Sandy Engelhardt

Toward knowledge-based liver surgery: holistic information processing for surgical decision support

PurposeMalignant neoplasms of the liver are among the most frequent cancers worldwide. Given the diversity of options for liver cancer therapy, the choice of treatment depends on various parameters including patient condition, tumor size and location, liver function, and previous interventions. To address this issue, we present the first approach to treatment strategy planning based on holistic processing of patient-individual data, practical knowledge (i.e., case knowledge), and factual knowledge (e.g., clinical guidelines and studies).MethodsThe contributions of this paper are as follows: (1) a formalized dynamic patient model that incorporates all the heterogeneous data acquired for a specific patient in the whole course of disease treatment; (2) a concept for formalizing factual knowledge; and (3) a technical infrastructure that enables storing, accessing, and processing of heterogeneous data to support clinical decision making.ResultsOur patient model, which currently covers 602 patient-individual parameters, was successfully instantiated for 184 patients. It was sufficiently comprehensive to serve as the basis for the formalization of a total of 72 rules extracted from studies on patients with colorectal liver metastases or hepatocellular carcinoma. For a subset of 70 patients with these diagnoses, the system derived an average of

Comprehensive patient-specific information preprocessing for cardiac surgery simulations.

37 \pm 15

High Performance Computing for Cognition-Guided Cardiac Surgery: Soft Tissue Simulation for Mitral Valve Reconstruction in Knowledge-Based Surgery Assistance

37±15 assertions per patient.ConclusionThe proposed concept paves the way for holistic treatment strategy planning by enabling joint storing and processing of heterogeneous data from various information sources.

Towards an open-source semantic data infrastructure for integrating clinical and scientific data in cognition-guided surgery

PURPOSE Analysis of mitral valve morphology during reconstruction is routinely based on visual assessment and subjective, poorly reproducible measurements. We prove the feasibility of a new intraoperative system for quantitative mitral valve analysis. DESCRIPTION The proposed computer-based assistance system enables accurate intraoperative localization of anatomic landmarks on the mitral valve apparatus using optical tracking technology. Measurement and visualization strategies were specifically developed and tailored for mitral valve operations. EVALUATION The feasibility of intraoperative quantitative measurements was successfully shown for 9 patients. Precise geometric descriptions of the valve were obtained and adequately visualized, providing valuable decision support during the intervention. The mean annular area obtained from the intraoperative measurements was 736 ± 266 mm(2), in good agreement with the mean area of the implanted prosthetic rings of 617 ± 124 mm(2), which are slightly smaller due to annular downsizing. Comparison with preoperative three-dimensional echocardiography revealed differences between the beating heart, with transverse and septolateral annular diameters of 40.6 ± 15.4 mm and 41.2 ± 8.2 mm, and the intraoperative cardioplegic condition, with corresponding diameters of 34.3 ± 6.9 mm and 27.4 ± 5.6 mm. CONCLUSIONS Mitral valve analysis by optical tracking represents a unique technologic advance in intraoperative assessment, providing the surgeon with an extended quantitative perception of surgical target. This technology promotes a major philosophical change from an empirical procedure toward a quantitatively predictable modern reconstructive operation.

Gestaltung patientenspezifischer Annuloplastieringe

PurposePatient-specific biomechanical simulations of the behavior of soft tissue gain importance in current surgery assistance systems as they can provide surgeons with valuable ancillary information for diagnosis and therapy. In this work, we aim at supporting minimally invasive mitral valve reconstruction (MVR) surgery by providing scenario setups for FEM-based soft tissue simulations, which simulate the behavior of the patient-individual mitral valve subject to natural forces during the cardiac cycle after an MVR. However, due to the complexity of these simulations and of their underlying mathematical models, it is difficult for non-engineers to sufficiently understand and adequately interpret all relevant modeling and simulation aspects. In particular, it is challenging to set up such simulations in automated preprocessing workflows such that they are both patient-specific and still maximally comprehensive with respect to the model.MethodsIn this paper, we address this issue and present a fully automated chain of preprocessing operators for setting up comprehensive, patient-specific biomechanical models on the basis of patient-individual medical data. These models are suitable for FEM-based MVR surgery simulation. The preprocessing methods are integrated into the framework of the Medical Simulation Markup Language and allow for automated information processing in a data-driven pipeline.ResultsWe constructed a workflow for holistic, patient-individual information preprocessing for MVR surgery simulations. In particular, we show how simulation preprocessing can be both fully automated and still patient-specific, when using a series of dedicated MVR data analytics operators. The outcome of our operator chain is visualized in order to help the surgeon understand the model setup.ConclusionWith this work, we expect to improve the usability of simulation-based MVR surgery assistance, through allowing for fully automated, patient-specific simulation setups. Combined visualization of the biomechanical model setup and of the corresponding surgery simulation results fosters the understandability and transparency of our assistance environment.

Automatic Cardiac Disease Assessment on cine-MRI via Time-Series Segmentation and Domain Specific Features

Mitral valve reconstruction is a widespread surgical method to repair incompetent mitral valves. During reconstructive surgery the judgement of mitral valve geometry and subvalvular apparatus is mandatory in order to choose for the appropriate repair strategy. To date, intraoperative analysis of mitral valve is merely based on visual assessment and inaccurate sizer devices, which do not allow for any accurate and standardized measurement of the complex three-dimensional anatomy. We propose a new intraoperative computer-assisted method for mitral valve measurements using a pointing instrument together with an optical tracking system. Sixteen anatomical points were defined on the mitral apparatus. The feasibility and the reproducibility of the measurements have been tested on a rapid prototyping (RP) heart model and a freshly exercised porcine heart. Four heart surgeons repeated the measurements three times on each heart. Morphologically important distances between the measured points are calculated. We achieved an interexpert variability mean of 2.28 +/- 1:13 mm for the 3D-printed heart and 2.45 +/- 0:75 mm for the porcine heart. The overall time to perform a complete measurement is 1-2 minutes, which makes the method viable for virtual annuloplasty during an intervention.

Computer-based comparison of different methods for selecting mitral annuloplasty ring size

Medical simulations play an increasingly important role in today’s clinical and surgical treatment processes. The scope of this work is the support of the surgical operation of a mitral valve reconstruction (MVR) by means of biomechanical simulations. Based on numerical simulation, the natural anatomical setting, the ring implantation and the valve closure are modelled and efficiently computed in order to provide surgeons during the operation with additional morphological and functional information. Our simulation is based on the Finite Element Method (FEM) and implemented using the open-source C++ FEM software HiFlow3. Integrating patient data and surgical expert knowledge, and making efficient use of High-Performance Computing (HPC) methods allows for obtaining valuable simulation results for surgery assistance in adequate times. In this work, we focus on the intelligent setup of the biomechanical model and the flexible interfaces of the HPC-based implementation of the resulting MVR simulation, thereby aiming at a cognition-guided, patient-specific integration into systems for surgery assistance.

Towards Automatic Assessment of the Mitral Valve Coaptation Zone from 4D Ultrasound

In the surgical domain, individual clinical experience, which is derived in large part from past clinical cases, plays an important role in the treatment decision process. Simultaneously the surgeon has to keep track of a large amount of clinical data, emerging from a number of heterogeneous systems during all phases of surgical treatment. This is complemented with the constantly growing knowledge derived from clinical studies and literature. To recall this vast amount of information at the right moment poses a growing challenge that should be supported by adequate technology. While many tools and projects aim at sharing or integrating data from various sources or even provide knowledge-based decision support - to our knowledge - no concept has been proposed that addresses the entire surgical pathway by accessing the entire information in order to provide context-aware cognitive assistance. Therefore a semantic representation and central storage of data and knowledge is a fundamental requirement. We present a semantic data infrastructure for integrating heterogeneous surgical data sources based on a common knowledge representation. A combination of the Extensible Neuroimaging Archive Toolkit (XNAT) with semantic web technologies, standardized interfaces and a common application platform enables applications to access and semantically annotate data, perform semantic reasoning and eventually create individual context-aware surgical assistance. The infrastructure meets the requirements of a cognitive surgical assistant system and has been successfully applied in various use cases. The system is based completely on free technologies and is available to the community as an open-source package.