What is the impact of digital technologies on removable complete dentures: Advances, challenges, and clinical implications: A narrative review

Abstract

Background

With the rapid advancement of digital technologies, dentistry has witnessed significant innovations, particularly in the fabrication of removable complete dentures. The objective of this narrative review is to examine the evolution, current state, and future directions of digital removable complete dentures, with a focus on comparing computer-aided design and computer-aided manufacturing (CAD/CAM) approaches to conventional techniques in terms of clinical efficiency and patient satisfaction.

Methods

A narrative review was conducted by searching PubMed, Scopus, Embase, and Web of Science for articles published between January 2010 and April 2025. Relevant keywords related to digital dentures, CAD/CAM, 3D printing, and patient outcomes were used. Studies focusing on digital complete denture fabrication and comparisons with conventional methods were included.

Results

Evidence indicates that digitally fabricated complete dentures demonstrate comparable or superior outcomes in retention, adaptation, and patient satisfaction. They also reduce the number of clinical visits and post-insertion adjustments. However, concerns remain regarding material properties, cost-effectiveness, and long-term performance.

Conclusions

Digital denture fabrication presents a promising alternative to conventional methods, although further advancements in materials and long-term clinical validation are needed. Tailored implementation of digital workflows can enhance treatment efficiency and patient experience in removable prosthodontics.

Graphical Abstract

Introduction

The digital paradigm shift in prosthodontics

The field of prosthodontics is undergoing a profound transformation that extends beyond technological progress and signifies a fundamental shift from traditional craftsmanship toward data-driven precision biomanufacturing in edentulous rehabilitation. The emergence of digital removable complete dentures has redefined conventional clinical workflows through the integration of computer-aided design (CAD) and computer-aided manufacturing (CAM) technologies. These digital systems enable streamlined, precise, and efficient fabrication processes compared with conventional manual techniques that relied extensively on individual craftsmanship and multiple patient appointments (Jafarpour et al. 2024). This transformation necessitates a re-examination of established concepts in material science, biomechanics, and clinical workflow design, ultimately reshaping the framework of prosthodontic care in an aging global population.

The ongoing digital transition is underpinned by fundamental scientific principles governing the interactions among materials, biological tissues, and manufacturing processes. A deep understanding of these principles is essential to explain clinical phenomena such as the influence of polymer chemistry on mechanical performance or the role of surface nanotopography in microbial adhesion. Such knowledge moves the discipline beyond incremental technical refinements toward evidence-based innovation. The convergence of digital technologies with biomimetic material design and the broader principles of personalized medicine offers unique opportunities to enhance treatment outcomes and address the complex needs of elderly patients requiring prosthodontic rehabilitation (Jafarpour et al. 2024; Zupancic Cepic et al. 2023).

Clinical relevance and broader scientific implications

There is a pressing need to examine the practicalities of digital denture fabrication, assess its clinical outcomes, and better understand patient perspectives, as exploring these aspects provides valuable insight into how digital technologies are reshaping prosthodontic care and setting new standards for edentulous rehabilitation (Zupancic Cepic et al. 2023). Beyond the immediate clinical context, advances in digital denture fabrication have implications for multiple scientific domains, including automation in healthcare delivery, integration of artificial intelligence in medical device design, and the development of patient-specific therapeutic approaches that align with precision medicine principles.

The significance of this topic extends to the broader challenge of global healthcare associated with population aging. As life expectancy continues to rise worldwide, the demand for efficient, accessible, and high-quality prosthodontic care is becoming increasingly important. Digital technologies provide promising solutions by promoting standardization and reproducibility while facilitating the delivery of care with a reduced patient burden. These features are particularly valuable for geriatric populations who often experience mobility limitations and multiple comorbid medical conditions (Nations, 2020).

Historical evolution and technological foundations

The evolution of digital dentures began in the early 2000 s with the initial application of CAD/CAM technologies to removable prosthodontics, though initially limited by software capabilities and material constraints. The field has progressed rapidly over the past two decades, with early systems focusing primarily on milling pre-polymerized polymethyl methacrylate (PMMA) pucks, while contemporary approaches now encompass both subtractive manufacturing (milling) and additive manufacturing (3D printing) techniques (Nations, 2020; Goodacre et al. 2012). This technological progression represents more than an incremental improvement. It embodies a disruptive innovation that fundamentally transforms the manufacturing paradigm from traditional compression molding and lost-wax techniques to computer-controlled precision manufacturing.

The initiation of our literature search from 2010 reflects the period when digital denture technologies transitioned from experimental concepts to commercially viable clinical systems. While isolated reports of digital approaches existed earlier, the first commercial CAD/CAM denture systems became available around 2011, with subsequent rapid development occurring primarily between 2013-2015 (Bidra et al. 2013; Goodacre et al. 2012). This timeframe captures the clinically relevant evolution of technologies that practitioners can currently implement, distinguishing developmental phases from established clinical applications.

Conceptual framework and review objectives

This review is organized around a unifying conceptual framework that reflects the transition from traditional artisanal prosthodontics to an integrated digital and biological manufacturing paradigm. The proposed framework encompasses three interrelated dimensions. The first dimension addresses material science foundations, focusing on the understanding of polymer chemistry, cross-linking mechanisms, and structure–property relationships. The second dimension concerns the biological interface, emphasizing tissue adaptation, microbial interactions, and biocompatibility at the molecular level. The third dimension highlights clinical translation through the evaluation of workflow efficiency, patient-centered outcomes, and contemporary models of healthcare delivery.

The specific objectives of this narrative review are to:

1. Critically evaluate the current evidence base for digital complete dentures, identifying areas of robust evidence versus preliminary or conflicting findings

2. Analyze the fundamental scientific principles underlying observed clinical and laboratory outcomes

3. Compare manufacturing technologies (milling versus 3D printing) through mechanistic understanding rather than descriptive reporting

4. Assess patient-centered outcomes within the context of broader healthcare delivery and population health

5. Project future directions based on emerging technologies and scientific principles

This narrative review format was selected to allow comprehensive exploration of complex, multifaceted topics that extend beyond narrowly defined clinical questions. While we provide transparency regarding literature selection through a flow diagram, the synthesis remains interpretive and conceptual rather than purely systematic.

Materials and methods

Literature search strategy

This narrative review employed a comprehensive but non-systematic approach to literature identification and synthesis. The methodology prioritized depth of analysis and conceptual integration over exhaustive systematic enumeration.

A comprehensive literature search was conducted using the electronic databases PubMed/MEDLINE, Scopus, Embase, and Web of Science. The search encompassed articles published between January 2010 and April 2025. The selection of 2010 as the starting point was deliberate, reflecting the period when digital denture technologies transitioned from experimental concepts to clinically applicable systems. While earlier developmental work existed, the vast majority of clinically relevant innovations occurred after 2011, with particularly rapid advancement between 2013-2015 (Bidra et al. 2013; Goodacre et al. 2012).

The following search terms were used in various combinations: "digital dentures," "CAD/CAM dentures," "3D-printed dentures," "additive manufacturing dentures," "milled dentures," "digital complete dentures," "complete denture fabrication," "edentulous," "digital workflow," "patient satisfaction," "denture retention," "denture adaptation," and "mechanical properties."

Study selection criteria

Articles were selected based on the following inclusion criteria:

1. English language publications

2. Clinical trials, case reports, case series, comparative studies, systematic reviews, and meta-analyses

3. Studies discussing digital complete denture fabrication methods

4. Studies comparing digital and conventional denture fabrication

5. Studies reporting clinical outcomes or material properties of digital dentures

Exclusion criteria were:

1. Publications in languages other than English

2. Studies focusing exclusively on partial dentures or implant-supported prostheses

3. Opinion articles without original data

4. Conference abstracts without full-text availability

Data synthesis and analysis approach

After initial screening of titles and abstracts, relevant articles were retrieved for full-text review. The reference lists of selected articles were manually searched to identify additional relevant studies The final selection included 63 articles that met the inclusion criteria and substantially contributed to the focus areas of this narrative review. This approach allowed for selective inclusion of high-quality evidence that addresses key conceptual questions, rather than exhaustive systematic enumeration.

Figure 1 is provided for transparency regarding literature selection and to illustrate the search process. However, it is important to clarify that this flowchart serves to document the literature identification process rather than indicate systematic review methodology. The synthesis presented in this review remains narrative and interpretive, focusing on conceptual integration and critical analysis of fundamental principles rather than purely quantitative meta-analysis.

Fig. 1.

Literature selection flowchart. This diagram is provided for transparency regarding the search and selection process. The review synthesis remains narrative rather than systematic, emphasizing conceptual integration and critical analysis of fundamental scientific principles underlying digital denture technologies

Evolution of digital denture fabrication

From conventional to digital: historical perspective and conceptual transformation

Complete denture fabrication remained largely unchanged for nearly a century before digital technologies began to transform the field. Conventional denture fabrication typically involves a five-appointment process: preliminary impressions, final impressions, jaw relations records, try-in with arranged teeth, and denture delivery. This approach, while time-tested, presents several limitations including multiple patient visits, laboratory-dependent processes, material polymerization shrinkage, and reliance on practitioner skill for consistent outcomes.

The transition from conventional to digital methods represents more than a change in tools. It reflects a fundamental shift in manufacturing philosophy. Traditional approaches were rooted in empirical craftsmanship, where outcomes largely depended on individual skill and experience. In contrast, digital methods enable data-driven precision, reproducibility, and the capacity for continuous improvement through feedback mechanisms and computational optimization.

The earliest efforts to incorporate digital technology into removable prosthodontics began in the 1990 s but faced significant challenges due to limitations in scanning technology, software capabilities, and manufacturing options. The commercial availability of CAD/CAM dentures began around 2011, with systems initially focusing on milling pre-polymerized PMMA pucks (Goodacre et al. 2012). These early systems maintained some conventional clinical steps while digitizing others, creating hybrid workflows that gradually evolved toward fully digital processes.

Current digital fabrication methods

Subtractive manufacturing (Milling)

CAD/CAM milling technology represents the first widely adopted digital approach to denture fabrication. This process involves scanning either conventional impressions or existing dentures, or direct intraoral scanning of edentulous arches. Digital design software is then used to virtually design the denture base and arrange teeth according to anatomical landmarks and aesthetic considerations. The completed design is translated into milling instructions for computer-controlled machines that carve the denture from pre-polymerized PMMA pucks.

The superior mechanical properties observed in milled dentures compared to 3D-printed alternatives stem from fundamental polymer chemistry principles. Pre-polymerized PMMA pucks used in milling undergo industrial polymerization under controlled temperature and pressure conditions, resulting in high degree of conversion, uniform cross-linking density, and minimal residual monomer content. This industrial processing achieves molecular-level organization that is challenging to replicate in layer-by-layer additive processes (Kane and Shah 2023; Mubaraki et al. 2022).

Studies have demonstrated that milled denture bases exhibit superior adaptation to underlying tissues compared to conventional heat-polymerized bases (Steinmassl et al. 2018). Additionally, the bond strength between denture teeth and milled PMMA bases is comparable to conventional methods, addressing an early concern about the durability of milled prostheses (Kane and Shah 2023).

Additive manufacturing (3D Printing)

More recently, additive manufacturing technologies have been applied to complete denture fabrication. This process uses digital light processing (DLP), stereolithography (SLA), or other 3D printing technologies to build denture bases layer by layer from photopolymerizable resins (Shafiei et al. 2019; Zhang et al. 2021).

The challenges in achieving mechanical properties comparable to milled or conventional dentures through 3D printing relate to fundamental material science constraints. Layer-by-layer fabrication creates anisotropic structures where inter-layer adhesion represents potential failure planes. The degree of conversion in photopolymerized resins is often lower than in heat-processed materials, and the rapid polymerization kinetics can result in internal stresses and incomplete cross-linking. Additionally, oxygen inhibition at layer interfaces and incomplete monomer conversion contribute to inferior mechanical properties (Abdelghaffar 2024).

3D printing offers unique advantages, including the ability to reproduce complex geometries and undercuts that might be challenging for milling technologies. Studies demonstrated that 3D-printed dentures exhibited superior adaptation in peripheral seal areas where minor undercuts exist, which is particularly advantageous for maxillary dentures where border seal is critical for retention (Charoenphol and Peampring 2023). However, concerns regarding the mechanical properties of printed resins persist, with studies reporting significantly lower fracture resistance in 3D-printed dentures compared to conventional heat-processed PMMA (Abdelghaffar 2024).

Comparative analysis of manufacturing techniques

Table 1 provides a comparative overview of the three primary manufacturing techniques for complete dentures: milling, 3D printing, and conventional processing. This comparison is enhanced to include underlying scientific principles that explain observed differences, moving beyond descriptive reporting to mechanistic understanding.

Table 1.

Comparison of Manufacturing Techniques for Complete Dentures with Underlying Scientific Principles

Aspect	Milled Digital Dentures	3D-Printed Digital Dentures	Conventional Dentures	Underlying Scientific Principle/Implication	Ref
Fabrication Method	Subtractive manufacturing from pre-polymerized PMMA pucks	Additive manufacturing using photopolymerization of liquid resins	Heat-polymerized PMMA with compression molding technique	Milling utilizes industrially polymerized materials with optimized cross-linking; 3D printing faces challenges of layer adhesion and incomplete conversion; conventional methods balance polymerization control with processing shrinkage	(Anadioti et al. 2020; Lee et al. 2016; Zhang et al. 2021)
Fit Accuracy	Superior in overall intaglio and primary bearing areas	Superior in peripheral/posterior palatal seal areas and undercuts	Acceptable but affected by polymerization shrinkage	Digital methods eliminate human error and material shrinkage variability; 3D printing can reproduce complex geometries; milling precision limited by tool geometry in undercuts	(Steinmassl et al. 2018)
Material Properties	Superior mechanical properties compared to 3D-printed	Improving but generally inferior mechanical properties compared to conventional and milled	Well-established mechanical properties	Pre-polymerized blocks have uniform cross-linking density and high conversion; layer-wise printing creates anisotropy and potential inter-layer weak points; conventional methods achieve good properties but with greater batch variability	(Jafarpour et al. 2024; Zeidan et al. 2022)
Surface Characteristics	Smooth surface with low biofilm formation	Rougher surface with higher biofilm formation	Good surface polish with moderate biofilm formation	Milled surfaces are machined to precise tolerances; printed surfaces retain layer lines and require post-processing; surface roughness and energy directly influence microbial adhesion through van der Waals forces and hydrophobic interactions	(Larijani et al. 2022)
Clinical Applications	Ideal for cases requiring high precision in stress-bearing areas	Beneficial for cases with undercuts and complex anatomical features	Universal application with established protocols	Material and geometric capabilities determine optimal clinical indications based on biomechanical requirements	(Jafarpour et al. 2024)
Workflow Efficiency	Digital workflow with fewer appointments	Digital workflow with fewer appointments	Multiple appointments and laboratory procedures	Digital workflows reduce manual steps and human touch-points, enabling standardization and reproducibility	(Takaichi et al. 2022)

The distinct characteristics of each manufacturing technique illustrated in Table 1 demonstrate why a personalized, evidence-based approach to fabrication method selection is essential. Clinicians must weigh material science fundamentals, biomechanical requirements, anatomical considerations, and patient-specific factors when selecting the optimal manufacturing approach.

Digital workflows in clinical practice

Digital denture fabrication typically follows one of three workflow patterns:

1. Conventional-Digital Hybrid: Conventional clinical steps (impressions, jaw relations) followed by digital laboratory processes

2. Partially Digital: Digital impressions or scans of conventional impressions, followed by digital design and manufacturing

3. Fully Digital: Intraoral scanning of edentulous arches, digital articulation, design, and manufacturing

Each approach offers different advantages depending on the specific clinical scenario, available technology, and practitioner preference. Studies noted that fully digital workflows significantly reduce the number of appointments, with some systems requiring as few as two visits compared to the conventional five-appointment process (Mubaraki et al. 2022). This efficiency translates to less chair time, reduced practitioner fatigue, and greater patient convenience.

Figure 2 illustrates the sequential processes from initial data acquisition through manufacturing to clinical outcomes assessment. Color-coded pathways demonstrate the procedural differences and convergence points across methodologies, ultimately leading to comparable clinical outcome measures.

Fig. 2.

Comparative workflow analysis of conventional, digital, and hybrid approaches in dental prosthesis fabrication. This original illustration was created for this review to synthesize workflow concepts from multiple sources

Clinical and material considerations

Retention and adaptation

The retention of complete dentures is fundamentally influenced by the accuracy of adaptation to underlying tissues. Several studies have compared the retention of digital versus conventional dentures with mixed but generally positive results favoring digital techniques.

Studies reported significantly higher retention values for 3D-printed maxillary complete dentures compared to conventional dentures (15.05 N versus 12.05 N, respectively) (Qadir and Abdulkareem 2023). Similarly, rapid prototyped dentures exhibited superior retention and patient satisfaction compared to conventional alternatives (Zohny et al. 2021).

The mechanism behind improved retention in digital dentures is multifaceted and grounded in fundamental physics and material science. First, digital manufacturing eliminates polymerization shrinkage—a phenomenon driven by reduction in free volume as monomers convert to polymer networks. Second, the precision of computer-controlled manufacturing maintains dimensional accuracy at the micrometer scale, accurately reproducing surface details captured in impressions. Third, the quality of peripheral seal relates to both geometric accuracy and material properties affecting interfacial contact and fluid film dynamics between denture and mucosa (Carlsson and Omar 2010; Charoenphol and Peampring 2023; Steinmassl et al. 2018).

Studies demonstrated that both milled and 3D-printed dentures maintain high dimensional accuracy, though with different patterns of deviation from master models. Milled dentures showed greater accuracy in primary stress-bearing areas, while 3D-printed dentures exhibited superior adaptation in peripheral and posterior palatal seal regions (Charoenphol and Peampring 2023).

Mechanical properties and durability

Critical analysis of current evidence

Before presenting comparative data, it is essential to critically evaluate the evidence base. Most studies examining mechanical properties of digital dentures are in vitro investigations using simplified loading conditions that may not fully replicate the complex oral environment. Sample sizes are often small, and standardization of testing protocols varies across studies. Furthermore, 3D printing materials are rapidly evolving, meaning that findings from studies using earlier-generation resins may not apply to current materials (Faraj et al. 2024).

Conflicting findings regarding surface roughness across studies likely reflect differences in measurement techniques (contact versus optical profilometry), surface location measured (intaglio versus polished surface), and post-processing protocols applied. These methodological variations complicate direct comparisons and highlight the need for standardized testing protocols (Abdelghaffar 2024; Osman et al. 2023).

Long-term clinical validation remains a critical gap in the literature. Most studies report outcomes over months rather than years, providing limited insight into material degradation, wear, staining, and dimensional stability over clinically relevant timeframes. The lack of controlled longitudinal studies with adequate follow-up (>3 years) represents a significant limitation in recommending digital methods as equivalent or superior to conventional techniques with century-long clinical track records (Alghazzawi 2016; Baba et al. 2016; Goodacre et al. 2018).

Comparative mechanical performance

A comprehensive comparison of digital and conventional complete dentures across multiple clinical and material parameters is presented in Table 2. This synthesis represents current evidence while acknowledging limitations and areas of uncertainty.

Table 2.

Comprehensive Comparison of Digital vs. Conventional Complete Dentures

Parameter	Digital Dentures	Conventional Dentures	Key Studies & Findings	Evidence Quality & Limitations
Clinical Efficiency	• Fewer appointments• Reduced chair time• Digital storage capability• Easier reproducibility	• Multiple appointments• Longer chair time• Physical storage requirements• More complex reproduction process	• Zupancic  (2023) (Zupancic Cepic et al. 2023): Digital dentures showed higher Sato score (73.2 ± 12.3) vs. conventional dentures (67.4 ± 11.8)• Carreiro (2021) (Carreiro et al. 2021): Digital workflow required fewer clinical sessions	Moderate evidence quality; most studies short-term; workflow efficiency well-documented but long-term maintenance requirements less clear
Retention	• 3D-Printed: Superior retention in multiple studies• Milled: Comparable or better retention than conventional	• Generally acceptable but typically lower retention values than digital alternatives	• Qadir (2023) (Qadir and Abdulkareem 2023): 3D-printed dentures significantly more retentive (15.05 N) than conventional (12.05 N) (p<0.029)• Zohny (2021) (Zohny et al. 2021): Significantly higher retention in rapid prototyped dentures	Moderate evidence; sample sizes often small; retention measurement methods vary; need for larger multicenter studies
Adaptation	• Milled: Superior fit in overall and primary stress-bearing areas• 3D-Printed: Better adaptation in peripheral/posterior palatal seal areas with undercuts	• Acceptable adaptation but generally less precise due to polymerization shrinkage	• Charoenphol (2023) (Charoenphol and Peampring 2023): Milled dentures more accurate in overall intaglio area, while 3D-printed better in peripheral seal areas• Emera (2022) (Emera et al. 2022): Statistically insignificant difference in adaptation	Moderate evidence; conflicting findings may reflect measurement methodologies; clinical significance of small dimensional differences unclear
Surface Properties	• Surface roughness comparable to conventional• 3D-Printed: Generally rougher surface leading to higher biofilm formation	• Well-established surface properties• Better polish compared to digital	• Abdelghaffar (2024) (Abdelghaffar 2024): No significant difference in surface roughness• Osman (2023) (Osman et al. 2023): 3D-printed dentures showed highest biofilm formation	Conflicting findings likely due to measurement techniques and post-processing variations; need for standardized protocols
Mechanical Properties	• Milled: Superior or comparable to conventional• 3D-Printed: Generally lower fracture resistance	• Higher fracture resistance<br>• Well-established long-term durability	• Abdelghaffar (2024) (Abdelghaffar 2024): Conventional PMMA significantly higher fracture resistance (572.49±13.07 N) vs. 3D-printed (202.51±10.35 N)• Kane (2022) (Kane and Shah 2023): Milled performed similarly to heat processed	Moderate-to-strong evidence for inferior 3D-printed properties; however, materials rapidly evolving; newer resins may perform better
Patient Satisfaction	• Generally high satisfaction scores• Better reported comfort and quality of life in some studies	•Well-established satisfaction profiles• In some studies, slightly higher OHIP scores	• Zupancic (2023) (Zupancic Cepic et al. 2023): Quality of life slightly higher in conventional (OHIP-20: 101.7±12.0) vs. digital (95.6±24.2)• Cristache (2020) (Cristache et al. 2020): OHIP-EDENT improved from 52.57 to 20.43 after 18 months	Patient satisfaction influenced by multiple factors; differences between methods generally small and clinically insignificant; placebo and novelty effects possible
Long-term Performance	• Limited long-term clinical data• Questions remain about material degradation and durability	• Well-documented long-term performance	• Cristache (2020) (Cristache et al. 2020): 18-month follow-up showed improved outcomes• Most studies <2 years follow-up	Critical gap: insufficient long-term data (>3 years) for digital methods; major limitation for clinical recommendations

Studies evaluated the shear bond strength between denture teeth and various base materials, finding that milled PMMA bases performed similarly to conventional heat-processed PMMA, while 3D-printed bases showed significantly lower bond strength (Kane and Shah 2023). This finding relates to fundamental differences in surface chemistry and topography between milled and printed materials. The machined surface of milled PMMA presents a relatively smooth, homogeneous substrate for adhesive bonding, while printed surfaces may contain uncured resin layers, polymerization inhibition zones, and complex topography that affects adhesive penetration and mechanical interlocking (Kane and Shah 2023).

Fracture resistance represents another critical consideration, with studies reporting that conventional PMMA dentures demonstrated substantially higher fracture resistance (572.49 N) compared to 3D-printed alternatives (202.51 N) [11]. This significant difference reflects fundamental material science principles: conventional and milled PMMA achieve higher cross-linking density and more uniform molecular structure compared to layer-wise photopolymerized materials. The presence of inter-layer boundaries in 3D-printed structures creates potential stress concentration sites and crack propagation pathways (Abdelghaffar 2024; Dimitrova et al. 2022).

Surface characteristics and microbial interactions

Surface characteristics of digital dentures influence both patient comfort and microbial adherence. Interestingly, studies found no significant difference in surface roughness between conventional and 3D-printed dentures, suggesting comparable patient comfort might be expected (Abdelghaffar 2024). However, manufacturing technique influences microbial properties, with 3D-printed dentures showing significantly higher Candida albicans adhesion and biofilm formation compared to conventional and milled alternatives (Osman et al. 2023).

The elevated biofilm formation on 3D-printed surfaces, despite similar macroscopic roughness measurements, likely reflects nanotopography and surface energy differences. Mrophobic effects aicrobial adhesion is governed by van der Waals forces, electrostatic interactions, and hydt the nanometer scale. Even when average roughness (Ra) values are comparable, differences in surface chemistry (residual monomers, photoinitiator byproducts) and nanoscale texture can significantly affect the thermodynamics of bacterial adhesion and the strength of interfacial bonds (Osman et al. 2023; Teughels et al. 2006).

This finding has important implications for denture stomatitis risk and emphasizes the need for meticulous oral hygiene protocols for patients with printed prostheses.

Patient satisfaction and quality of life

Patient-centered outcomes assessment

Patient-centered outcomes represent crucial measures of prosthetic success beyond purely technical parameters. A crossover study allowing patients to experience both digital and conventional dentures found that while clinical efficiency scores were slightly higher for digital dentures (particularly regarding stability), quality of life measures remained comparable between the two approaches (Zupancic Cepic et al. 2023).

Studies reported significant improvements in both Visual Analogue Scale scores and Oral Health Impact Profile for Edentulous Patients (OHIP-EDENT) scores following treatment with 3D-printed nanocomposite dentures (Zeidan et al. 2022). Other research noted that digital dentures provided better satisfaction, comfort, and retention while requiring fewer follow-up sessions compared to conventional alternatives. However, masticatory performance and quality of life measures were similar between the two approaches, suggesting that while technical improvements are achievable with digital methods, functional outcomes may reach similar endpoints (Qadir and Abdulkareem 2023).

Factors influencing patient acceptance

Factors influencing patient satisfaction with digital dentures include improved initial fit, reduced chairside adjustment time, and the ability to precisely duplicate existing dentures when replacing worn prostheses. From a broader healthcare perspective, the reduction in appointment requirements and the implementation of streamlined workflows align with value-based care models that prioritize efficiency, patient convenience, and the minimization of treatment burden. These factors are particularly important for elderly populations and for individuals facing transportation or mobility challenges (Cunha et al. 2013).

The comparable quality of life outcomes between digital and conventional dentures, despite technical differences, highlight the multifactorial nature of patient satisfaction. Psychological factors, adaptation capacity, expectations, and clinician-patient interactions all contribute to perceived treatment success. This underscores the importance of patient-centered care models that extend beyond technical excellence to encompass communication, shared decision-making, and individualized treatment planning.

Clinical applications and special considerations

Immediate complete dentures

Digital workflows offer particular advantages for immediate complete denture fabrication. Studies described a digital approach for fabricating a printed maxillary immediate complete denture for a patient with severely compromised maxillary dentition. The workflow involved intraoral scanning, virtual extractions and alveoloplasty, digital denture design, and 3D printing. This approach allowed for precise planning of post-extraction prosthetics and immediate delivery following surgery, with the opportunity to digitally duplicate and refine the prosthesis after initial healing (Mendonça et al. 2021).

The ability to virtually extract teeth and predict ridge contours represents a significant advantage over conventional immediate denture techniques, which typically require more extensive clinical judgment and experience. Additionally, digital duplication capabilities facilitate the fabrication of definitive prostheses that maintain the established aesthetic and functional parameters of the immediate denture while incorporating adaptations for healed tissues (Mendonça et al. 2021).

The geriatric patient

Elderly patients may particularly benefit from digital denture approaches, and this application has broader implications for geriatric healthcare delivery and aging-in-place models. The global demographic shift toward aging populations creates increasing demand for efficient, accessible prosthodontic services (Economic, 2020).

Reduced appointment numbers and shorter chair times minimize fatigue for patients with physical limitations or cognitive impairments. The improved initial fit often observed with digital dentures may also facilitate adaptation for geriatric patients who might struggle with conventional denture learning curves (Bidra et al. 2013).

Furthermore, the digital archiving of prosthetic designs provides significant advantages for elderly patients who may experience more frequent denture fractures or loss. Replacement dentures can be fabricated with minimal clinical intervention, reducing the burden on both patients and caregivers. This aspect of digital technology aligns with supportive care models and teledentistry concepts, potentially enabling remote monitoring and rapid prosthesis replacement for homebound or institutionalized patients (Monterubbianesi et al. 2022) (Park et al. 2019).

Complex anatomical situations

Digital technologies offer unique solutions for patients with anatomical challenges such as severe ridge resorption, maxillofacial defects, or microstomia. The precision of digital design tools allows practitioners to maximize denture-bearing areas while carefully navigating anatomical limitations. The virtual environment permits detailed analysis of undercut areas and path of insertion considerations before physical manufacturing.

For patients with restricted mouth opening, digital approaches reduce the need for multiple impression procedures, which can be particularly challenging in these cases. Additionally, the precise control over denture thickness in digital design helps create prostheses that balance structural integrity with patient comfort for compromised ridges.

Critical evaluation of the evidence base

A rigorous review must assess not only what the literature reports but also the quality and limitations of that evidence. This critical evaluation is essential for clinicians and researchers to appropriately interpret findings and identify knowledge gaps.

Methodological considerations and quality assessment

The current evidence base for digital complete dentures consists primarily of in vitro studies, small clinical trials, and short-term observational studies. While these provide valuable preliminary data, several limitations warrant consideration:

1. Study Design Limitations: Most clinical studies comparing digital and conventional dentures are non-randomized with small sample sizes (n < 30), limiting statistical power and generalizability. Few studies employ blinding, creating potential for observer bias in subjective assessments (Emera et al. 2022; Qadir and Abdulkareem 2023; Zohny et al. 2021; Zupancic Cepic et al. 2023).

2. In Vitro Study Limitations: Laboratory studies of mechanical properties, adaptation, and surface characteristics employ standardized testing that may not fully replicate the complex, dynamic oral environment. Cyclic loading patterns, thermal cycling, and chemical exposure in laboratory settings are simplified compared to actual clinical conditions (Gopi Chander et al. 2019) (Abdelghaffar 2024; Bencharit et al. 2024).

3. Follow-up Duration: The majority of clinical studies report outcomes over 6–18 months, with very few extending beyond 2 years (Cristache et al. 2020; Goodacre et al. 2018). This limited follow-up period is insufficient to assess long-term material degradation, dimensional stability, wear patterns, and patient satisfaction trajectories that are critical for comparing new technologies to century-old conventional methods with well-established longevity.

4. Heterogeneity of Materials and Protocols: The rapid evolution of 3D printing materials and the variety of CAD/CAM systems create significant heterogeneity across studies. Findings specific to one material or system may not generalize to others, complicating evidence synthesis (Faraj et al. 2024) (Bencharit et al. 2024).

5. Publication Bias: The relatively novel nature of digital denture technologies may create publication bias favoring positive findings, with negative or null results less likely to be published or presented

Areas of robust evidence

Despite limitations, certain findings demonstrate consistency across multiple studies:

• Workflow Efficiency: Strong evidence supports reduced appointment numbers and chair time with digital workflows (Carreiro et al. 2021; Mubaraki et al. 2022; Zupancic Cepic et al. 2023).

• Milled Denture Properties: Consistent evidence indicates that milled PMMA dentures achieve mechanical properties comparable to conventional dentures (Kane and Shah 2023; Steinmassl et al. 2018; Zeidan et al. 2022).

• Dimensional Accuracy: Multiple studies confirm high dimensional accuracy of digitally manufactured dentures, particularly in primary bearing areas [8,14,26].

Areas of conflicting or limited evidence

Several important areas require further investigation:

• 3D-Printed Material Longevity: While current-generation printed resins show inferior mechanical properties, materials are rapidly evolving. Long-term clinical validation is urgently needed (Dimitrova et al. 2022) (Abdelghaffar 2024).

• Cost-Effectiveness: Comprehensive economic analyses accounting for equipment costs, material expenses, labor time, and long-term maintenance are lacking (Kalberer et al. 2019; Srinivasan et al. 2018).

• Patient Preference and Adaptation: Studies show variable results regarding patient satisfaction differences between digital and conventional dentures, likely reflecting multiple confounding factors (Carreiro et al. 2021; Cristache et al. 2020; Zupancic Cepic et al. 2023).

• Surface Properties and Biofilm Formation: Conflicting findings regarding surface roughness and microbial adhesion likely reflect methodological differences in measurement techniques and post-processing protocols (Abdelghaffar 2024; Osman et al. 2023).

This critical appraisal reveals that while digital denture technologies show promise, evidence quality is generally moderate, and significant knowledge gaps persist. Clinicians should interpret the literature judiciously, recognizing that current evidence supports cautious implementation rather than wholesale replacement of conventional techniques.

Future directions and emerging technologies

Material science advancements

The future of digital dentures is intrinsically linked to advances in polymer chemistry and materials science. Rather than simply listing possibilities, we must envision how fundamental material innovations will transform clinical practice (Bencharit et al. 2024).

The evolution of printable denture materials continues at a rapid pace, with manufacturers developing resins with improved mechanical properties, biocompatibility, and aesthetics. Research evaluated the physical properties of newer 3D-printed denture materials, finding significant variability in bonding strength and wear resistance between manufacturers, highlighting the importance of material selection and the potential for continued improvement (Smith et al. 2021).

Promising developments include:

1. Nanoparticle-Reinforced Composites: Incorporation of ceramic or metallic nanoparticles (TiO2, ZrO2, silica) can enhance mechanical properties, reduce microbial adhesion, and improve biocompatibility. Studies demonstrated successful clinical outcomes using PMMA-TiO2 nanocomposites for 3D-printed dentures (Cristache et al. 2020). The mechanism involves nanoparticles acting as stress transfer agents and crack deflection sites, improving fracture toughness while potentially providing antimicrobial properties through photocatalytic effects (Reymus et al. 2020) (Cristache et al. 2020).

2. Gradient and Functionally Graded Materials: Future denture bases may incorporate spatially varying material properties—softer, more compliant materials at the tissue interface for comfort and stress distribution, transitioning to harder, more wear-resistant materials at occlusal surfaces. This biomimetic approach mirrors natural tooth structure (enamel-dentin-pulp gradient) and bone architecture (cortical-trabecular transition) (Zhang et al. 2013).

3. Self-Healing and Adaptive Materials: Research into polymers with dynamic covalent bonds or supramolecular structures could yield denture materials capable of autonomous repair of micro-cracks, potentially extending prosthesis lifespan and reducing catastrophic fracture incidence (Yang and Urban 2013).

4. Bioactive and Antimicrobial Materials: Integration of antimicrobial agents (quaternary ammonium compounds, antimicrobial peptides) or bioactive molecules (growth factors, remineralizing agents) directly into denture base materials could reduce denture stomatitis incidence and promote tissue health (Gendreau and Loewy 2011).

Artificial intelligence and machine learning integration

Artificial intelligence applications in digital denture design represent an emerging frontier with transformative potential that extends beyond incremental improvement to fundamental paradigm shift.

Machine learning algorithms could potentially:

1. Automated Optimal Design: Analyze thousands of successful denture cases to identify optimal tooth arrangements, occlusal schemes, and base contours for specific anatomical situations. Deep learning models trained on large datasets of successful clinical outcomes could recognize patterns imperceptible to human clinicians, potentially standardizing and improving outcomes across practitioners with varying expertise.

2. Predictive Analytics for Patient Outcomes: AI models could forecast patient adaptation challenges, identify optimal pressure distribution patterns for specific ridge morphologies, and predict long-term retention and stability based on anatomical parameters and patient characteristics (Esteva et al. 2017).

3. Real-Time Fabrication Optimization: Integration of AI with manufacturing processes could enable real-time adjustment of printing or milling parameters based on material behavior, environmental conditions, and quality monitoring, ensuring consistent output quality (Wang et al. 2011).

4. Personalized Treatment Planning: By integrating patient medical history, anatomical scans, functional assessment data, and genomic information, AI systems could recommend truly personalized prosthodontic approaches aligned with precision medicine principles (Ashley 2016).

AI-assisted design could particularly benefit clinicians with limited experience in complete denture therapy, potentially democratizing access to high-quality prosthodontic care. However, ethical considerations regarding clinical decision-making autonomy, algorithm transparency, and liability must be addressed as these technologies mature.

Smart dentures and sensor integration

The convergence of digital fabrication with micro-electronics and sensor technologies opens possibilities for "smart dentures" that actively monitor and respond to the oral environment:

1. Masticatory Force Monitoring: Embedded pressure sensors could provide real-time feedback on occlusal forces, enabling objective assessment of masticatory function and early detection of adverse loading patterns that could lead to tissue trauma or prosthesis fracture (Beaulieu-Jones et al., 2016).

2. Medication Delivery Systems: Integration of controlled-release drug delivery systems within denture bases could enable localized treatment of denture stomatitis or other oral pathologies (Fine et al. 2013).

3. Health Monitoring: Sensors detecting salivary biomarkers, pH changes, or temperature variations could provide early warning of systemic health changes, aligning with the concept of the oral cavity as a window to systemic health (Giannobile et al. 2009).

4. Adaptive Dentures: Future materials incorporating stimuli-responsive polymers could adjust their properties (stiffness, surface characteristics) in response to environmental conditions or patient needs, optimizing comfort and function dynamically (Stuart et al. 2010).

Integration with complementary digital technologies

The true potential of digital dentures emerges through integration with complementary technologies, creating comprehensive digital ecosystems for prosthodontic care:

1. Cone-Beam Computed Tomography Integration: Combining CBCT data with intraoral scans enables visualization of underlying bone morphology and soft tissue thickness, facilitating optimal pressure distribution in denture design and predictive modeling of tissue response (Beuer et al. 2008).

2. Three-Dimensional Facial Scanning: Integration of 3D facial metrics into tooth arrangement algorithms could enhance aesthetic outcomes by incorporating facial symmetry, proportions, and dynamic smile analysis into prosthetic design (Cai and Liu 2022) (Park et al. 2019).

3. Digital Implant Planning: Seamless integration of digital denture workflows with computer-guided implant planning allows coordinated transition from conventional complete dentures to implant-supported overdentures, improving treatment predictability and patient outcomes (D'haese et al., 2017).

4. Teledentistry and Remote Monitoring: Digital archiving and telecommunication technologies could enable remote consultation, virtual try-ins, and rapid prosthesis replacement for patients with geographic or mobility barriers, expanding access to prosthodontic care (Monterubbianesi et al. 2022).

Four-dimensional printing and programmable materials

Looking further ahead, four-dimensional (4D) printing, which refers to additive manufacturing of structures capable of changing their shape or properties over time in response to external stimuli such as temperature, moisture, or pH, represents an emerging frontier technology with promising potential for future prosthodontic applications:

Materials that adapt their shape to optimize fit after initial placement, respond to temperature or moisture changes to enhance retention, or undergo programmed degradation to facilitate staged tissue conditioning represent possibilities at the intersection of materials science, engineering, and biology (Tibbits 2014).

Clinical recommendations and decision-making framework

Based on critical evaluation of current evidence and consideration of fundamental scientific principles, the following recommendations provide a framework for thoughtful implementation of digital denture technologies.

Evidence-based case selection

Digital dentures appear particularly advantageous for:

1. Immediate Dentures: Digital workflows enabling virtual surgical planning and precise prosthesis fabrication (Mendonça et al. 2021).

2. Time-Constrained Patients: Individuals requiring fewer appointments due to geographic, occupational, or health limitations (Carreiro et al. 2021; Mubaraki et al. 2022).

3. Denture Duplication or Replacement: Cases where existing prostheses are satisfactory but require replacement due to wear or damage (Baba et al. 2021; Mendonça et al. 2021).

4. Complex Anatomical Cases: Situations requiring precise reproduction of undercuts or detailed peripheral seal areas (Charoenphol and Peampring 2023).

5. Geriatric Patients with Mobility Limitations: Reduced appointment burden particularly beneficial for elderly or frail populations (Cunha et al. 2013) (Bidra et al. 2013).

Workflow selection strategy

Practitioners should consider a staged approach to digital implementation:

1. Entry Level: Hybrid workflows combining conventional impressions with digital design and manufacturing offer accessible entry points for practices new to digital technology

2. Intermediate Level: Partial digital workflows incorporating intraoral scanning with conventional jaw relation records

3. Advanced Level: Fully digital workflows appropriate for practices with comprehensive digital infrastructure and expertise

Selection should balance practice capabilities, patient needs, and economic considerations rather than pursuing technology for its own sake.

Material selection guidelines

Based on current evidence:

1. High Functional Demand Cases: For patients with higher masticatory forces, parafunctional habits, or implant-supported overdentures, milled PMMA currently offers superior mechanical properties [6,11]

2. Complex Geometry Cases: Situations requiring precise reproduction of peripheral seal areas or complex undercuts may benefit from 3D printing capabilities (Charoenphol and Peampring 2023).

3. Aesthetic Priority Cases: Both technologies can achieve excellent aesthetics; selection should prioritize mechanical and biological considerations

4. Consideration of Emerging Materials: Newer-generation 3D printing resins show improved properties; clinicians should stay informed about material evolution (Smith et al. 2021).

Patient communication and informed consent

Patients should be informed about:

1. The relative novelty of digital denture materials, particularly 3D-printed resins

2. Limited long-term clinical data compared to conventional methods

3. Potential advantages (fewer appointments, precise reproducibility) and limitations (material properties, costs)

4. Individual suitability based on anatomical, functional, and economic factors

This transparency enables shared decision-making and sets appropriate expectations.

Hygiene protocols and maintenance

Given potential for increased microbial adherence to some printed materials, comprehensive denture hygiene instructions are essential:

1. Regular mechanical cleaning with appropriate brushes

2. Chemical disinfection protocols appropriate for material type

3. Professional cleaning and assessment at regular intervals

4. Patient education regarding denture stomatitis risk factors

Particular emphasis should be placed for patients with compromised immune function or diabetes (Osman et al. 2023).

Economic considerations

Practitioners should conduct individualized cost-benefit analyses considering:

1. Initial equipment and software investment

2. Material costs per prosthesis

3. Labor time and personnel training requirements

4. Practice volume and patient demographics

5. Potential for expanded service offerings

6. Long-term maintenance and equipment depreciation

Current evidence does not clearly establish superior cost-effectiveness for either digital or conventional approaches; economic viability depends heavily on practice-specific factors (Kalberer et al. 2019; Srinivasan et al. 2018).

Continuing education and skill development

The steep learning curve associated with digital workflows necessitates:

1. Structured training programs for clinicians and laboratory technicians

2. Ongoing education regarding material properties and technological advances

3. Clinical mentorship and case review

4. Participation in professional networks and study clubs focused on digital dentistry

Investment in human capital is as critical as investment in technology (Steinmassl et al. 2017).

Conclusion

Summary of key findings

Digital removable complete dentures represent more than incremental technological advancement—they embody a fundamental paradigm shift from artisanal craftsmanship to data-driven, precision biomanufacturing in prosthodontic care. Current evidence, while demonstrating moderate quality overall, suggests comparable or superior retention and patient satisfaction with digital dentures, particularly following appropriate adjustments and adaptation periods. Milled dentures currently demonstrate mechanical properties more similar to conventional dentures than their printed counterparts, though rapid advancements in printable materials may soon address these differences.

Critical evaluation of the evidence base reveals both strengths and limitations. While workflow efficiency and dimensional accuracy are well-documented, significant knowledge gaps persist regarding long-term material performance, comprehensive cost-effectiveness, and optimal patient selection criteria. The rapid evolution of materials and technologies creates a moving target for evidence-based recommendations.

Fundamental scientific principles

Understanding the "why" behind clinical observations is essential for advancing the field:

• Material science principles governing polymer chemistry, cross-linking mechanisms, and structure-property relationships explain observed differences in mechanical performance between manufacturing methods

• Surface science and microbiology fundamentals elucidate why nanotopography and surface energy affect microbial adhesion despite similar macroscopic roughness

• Biomechanical principles clarify how dimensional accuracy and adaptation influence retention through peripheral seal physics and pressure distribution

• Manufacturing engineering concepts explain the inherent trade-offs between different fabrication approaches

Future innovations must build upon these fundamental principles rather than pursuing technology for its own sake.

Broader healthcare and societal implications

The significance of digital denture technologies extends beyond prosthodontics to broader scientific and societal domains:

1. Aging Population Health: As global demographics shift toward older populations, efficient, accessible prosthodontic solutions become increasingly critical for maintaining quality of life, nutritional health, and social engagement (Economic, 2020).

2. Healthcare Automation and Standardization: Digital workflows demonstrate how automation can enhance consistency while preserving opportunities for individualized, patient-centered care—lessons applicable across healthcare delivery (Porter 2010).

3. Precision Medicine Integration: Digital denture fabrication exemplifies patient-specific therapeutic approaches aligned with precision medicine principles, with potential for future integration of genetic, physiological, and behavioral data (Ashley 2016).

4. Biomimetic Material Design: Advances in denture materials contribute to broader understanding of synthetic-biological interfaces and inform development of other biomedical devices (Zhang et al. 2013).

5. Artificial Intelligence in Healthcare: AI-assisted denture design represents microcosm of broader questions regarding algorithm transparency, clinical decision-making autonomy, and human-machine collaboration in healthcare (Choi and Kim 2015).

Research priorities and future directions

Advancing the field requires coordinated efforts across multiple domains:

1. Long-Term Clinical Validation: Rigorously designed, adequately powered, longitudinal studies (≥5 years) comparing digital and conventional dentures with standardized outcome measures (Alghazzawi 2016).

2. Material Science Innovation: Development of next-generation polymers addressing current limitations in 3D-printed materials while exploring functionally graded, self-healing, and bioactive materials (Gendreau and Loewy 2011).

3. Artificial Intelligence and Machine Learning: Translation of AI/ML research into clinically validated design algorithms with appropriate regulatory oversight and ethical frameworks (Ashley 2016).

4. Economic and Health Services Research: Comprehensive cost-effectiveness analyses across diverse healthcare settings and patient populations, including societal perspective analyses (Drummond et al. 2015).

5. Patient-Centered Outcomes Research: Investigation of patient preferences, adaptation patterns, and quality of life trajectories using validated instruments in diverse populations (Wismeijer et al. 2018).

6. Standardization Efforts: Development of consensus protocols for manufacturing, testing, and clinical application to enable meaningful comparison across studies and systems (Russo et al. 2019).

7. Integration Research: Studies examining optimal combination of digital denture technologies with complementary innovations (CBCT, facial scanning, implant planning, teledentistry) (Cooke et al. 1988) (Beuer et al. 2008).

Clinical implementation philosophy

The clinical implementation of digital denture technology should be approached with scientific rigor, clinical wisdom, and patient-centered values. While digital workflows offer important benefits including reduced appointment numbers, precise reproducibility, and digital archiving capabilities, conventional techniques remain viable alternatives with well-established long-term outcomes. The decision to implement digital technologies should reflect thoughtful consideration of specific patient needs, material limitations, economic factors, and evidence quality rather than technological enthusiasm alone.

Excellence in prosthodontic care, whether achieved through conventional or digital approaches, depends on the integration of technical expertise, scientific understanding, clinical judgment, and compassionate patient communication. Digital technologies serve as powerful tools that, when applied appropriately, can enhance the delivery of patient-centered care. However, they do not replace the fundamental clinical competencies and humanistic principles that remain central to high-quality prosthodontic practice.

Vision for the future

As digital denture technologies continue to evolve, the field stands at an inflection point. The convergence of advanced materials, artificial intelligence, sensor technologies, and digital manufacturing creates unprecedented opportunities for transforming prosthodontic care. However, realizing this potential requires continued commitment to:

• Rigorous scientific investigation guided by fundamental principles

• Critical evaluation of evidence quality and limitations

• Patient-centered implementation that prioritizes outcomes over novelty

• Ethical frameworks for emerging technologies

• Interdisciplinary collaboration across materials science, engineering, computer science, and clinical dentistry

• Accessible, equitable distribution of technological benefits across diverse populations

The ultimate measure of success will not be technological sophistication but rather improvement in patient health, quality of life, and access to care. This patient-centered, scientifically grounded approach positions the field to harness digital innovations while maintaining the humanistic values that define healthcare excellence.

Authors’ contributions

P.M.: Literature search strategy development, data curation, formal analysis, investigation, exporting, visualization, translation, and writing – original draft. S.Z.: Conceptualization, validation, disseminating results, Supervision, project administration, methodology, and writing – review & editing. All authors read and approved the final manuscript.

Funding

No specific funding was received from public, commercial, or non-profit funding agencies for the conduct of this study.

Data availability

The data supporting the findings of this study are available from the corresponding author upon reasonable request.

Declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable to this study.

Competing interests

The authors declare that they have no competing interests.