Artificial intelligence directed development of a digital twin to measure soft tissue shift during head and neck surgery

• Published in: PloS one 2023-08, Vol.18 (8), p.e0287081-e0287081
• Main Authors: Männle, David, Pohlmann, Jan, Monji-Azad, Sara, Hesser, Jürgen, Rotter, Nicole, Affolter, Annette, Lammert, Anne, Kramer, Benedikt, Ludwig, Sonja, Huber, Lena, Scherl, Claudia
• Format: Article
• Language: English
• Subjects: Analysis; Animals; Apexes; Artificial Intelligence; Artificial tissues; Biology and Life Sciences; Cadaver; Cadavers; Cameras; Cold; Computer and Information Sciences; Computer graphics; Computer software industry; Digital twins; Forecasts and trends; Formability; Head - surgery; Head and neck; Machine learning; Measurement; Medicine and Health Sciences; Navigation systems; Nervous system; Neurosurgery; Photogrammetry; Scanners; Soft tissues; Software; Surgery; Swine; Temperature; Temperature changes; Tissues; Tumors; Twins; Volume measurement
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0287081

Digital twins derived from 3D scanning data were developed to measure soft tissue deformation in head and neck surgery by an artificial intelligence approach. This framework was applied suggesting feasibility of soft tissue shift detection as a hitherto unsolved problem. In a pig head cadaver model 104 soft tissue resection had been performed. The surface of the removed soft tissue (RTP) and the corresponding resection cavity (RC) was scanned (N = 416) to train an artificial intelligence (AI) with two different 3D object detectors (HoloLens 2; ArtecEva). An artificial tissue shift (TS) was created by changing the tissue temperature from 7,91±4,1°C to 36,37±1,28°C. Digital twins of RTP and RC in cold and warm conditions had been generated and volumes were calculated based on 3D surface meshes. Significant differences in number of vertices created by the different 3D scanners (HoloLens2 51313 vs. ArtecEva 21694, p