Haptics in Robot-Assisted Surgery: Challenges and Benefits

Robotic surgery is transforming the current surgical practice, not only by improving the conventional surgical methods but also by introducing innovative robot-enhanced approaches that broaden the capabilities of clinicians. Being mainly of man-machine collaborative type, surgical robots are seen as media that transfer pre- and intra-operative information to the operator and reproduce his/her motion, with appropriate filtering, scaling, or limitation, to physically interact with the patient. The field, however, is far from maturity and, more critically, is still a subject of controversy in medical communities. Limited or absent haptic feedback is reputed to be among reasons that impede further spread of surgical robots. In this paper objectives and challenges of deploying haptic technologies in surgical robotics is discussed and a systematic review is performed on works that have studied the effects of providing haptic information to the users in major branches of robotic surgery. It has been tried to encompass both classical works and the state of the art approaches, aiming at delivering a comprehensive and balanced survey both for researchers starting their work in this field and for the experts

A Framework for Tumor Localization in Robot-Assisted Minimally Invasive Surgery

Manual palpation of tissue is frequently used in open surgery, e.g., for localization of tumors and buried vessels and for tissue characterization. The overall objective of this work is to explore how tissue palpation can be performed in Robot-Assisted Minimally Invasive Surgery (RAMIS) using laparoscopic instruments conventionally used in RAMIS. This thesis presents a framework where a surgical tool is moved teleoperatively in a manner analogous to the repetitive pressing motion of a finger during manual palpation. We interpret the changes in parameters due to this motion such as the applied force and the resulting indentation depth to accurately determine the variation in tissue stiffness. This approach requires the sensorization of the laparoscopic tool for force sensing. In our work, we have used a da Vinci needle driver which has been sensorized in our lab at CSTAR for force sensing using Fiber Bragg Grating (FBG). A computer vision algorithm has been developed for 3D surgical tool-tip tracking using the da Vinci \u27s stereo endoscope. This enables us to measure changes in surface indentation resulting from pressing the needle driver on the tissue. The proposed palpation framework is based on the hypothesis that the indentation depth is inversely proportional to the tissue stiffness when a constant pressing force is applied. This was validated in a telemanipulated setup using the da Vinci surgical system with a phantom in which artificial tumors were embedded to represent areas of different stiffnesses. The region with high stiffness representing tumor and region with low stiffness representing healthy tissue showed an average indentation depth change of 5.19 mm and 10.09 mm respectively while maintaining a maximum force of 8N during robot-assisted palpation. These indentation depth variations were then distinguished using the k-means clustering algorithm to classify groups of low and high stiffnesses. The results were presented in a colour-coded map. The unique feature of this framework is its use of a conventional laparoscopic tool and minimal re-design of the existing da Vinci surgical setup. Additional work includes a vision-based algorithm for tracking the motion of the tissue surface such as that of the lung resulting from respiratory and cardiac motion. The extracted motion information was analyzed to characterize the lung tissue stiffness based on the lateral strain variations as the surface inflates and deflates

Bayesian changepoint analysis for atomic force microscopy and soft material indentation

Material indentation studies, in which a probe is brought into controlled physical contact with an experimental sample, have long been a primary means by which scientists characterize the mechanical properties of materials. More recently, the advent of atomic force microscopy, which operates on the same fundamental principle, has in turn revolutionized the nanoscale analysis of soft biomaterials such as cells and tissues. This paper addresses the inferential problems associated with material indentation and atomic force microscopy, through a framework for the changepoint analysis of pre- and post-contact data that is applicable to experiments across a variety of physical scales. A hierarchical Bayesian model is proposed to account for experimentally observed changepoint smoothness constraints and measurement error variability, with efficient Monte Carlo methods developed and employed to realize inference via posterior sampling for parameters such as Young's modulus, a key quantifier of material stiffness. These results are the first to provide the materials science community with rigorous inference procedures and uncertainty quantification, via optimized and fully automated high-throughput algorithms, implemented as the publicly available software package BayesCP. To demonstrate the consistent accuracy and wide applicability of this approach, results are shown for a variety of data sets from both macro- and micro-materials experiments--including silicone, neurons, and red blood cells--conducted by the authors and others.Comment: 20 pages, 6 figures; submitted for publicatio

Atomic force microscopy-based mechanobiology

Mechanobiology emerges at the crossroads of medicine, biology, biophysics and engineering and describes how the responses of proteins, cells, tissues and organs to mechanical cues contribute to development, differentiation, physiology and disease. The grand challenge in mechanobiology is to quantify how biological systems sense, transduce, respond and apply mechanical signals. Over the past three decades, atomic force microscopy (AFM) has emerged as a key platform enabling the simultaneous morphological and mechanical characterization of living biological systems. In this Review, we survey the basic principles, advantages and limitations of the most common AFM modalities used to map the dynamic mechanical properties of complex biological samples to their morphology. We discuss how mechanical properties can be directly linked to function, which has remained a poorly addressed issue. We outline the potential of combining AFM with complementary techniques, including optical microscopy and spectroscopy of mechanosensitive fluorescent constructs, super-resolution microscopy, the patch clamp technique and the use of microstructured and fluidic devices to characterize the 3D distribution of mechanical responses within biological systems and to track their morphology and functional state.Peer ReviewedPostprint (published version

Mechanobiology of the basement membrane

The microenvironment (ME) of epithelial cells lies at the heart of the function and architecture of most organs. Epithelial cells define the function of the organ. The stroma ensures that the highly specialized MEs within an organ are correctly assembled. A key organising element of the ME is the rather stiff basement membrane (BM), which is the structural part that passively, through its mechanical rigidity and actively through signalling via its components separates the luminal epithelia from the stromal fibroblasts, creating and maintaining tissue polarity to ensure proper function of the organ. The primary goal of this work is to find universal features of the BM and epithelial cells across organs and to understand how the cells mechanobiology is influenced by the BM. The cells mechanobiology is defined by the interaction of the cells integrins with the BMs proteins, notably laminin, perlecan and collagen IV. Disturbing either of the interaction partners quickly leads to distinct new mechanobiological phenotypes of the epithelial cells, without the need for genetic modifications. Further, I will show that changes to the BM by cancer cells are a key step in forming invasive carcinomas which goes together with recent research that shows that the mechanics of epithelial cells and extra-cellular matrix (ECM) are fundamentally altered. In the case of BMs and the extracellular matrix in general, the mechanical properties are governed by the type of fibres and the state of cross-linking. The only tool available for characterizing this physical properties of cells and ECM components under physiological conditions is the atomic force microscope. It gives insight about stiffness and E-modulus on a sub-micrometer scale and is very sensitive to changes in the low Pascal-range. The combination with confocal light microscopy allows one to correlate changes in ridigity to cytoskeletion localisation, to understand what part of the cytoskeleton defines the mechanics and how this is changed by disturbing cell-BM interactions