Registration of cone beam computed tomography data and intraoral surface scans – A prerequisite for guided implant surgery with CAD/CAM drilling guides. Issue 9 (20th July 2016)

• Record Type: Journal Article
• Authors: Flügge, Tabea; Derksen, Wiebe; te Poel, Jobine; Hassan, Bassam; Nelson, Katja; Wismeijer, Daniel
• Is Part Of: Clinical oral implants research. Volume 28:Issue 9(2017)
• Page Start: 1113
• Page End: 1118
• Publication Date: 2016-07-20
• Subjects: CAD/CAM -- cone beam computed tomography -- guided implant surgery; Dental implants -- Research -- Periodicals; 617.69
• DOI: 10.1111/clr.12925
• Languages: English
• ISSNs: 0905-7161

Abstract

Abstract: Objectives: Guided implant surgery (GIS) is performed with drilling guides that are produced on the virtual tooth model using CAD/CAM technology. The prerequisite for this workflow is the alignment of patients cone beam computed tomography CBCT and surface scan (registration). Dental restorations may cause deteriorating imaging artifacts in CBCT data, which in turn can have an impact on the registration process. The influence of the user and the preprocessing of data and of image artifacts on the registration accuracy were examined. Material and Methods: CBCT data and intraoral surface scans of 36 patients were used for virtual implant planning in coDiagnostiX (Dentalwings, Montreal, Canada). CBCT data were reconstructed to a three‐dimensional anatomical model with the default settings provided by the software and also manually by four different examiners. Subsequently, the CBCT and intraoral surface models were registered by each examiner with the help of anatomical landmarks. Patients' data were subdivided into four groups (A–D) according to the number of metallic restorations: A = 0–2 restorations, B = 3–5 restorations, C = 6–8 restorations and D > 8 restorations. After registration, the distances between CBCT and dental surface models were measured. Linear regression models were used to assess the influence of the segmentation, the examiner and to the number of restorations ( P < 0.05). Results: The deviations between surface scan and CBCT models accounted to 0.54 mm (mean). The mean deviations were 0.69 mm (max. 24.8 mm) and 0.4 mm (max. 9.1 mm) for default and manual segmentation, respectively. Mean deviations of 0.36 mm (Group A), 0.43 mm (Group B), 0.67 mm (Group C) and 1.01 mm (Group D) were recorded. The segmentation ( P = 0.000), the user ( P = 0.0052) and the number of restorations ( P = 0.0337) had a significant influence on the registration accuracy. Conclusions: The deviation between CBCT and surface scan model resulting from inaccurate registration is transferred to the surgical field and results in a deviation between the planned and actual implant position. The registration accuracy in commercial virtual implant planning software is significantly influenced by the preprocessing of imported data, by the user and by the number of restorations resulting in clinically non‐acceptable deviations encoded in drilling guides.