergence speed is improved 16- to 27-fold for the new algorithms.

CONCLUSION

These results suggest that the new method can be used for hand/eye and coil calibration of a robotized TMS system. Two complex steps can be simplified using a least-squares approach.

Evaluation of hand-eye and robot-world calibration algorithms for TMS application

In this paper we compare three approaches to solve the hand-eye and robot-world calibration problem, for their application to a Transcranial Magnetic Stimulation (TMS) system. The selected approaches are: i) non-orthogonal approach (QR24); ii) stochastic global optimization (SGO); iii) quaternion-based (QUAT) method. Performance were evaluated in term of translation and rotation errors, and computational time. The experimental setup is composed of a 7 dof Panda robot (by Franka Emika GmbH) and a Polaris Vicra camera (by Northern Digital Inc) combined with the SofTaxic Optic software (by E.M.S. srl). The SGO method resulted to have the best performance, since it provides lowest errors and high stability over different datasets and number of calibration points. The only drawback is its computational time, which is higher than the other two, but this parameter is not relevant for TMS application. Over the different dataset used in our tests, the small workspace (sphere with radius of 0.05m) and a number of calibration points around 150 allow to achieve the best performance with the SGO method, with an average error of 0.83 ± 0.35mm for position and 0.22 ± 0.12deg for orientation.

A visual probe positioning tool for 4D ultrasound-guided radiotherapy

Ultrasound (US) guidance is a rapidly growing area in image-guided radiotherapy. For motion compensation, the therapy target needs to be visualized with the US probe to continuously determine its position and adapt for shifts. While US has obvious benefits such as real-time capability and proven safety, one of the main drawbacks to date is its user dependency - high quality results require long years of clinical experience. To provide positioning assistance for the setup of US equipment by non-experts, we developed a visual guidance tool combining real-time US volume and CT visualization in a geometrically calibrated setup. By using a 4D US station with real-time data access and an optical tracking system, we achieved a calibration accuracy of 1.2 mm and a mean 2D contour distance of 1.7 mm between organ boundaries identified in US and CT. With this low calibration error as well as the good visual alignment of the structures, the developed probe positioning tool could be a valuable aid for ultrasound-guided radiotherapy and other interventions by guiding the user to a suitable acoustic window while potentially improving setup reproducibility.

Calibration of mobile manipulators using 2D positional features

Robotic manipulators are increasingly being attached to Automatic Ground Vehicles (AGVs) to aid in the efficiency of assembly for manufacturing systems. However, calibrating these mobile manipulators is difficult as the offset between the robotic manipulator and the AGV is often unknown. This paper provides a novel, simple, and low-cost method for calibrating and measuring the performance of mobile manipulators by using data collected from a laser retroreflector that digitally detects the horizontal two-dimensional (2D) position of reflectors on an artifact as well as a navigation system that provides the heading angle and 2D position of the AGV. The method is mathematically presented by providing a closed form solution to the positional component of the 2D robotworld/hand-eye calibration problem AX Y= B. The method is then applied to simulated data as well as data collected in a laboratory setting and compared to other methods.

Impact of robotic ultrasound image guidance on plan quality in SBRT of the prostate

OBJECTIVE

Ultrasound provides good image quality, fast volumetric imaging and is established for abdominal image guidance. Robotic transducer placement may facilitate intrafractional motion compensation in radiation therapy. We consider integration with the CyberKnife and study whether the kinematic redundancy of a seven-degrees-of-freedom robot allows for acceptable plan quality for prostate treatments.

METHODS

Reference treatment plans were generated for 10 prostate cancer cases previously treated with the CyberKnife. Considering transducer and prostate motion by different safety margins, 10 different robot poses, and 3 different elbow configurations, we removed all beams colliding with robot or transducer. For each combination, plans were generated using the same strict dose constraints and the objective to maximize the target coverage. Additionally, plans for the union of all unblocked beams were generated.

RESULTS

In 9 cases the planning target coverage with the ultrasound robot was within 1.1 percentage points of the reference coverage. It was 1.7 percentage points for one large prostate. For one preferable robot position, kinematic redundancy decreased the average number of blocked beam directions from 23.1 to 14.5.

CONCLUSION

The impact of beam blocking can largely be offset by treatment planning and using a kinematically redundant robot. Plan quality can be maintained by carefully choosing the ultrasound robot position and pose. For smaller planning target volumes the difference in coverage is negligible for safety margins of up to 35 mm. Advances in knowledge: Integrating a robot for online intrafractional image guidance based on ultrasound can be realized while maintaining acceptable plan quality for prostate cancer treatments with the CyberKnife.

Registration of a hybrid robot using the Degradation-Kronecker method and a purely nonlinear method

Although the registration of a robot is crucial in order to identify its pose with respect to a tracking system, there is no reported solution to address this issue for a hybrid robot. Different from classical registration, the registration of a hybrid robot requires the need to solve an equation with three unknowns where two of these unknowns are coupled together. This property makes it difficult to obtain a closed-form solution. This paper is a first attempt to solve the registration of a hybrid robot. The Degradation-Kronecker (D-K) method is proposed as an optimal closed-form solution for the registration of a hybrid robot in this paper. Since closed-form methods generally suffer from limited accuracy, a purely nonlinear (PN) method is proposed to complement the D-K method. With simulation and experiment results, it has been found that both methods are robust. The PN method is more accurate but slower as compared to the D-K method. The fast computation property of the D-K method makes it appropriate to be applied in real-time circumstances, while the PN method is suitable to be applied where good accuracy is preferred.