Quantitative 3D Evaluation of Facial Soft Tissue Modifications Following Complete Denture Treatment in Edentulous Patients: A Prospective Before–After Study

<b>Background</b>: Three-dimensional (3D) facial scanning is an objective, non-invasive method for quantifying facial soft-tissue changes following complete denture (CD) rehabilitation. Reliable quantification of these changes in completely edentulous patients can support more predictable aesthetic and functional outcomes. <b>Methods</b>: This prospective before-after observational study included 30 completely edentulous patients (12 men, 18 women; age 48-87 years; mean ± SD: 67.8 ± 9.2 years) who received new maxillary and mandibular CDs. Structured-light 3D facial scans were obtained at baseline (edentulous, without dentures) and post-rehabilitation with dentures in place, in relaxed posture (RP) and maximal intercuspation (MI). Sixty-five validated anthropometric landmarks were analyzed. Primary outcomes were lower facial height (Sn-Gn), nasolabial angle (Cm-Sn-Ls), lower facial convexity (Ls-Li-Pg), mouth width (Ch-Ch), and upper vermilion height (Ls-Sto). Pre-post changes were assessed using paired-sample tests (<i>p</i> < 0.05). <b>Results</b>: Thirty-four of 65 parameters (52.3%) demonstrated significant post-treatment changes (<i>p</i> < 0.05), mainly in the perioral and lower facial regions. The reported parameters were selected due to their clinical relevance in evaluating perioral support and facial profile changes after complete denture treatment. In RP, upper lip thickness increased from 3.69 ± 0.97 mm to 4.96 ± 1.11 mm (Δ = +1.27 mm; <i>p</i> < 0.0001) and lower lip thickness from 6.18 ± 2.69 mm to 7.36 ± 1.52 mm (Δ = +1.18 mm; <i>p</i> = 0.0408). The nasolabial angle decreased from 116.08 ± 9.17° to 108.06 ± 9.56° (Δ = -8.02°; <i>p</i> = 0.0016). In MI, mouth width increased from 55.72 ± 3.43 mm to 57.97 ± 3.13 mm (Δ = +2.25 mm; <i>p</i> = 0.0102). <b>Conclusions</b>: Complete denture rehabilitation produces measurable, clinically relevant improvements in facial soft-tissue morphology in completely edentulous patients, particularly affecting lip support, mouth width, and the nasolabial profile. Structured-light 3D facial scanning provides a reproducible approach to objective outcome assessment and may support individualized denture design.

Authors

Institutions

Publication Details

Journal
Journal of Clinical Medicine
Published
2026-01-19
DOI
https://doi.org/10.3390/jcm15020796
Primary Topic
Orthodontics and Dentofacial Orthopedics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Quantitative 3D Evaluation of Facial Soft Tissue Modifications Following Complete Denture Treatment in Edentulous Patients: A Prospective Before–After Study

Adrian Cândea, Andrei-Bogdan Faur, I. Toser, Anca-Elena Anghel-Lorinți et al.
Journal of Clinical Medicine
Orthodontics and Dentofacial Orthopedics
article

Quantitative 3D Evaluation of Facial Soft Tissue Modifications Following Complete Denture Treatment in Edentulous Patients: A Prospective Before–After Study

Adrian Cândea, Andrei-Bogdan Faur, I. Toser, Anca-Elena Anghel-Lorinți, George Dumitru Constantin, Anca Jivanescu, Ioana Veja
article en

Abstract

<b>Background</b>: Three-dimensional (3D) facial scanning is an objective, non-invasive method for quantifying facial soft-tissue changes following complete denture (CD) rehabilitation. Reliable quantification of these changes in completely edentulous patients can support more predictable aesthetic and functional outcomes. <b>Methods</b>: This prospective before-after observational study included 30 completely edentulous patients (12 men, 18 women; age 48-87 years; mean ± SD: 67.8 ± 9.2 years) who received new maxillary and mandibular CDs. Structured-light 3D facial scans were obtained at baseline (edentulous, without dentures) and post-rehabilitation with dentures in place, in relaxed posture (RP) and maximal intercuspation (MI). Sixty-five validated anthropometric landmarks were analyzed. Primary outcomes were lower facial height (Sn-Gn), nasolabial angle (Cm-Sn-Ls), lower facial convexity (Ls-Li-Pg), mouth width (Ch-Ch), and upper vermilion height (Ls-Sto). Pre-post changes were assessed using paired-sample tests (<i>p</i> < 0.05). <b>Results</b>: Thirty-four of 65 parameters (52.3%) demonstrated significant post-treatment changes (<i>p</i> < 0.05), mainly in the perioral and lower facial regions. The reported parameters were selected due to their clinical relevance in evaluating perioral support and facial profile changes after complete denture treatment. In RP, upper lip thickness increased from 3.69 ± 0.97 mm to 4.96 ± 1.11 mm (Δ = +1.27 mm; <i>p</i> < 0.0001) and lower lip thickness from 6.18 ± 2.69 mm to 7.36 ± 1.52 mm (Δ = +1.18 mm; <i>p</i> = 0.0408). The nasolabial angle decreased from 116.08 ± 9.17° to 108.06 ± 9.56° (Δ = -8.02°; <i>p</i> = 0.0016). In MI, mouth width increased from 55.72 ± 3.43 mm to 57.97 ± 3.13 mm (Δ = +2.25 mm; <i>p</i> = 0.0102). <b>Conclusions</b>: Complete denture rehabilitation produces measurable, clinically relevant improvements in facial soft-tissue morphology in completely edentulous patients, particularly affecting lip support, mouth width, and the nasolabial profile. Structured-light 3D facial scanning provides a reproducible approach to objective outcome assessment and may support individualized denture design.

Journal of Clinical MedicineVol. 15(2)
Victor Babeș University of Medicine and Pharmacy Timișoara (RO), Vasile Goldis Western University of Arad (RO)
Good health and well-being
Openalex Percentile: Top 82%
Orthodontics and Dentofacial Orthopedics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.