DataVXAdvanced SciencePaper
journal article·2023-08Open access

Surgical Sealant with Integrated Shape‐Morphing Dual Modality Ultrasound and Computed Tomography Sensors for Gastric Leak Detection

Benjamin Suter, Alexandre H. C. Anthis, Anna‐Katharina Zehnder, Victor Mergen, Jachym Rosendorf, Lukas R. H. Gerken, Andrea A. Schlegel, Eva Korcakova, Vaclav Liska, Inge K. Herrmann

Advanced Science· Volume 10· Issue 23
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Source abstract

Abstract

Abstract Postoperative anastomotic leaks are the most feared complications after gastric surgery. For diagnostics clinicians mostly rely on clinical symptoms such as fever and tachycardia, often developing as a result of an already fully developed, i.e., symptomatic, surgical leak. A gastric fluid responsive, dual modality, electronic‐free, leak sensor system integrable into surgical adhesive suture support materials is introduced. Leak sensors contain high atomic number carbonates embedded in a polyacrylamide matrix, that upon exposure to gastric fluid convert into gaseous carbon dioxide (CO2). CO2 bubbles remain entrapped in the hydrogel matrix, leading to a distinctly increased echogenic contrast detectable by a low‐cost and portable ultrasound transducer, while the dissolution of the carbonate species and the resulting diffusion of the cation produces a markedly reduced contrast in computed tomography imaging. The sensing elements can be patterned into a variety of characteristic shapes and can be combined with nonreactive tantalum oxide reference elements, allowing the design of shape‐morphing sensing elements visible to the naked eye as well as artificial intelligence‐assisted automated detection. In summary, shape‐morphing dual modality sensors for the early and robust detection of postoperative complications at deep tissue sites, opening new routes for postoperative patient surveillance using existing hospital infrastructure is reported.
Source: crossref · Quality: baseline

Research context

Polymers

OpenAlex topics: Cardiac, Anesthesia and Surgical Outcomes · Thyroid and Parathyroid Surgery · Surgical Simulation and Training

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Nanoparticle Systems Engineering Laboratory Institute of Energy and Process Engineering (IEPE) Department of Mechanical and Process Engineering (D‐MAVT) ETH Zurich Sonneggstrasse 3 Zürich 8092 Switzerland

Particles‐Biology Interactions Department of Materials Meet Life Swiss Federal Laboratories for Materials Science and Technology (Empa) Lerchenfeldstrasse 5 St. Gallen 9014 Switzerland

Diagnostic and Interventional Radiology University Hospital Zurich University of Zurich Rämistrasse 100 Zürich 8091 Switzerland

Department of Surgery Faculty of Medicine in Pilsen Charles University Alej Svobody 923/80 Pilsen 32300 Czech Republic

Biomedical Center Faculty of Medicine in Pilsen Charles University Alej Svobody 1655/76 Pilsen 32300 Czech Republic

Department of Surgery and Transplantation Swiss HPB Centre University Hospital Zurich Rämistrasse 100 Zurich 8091 Switzerland

Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico Centre of Preclinical Research Milan 20122 Italy

Transplantation Center, Digestive Disease and Surgery Institute and Department of Immunity and Inflammation, Lerner Research Institute Cleveland Clinic 9620 Carnegie Ave Cleveland OH 44106 United States

Department of Imaging Methods Faculty of Medicine in Pilsen, Charles University Alej Svobody 80 Pilsen 30460 Czech Republic

Funding

Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung

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