Contact and penetration patterns in digital jaw-motion workflows: a within-case comparison

BACKGROUND: In fully digital workflows for monolithic restorations, virtual articulation combines interarch alignment with simulated movement. Wear-facet-informed AI estimates movement paths from intraoral scan morphology. This exploratory within-case study compared three workflows' software-rendered contact/penetration footprints using Contact Area Fraction (CAF). METHODS: Fourteen paired intraoral scan datasets underwent exocad processing using IOS-derived maximal intercuspal position (MIP) with average-value virtual articulation (IOS-AV; a common chairside digital reference), AI-derived MIP with axiography-programmed virtual articulation (AX), and the same AI-derived MIP with AI jaw-motion file-driven simulation (AI-JM). A pre-specified Python pipeline quantified CAF (%) as the proportion of red plus magenta pixels within the mapped region of exported color-coded 3D proximity/contact PDFs. Paired within-case comparisons used Friedman and post-hoc Wilcoxon signed-rank tests with Holm correction. RESULTS: CAF differed significantly among workflows (Friedman χ²(2)=13.86, p=0.001; Kendall's W=0.495). Median (IQR) CAF was 2.19% (1.59-3.67) for AI-JM, 3.01% (2.40-4.20) for AX, and 3.56% (2.57-4.50) for IOS-AV. AI-JM yielded the lowest CAF in 12/14 cases and significantly lower CAF than AX and IOS-AV (both Holm-adjusted p=0.04); AX and IOS-AV did not differ significantly. CONCLUSIONS: AI-JM showed a smaller combined contact/penetration footprint than the tested comparators under the study conditions. IOS-AV comparisons reflect differences in both initial alignment and movement simulation; AX and AI-JM shared identical AI-derived alignment. Findings concern geometric compatibility with recorded morphology, not independently validated patient-specific movement accuracy. CLINICAL SIGNIFICANCE: The smaller software-rendered contact/penetration footprint highlights AI-JM's potential to complement virtual occlusal assessment when planning monolithic restorations.

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Publication Details

Journal
Journal of Dentistry
Published
2026-11-01
DOI
https://doi.org/10.1016/j.jdent.2026.107146
Primary Topic
Dental materials and restorations
Type
article
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article

Contact and penetration patterns in digital jaw-motion workflows: a within-case comparison

Gyula Marada, Attila Mühl, Kinga Turzó, Judit Borbély et al.
7 links
Journal of Dentistry
Dental materials and restorations
article

Contact and penetration patterns in digital jaw-motion workflows: a within-case comparison

Gyula Marada, Attila Mühl, Kinga Turzó, Judit Borbély, Patrik Sashegyi, József Prugberger, Ákos Nagy
article en

Abstract

BACKGROUND: In fully digital workflows for monolithic restorations, virtual articulation combines interarch alignment with simulated movement. Wear-facet-informed AI estimates movement paths from intraoral scan morphology. This exploratory within-case study compared three workflows' software-rendered contact/penetration footprints using Contact Area Fraction (CAF). METHODS: Fourteen paired intraoral scan datasets underwent exocad processing using IOS-derived maximal intercuspal position (MIP) with average-value virtual articulation (IOS-AV; a common chairside digital reference), AI-derived MIP with axiography-programmed virtual articulation (AX), and the same AI-derived MIP with AI jaw-motion file-driven simulation (AI-JM). A pre-specified Python pipeline quantified CAF (%) as the proportion of red plus magenta pixels within the mapped region of exported color-coded 3D proximity/contact PDFs. Paired within-case comparisons used Friedman and post-hoc Wilcoxon signed-rank tests with Holm correction. RESULTS: CAF differed significantly among workflows (Friedman χ²(2)=13.86, p=0.001; Kendall's W=0.495). Median (IQR) CAF was 2.19% (1.59-3.67) for AI-JM, 3.01% (2.40-4.20) for AX, and 3.56% (2.57-4.50) for IOS-AV. AI-JM yielded the lowest CAF in 12/14 cases and significantly lower CAF than AX and IOS-AV (both Holm-adjusted p=0.04); AX and IOS-AV did not differ significantly. CONCLUSIONS: AI-JM showed a smaller combined contact/penetration footprint than the tested comparators under the study conditions. IOS-AV comparisons reflect differences in both initial alignment and movement simulation; AX and AI-JM shared identical AI-derived alignment. Findings concern geometric compatibility with recorded morphology, not independently validated patient-specific movement accuracy. CLINICAL SIGNIFICANCE: The smaller software-rendered contact/penetration footprint highlights AI-JM's potential to complement virtual occlusal assessment when planning monolithic restorations.

Journal of Dentistry
Semmelweis University (HU), University of Pecs (HU)
Good health and well-being
Openalex Percentile: Top 10%
Dental materials and restorations
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