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

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).

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.

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.

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.

The smaller software-rendered contact/penetration footprint highlights AI-JM's potential to complement virtual occlusal assessment when planning monolithic restorations.