Effects of Storage Time, Internal Design and Printing Workflow on Accuracy and Stability of 3D-Printed Dental Models

INTRODUCTION AND AIMS: Accurate, stable 3D-printed models are essential for digital dental workflows. This study evaluated the effects of storage time, internal design and printing workflows on the dimensional stability and accuracy of dental models. METHODS: A maxillary typodont was scanned to generate a reference digital model. Three internal designs were created: hollow with perforated base (HB), solid (S) and support structure with perforated base (SB). Sixty models fabricated via Form 3 (SLA) and Straumann P30+ (DLP) printers were stored under controlled indoor conditions and scanned at 7 time points within 4 weeks. Geomagic Control software analysed accuracy (trueness/precision via best-fit alignment and root mean square [RMS] values) and volume. RESULTS: For the DLP workflow, trueness and volume significantly changed over time (P < .001). Trueness decreased after 2 weeks for S and SB and after 3 weeks for HB. Volume decreased after 1 week for all designs. Precision showed no significant changes. Volume was negatively correlated with trueness (RMS values) and storage time, while storage time positively correlated with trueness (RMS values) (all P < .001). Conversely, models printed by the SLA workflow showed no significant changes in trueness, precision, or volume over 4 weeks, demonstrating significantly higher stability than that of the DLP workflow (P < .001). Internal design had no significant effect. CONCLUSIONS: Storage time significantly affects trueness in the evaluated DLP workflow, with volumetric shrinkage being a highly probable contributing factor, whereas models printed by the SLA workflow remain stable for up to 4 weeks. Internal design showed no significant dimensional effect. CLINICAL RELEVANCE: Variations across specific printing workflows may influence the dimensional stability of dental models. To ensure accuracy, models from the evaluated DLP workflow require use within 2 weeks, whereas the tested SLA workflow is recommended for applications requiring storage or transportation.