Accurate needle placement in deep-seated liver tumours can be difficult. In this work, we disclose two new manually controlled steerable needles for 17G radio-frequency ablation probe placement. The needles contain stylets with embedded compliant joints for active tip articulations, and concentric tubes for (curved-path) guidance. Needle steering was evaluated sequentially by intended users and in intended-use tissue types. Six interventional radiologists evaluated the needle in repeated ultrasound-guided steering tasks in liver-mimicking phantoms. Targets were located at a 100 mm depth and 20 mm lateral offset from the initial insertion line. The resulting mean absolute tip placement error was 1.0 ± 1.0 mm. Subsequently, steering-induced tissue damage was evaluated in fresh cirrhotic human liver explants. The surface area of puncture holes was estimated in scanned histology slides, using a connected-components analysis. The mean surface area was 0.26 ± 0.16 mm² after steering with a median radius of curvature of 0.7 × 10³ mm, versus 0.35 ± 0.15 mm² after straight-path insertions with the steerable needle and 0.15 ± 0.09 mm² after straight-path RFA probe insertions. The steering mechanisms proposed enable clinically relevant path corrections for 17G needles. Radiologists were quickly adept in curved-path RFA probe placement and the evaluation of histological tissue damage demonstrated a potentially safe use during liver interventions.

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In this dissertation, we analyse the safe use of medical technology, considering the training of users, technical demands of used devices and instruments, and the surgical workflow. As each of these elements will vary depending on the experience of the user, the equipment used, and variations in the environment; a unique set of parameters for safe use emerges: a ‘safe surgical signature’. The aim of this thesis is to objectively measure safe application of medical technology in the Operating Room (OR), considering the three main pillars linked to the user, the devices, and environment. All three pillars need to be addressed, present and lined up, to reach its final goal; safe use.@en

Background: Surgical Process Modelling (SPM) offers the possibility to automatically gain insight in the surgical workflow, with the potential to improve OR logistics and surgical care. Most studies have focussed on phase recognition modelling of the laparoscopic cholecystectomy, because of its standard and frequent execution. To demonstrate the broad applicability of SPM, more diverse and complex procedures need to be studied. The aim of this study is to investigate the accuracy in which we can recognise and extract surgical phases in laparoscopic hysterectomies (LHs) with inherent variability in procedure time. To show the applicability of the approach, the model was used to automatically predict surgical end-times. Methods: A dataset of 40 video-recorded LHs was manually annotated for instrument use and divided into ten surgical phases. The use of instruments provided the feature input for building a Random Forest surgical phase recognition model that was trained to automatically recognise surgical phases. Tenfold cross-validation was performed to optimise the model for predicting the surgical end-time throughout the procedure. Results: Average surgery time is 128 ± 27 min. Large variability within specific phases is seen. Overall, the Random Forest model reaches an accuracy of 77% recognising the current phase in the procedure. Six of the phases are predicted accurately over 80% of their duration. When predicting the surgical end-time, on average an error of 16 ± 13 min is reached throughout the procedure. Conclusions: This study demonstrates an intra-operative approach to recognise surgical phases in 40 laparoscopic hysterectomy cases based on instrument usage data. The model is capable of automatic detection of surgical phases for generation of a solid prediction of the surgical end-time.

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Introduction: Electrosurgery is used in 80% of surgical procedures. The technique allows surgeons to skilfully dissect tissues and achieve haemostasis. Since improper use of electrosurgery can lead to serious adverse events, training is required to potentially reduce the number and severity of these events. In this study we evaluate education and training in electrosurgery for surgical residents. Material and methods: Residents from six surgical subspecialties in the Netherlands were invited to anonymously complete a digital questionnaire about training, supervision and adverse events regarding electrosurgery. Results: Of the 197 respondents, 69% had received some form of training; mostly a single theoretical lecture. The feeling of competence in theory and practical skills was positively rated by 39% and 71%, respectively. Moreover, 35% judged the theoretical knowledge of their supervisors as insufficient and 65% changed their electrosurgical application technique to the preference of the supervisor. 30% of the residents had encountered a serious adverse event (e.g., burn wounds) related to the application of electrosurgery. Conclusions: The training of residents in theoretical aspects of electrosurgery is limited. Residents are not satisfied with the acquired theoretical knowledge of themselves and of their supervisors. Since adverse events related to electrosurgery occur frequently, more extensive education for both residents and their supervisors is needed to enhance patient safety@en

The benefits of electrosurgery have been acknowledged since the early 1920s, and nowadays more than 80% of surgical procedures involve devices that apply energy to tissues. Despite its widespread use, it is currently unknown how the operator's choices with regard to instrument selection and application technique are related to complications. As such, the manner in which electrosurgery is applied can have a serious influence on the outcome of the procedure and the well-being of patients. The aim of this study is to investigate the variety of differences in usage of electrosurgical devices. Our approach is to measure these parameters to provide insight into application techniques. A sensor was developed that records the magnitude of electric current delivered to an electrosurgical device at a frequency of 10 Hz. The sensor is able to detect device activation times and a reliable estimate of the power-level settings. Data were recorded for 91 laparoscopic cholecystectomies performed by different surgeons and residents. Results of the current measurement data show differences in the way electrosurgery is applied by surgeons and residents during a laparoscopic cholecystectomy. Variations are seen in the number of activations, the activation time, and the approach for removal of the gallbladder. Analysis showed that experienced surgeons have a longer activation time than residents (3.01 vs 1.41 seconds, P <.001) and a lower number of activations (102 vs 123). This method offers the opportunity to relate application techniques to clinical outcome and to provide input for the development of a best practice model.

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More and more medical technology is finding its way to the operating room, which is a great benefit for efficiency and patient safety. However, it may also cause disturbances in the workflow. Living labs and Test Beds such as a Research Operating Room can provide a real-life setting in which safe implementation/ research in the field of work processes and protocols can be studied. In this paper, we discuss the added value of such a Living Lab, illustrated by two cases@en

The unavailability of the required surgical instruments at the start of a procedure is undesirable. It causes delays and stress in the operating room (OR), which can lead to additional risks for the patients. Issues with availability of surgical instruments may become visible just before the start of the procedure but are induced earlier in the delivery process. Therefore, efficient and safe supply chain management is essential. Just in time ( JIT) is a concept widely applied in industrial sectors to improve efficiency and quality. The aim of this study is to design a JIT process for the delivery of surgical instruments and to assess the potential risks. The JIT delivery process of surgical instruments was designed for a Dutch hospital working with an external Central Sterile Supply Department (CSSD). Hazards (ie, sources of potential adverse events) were identified according to the Healthcare Failure Mode and Effects Analysis (HFMEA) methodology. The risks of applying JIT principles to the delivery of surgical instruments were compared to the risks involved with the current situation of the hospital at the time of this study (supply-driven delivery). The results showed that the total (high-)risk score of the JIT situation was similar to that of the current situation, although the number of (high-risk) hazards was slightly higher. However, almost half of the hazards were ‘controlled’ (when actions to remove the hazard were taken later in the process), in contrast to the current situation in which only about 10% of the (high-risk) hazards were ‘controlled’. The JIT delivery of surgical instruments is expected to present less risks compared to the current situation. The multiple requirements for information technology support and a higher level of trust between the CSSD and OR department should be taken into account in order to improve the supply chain management of surgical instruments.@en

Operating Room (OR) scheduling is crucial to allow efficient use of ORs. Currently, the predicted durations of surgical procedures are unreliable and the OR schedulers have to follow the progress of the procedures in order to update the daily planning accordingly. The OR schedulers often acquire the needed information through verbal communication with the OR staff, which causes undesired interruptions of the surgical process. The aim of this study was to develop a system that predicts in real-time the remaining procedure duration and to test this prediction system for reliability and usability in an OR. The prediction system was based on the activation pattern of one single piece of equipment, the electrosurgical device. The prediction system was tested during 21 laparoscopic cholecystectomies, in which the activation of the electrosurgical device was recorded and processed in real-time using pattern recognition methods. The remaining surgical procedure duration was estimated and the optimal timing to prepare the next patient for surgery was communicated to the OR staff. The mean absolute error was smaller for the prediction system (14 min) than for the OR staff (19 min). The OR staff doubted whether the prediction system could take all relevant factors into account but were positive about its potential to shorten waiting times for patients. The prediction system is a promising tool to automatically and objectively predict the remaining procedure duration, and thereby achieve optimal OR scheduling and streamline the patient flow from the nursing department to the OR.@en

Efficiency in the Operating Room (OR) is a topic of growing interest. Planning of care is a crucial element to ensure optimal use of the ORs. Currently, OR scheduling is considered as a complex task based on predictions of surgery duration. The latter are often based on average times, but turn out to be inaccurate in practice because of various factors (such as complexity, patient's characteristics, unexpected events, etc). The aim of this study is to develop a prediction system that estimates in real-time the remaining duration of a surgical procedure. The prediction system was based on monitoring the progress of a procedure by recording the activation of a single piece of equipment in the OR, the electrosurgical device. Support Vector Machines was then used as a classifier to predict the remaining surgical procedure duration and thereby the optimal timing to start preparing the next patient for surgery. The classifier was trained with data on the activation of the electrosurgical device during 55 laparoscopic cholecystectomies. The performance tests showed a mean error rate about 0.2, which means that about 80% of the procedures were classified correctly. The real-time prediction system is a promising tool to improve OR planning and decrease unnecessary patients' waiting times.

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