Intraoperative process monitoring using generalized surgical process models

Der Chirurg in einem modernen Operationssaal kann auf die Funktionen einer Vielzahl technischer, seine Arbeit unterstützender, Geräte zugreifen. Diese Geräte und damit auch die Funktionen, die diese zur Verfügung stellen, sind nur unzureichend miteinander vernetzt. Die unzureichende Interoperabilität der Geräte bezieht sich dabei nicht nur auf den Austausch von Daten untereinander, sondern auch auf das Fehlen eines zentralen Wissens über den gesamten Ablauf des chirurgischen Prozesses. Es werden daher Systeme benötigt, die Prozessmodelle verarbeiten und damit globales Wissen über den Prozess zur Verfügung stellen können. Im Gegensatz zu den meisten Prozessen, die in der Wirtschaft durch Workflow Management-Systeme (WfMS) unterstützt werden, ist der chirurgische Prozess durch eine hohe Variabilität gekennzeichnet. Mittlerweile gibt es viele Ansätze feingranulare, hochformalisierte Modelle des chirurgischen Prozesses zu erstellen. In dieser Arbeit wird zum einen die Qualität eines, auf patienten individuellen Eingriffen basierenden, generalisierten Modells hinsichtlich der Abarbeitung durch ein WfMS untersucht, zum anderen werden die Voraussetzungen die, die vorgelagerten Systeme erfüllen müssen geprüft. Es wird eine Aussage zur Abbruchrate der Pfadverfolgung im generalisierten Modell gemacht, das durch eine unterschiedliche Anzahl von patientenindividuellen Modellen erstellt wurde. Zudem wird die Erfolgsrate zum Wiederfinden des Prozesspfades im Modell ermittelt. Ausserdem werden die Anzahl der benötigten Schritte zumWiederfinden des Prozesspfades im Modell betrachtet.:List of Figures iv List of Tables vi 1 Introduction 1 1.1 Motivation 1 1.2 Problems and objectives 3 2 State of research 6 2.1 Definitions of terms 6 2.1.1 Surgical process 6 2.1.2 Surgical Process Model 7 2.1.3 gSPM and surgical workflow 7 2.1.4 Surgical workflow management system 8 2.1.5 Summary 9 2.2 Workflow Management Systems 10 2.2.1 Agfa HealthCare - ORBIS 10 2.2.2 Siemens Clinical Solutions - Soarian 10 2.2.3 Karl Storz - ORchestrion 10 2.2.4 YAWL BPM 11 2.3 Sensor systems 12 2.3.1 Sensors according to DIN1319 13 2.3.2 Video-based sensor technology 14 2.3.3 Human-based sensor technology 15 2.3.4 Summary 15 2.4 Process model 15 2.4.1 Top-Down 15 2.4.2 Bottom-Up 17 2.4.3 Summary 18 2.5 Methods for creating the ICCAS process model 18 2.5.1 Recording of the iSPMs 18 2.5.2 Creation of the gSPMs 20 2.6 Summary 21 3 Model-based design of workflow schemas 23 3.1 Abstract 24 3.2 Introduction 25 3.3 Model driven design of surgical workflow schemata 27 3.3.1 Recording of patient individual surgical process models 27 3.3.2 Generating generalized SPM from iSPMs 27 3.3.3 Transforming gSPM into workflow schemata 28 3.4 Summary and Outlook 30 4 Model-based validation of workflow schemas 31 4.1 Abstract 32 4.2 Introduction 33 4.3 Methods 36 4.3.1 Surgical Process Modeling 36 4.3.2 Workflow Schema Generation 38 4.3.3 The SurgicalWorkflow Management and Simulation System 40 4.3.4 System Validation Study Design 42 4.4 Results 44 4.5 Discussion 47 4.6 Conclusion 50 4.7 Acknowledgments 51 5 Influence of missing sensor information 52 5.1 Abstract 53 5.2 Introduction 54 5.3 Methodology 57 5.3.1 Surgical process modeling 57 5.3.2 Test system 59 5.3.3 System evaluation study design 61 5.4 Results 63 5.5 Discussion 66 5.6 Conclusion 68 5.7 Acknowledgments 68 5.8 Conflict of interest 68 6 Summary and outlook 69 6.1 Summary 69 6.2 Outlook 70 Bibliography 7

Factors affecting augmented reality head-mounted device performance in real OR

PURPOSE Over the last years, interest and efforts to implement augmented reality (AR) in orthopedic surgery through head-mounted devices (HMD) have increased. However, the majority of experiments were preclinical and within a controlled laboratory environment. The operating room (OR) is a more challenging environment with various confounding factors potentially affecting the performance of an AR-HMD. The aim of this study was to assess the performance of an AR-HMD in a real-life OR setting. METHODS An established AR application using the HoloLens 2 HMD was tested in an OR and in a laboratory by two users. The accuracy of the hologram overlay, the time to complete the trial, the number of rejected registration attempts, the delay in live overlay of the hologram, and the number of completely failed runs were recorded. Further, different OR setting parameters (light condition, setting up partitions, movement of personnel, and anchor placement) were modified and compared. RESULTS Time for full registration was higher with 48 s (IQR 24 s) in the OR versus 33 s (IQR 10 s) in the laboratory setting (p < 0.001). The other investigated parameters didn't differ significantly if an optimal OR setting was used. Within the OR, the strongest influence on performance of the AR-HMD was different light conditions with direct light illumination on the situs being the least favorable. CONCLUSION AR-HMDs are affected by different OR setups. Standardization measures for better AR-HMD performance include avoiding direct light illumination on the situs, setting up partitions, and minimizing the movement of personnel

Augmented reality navigation for spinal pedicle screw instrumentation using intraoperative 3D imaging

BACKGROUND CONTEXT Due to recent developments in augmented reality with head-mounted devices, holograms of a surgical plan can be displayed directly in the surgeon's field of view. To the best of our knowledge, three dimensional (3D) intraoperative fluoroscopy has not been explored for the use with holographic navigation by head-mounted devices in spine surgery. PURPOSE To evaluate the surgical accuracy of holographic pedicle screw navigation by head-mounted device using 3D intraoperative fluoroscopy. STUDY DESIGN In this experimental cadaver study, the accuracy of surgical navigation using a head-mounted device was compared with navigation with a state-of-the-art pose-tracking system. METHODS Three lumbar cadaver spines were embedded in nontransparent agar gel, leaving only commonly visible anatomy in sight. Intraoperative registration of preoperative planning was achieved by 3D fluoroscopy and fiducial markers attached to lumbar vertebrae. Trackable custom-made drill sleeve guides enabled real-time navigation. In total, 20 K-wires were navigated into lumbar pedicles using AR-navigation, 10 K-wires by the state-of-the-art pose-tracking system. 3D models obtained from postexperimental CT scans were used to measure surgical accuracy. MF is the founder and shareholder of Incremed AG, a Balgrist University Hospital start-up focusing on the development of innovative techniques for surgical executions. The other authors declare no conflict of interest concerning the contents of this study. No external funding was received for this study. RESULTS No significant difference in accuracy was measured between AR-navigated drillings and the gold standard with pose-tracking system with mean translational errors between entry points (3D vector distance; p=.85) of 3.4±1.6 mm compared with 3.2±2.0 mm, and mean angular errors between trajectories (3D angle; p=.30) of 4.3°±2.3° compared with 3.5°±1.4°. CONCLUSIONS In conclusion, holographic navigation by use of a head-mounted device achieve accuracy comparable to the gold standard of high-end pose-tracking systems. CLINICAL SIGNIFICANCE These promising results could result in a new way of surgical navigation with minimal infrastructural requirements but now have to be confirmed in clinical studies

Standard Versus Natural: Assessing the Impact of Environmental Variables on Organic Matter Decomposition in Streams Using Three Substrates

The decomposition of allochthonous organic matter, such as leaves, is a crucial ecosystem process in low-order streams. Microbial communities, including fungi and bacteria, colonize allochthonous organic material, break up large molecules, and increase the nutritional value for macroinvertebrates. Environmental variables are known to affect microbial as well as macroinvertebrate communities and alter their ability to decompose organic matter. Studying the relationship between environmental variables and decomposition has mainly been realized using leaves, with the drawbacks of differing substrate composition and consequently between-study variability. To overcome these drawbacks, artificial substrates have been developed, serving as standardizable surrogates. In the present study, we compared microbial and total decomposition of leaves with the standardized substrates of decotabs and, only for microbial decomposition, of cotton strips, across 70 stream sites in a Germany-wide study. Furthermore, we identified the most influential environmental variables for the decomposition of each substrate from a range of 26 variables, including pesticide toxicity, concentrations of nutrients, and trace elements, using stability selection. The microbial as well as total decomposition of the standardized substrates (i.e., cotton strips and decotabs) were weak or not associated with that of the natural substrate (i.e., leaves, r(2) < 0.01 to r(2) = 0.04). The decomposition of the two standardized substrates, however, showed a moderate association (r(2) = 0.21), which is probably driven by their similar composition, with both being made of cellulose. Different environmental variables were identified as the most influential for each of the substrates and the directions of these relationships contrasted between the substrates. Our results imply that these standardized substrates are unsuitable surrogates when investigating the decomposition of allochthonous organic matter in streams. Environ Toxicol Chem 2023;00:1-12. (c) 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC

Marker-free surgical navigation of rod bending using a stereo neural network and augmented reality in spinal fusion

The instrumentation of spinal fusion surgeries includes pedicle screw placement and rod implantation. While several surgical navigation approaches have been proposed for pedicle screw placement, less attention has been devoted towards the guidance of patient-specific adaptation of the rod implant. We propose a marker-free and intuitive Augmented Reality (AR) approach to navigate the bending process required for rod implantation. A stereo neural network is trained from the stereo video streams of the Microsoft HoloLens in an end-to-end fashion to determine the location of corresponding pedicle screw heads. From the digitized screw head positions, the optimal rod shape is calculated, translated into a set of bending parameters, and used for guiding the surgeon with a novel navigation approach. In the AR-based navigation, the surgeon is guided step-by-step in the use of the surgical tools to achieve an optimal result. We have evaluated the performance of our method on human cadavers against two benchmark methods, namely conventional freehand bending and marker-based bending navigation in terms of bending time and rebending maneuvers. We achieved an average bending time of 231s with 0.6 rebending maneuvers per rod compared to 476s (3.5 rebendings) and 348s (1.1 rebendings) obtained by our freehand and marker-based benchmarks, respectively

Ferromagnetic MnSb2Te4: A p-type topological insulator with magnetic gap closing at high Curie temperatures of 45-50K

Resumen del trabajo presentado al APS March Meeting, celebrado de forma virtual del 13 al 19 de marzo de 2021Mn enables the formation of intrinsic magnetic topological insulatorsfor the quantum anomalous Hall effect with A1B2C4 stoichiometry, e. g., antiferromagnetic MnBi2Te4 with 25 K Néel temperature. Here, we showthat p-type MnSb2Te4, previously considered topologically trivial, is a ferromagnetic topological insulator with high Curie temperature of 45 to 50 K.It displays out-of-plane magnetic anisotropy, the nontrivial topology is robust in band structure calculations towards magnetic disorder, provides aDirac point of the topological surface state close to the Fermi level with out-of-plane spin polarization in spin-ARPES, and exhibits a magneticallyinduced band gap of 17 meV that closes at the Curie temperature as demonstrated by scanning tunneling spectroscopy. Moreover, it displays acritical exponent of magnetization β≈1, indicating the vicinity of a quantum critical point. We identify the influences of structural and magneticdisorder that render MnSb2Te4 the ideal system for tuning electric and magnetic properties of quantum anomalous Hall systems.Peer reviewe

Intraoperative process monitoring using generalized surgical process models

Der Chirurg in einem modernen Operationssaal kann auf die Funktionen einer Vielzahl technischer, seine Arbeit unterstützender, Geräte zugreifen. Diese Geräte und damit auch die Funktionen, die diese zur Verfügung stellen, sind nur unzureichend miteinander vernetzt. Die unzureichende Interoperabilität der Geräte bezieht sich dabei nicht nur auf den Austausch von Daten untereinander, sondern auch auf das Fehlen eines zentralen Wissens über den gesamten Ablauf des chirurgischen Prozesses. Es werden daher Systeme benötigt, die Prozessmodelle verarbeiten und damit globales Wissen über den Prozess zur Verfügung stellen können. Im Gegensatz zu den meisten Prozessen, die in der Wirtschaft durch Workflow Management-Systeme (WfMS) unterstützt werden, ist der chirurgische Prozess durch eine hohe Variabilität gekennzeichnet. Mittlerweile gibt es viele Ansätze feingranulare, hochformalisierte Modelle des chirurgischen Prozesses zu erstellen. In dieser Arbeit wird zum einen die Qualität eines, auf patienten individuellen Eingriffen basierenden, generalisierten Modells hinsichtlich der Abarbeitung durch ein WfMS untersucht, zum anderen werden die Voraussetzungen die, die vorgelagerten Systeme erfüllen müssen geprüft. Es wird eine Aussage zur Abbruchrate der Pfadverfolgung im generalisierten Modell gemacht, das durch eine unterschiedliche Anzahl von patientenindividuellen Modellen erstellt wurde. Zudem wird die Erfolgsrate zum Wiederfinden des Prozesspfades im Modell ermittelt. Ausserdem werden die Anzahl der benötigten Schritte zumWiederfinden des Prozesspfades im Modell betrachtet.:List of Figures iv List of Tables vi 1 Introduction 1 1.1 Motivation 1 1.2 Problems and objectives 3 2 State of research 6 2.1 Definitions of terms 6 2.1.1 Surgical process 6 2.1.2 Surgical Process Model 7 2.1.3 gSPM and surgical workflow 7 2.1.4 Surgical workflow management system 8 2.1.5 Summary 9 2.2 Workflow Management Systems 10 2.2.1 Agfa HealthCare - ORBIS 10 2.2.2 Siemens Clinical Solutions - Soarian 10 2.2.3 Karl Storz - ORchestrion 10 2.2.4 YAWL BPM 11 2.3 Sensor systems 12 2.3.1 Sensors according to DIN1319 13 2.3.2 Video-based sensor technology 14 2.3.3 Human-based sensor technology 15 2.3.4 Summary 15 2.4 Process model 15 2.4.1 Top-Down 15 2.4.2 Bottom-Up 17 2.4.3 Summary 18 2.5 Methods for creating the ICCAS process model 18 2.5.1 Recording of the iSPMs 18 2.5.2 Creation of the gSPMs 20 2.6 Summary 21 3 Model-based design of workflow schemas 23 3.1 Abstract 24 3.2 Introduction 25 3.3 Model driven design of surgical workflow schemata 27 3.3.1 Recording of patient individual surgical process models 27 3.3.2 Generating generalized SPM from iSPMs 27 3.3.3 Transforming gSPM into workflow schemata 28 3.4 Summary and Outlook 30 4 Model-based validation of workflow schemas 31 4.1 Abstract 32 4.2 Introduction 33 4.3 Methods 36 4.3.1 Surgical Process Modeling 36 4.3.2 Workflow Schema Generation 38 4.3.3 The SurgicalWorkflow Management and Simulation System 40 4.3.4 System Validation Study Design 42 4.4 Results 44 4.5 Discussion 47 4.6 Conclusion 50 4.7 Acknowledgments 51 5 Influence of missing sensor information 52 5.1 Abstract 53 5.2 Introduction 54 5.3 Methodology 57 5.3.1 Surgical process modeling 57 5.3.2 Test system 59 5.3.3 System evaluation study design 61 5.4 Results 63 5.5 Discussion 66 5.6 Conclusion 68 5.7 Acknowledgments 68 5.8 Conflict of interest 68 6 Summary and outlook 69 6.1 Summary 69 6.2 Outlook 70 Bibliography 7

Intraoperative process monitoring using generalized surgical process models

Der Chirurg in einem modernen Operationssaal kann auf die Funktionen einer Vielzahl technischer, seine Arbeit unterstützender, Geräte zugreifen. Diese Geräte und damit auch die Funktionen, die diese zur Verfügung stellen, sind nur unzureichend miteinander vernetzt. Die unzureichende Interoperabilität der Geräte bezieht sich dabei nicht nur auf den Austausch von Daten untereinander, sondern auch auf das Fehlen eines zentralen Wissens über den gesamten Ablauf des chirurgischen Prozesses. Es werden daher Systeme benötigt, die Prozessmodelle verarbeiten und damit globales Wissen über den Prozess zur Verfügung stellen können. Im Gegensatz zu den meisten Prozessen, die in der Wirtschaft durch Workflow Management-Systeme (WfMS) unterstützt werden, ist der chirurgische Prozess durch eine hohe Variabilität gekennzeichnet. Mittlerweile gibt es viele Ansätze feingranulare, hochformalisierte Modelle des chirurgischen Prozesses zu erstellen. In dieser Arbeit wird zum einen die Qualität eines, auf patienten individuellen Eingriffen basierenden, generalisierten Modells hinsichtlich der Abarbeitung durch ein WfMS untersucht, zum anderen werden die Voraussetzungen die, die vorgelagerten Systeme erfüllen müssen geprüft. Es wird eine Aussage zur Abbruchrate der Pfadverfolgung im generalisierten Modell gemacht, das durch eine unterschiedliche Anzahl von patientenindividuellen Modellen erstellt wurde. Zudem wird die Erfolgsrate zum Wiederfinden des Prozesspfades im Modell ermittelt. Ausserdem werden die Anzahl der benötigten Schritte zumWiederfinden des Prozesspfades im Modell betrachtet.:List of Figures iv List of Tables vi 1 Introduction 1 1.1 Motivation 1 1.2 Problems and objectives 3 2 State of research 6 2.1 Definitions of terms 6 2.1.1 Surgical process 6 2.1.2 Surgical Process Model 7 2.1.3 gSPM and surgical workflow 7 2.1.4 Surgical workflow management system 8 2.1.5 Summary 9 2.2 Workflow Management Systems 10 2.2.1 Agfa HealthCare - ORBIS 10 2.2.2 Siemens Clinical Solutions - Soarian 10 2.2.3 Karl Storz - ORchestrion 10 2.2.4 YAWL BPM 11 2.3 Sensor systems 12 2.3.1 Sensors according to DIN1319 13 2.3.2 Video-based sensor technology 14 2.3.3 Human-based sensor technology 15 2.3.4 Summary 15 2.4 Process model 15 2.4.1 Top-Down 15 2.4.2 Bottom-Up 17 2.4.3 Summary 18 2.5 Methods for creating the ICCAS process model 18 2.5.1 Recording of the iSPMs 18 2.5.2 Creation of the gSPMs 20 2.6 Summary 21 3 Model-based design of workflow schemas 23 3.1 Abstract 24 3.2 Introduction 25 3.3 Model driven design of surgical workflow schemata 27 3.3.1 Recording of patient individual surgical process models 27 3.3.2 Generating generalized SPM from iSPMs 27 3.3.3 Transforming gSPM into workflow schemata 28 3.4 Summary and Outlook 30 4 Model-based validation of workflow schemas 31 4.1 Abstract 32 4.2 Introduction 33 4.3 Methods 36 4.3.1 Surgical Process Modeling 36 4.3.2 Workflow Schema Generation 38 4.3.3 The SurgicalWorkflow Management and Simulation System 40 4.3.4 System Validation Study Design 42 4.4 Results 44 4.5 Discussion 47 4.6 Conclusion 50 4.7 Acknowledgments 51 5 Influence of missing sensor information 52 5.1 Abstract 53 5.2 Introduction 54 5.3 Methodology 57 5.3.1 Surgical process modeling 57 5.3.2 Test system 59 5.3.3 System evaluation study design 61 5.4 Results 63 5.5 Discussion 66 5.6 Conclusion 68 5.7 Acknowledgments 68 5.8 Conflict of interest 68 6 Summary and outlook 69 6.1 Summary 69 6.2 Outlook 70 Bibliography 7