Point cloud registration for measuring shape dependence of soft tissue deformation by digital twins in head and neck surgery

• Verfasst von: Monji Azad, Sara [VerfasserIn]
• Verfasst von: Männle, David [VerfasserIn]
• Verfasst von: Hesser, Jürgen [VerfasserIn]
• Verfasst von: Pohlmann, Jan [VerfasserIn]
• Verfasst von: Rotter, Nicole [VerfasserIn]
• Verfasst von: Affolter, Annette [VerfasserIn]
• Verfasst von: Weis, Cleo-Aron Thias [VerfasserIn]
• Verfasst von: Ludwig, Sonja [VerfasserIn]
• Verfasst von: Scherl, Claudia [VerfasserIn]
• Titel: Point cloud registration for measuring shape dependence of soft tissue deformation by digital twins in head and neck surgery
• Verf.angabe: Sara Monji-Azad, David Männle, Jürgen Hesser, Jan Pohlmann, Nicole Rotter, Annette Affolter, Cleo Aron Weis, Sonja Ludwig, Claudia Scherl
• E-Jahr: 2024
• Jahr: January-December 2024
• Umfang: 7 S.
• Fussnoten: Online veröffentlicht: 9. Januar 2024 ; Gesehen am 10.04.2025
• Titel Quelle: Enthalten in: Biomedicine hub
• Ort Quelle: Basel : S. Karger AG, 2016
• Jahr Quelle: 2024
• Band/Heft Quelle: 9(2024), 1, Seite 9-15
• ISSN Quelle: 2296-6870
• DOI: doi:10.1159/000535421
• Datenträger: Online-Ressource
• Sprache: eng
• Bibliogr. Hinweis: Forschungsdaten: Monji Azad, Sara, 1986 - : DeformedTissue dataset
• K10plus-PPN: 1922068209

Abstract

Introduction: A 2½ D point cloud registration method was developed to generate digital twins of different tissue shapes and resection cavities by applying a machine learning (ML) approach. This demonstrates the feasibility of quantifying soft tissue shifts. Methods: An ML model was trained using simulated surface scan data obtained from tumor resections in a pig head cadaver model. It hereby uses 438 2½ D scans of the tissue surface. Tissue shift was induced by a temperature change from 7.91 ± 4.1°C to 36.37 ± 1.28°C. Results: Digital twins were generated from various branched and compact resection cavities (RCs) and cut tissues (CT). A temperature increase induced a tissue shift with a significant volume increase of 6 mL and 2 mL in branched and compact RCs, respectively (p = 0.0443; 0.0157). The volumes of branched and compact CT were decreased by 3 and 4 mL (p < 0.001). In the warm state, RC and CT no longer fit together because of the significant tissue deformation. Although not significant, the compact RC showed a greater tissue deformation of 1 μL than the branched RC with 0.5 μL induced by the temperature change (p = 0.7874). The branched and compact CT forms responded almost equally to changes in temperature (p = 0.1461). Conclusions: The simulation experiment of induced soft tissue deformation using digital twins based on 2½ D point cloud models proved that our method helps to quantify shape-dependent tissue shifts.