25th International Congress of the European Association for Endoscopic Surgery (EAES) Frankfurt, Germany, 14-17 June 2017 : Oral Presentations

Introduction: Ouyang has recently proposed hiatal surface area (HSA) calculation by multiplanar multislice computer tomography (MDCT) scan as a useful tool for planning treatment of hiatus defects with hiatal hernia (HH), with or without gastroesophageal reflux (MRGE). Preoperative upper endoscopy or barium swallow cannot predict the HSA and pillars conditions. Aim to asses the efficacy of MDCT’s calculation of HSA for planning the best approach for the hiatal defects treatment. Methods: We retrospectively analyzed 25 patients, candidates to laparoscopic antireflux surgery as primary surgery or hiatus repair concomitant with or after bariatric surgery. Patients were analyzed preoperatively and after one-year follow-up by MDCT scan measurement of esophageal hiatus surface. Five normal patients were enrolled as control group. The HSA’s intraoperative calculation was performed after complete dissection of the area considered a triangle. Postoperative CT-scan was done after 12 months or any time reflux symptoms appeared. Results: (1) Mean HSA in control patients with no HH, no MRGE was cm2 and similar in non-complicated patients with previous LSG and cruroplasty. (2) Mean HSA in patients candidates to cruroplasty was 7.40 cm2. (3) Mean HSA in patients candidates to redo cruroplasty for recurrence was 10.11 cm2. Discussion. MDCT scan offer the possibility to obtain an objective measurement of the HSA and the correlation with endoscopic findings and symptoms. The preoperative information allow to discuss with patients the proper technique when a HSA[5 cm2 is detected. During the follow-up a correlation between symptoms and failure of cruroplasty can be assessed. Conclusions: MDCT scan seems to be an effective non-invasive method to plan hiatal defect treatment and to check during the follow-up the potential recurrence. Future research should correlate in larger series imaging data with intraoperative findings

Ultrasound-based assessment and management of postmenopausal bleeding and endometrial polyps

This thesis has evaluated aspects of ultrasound-based assessment and management of women with postmenopausal bleeding and endometrial polyps. The efficacy of transrectal ultrasound scan (TRS) was assessed in 103 consecutive postmenopausal women with an axial uterus. TRS was accepted by two-thirds of the women and the proportion of satisfactory endometrial assessments was significantly higher on TRS compared to transvaginal scan (TVS), 91% (95% CI 84-98) vs 62% (95% CI 50-74), respectively. In the subgroup of 50 women with postmenopausal bleeding and an axial uterus, the endometrial thickness measured significantly thinner on TRS by a median of 1.2mm (IQR 0.4-3) compared to TVS. Furthermore, subjective pattern recognition for endometrial cancer was less accurate on TVS compared to TRS when the uterus is in an axial position. The interrater reliability of ultrasound subjective pattern recognition for endometrial cancer was prospectively assessed in 40 women with postmenopausal bleeding and a thickened endometrium (≥4.5mm); a good level of agreement (κ = 0.78, 95% CI 0.61-0.95) was found between an expert and an average operator. The diagnostic accuracy of ultrasound subjective pattern recognition for endometrial cancer was assessed in 240 consecutive women with postmenopausal bleeding and a thickened endometrium (≥4.5mm) and available histology. It performed well with a sensitivity and specificity of 88% (95% CI 77-95) and 97% (95% CI 94-99), respectively. The presence of focal malignancy within endometrial polyps was the most common cause of a false-negative diagnosis of endometrial cancer. Endometrial cancer was diagnosed on ultrasound by subjective pattern recognition and simultaneously assessed for the presence of deep myometrial invasion and cervical stromal invasion in 51 women. We found that the accuracy of ultrasound in the preoperative staging of endometrial cancer was comparable to MRI (sensitivity and specificity, 86% vs 77% and 66% vs 76%, respectively). A clinical model was presented to estimate the risk (low, intermediate, or high) of pre-malignancy or malignancy in postmenopausal endometrial polyps. The model included polyp size, the presence or absence of intralesional cystic spaces and the patient’s BMI as clinical variables. Accordingly, approximately one-third of postmenopausal polyps would be categorised as high- or intermediate-risk and they would account for over 90% of all premalignant/malignant polyps, while the remaining polyps would be categorised as low-risk with a 1/18 risk of pre-malignancy or malignancy. The overall accuracy of the model in predicting premalignant or malignant postmenopausal polyps was 92% (95% CI 86.0-97.4). The natural history of expectantly managed endometrial polyps was assessed retrospectively in 112 polyps over a median follow-up of 22.5 months (range 6-136). We found that polyps’ growth rates varied, and it was not possible to predict an individual polyp’s growth based on the patient’s clinical characteristics or polyp’s morphological features. Polyp’s growth rate was not associated with the risk of developing abnormal uterine bleeding (AUB). Some polyps underwent spontaneous regression (7/112, 6%) and this occurred more frequently among premenopausal women and those who were symptomatic of AUB

Microscope Embedded Neurosurgical Training and Intraoperative System

In the recent years, neurosurgery has been strongly influenced by new technologies. Computer Aided Surgery (CAS) offers several benefits for patients\u27 safety but fine techniques targeted to obtain minimally invasive and traumatic treatments are required, since intra-operative false movements can be devastating, resulting in patients deaths. The precision of the surgical gesture is related both to accuracy of the available technological instruments and surgeon\u27s experience. In this frame, medical training is particularly important. From a technological point of view, the use of Virtual Reality (VR) for surgeon training and Augmented Reality (AR) for intra-operative treatments offer the best results. In addition, traditional techniques for training in surgery include the use of animals, phantoms and cadavers. The main limitation of these approaches is that live tissue has different properties from dead tissue and that animal anatomy is significantly different from the human. From the medical point of view, Low-Grade Gliomas (LGGs) are intrinsic brain tumours that typically occur in younger adults. The objective of related treatment is to remove as much of the tumour as possible while minimizing damage to the healthy brain. Pathological tissue may closely resemble normal brain parenchyma when looked at through the neurosurgical microscope. The tactile appreciation of the different consistency of the tumour compared to normal brain requires considerable experience on the part of the neurosurgeon and it is a vital point. The first part of this PhD thesis presents a system for realistic simulation (visual and haptic) of the spatula palpation of the LGG. This is the first prototype of a training system using VR, haptics and a real microscope for neurosurgery. This architecture can be also adapted for intra-operative purposes. In this instance, a surgeon needs the basic setup for the Image Guided Therapy (IGT) interventions: microscope, monitors and navigated surgical instruments. The same virtual environment can be AR rendered onto the microscope optics. The objective is to enhance the surgeon\u27s ability for a better intra-operative orientation by giving him a three-dimensional view and other information necessary for a safe navigation inside the patient. The last considerations have served as motivation for the second part of this work which has been devoted to improving a prototype of an AR stereoscopic microscope for neurosurgical interventions, developed in our institute in a previous work. A completely new software has been developed in order to reuse the microscope hardware, enhancing both rendering performances and usability. Since both AR and VR share the same platform, the system can be referred to as Mixed Reality System for neurosurgery. All the components are open source or at least based on a GPL license

Real-time hybrid cutting with dynamic fluid visualization for virtual surgery

It is widely accepted that a reform in medical teaching must be made to meet today's high volume training requirements. Virtual simulation offers a potential method of providing such trainings and some current medical training simulations integrate haptic and visual feedback to enhance procedure learning. The purpose of this project is to explore the capability of Virtual Reality (VR) technology to develop a training simulator for surgical cutting and bleeding in a general surgery

Patient Specific Systems for Computer Assisted Robotic Surgery Simulation, Planning, and Navigation

The evolving scenario of surgery: starting from modern surgery, to the birth of medical imaging and the introduction of minimally invasive techniques, has seen in these last years the advent of surgical robotics. These systems, making possible to get through the difficulties of endoscopic surgery, allow an improved surgical performance and a better quality of the intervention. Information technology contributed to this evolution since the beginning of the digital revolution: providing innovative medical imaging devices and computer assisted surgical systems. Afterwards, the progresses in computer graphics brought innovative visualization modalities for medical datasets, and later the birth virtual reality has paved the way for virtual surgery. Although many surgical simulators already exist, there are no patient specific solutions. This thesis presents the development of patient specific software systems for preoperative planning, simulation and intraoperative assistance, designed for robotic surgery: in particular for bimanual robots that are becoming the future of single port interventions. The first software application is a virtual reality simulator for this kind of surgical robots. The system has been designed to validate the initial port placement and the operative workspace for the potential application of this surgical device. Given a bimanual robot with its own geometry and kinematics, and a patient specific 3D virtual anatomy, the surgical simulator allows the surgeon to choose the optimal positioning of the robot and the access port in the abdominal wall. Additionally, it makes possible to evaluate in a virtual environment if a dexterous movability of the robot is achievable, avoiding unwanted collisions with the surrounding anatomy to prevent potential damages in the real surgical procedure. Even if the software has been designed for a specific bimanual surgical robot, it supports any open kinematic chain structure: as far as it can be described in our custom format. The robot capabilities to accomplish specific tasks can be virtually tested using the deformable models: interacting directly with the target virtual organs, trying to avoid unwanted collisions with the surrounding anatomy not involved in the intervention. Moreover, the surgical simulator has been enhanced with algorithms and data structures to integrate biomechanical parameters into virtual deformable models (based on mass-spring-damper network) of target solid organs, in order to properly reproduce the physical behaviour of the patient anatomy during the interactions. The main biomechanical parameters (Young's modulus and density) have been integrated, allowing the automatic tuning of some model network elements, such as: the node mass and the spring stiffness. The spring damping coefficient has been modeled using the Rayleigh approach. Furthermore, the developed method automatically detect the external layer, allowing the usage of both the surface and internal Young's moduli, in order to model the main parts of dense organs: the stroma and the parenchyma. Finally the model can be manually tuned to represent lesion with specific biomechanical properties. Additionally, some software modules of the simulator have been properly extended to be integrated in a patient specific computer guidance system for intraoperative navigation and assistance in robotic single port interventions. This application provides guidance functionalities working in three different modalities: passive as a surgical navigator, assistive as a guide for the single port placement and active as a tutor preventing unwanted collision during the intervention. The simulation system has beed tested by five surgeons: simulating the robot access port placemen, and evaluating the robot movability and workspace inside the patient abdomen. The tested functionalities, rated by expert surgeons, have shown good quality and performance of the simulation. Moreover, the integration of biomechanical parameters into deformable models has beed tested with various material samples. The results have shown a good visual realism ensuring the performance required by an interactive simulation. Finally, the intraoperative navigator has been tested performing a cholecystectomy on a synthetic patient mannequin, in order to evaluate: the intraoperative navigation accuracy, the network communications latency and the overall usability of the system. The tests performed demonstrated the effectiveness and the usability of the software systems developed: encouraging the introduction of the proposed solution in the clinical practice, and the implementation of further improvements. Surgical robotics will be enhanced by an advanced integration of medical images into software systems: allowing the detailed planning of surgical interventions by means of virtual surgery simulation based on patient specific biomechanical parameters. Furthermore, the advanced functionalities offered by these systems, enable surgical robots to improve the intraoperative surgical assistance: benefitting of the knowledge of the virtual patient anatomy

Activity profiling for minimally invasive surgery

Imperial Users onl

Surgical spectral imaging

Recent technological developments have resulted in the availability of miniaturised spectral imaging sensors capable of operating in the multi- (MSI) and hyperspectral imaging (HSI) regimes. Simultaneous advances in image-processing techniques and artificial intelligence (AI), especially in machine learning and deep learning, have made these data-rich modalities highly attractive as a means of extracting biological information non-destructively. Surgery in particular is poised to benefit from this, as spectrally-resolved tissue optical properties can offer enhanced contrast as well as diagnostic and guidance information during interventions. This is particularly relevant for procedures where inherent contrast is low under standard white light visualisation. This review summarises recent work in surgical spectral imaging (SSI) techniques, taken from Pubmed, Google Scholar and arXiv searches spanning the period 2013–2019. New hardware, optimised for use in both open and minimally-invasive surgery (MIS), is described, and recent commercial activity is summarised. Computational approaches to extract spectral information from conventional colour images are reviewed, as tip-mounted cameras become more commonplace in MIS. Model-based and machine learning methods of data analysis are discussed in addition to simulation, phantom and clinical validation experiments. A wide variety of surgical pilot studies are reported but it is apparent that further work is needed to quantify the clinical value of MSI/HSI. The current trend toward data-driven analysis emphasises the importance of widely-available, standardised spectral imaging datasets, which will aid understanding of variability across organs and patients, and drive clinical translation

Competency Based Assessment Using Virtual Reality (VERT): Is It a Realistic Possibility ?

The education of the radiography profession is based within higher education establishments, yet a critical part of all radiography programmes is the clinical component where students learn the practical skills of the profession. Assessments therefore not only have to assess a student’s knowledge, but also their clinical competence and core skills in line with both Health and Care Professions Council and the Society and College of Radiographers requirements. This timely thesis examines the possibility of using the Virtual Environment for RadioTherapy (VERT) as an assessment tool to evaluate a student’s competence so giving the advantage of a standard assessment and relieving time pressures in the clinical department. A mixed methods approach was taken which can be described as a Quantitative Qualitative design with the emphasis being on the Quantitative element; a so called QUAN qual design. The quantitative evaluation compared two simulations, one in the virtual reality environment and another in the department using a real treatment machine. Students were asked to perform two electron setups in each simulation; the order being randomly decided and so the study would be described as a randomised cross-over design. Following this, qualitative data was collected in student focus groups to explore student perspectives in more depth. Findings indicated that the performance between the two simulators was significantly different, p < 0∙001; the virtual simulation scoring significantly lower than the hospital based simulation overall and in virtually all parameters being assessed. Thematic analysis of the qualitative data supported this finding and identified 4 main themes; equipment use, a lack of reality, learning opportunities and assessment of competence. One other sub-theme identified for reality was that of the environment and senses