Human in vivo liver and tumor bioimpedance measured with biopsy needle

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Tissue classification from electric impedance spectroscopy for haptic feedback in minimally invasive surgery

Haptic feedback is missing in teleoperated surgical robots creating a sensory disconnect from the surgeon and their patient. This thesis proposes using the electric impedance of tissues, instead of the traditionally used mechanical impedance, to develop haptic feedback for surgical robots. Electric impedance spectroscopy (EIS) and a modified surgical needle were successfully able to measure the electric impedance for gel-based phantoms, ex-vivo tissue, and freshly excised organs. Processes for fitting the electric impedance of these tissues to the double-dispersion Cole model were developed including stochastic and deterministic approaches. The tissues were classified with least square error, k-Nearest Neighbour and Na??ve Bayes using the measured electric impedance and the extracted model parameter values. The thesis culminates in applications of using EIS as part of implementing vibrotactile and force feedback applications involving sets of user trials to validate its effectiveness in identifying the tissue through haptic feedback

Guiding deep brain stimulation neurosurgery with optical spectroscopy

Savoir différiencier les différentes types de tissus représente un aspect important lors d’interventions médicales, que ce soit pour aider au diagnostic d’une maladie ou pour le guidage chirurgical. Il est généralement très difficile de distinguer les tissus sains des tissus pathologiques à l’oeil nu et la navigation chirurgicale peut parfois être difficile dans les grands organes où la structure ciblé se trouve enfouie profondément. De nouvelles méthodes susceptibles d’accroître la réussite de telles interventions médicales suscitent actuellement de l’intérêt chez les professionnels de la santé. La spectroscopie optique, en analysant les interactions lumière-tissu dans une plage spectrale définie, est un outil permettant de différencier les tissus avec une résolution et une sensibilité bien supérieures à celles de l’oeil humain. Tout au long de cette thèse, je détaillerai comment la spectroscopie optique a été utilisée pour créer et améliorer un système de guidage optique utilisé pour la stimulation cérébrale profonde en neurochirurgie, en particulier pour le traitement de la maladie de Parkinson. Pour commencer, je montrerai comment les informations spectroscopiques peuvent fournir une rétroaction peropératoire en temps réel à un neurochirurgien, au cours de la phase d’implantation de la procédure, avec une sonde qui n’induit aucune invasion supplémentaire. Je présenterai l’investigation de deux modalités spectroscopiques différentes pour la discrimination tissulaire pour le guidage, soit la spectroscopie à réflectance diffuse et la spectroscopie de diffusion Raman anti-Stokes cohérente. Les avantages et les inconvénients des deux techniques, ainsi que leurs aptitude à la traduction prometteuse pour cette application seront abordés. Par la suite, je présenterai une nouvelle technique d’analyse de données pour extraire l’oxygénation des tissus à partir de spectres de réflectance diffus dans le but d’améliorer la précision de mesure en spectroscopie rétinienne et ultimement de porter un diagnostique. Bien que conçu pour la rétine, l’algorithme peut également être utilisé pour analyser les spectres acquis lors d’une neurochirurgie afin de fournir des informations à la fois discriminantes et diagnostiques. Finalement, je montrerai des preuves de diffusion anisotrope de la lumière dans les axones myélinisés de la moelle épinière et discuterai des conséquences que cela pourrait avoir sur les simulations actuelles de la propagation des photons dans le cerveau, qui feront partie intégrante d’un guidage optique efficace.Differentiating tissue types is an important aspect of guiding medical interventions whether it be for disease diagnosis or for surgical guidance. However, diseased and healthy tissues are often hard to discriminate by human vision alone and surgical navigation can be difficult to accomplish in large organs where the target structure lies deep within the body. New methods that can increase certainty in such medical interventions are therefore of great interest to healthcare professionals. Optical spectroscopy is a tool which can be exploited to probe discriminatory information in tissue by analyzing light-tissue interactions with a spectral range, resolution and sensitivity much greater than the human eye. Throughout this thesis, I will explain how I have leveraged optical spectroscopy to create, and improve, an optical guidance system for deep brain stimulation neurosurgery, specifically for the treatment of Parkinson’s disease. I will begin by describing how spectroscopic information can provide real-time feedback to a surgeon during the procedure, in the hopes of ultimately improving treatment outcome. To this end, I will present the investigation of two different spectroscopic modalities for optical guidance: diffuse reflectance spectroscopy, and coherent anti-Stokes Raman scattering spectroscopy. The advantages and disadvantages of both techniques will be discussed along with their promising translatability for this application. Following this, I will present a novel data analysis technique for extracting the tissue oxygenation from diffuse reflectance spectra with the aim of improved diagnostic information in retinal spectroscopy. While designed for the retina, the algorithm can also be used to analyze spectra acquired during a neurosurgery to provide both discriminatory and diagnostic information. Lastly, I will show evidence of anisotropic light scattering in the myelinated axons of the spinal cord and discuss the implications this may have on current photon propagation simulations in the brain, which will be integral for effective optical guidance

Development and evaluation of hand-held robotic technology for safe and successful peripheral intravenous catheterization on pediatric patients

Peripheral IntraVenous Catheterization (PIVC) is often required in hospitals to fulfil urgent needs of blood sampling or fluid/medication administration. Despite of the importance of a high success rate, the conventional PIVC operation suffers from low insertion accuracy especially on young pediatric patients. On average, each pediatric patient is submitted to 2.1 attempts before venous access is obtained, with around 50% failure for the first attempt. The risks of such multiple attempts can be severe and life-threatening as they can cause serious extravasation injuries. Given the levels of precision and controllability needed for PIVC, robotic systems show a good potential to effectively assist the operation and improve its success rate. Therefore, this study aims to provide such robotic assistance by focusing on the most challenging and error-prone parts of the operation. In order to understand the difficulties of a pediatric PIVC, a survey investigation is conducted with specialists at the beginning of this research. The feedbacks from this survey indicates an urgent need of a hand-held robot to assist in the catheter insertion control to precisely access the target vein. To achieve the above goal, a novel venipuncture detection system based on sensing the electrical impedance of the contacting tissue at the needle tip has been proposed and developed. Then several ex-vivo and in-vivo experiments were conducted to assess this detection system. Experimental results show that this system can be highly effective to detect venipuncture. Subsequently, based on this venipuncture detection system, four different handheld robots have been developed to provide different levels of autonomy and assistance while executing a PIVC insertion: 1. SVEI, short for \u2018Smart Venous Enter Indicator\u2019, is the simplest device without actuation. The user needs to do the whole PIVC operation, and this device only provides an indication of venipuncture by lighting up an LED. 5 2. SAID, short for \u2018Semi-Autonomous Intravenous access Device\u2019, integrates a motor to control the catheter insertion. The user is required to hold the device still and target it to a vein site. He/She then activates the device. The device inserts the catheter automatically and stops it when venipuncture is detected. 3. SDOP, short for \u2018Smart hand-held Device for Over-puncture Prevention\u2019, integrates a latch-based disengage mechanism to prevent over-puncture during PIVC. The user can keep the conventional way of operation and do the insertion manually. At the moment of venipuncture, the device automatically activates the disengage mechanism to stop further advancement of the catheter. 4. CathBot represents \u2018hand-held roBot for peripheral intravenous Catheterization\u2019. The device uses a crank-slider mechanism and a solenoid actuator to convert the complicated intravenous catheterization motion to a simple linear forward motion. The user just needs to push the device\u2019s handle forwards and the device completes the whole PIVC insertion procedure automatically. All the devices were characterized to ensure they can satisfy the design specifications. Then a series of comparative experiments were conducted to assess each of them. In the first experiment, 25 na\uefve subjects were invited to perform 10 trials of PIVC on a realistic baby arm phantom. The subjects were divided into 5 groups, and each group was asked to do the PIVC with one device only (SVEI, SAID, SDOP, CathBot and regular iv catheter). The experimental results show that all devices can provide the needed assistance to significantly facilitate and improve the success rates compared to the conventional method. People who have no experience of PIVC operation before can achieve considerably high success rates in robot-assisted PIVC (86% with SVEI, 80% with SAID, 78% with SDOP and 84% with CathBot) compared to the control group (12%) who used a regular iv catheter. Also, all 5 subjects using SVEI, 3 out of 5 subjects using SAID, 2 out of 5 subjects using SDOP and 4 out of 5 subjects using CathBot were able to successfully catheterize the baby arm phantom on their first attempt, while no subjects in the control group succeeded in their first attempts. Since SVEI showed the best results, it was selected for the second round of evaluation. In the second experiment, clinicians including both PIVC experts and general clinicians were invited to perform PIVC on a realistic baby arm phantom with 3 trials using SVEI and 3 trials in the conventional way. The results demonstrate that SVEI can bring great benefits to both specialists and general clinicians. The average success rates were found to be significantly improved from 48.3% to 71.7% when SVEI was used. The experimental results reveal that all experts achieved better or equal results with SVEI compared to the conventional method, and 9 out of 12 non-experts also had better or equal performance when SVEI was used. Finally, subjective feedback acquired through post-trial questionnaires showed that all devices were highly rated in terms of usability. Overall, the results of this doctoral research support continued investment in the technology to bring the handheld robotic devices closer to clinical us

Using Raman Spectroscopy for Intraoperative Margin Analysis in Breast Conserving Surgery

Breast Conserving Surgery (BCS) in the treatment of breast cancer aims to provide optimal oncological results, with minimal tissue excision to optimise cosmetic outcome. Positive margins due to an inadequate resection occurs in 17% of UK patients undergoing BCS and prompts recommendation for further tissue re-excision to reduce recurrence risk. A second operation causes patient anxiety and significant healthcare costs. This issue could be resolved with accurate intra-operative margin analysis (IMA) to enable excision of all cancerous tissue at the index procedure. High wavenumber Raman Spectroscopy (HWN RS) is a vibrational spectroscopy highly sensitive to changes in protein/lipid environment and water content –biochemical differences found between tumour and normal breast tissue. We proposed that HWN RS could be used to differentiate between tumour and non-tumour breast tissue with a view to future IMA. This thesis presents the development of a Raman system to measure the HWN region capable of accurately detecting changes in protein, lipid and water content, in the presence of highly fluorescent surgical pigments such as blue dye that are present in surgically excised specimens. We investigate the relationship between changes in the HWN spectra with changes in water content in constructed breast phantoms to mimic protein and lipid rich environments and biological tissue. Human breast tissue of paired tumour and non-tumour samples were then measured and analysed. We found that breast tumour tissue is a protein rich, high water, low fat environment and that non-tumour is a low protein, fat rich environment with a low water content, and this can be used to identify breast cancer using HWN RS with excellent accuracy of over 90%. This thesis demonstrates a HWN RS Raman system capable of differentiating between tumour and non-tumour tissue in human breast tissue, and this has the potential to provide IMA in BCS

Biosensors for Diagnosis and Monitoring

Biosensor technologies have received a great amount of interest in recent decades, and this has especially been the case in recent years due to the health alert caused by the COVID-19 pandemic. The sensor platform market has grown in recent decades, and the COVID-19 outbreak has led to an increase in the demand for home diagnostics and point-of-care systems. With the evolution of biosensor technology towards portable platforms with a lower cost on-site analysis and a rapid selective and sensitive response, a larger market has opened up for this technology. The evolution of biosensor systems has the opportunity to change classic analysis towards real-time and in situ detection systems, with platforms such as point-of-care and wearables as well as implantable sensors to decentralize chemical and biological analysis, thus reducing industrial and medical costs. This book is dedicated to all the research related to biosensor technologies. Reviews, perspective articles, and research articles in different biosensing areas such as wearable sensors, point-of-care platforms, and pathogen detection for biomedical applications as well as environmental monitoring will introduce the reader to these relevant topics. This book is aimed at scientists and professionals working in the field of biosensors and also provides essential knowledge for students who want to enter the field