Citation: Probst, J.; Dritsas, K.; Halazonetis, D.; Ren, Y.; Katsaros, C.; Gkantidis, N. Precision of a Hand-Held 3D Surface Scanner in Dry and Wet Skeletal Surfaces: An Ex Vivo Study. Diagnostics 2022, 12, 2251. https://doi.org/10.3390/ diagnostics12092251 Academic Editor: Rute Santos Received: 3 July 2022 Accepted: 16 September 2022 Published: 18 September 2022 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affil- iations. Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). diagnostics Article Precision of a Hand-Held 3D Surface Scanner in Dry and Wet Skeletal Surfaces: An Ex Vivo Study Jannis Probst 1 , Konstantinos Dritsas 1 , Demetrios Halazonetis 2 , Yijin Ren 3 , Christos Katsaros 1 and Nikolaos Gkantidis 1, * 1 Department of Orthodontics and Dentofacial Orthopedics, School of Dental Medicine, University of Bern, CH-3010 Bern, Switzerland 2 Department of Orthodontics, School of Dentistry, National and Kapodistrian University of Athens, GR-11527 Athens, Greece 3 Department of Orthodontics, W.J. Kolff Institute, University Medical Center Groningen, University of Groningen, 9700 RB Groningen, The Netherlands * Correspondence: nikolaos.gkantidis@unibe.ch Abstract: Three-dimensional surface scans of skeletal structures have various clinical and research applications in medicine, anthropology, and other relevant fields. The aim of this study was to test the precision of a widely used hand-held surface scanner and the associated software’s 3D model generation-error in both dry and wet skeletal surfaces. Ten human dry skulls and ten mandibles (dry and wet conditions) were scanned twice with an industrial scanner (Artec Space Spider) by one operator. Following a best-fit superimposition of corresponding surface model pairs, the mean absolute distance (MAD) between them was calculated on ten anatomical regions on the skulls and six on the mandibles. The software’s 3D model generation process was repeated for the same scan of four dry skulls and four mandibles (wet and dry conditions), and the results were compared in a similar manner. The median scanner precision was 31 μm for the skulls and 25 μm for the mandibles in dry conditions, whereas in wet conditions it was slightly lower at 40 μm for the mandibles. The 3D model generation-error was negligible (range: 5–10 μm). The Artec Space Spider scanner exhibits very high precision in the scanning of dry and wet skeletal surfaces. Keywords: diagnosis; documentation; computer-assisted; imaging; three-dimensional; digital image processing; bone and bones 1. Introduction 3D surface imaging with hand-held scanners has been widely used in the latest years for various scientific, as well as industrial, applications [1,2]. The scanners’ favorable price, the ease of usage, and the user-friendlier software may have contributed to its increasing popularity [3]. Such scanners are often used to scan skeletal specimens for different applications [4,5]. For example, one of the main goals of radiologic research is the improvement of image quality while keeping the radiation dose as low as possible to minimize the associated risks [6]. However, ethical considerations make the execution of relevant studies on human subjects impossible unless the patient directly benefits from the acquired images, which is rarely the case when repeated exposures are required. To overcome this limitation, dry human skeletal specimens are commonly used in ex vivo radiographic settings, and the missing soft tissues are often simulated by embedding them in water or similar liquid materials [7]. For various research purposes, these specimens are also digitally transformed to three-dimensional (3D) surface models, either segmented from radiographic data, such as computed tomographies (CT) and cone beam computed tomographies (CBCT), or directly scanned with accurate industrial scanners [8,9]. The latter approach is usually preferable when highly accurate surface models are sought because it does not involve the segmentation error, which is unavoidable when obtaining Diagnostics 2022, 12, 2251. https://doi.org/10.3390/diagnostics12092251 https://www.mdpi.com/journal/diagnostics