Digital impression workflows and mucosal considerations in removable complete dentures

Introduction

In modern prosthodontics, intraoral scanner–based digital impression systems have been increasingly incorporated into clinical workflows for removable prosthodontics.1 This technology fundamentally redefines the initial clinical modeling phase by directly capturing high-resolution three-dimensional spatial data of the oral cavity.1 Previous studies have shown that intraoral scanning technology achieves satisfactory accuracy and demonstrates a relatively short learning curve.2 By bypassing the clinical procedures required for mixing and loading conventional elastomeric impression materials, clinicians can reduce patient discomfort, anxiety, and gag reflexes. The resulting digital master model serves as a highly accurate virtual representation of the dental arches, eliminating the need for physical diagnostic gypsum models. This digital workflow significantly shortens chairside treatment time and improves communication with dental laboratories.

However, extending this digital workflow to complete denture fabrication introduces complex anatomical challenges associated with soft tissue dynamics.3,4 Unlike rigid teeth, the edentulous residual ridge and alveolar mucosa are highly displaceable, lack stable anatomical landmarks, and exhibit variable morphology, which compromises the image-stitching algorithms of intraoral scanners. Hypermobile or flabby tissues deform under the minor pressure exerted by oral tissue retractors, resulting in geometric distortion of the digital master model.3 Furthermore, passive optical scanning cannot apply selective pressure or capture dynamic muscle movements, making it difficult to establish a definitive master model with an accurate peripheral seal. This physiological limitation directly threatens the retention, support, and stability of the final prosthesis. Therefore, the feasibility and clinical application of a fully digital intraoral scanning workflow for completely edentulous patients warrant further discussion. Contemporary digital impression protocols for edentulous arch rehabilitation are summarized in Table 1.

Table 1.

Characteristics, vestibular accuracy, and scanning efficiency of contemporary digital impression protocols for edentulous arch rehabilitation.

Digital impression protocol	Mechanism of soft tissue management	Vestibular accuracy (μm)	Scanning efficiency (seconds)	Reference
Myofunctional hybrid	3D prototype denture with functional tissue conditioner.	High border adaptation	Varies clinically	4
Standard IOS protocol	Passive optical scan without active border molding.	72.4 ± 8.9	204 ± 15	5
Reference-point protocol	1 mm markers at 5 mm intervals with standardized tissue traction.	48.7 ± 6.3	130 ± 9	5

To overcome these soft tissue limitations, several digital impression protocols have been developed for clinical application.4 The reference-point-enhanced scanning technique utilizes temporary physical markers (e.g., 1-mm-diameter beads) placed on the edentulous mucosa to provide stable tracking coordinates for the scanner. Alternatively, hybrid techniques employ a 3D-printed or milled prototype denture as a custom tray to record functional border movements under occlusal loading. Previous studies reported that incorporating physical reference points improved the trueness of the vestibular region to 48.7 ± 6.3 μm, compared with 72.4 ± 8.9 μm obtained using conventional scanning protocols, while simultaneously reducing scan-processing time by 37%.5 Furthermore, a myofunctional hybrid technique can be performed directly intraorally by utilizing a 3D-printed prototype denture in combination with a functional tissue conditioner.4

Despite these technical refinements, current digital impression methods still have clear limitations, particularly in obtaining accurate maxillomandibular relationship records in patients with extensive posterior tooth loss without physical record bases.1 Additionally, assembling milled PMMA denture bases and artificial teeth during denture fabrication may introduce minor bonding discrepancies. Therefore, current clinical workflows for complete denture fabrication continue to employ a two-stage approach involving conventional impressions followed by digital design rather than a completely digital workflow. Future developments should focus on the integration of artificial intelligence–assisted scanning software capable of predicting mucosal displacement under functional loading and combining intraoral scan data with three-dimensional facial scans and CBCT datasets. Validation of these integrated digital workflows through long-term clinical studies will be essential for establishing a truly cast-free and clinically stable complete denture fabrication workflow.

Funding Statement

The authors thank the Taipei Medical University, Wan Fang Hospital, Taiwan for financially supporting this research under the contract 115-wf-phd-05 to Fu-Chuan Tsai.