A Survey on the Current Status and Future Challenges Towards Objective Skills Assessment in Endovascular Surgery

Minimally-invasive endovascular interventions have evolved rapidly over the past decade, facilitated by breakthroughs in medical imaging and sensing, instrumentation and most recently robotics. Catheter based operations are potentially safer and applicable to a wider patient population due to the reduced comorbidity. As a result endovascular surgery has become the preferred treatment option for conditions previously treated with open surgery and as such the number of patients undergoing endovascular interventions is increasing every year. This fact coupled with a proclivity for reduced working hours, results in a requirement for efficient training and assessment of new surgeons, that deviates from the “see one, do one, teach one” model introduced by William Halsted, so that trainees obtain operational expertise in a shorter period. Developing more objective assessment tools based on quantitative metrics is now a recognised need in interventional training and this manuscript reports the current literature for endovascular skills assessment and the associated emerging technologies. A systematic search was performed on PubMed (MEDLINE), Google Scholar, IEEXplore and known journals using the keywords, “endovascular surgery”, “surgical skills”, “endovascular skills”, “surgical training endovascular” and “catheter skills”. Focusing explicitly on endovascular surgical skills, we group related works into three categories based on the metrics used; structured scales and checklists, simulation-based and motion-based metrics. This review highlights the key findings in each category and also provides suggestions for new research opportunities towards fully objective and automated surgical assessment solutions

Exploration, design and application of simulation based technology in interventional cardiology

Medical education is undergoing a vast change from the traditional apprenticeship model to technology driven delivery of training to meet the demands of the new generation of doctors. With the reduction in the training hours of junior doctors, technology driven education can compensate for the time deficit in training. Each new technology arrives on a wave of great expectations; sometimes our expectations of true change are met and sometimes the new technology remains as a passing fashion only. The aim of the thesis is to explore, design and apply simulation based applications in interventional cardiology for educating the doctors and the public. Chapters 1and 2 present an overview of the current practice of education delivery and the evidence concerning simulation based education in interventional cardiology. Introduction of any new technology into an established system is often met with resistance. Hence Chapters 3 and 4 explore the attitudes and perceptions of consultants and trainees in cardiology towards the integration of a simulation based education into the cardiology curriculum. Chapters 5 and 6 present the “i-health project,” introduction of an electronic form for clinical information transfer from the ambulance crew to the hospital, enactment of case scenarios of myocardial infarction of varied levels of difficulty in a simulated environment and preliminary evaluation of the simulation. Chapter 7 focuses on educating the public in cardiovascular diseases and in coronary interventional procedures through simulation technology. Finally, Chapter 8 presents an overview of my findings, limitations and the future research that needs to be conducted which will enable the successful adoption of simulation based education into the cardiology curriculum.Open Acces

A systems approach to identifying patient safety problems in arterial surgery

In the face of the oft-quoted dictum ‘primum non nocere’, it is now widely recognised that a significant number of patients come to harm whilst in hospital. A large body of evidence demonstrates that half of all harm events are preventable and the operating theatre appears to be the most common site for adverse events to occur. For patients undergoing arterial intervention, technical expertise and risk-factor management are clearly important in achieving excellent outcomes. Recent research in vascular surgery has focussed on volume-outcome relationships and the impact of advancements in endovascular intervention. By contrast, there is a relative lack of research examining the extraordinarily complex system within which patients with arterial disease are treated. This thesis aims to develop a broad understanding of system failures and their relationship with patient safety and outcomes in arterial surgery in the British NHS. In section I (chapter 1 and 2) the systems approach is outlined and discussed and the rationale for adopting this approach in arterial surgery is provided. Section II consists of three exploratory studies: chapter 3 presents a systematic review of the literature examining the impact of system factors on safety in arterial surgery; chapter 4 reports a mixed-methods study exploring surgeons’ perceptions of the causes of adverse events in arterial surgery; and chapter 5 presents a multi-centre study of safety culture in vascular operating departments in England. Section III provides an account of the LEAP study: a multi-centre study of system failures occurring during aortic intervention. The methods and main findings of the LEAP study are presented in chapters 6 and 7. Chapter 8 reports on the determinants of intraoperative system failures and the relationship between intraoperative failure and patient outcome. Chapter 9 summarises the main findings and limitations of this thesis, and discusses recommendations for practice and future research.Open Acces

Quality-dependent Deep Learning for Safe Autonomous Guidewire Navigation

Cardiovascular diseases are the main cause ofdeath worldwide. State-of-the-art treatment often includes theprocess of navigating endovascular instruments through thevasculature. Automation of the procedure receives much at-tention lately and may increase treatment quality and unburdenclinicians. However, in order to ensure the patient’s safety theendovascular device needs to be steered carefully through thebody. In this work, we present a collection of medical criteriathat are considered by physicians during an intervention andthat can be evaluated automatically enabling a highly objectiveassessment. Additionally, we trained an autonomous controllerwith deep reinforcement learning to gently navigate within a2D simulation of an aortic arch. Among others, the controllerreduced the maximum and mean contact force applied to thevessel walls by 43% and 29%, respectively

Surgical Subtask Automation for Intraluminal Procedures using Deep Reinforcement Learning

Intraluminal procedures have opened up a new sub-field of minimally invasive surgery that use flexible instruments to navigate through complex luminal structures of the body, resulting in reduced invasiveness and improved patient benefits. One of the major challenges in this field is the accurate and precise control of the instrument inside the human body. Robotics has emerged as a promising solution to this problem. However, to achieve successful robotic intraluminal interventions, the control of the instrument needs to be automated to a large extent. The thesis first examines the state-of-the-art in intraluminal surgical robotics and identifies the key challenges in this field, which include the need for safe and effective tool manipulation, and the ability to adapt to unexpected changes in the luminal environment. To address these challenges, the thesis proposes several levels of autonomy that enable the robotic system to perform individual subtasks autonomously, while still allowing the surgeon to retain overall control of the procedure. The approach facilitates the development of specialized algorithms such as Deep Reinforcement Learning (DRL) for subtasks like navigation and tissue manipulation to produce robust surgical gestures. Additionally, the thesis proposes a safety framework that provides formal guarantees to prevent risky actions. The presented approaches are evaluated through a series of experiments using simulation and robotic platforms. The experiments demonstrate that subtask automation can improve the accuracy and efficiency of tool positioning and tissue manipulation, while also reducing the cognitive load on the surgeon. The results of this research have the potential to improve the reliability and safety of intraluminal surgical interventions, ultimately leading to better outcomes for patients and surgeons

Development and Pilot of a Patient Reported Outcome Measure for Proximal Thoracic Aortic Aneurysms

Background: Disease specific questionnaires are increasingly being used to evaluate treatment outcomes from the perspective of patients. There are currently no validated questionnaires that measure patient reported outcomes after proximal thoracic aortic aneurysm surgery. Objectives: To develop and pilot a newly formulated patient focussed questionnaire that measures the patient’s health status and health related quality of life before and after proximal thoracic aortic aneurysm surgery. Methods: Based on a literature review, a thematic analysis of audio recorded patient interviews and expert clinical testimony, a pool of items was generated to form a new questionnaire instrument. Suitable patients who were scheduled for elective aortic surgery at Liverpool Heart and Chest Hospital were identified and invited to participate in the pilot study. Patients were asked to complete the questionnaire prior to surgery and then at 6 weeks and 3 months after their operation. The newly developed instrument underwent preliminary testing for its appropriateness, acceptability, feasibility, interpretability, precision, reliability and responsiveness. Results: Several items from the CROQ (Coronary Revascularisation Outcomes Questionnaire) formed the basis of the instrument, with the addition of 10 items derived from a newly formulated conceptual model of proximal thoracic aortic disease. The items were arranged into four domains (symptoms, physical, psychosocial and cognitive). Initial testing showed that the newly developed instrument performed to acceptable standards. It showed good internal consistency (Cronbach’s alpha results for all domains >0.85), and test retest reliability (intraclass correlation coefficient for all domains >0.85). In paired sample tests, the values in each domain led to statistically significant differences from baseline at either 6 weeks or 3 months (p<0.05), supporting the construct validity and responsiveness of the instrument. Conclusions: The new instrument demonstrated satisfactory validity as well as good internal reliability and test retest reliability for each item across all four domains. The initial findings suggest that the measure is sensitive and responsive to the effects of surgical treatment for proximal thoracic aortic aneurysms

Assessment of surgical performance

Surgical patient outcomes are related to technical and non-technical skills of the surgeon. Trauma patient operative and management experience has declined since trainee duty-hour restrictions were mandated in 2003 resulting in less experience in technical surgical skills. The Advanced Surgical Skills for Exposure in Trauma (ASSET) cadaver-based course, teaching vascular exposure and haemorrhage control, was developed to fill this training gap. The aim of this Thesis is to develop surgeon performance metrics and to test surgeons before and after taking the ASSET course to determine whether such training improves performance of peripheral vascular control. The importance of training in surgical vascular control in both civilian and military practice, and a description of current surgical training for trauma are described in Chapter 1. Reviews of existing trauma training courses and surgical performance metrics are provided in Chapters 2 and 3, and show limited testing of training courses and lack of trauma surgical performance metrics. Data collection methods, evaluator training and analysis are described in Chapter 4. Chapter 5 evaluates self-confidence of surgeons performing the vascular control procedures in cadavers compared to the performance evaluated by trained evaluators. Preliminary validation of vascular-control performance metrics and testing of a standardized script with item analysis and inter-rater reliability are discussed in Chapter 6. Testing 40 surgeons performing 3 extremity vascular control procedures before and after training is reported in Chapter 7. ASSET training improves performance, but large performance variability, repeated errors and no improvements were found in some surgeons. Chapter 8 reports how blind video analysis checklist, global rating metrics, error occurrence and recovery show convergent validity with co-located evaluators. Chapter 9 identifies the key findings and implications, innovation of the work described in the Thesis and concludes with the potential impact on military readiness and my personal reflection on what I learnt.  Open Acces

Computer Vision in the Surgical Operating Room

Background: Multiple types of surgical cameras are used in modern surgical practice and provide a rich visual signal that is used by surgeons to visualize the clinical site and make clinical decisions. This signal can also be used by artificial intelligence (AI) methods to provide support in identifying instruments, structures, or activities both in real-time during procedures and postoperatively for analytics and understanding of surgical processes. Summary: In this paper, we provide a succinct perspective on the use of AI and especially computer vision to power solutions for the surgical operating room (OR). The synergy between data availability and technical advances in computational power and AI methodology has led to rapid developments in the field and promising advances. Key Messages: With the increasing availability of surgical video sources and the convergence of technologiesaround video storage, processing, and understanding, we believe clinical solutions and products leveraging vision are going to become an important component of modern surgical capabilities. However, both technical and clinical challenges remain to be overcome to efficiently make use of vision-based approaches into the clinic