Organ Shape Sensing using Pneumatically Attachable Flexible Rails in Robotic-Assisted Laparoscopic Surgery

In robotic-assisted partial nephrectomy, surgeons remove a part of a kidney often due to the presence of a mass. A drop-in ultrasound probe paired to a surgical robot is deployed to execute multiple swipes over the kidney surface to localise the mass and define the margins of resection. This sub-task is challenging and must be performed by a highly skilled surgeon. Automating this sub-task may reduce cognitive load for the surgeon and improve patient outcomes. The overall goal of this work is to autonomously move the ultrasound probe on the surface of the kidney taking advantage of the use of the Pneumatically Attachable Flexible (PAF) rail system, a soft robotic device used for organ scanning and repositioning. First, we integrate a shape-sensing optical fibre into the PAF rail system to evaluate the curvature of target organs in robotic-assisted laparoscopic surgery. Then, we investigate the impact of the stiffness of the material of the PAF rail on the curvature sensing accuracy, considering that soft targets are present in the surgical field. Finally, we use shape sensing to plan the trajectory of the da Vinci surgical robot paired with a drop-in ultrasound probe and autonomously generate an Ultrasound scan of a kidney phantom.Comment: 9 pages, 11 figure

Track-Guided Ultrasound Scanning for Tumour Margins Outlining in Robot-Assisted Partial Nephrectomy

Robot-Assisted Partial Nephrectomy (RAPN) is a medical procedure in which part of a kidney is removed, typically because of the presence of a tumour. RAPN is the second most diffused robotically assisted surgical procedure worldwide after prostatectomy [1]. The advantages of this robot-assisted procedure are detailed in [2], and in [3] it is argued that RAPN can be used in place of open surgery or total nephrectomy in some complex renal tumour cases. The RAPN procedure is thoroughly described in [4]. Methods used for the identification of the tumour include pre-operative Computer Tomography (CT) scans, Magnetic Resonance (MR) imaging and intraoperative Ultrasound (US) scans. The use of drop-in US probes for RAPN procedures is widely recognized as the golden standard for the intraoperative detection and margins outlining of the mass targeted. In [5] the authors show that the use of US dropin probes guided by robotic laparoscopic tools rather than standard laparoscopic tool is beneficial for the surgeon as it significantly increases the dexterity, hence, the field of view of the system

Pneumatically Attachable Flexible Rails for Track-Guided Ultrasound Scanning in Robotic-Assisted Partial Nephrectomy - A Preliminary Design Study

Robotic-assisted partial nephrectomy is a surgical operation in which part of a kidney is removed typically because of the presence of a mass. Pre-operative and intraoperative imaging techniques are used to identify and outline the target mass, thus the margins of the resection area on the kidney surface. Drop-in ultrasound probes are used to acquire intraoperative images: the probe is inserted through a trocar port, grasped with a robotic-assisted laparoscopic gripper and swiped on the kidney surface. Multiple swipes are performed to define the resection area. This is marked swipe by swipe using an electrocautery tool. During this procedure the probe often requires repositioning because of slippage from the target organ surface. Furthermore, the localization can be inaccurate when the target mass is in locations particularly hard to reach, and thus kidney repositioning could be required. A highly skilled surgeon is typically required to successfully perform this pre-operatory procedure. We propose a novel approach for the navigation of drop-in ultrasound probes: the use of pneumatically attachable flexible rails to enable swift, effortless, and accurate track-guided scanning of the kidney. The proposed system attaches on the kidney side surface with the use of a series of bio-inspired vacuum suckers. In this letter, the design of the proposed system and its use in robotic-assisted partial nephrectomy are presented for the first time

Rollout Sampling Approximate Policy Iteration

Several researchers have recently investigated the connection between reinforcement learning and classification. We are motivated by proposals of approximate policy iteration schemes without value functions which focus on policy representation using classifiers and address policy learning as a supervised learning problem. This paper proposes variants of an improved policy iteration scheme which addresses the core sampling problem in evaluating a policy through simulation as a multi-armed bandit machine. The resulting algorithm offers comparable performance to the previous algorithm achieved, however, with significantly less computational effort. An order of magnitude improvement is demonstrated experimentally in two standard reinforcement learning domains: inverted pendulum and mountain-car.Comment: 18 pages, 2 figures, to appear in Machine Learning 72(3). Presented at EWRL08, to be presented at ECML 200

Synergistic user ↔ context analytics

Various flavours of a new research field on (socio-)physical or personal analytics have emerged, with the goal of deriving semanticallyrich insights from people’s low-level physical sensing combined with their (online) social interactions. In this paper, we argue for more comprehensive data sources, including environmental and application-specific data, to better capture the interactions between users and their context, in addition to those among users. We provide some example use cases and present our ongoing work towards a synergistic analytics platform: a testbed based on mobile crowdsensing and IoT, a data model for representing the different sources of data and their connections, and a prediction engine for analyzing the data and producing insights

Androgens and the breast

Androgens have important physiological effects in women while at the same time they may be implicated in breast cancer pathologies. However, data on the effects of androgens on mammary epithelial proliferation and/or breast cancer incidence are not in full agreement. We performed a literature review evaluating current clinical, genetic and epidemiological data regarding the role of androgens in mammary growth and neoplasia. Epidemiological studies appear to have significant methodological limitations and thus provide inconclusive results. The study of molecular defects involving androgenic pathways in breast cancer is still in its infancy. Clinical and nonhuman primate studies suggest that androgens inhibit mammary epithelial proliferation and breast growth while conventional estrogen treatment suppresses endogenous androgens. Abundant clinical evidence suggests that androgens normally inhibit mammary epithelial proliferation and breast growth. Suppression of androgens using conventional estrogen treatment may thus enhance estrogenic breast stimulation and possibly breast cancer risk. Addition of testosterone to the usual hormone therapy regimen may diminish the estrogen/progestin increase in breast cancer risk but the impact of this combined use on mammary gland homeostasis still needs evaluation

Electrochemical integration of graphene with light absorbing copper-based thin films

We present an electrochemical route for the integration of graphene with light sensitive copper-based alloys used in optoelectronic applications. Graphene grown using chemical vapor deposition (CVD) transferred to glass is found to be a robust substrate on which photoconductive Cu_{x}S films of 1-2 um thickness can be deposited. The effect of growth parameters on the morphology and photoconductivity of Cu_{x}S films is presented. Current-voltage characterization and photoconductivity decay experiments are performed with graphene as one contact and silver epoxy as the other

Organ curvature sensing using pneumatically attachable flexible rails in robotic-assisted laparoscopic surgery

In robotic-assisted partial nephrectomy, surgeons remove a part of a kidney often due to the presence of a mass. A drop-in ultrasound probe paired to a surgical robot is deployed to execute multiple swipes over the kidney surface to localise the mass and define the margins of resection. This sub-task is challenging and must be performed by a highly-skilled surgeon. Automating this sub-task may reduce cognitive load for the surgeon and improve patient outcomes. The eventual goal of this work is to autonomously move the ultrasound probe on the surface of the kidney taking advantage of the use of the Pneumatically Attachable Flexible (PAF) rail system, a soft robotic device used for organ scanning and repositioning. First, we integrate a shape-sensing optical fibre into the PAF rail system to evaluate the curvature of target organs in robotic-assisted laparoscopic surgery. Then, we investigate the impact of the PAF rail’s material stiffness on the curvature sensing accuracy, considering that soft targets are present in the surgical field. We found overall curvature sensing accuracy to be between 1.44% and 7.27% over the range of curvatures present in adult kidneys. Finally, we use shape sensing to plan the trajectory of the da Vinci surgical robot paired with a drop-in ultrasound probe and autonomously generate an Ultrasound scan of a kidney phantom

Age at first childbirth and oral contraceptive use are associated with risk of androgen receptor-negative breast cancer: the Malmö Diet and Cancer Cohort.

Risk factors for breast cancer vary according to breast cancer subtype. This study analyzes the impact of potential risk factors in breast cancer by androgen receptor (AR) status