Influence of Scanner Precision and Analysis Software in Quantifying Three-Dimensional Intraoral Changes: Two-Factor Factorial Experimental Design

BackgroundThree-dimensional scans are increasingly used to quantify biological topographical changes and clinical health outcomes. Traditionally, the use of 3D scans has been limited to specialized centers owing to the high cost of the scanning equipment and the necessity for complex analysis softwa...

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Main Authors: O'Toole, Saoirse, Bartlett, David, Keeling, Andrew, McBride, John, Bernabe, Eduardo, Crins, Luuk, Loomans, Bas
Format: Article
Language:English
Published: JMIR Publications 2020-11-01
Series:Journal of Medical Internet Research
Online Access:https://www.jmir.org/2020/11/e17150
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author O'Toole, Saoirse
Bartlett, David
Keeling, Andrew
McBride, John
Bernabe, Eduardo
Crins, Luuk
Loomans, Bas
author_facet O'Toole, Saoirse
Bartlett, David
Keeling, Andrew
McBride, John
Bernabe, Eduardo
Crins, Luuk
Loomans, Bas
author_sort O'Toole, Saoirse
collection DOAJ
description BackgroundThree-dimensional scans are increasingly used to quantify biological topographical changes and clinical health outcomes. Traditionally, the use of 3D scans has been limited to specialized centers owing to the high cost of the scanning equipment and the necessity for complex analysis software. Technological advances have made cheaper, more accessible methods of data capture and analysis available in the field of dentistry, potentially facilitating a primary care system to quantify disease progression. However, this system has yet to be compared with previous high-precision methods in university hospital settings. ObjectiveThe aim of this study was to compare a dental primary care method of data capture (intraoral scanner) with a precision hospital-based method (laser profilometer) in addition to comparing open source and commercial software available for data analysis. MethodsLongitudinal dental wear data from 30 patients were analyzed using a two-factor factorial experimental design. Bimaxillary intraoral digital scans (TrueDefinition, 3M, UK) and conventional silicone impressions, poured in type-4 dental stone, were made at both baseline and follow-up appointments (mean 36 months, SD 10.9). Stone models were scanned using precision laser profilometry (Taicaan, Southampton, UK). Three-dimensional changes in both forms of digital scans of the first molars (n=76) were quantitatively analyzed using the engineering software Geomagic Control (3D Systems, Germany) and freeware WearCompare (Leeds Digital Dentistry, UK). Volume change (mm3) was the primary measurement outcome. The maximum point loss (μm) and the average profile loss (μm) were also recorded. Data were paired and skewed, and were therefore compared using Wilcoxon signed-rank tests with Bonferroni correction. ResultsThe median (IQR) volume change for Geomagic using profilometry and using the intraoral scan was –0.37 mm3 (–3.75-2.30) and +0.51 mm3 (–2.17-4.26), respectively (P<.001). Using WearCompare, the median (IQR) volume change for profilometry and intraoral scanning was –1.21 mm3 (–3.48-0.56) and –0.39 mm3 (–3.96-2.76), respectively (P=.04). WearCompare detected significantly greater volume loss than Geomagic regardless of scanner type. No differences were observed between groups with respect to the maximum point loss or average profile loss. ConclusionsAs expected, the method of data capture, software used, and measurement metric all significantly influenced the measurement outcome. However, when appropriate analysis was used, the primary care system was able to quantify the degree of change and can be recommended depending on the accuracy needed to diagnose a condition. Lower-resolution scanners may underestimate complex changes when measuring at the micron level.
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spelling doaj.art-e933b843a3b94809bb01098d0e8d6aee2022-12-21T20:12:05ZengJMIR PublicationsJournal of Medical Internet Research1438-88712020-11-012211e1715010.2196/17150Influence of Scanner Precision and Analysis Software in Quantifying Three-Dimensional Intraoral Changes: Two-Factor Factorial Experimental DesignO'Toole, SaoirseBartlett, DavidKeeling, AndrewMcBride, JohnBernabe, EduardoCrins, LuukLoomans, BasBackgroundThree-dimensional scans are increasingly used to quantify biological topographical changes and clinical health outcomes. Traditionally, the use of 3D scans has been limited to specialized centers owing to the high cost of the scanning equipment and the necessity for complex analysis software. Technological advances have made cheaper, more accessible methods of data capture and analysis available in the field of dentistry, potentially facilitating a primary care system to quantify disease progression. However, this system has yet to be compared with previous high-precision methods in university hospital settings. ObjectiveThe aim of this study was to compare a dental primary care method of data capture (intraoral scanner) with a precision hospital-based method (laser profilometer) in addition to comparing open source and commercial software available for data analysis. MethodsLongitudinal dental wear data from 30 patients were analyzed using a two-factor factorial experimental design. Bimaxillary intraoral digital scans (TrueDefinition, 3M, UK) and conventional silicone impressions, poured in type-4 dental stone, were made at both baseline and follow-up appointments (mean 36 months, SD 10.9). Stone models were scanned using precision laser profilometry (Taicaan, Southampton, UK). Three-dimensional changes in both forms of digital scans of the first molars (n=76) were quantitatively analyzed using the engineering software Geomagic Control (3D Systems, Germany) and freeware WearCompare (Leeds Digital Dentistry, UK). Volume change (mm3) was the primary measurement outcome. The maximum point loss (μm) and the average profile loss (μm) were also recorded. Data were paired and skewed, and were therefore compared using Wilcoxon signed-rank tests with Bonferroni correction. ResultsThe median (IQR) volume change for Geomagic using profilometry and using the intraoral scan was –0.37 mm3 (–3.75-2.30) and +0.51 mm3 (–2.17-4.26), respectively (P<.001). Using WearCompare, the median (IQR) volume change for profilometry and intraoral scanning was –1.21 mm3 (–3.48-0.56) and –0.39 mm3 (–3.96-2.76), respectively (P=.04). WearCompare detected significantly greater volume loss than Geomagic regardless of scanner type. No differences were observed between groups with respect to the maximum point loss or average profile loss. ConclusionsAs expected, the method of data capture, software used, and measurement metric all significantly influenced the measurement outcome. However, when appropriate analysis was used, the primary care system was able to quantify the degree of change and can be recommended depending on the accuracy needed to diagnose a condition. Lower-resolution scanners may underestimate complex changes when measuring at the micron level.https://www.jmir.org/2020/11/e17150
spellingShingle O'Toole, Saoirse
Bartlett, David
Keeling, Andrew
McBride, John
Bernabe, Eduardo
Crins, Luuk
Loomans, Bas
Influence of Scanner Precision and Analysis Software in Quantifying Three-Dimensional Intraoral Changes: Two-Factor Factorial Experimental Design
Journal of Medical Internet Research
title Influence of Scanner Precision and Analysis Software in Quantifying Three-Dimensional Intraoral Changes: Two-Factor Factorial Experimental Design
title_full Influence of Scanner Precision and Analysis Software in Quantifying Three-Dimensional Intraoral Changes: Two-Factor Factorial Experimental Design
title_fullStr Influence of Scanner Precision and Analysis Software in Quantifying Three-Dimensional Intraoral Changes: Two-Factor Factorial Experimental Design
title_full_unstemmed Influence of Scanner Precision and Analysis Software in Quantifying Three-Dimensional Intraoral Changes: Two-Factor Factorial Experimental Design
title_short Influence of Scanner Precision and Analysis Software in Quantifying Three-Dimensional Intraoral Changes: Two-Factor Factorial Experimental Design
title_sort influence of scanner precision and analysis software in quantifying three dimensional intraoral changes two factor factorial experimental design
url https://www.jmir.org/2020/11/e17150
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