Evaluating the stability of extended-pour alginate impression materials by using an optical scanning and digital method.

The dimensional stability of alginate dental impressions is a key factor for the reliability of delayed gypsum pouring and digital scanning. However, studies of the dimensional stability of alginates with conventional methods that consider the dimensional variations of large impressions are lacking. The purpose of this in vitro study was to investigate and compare 2 digital methods for the analysis of dimensional stability of large impressions made with 5 different extended-pour alginates and to assess dimensional stability up to 5 days. Impressions of a simplified master maxillary model were made with Alginoplast, Blueprint, Hydrogum 5, Orthoprint, and Phase Plus and then analyzed at different time points. Digital scans of the alginate impression surfaces were obtained with a desktop scanner and analyzed by evaluating the linear measurements between reference points and by using a novel method that consists of the analysis of the entire scanned surface to evaluate the expansion and contraction of the impressions. The first method revealed that the dimensional changes did not exceed 0.5%, with the exception of Phase Plus at day 3 (-0.6 ±0.7%), and the average dimensional variation was always lower than or equal to 0.2 mm. Blueprint was the most stable material (-0.2 ±0.6%). The second method revealed dimensional variations always lower than 0.03 mm and confirmed Blueprint as the best performing material (0.001 ±0.006 mm) and Phase Plus the worst (-0.019 ±0.006 mm). Both the methods used to evaluate alginate stability showed that the analyzed materials remain stable over time; the dimensional variations showed a similar trend, with differences in the absolute values depending on the applied method. Linear measurements are affected by the operator and choice of reference points; however, by evaluating the average variations of the entire structure surfaces, local variations should be minimized. The evaluation of the average variations with the second method offers the advantage of a rapid visual representation of these variations.

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