Higher Computed Tomography (CT) Scan Resolution Improves Accuracy of Patient-specific Mandibular Models When Compared to Cadaveric Gold Standard.

BACKGROUND: 3D-printed patient-specific anatomical models are becoming an increasingly popular tool for planning reconstructive surgeries to treat oral cancer. Currently there is a lack of information regarding model accuracy, and how the resolution of the computed tomography (CT) scan affects the accuracy of the final model. PURPOSE: The primary objective of this study was to determine the CT z-axis resolution necessary in creating a patient specific mandibular model with clinically acceptable accuracy for global bony reconstruction. This study also sought to evaluate the effect of the digital sculpting and 3D printing process on model accuracy. STUDY DESIGN: This was a cross-sectional study using cadaveric heads obtained from the Ohio State University Body Donation Program. INDEPENDENT VARIABLES: The first independent variable is CT scan slice thickness of either 0.675 , 1.25, 3.00, or 5.00 mm. The second independent variable is the three produced models for analysis (unsculpted, digitally sculpted, 3D printed). MAIN OUTCOME VARIABLE: The degree of accuracy of a model as defined by the root mean square (RMS) value, a measure of a model's discrepancy from its respective cadaveric anatomy. ANALYSES: All models were digitally compared to their cadaveric bony anatomy using a metrology surface scan of the dissected mandible. The RMS value of each comparison evaluates the level of discrepancy. One-way ANOVA tests (P < .05) were used to determine statistically significant differences between CT scan resolutions. Two-way ANOVA tests (P < .05) were used to determine statistically significant differences between groups. RESULTS: CT scans acquired for 8 formalin-fixed cadaver heads were processed and analyzed. The RMS for digitally sculpted models decreased as slice thickness decreased, confirming that higher resolution CT scans resulted in statistically more accurate model production when compared to the cadaveric gold standard. Furthermore, digitally sculpted models were significantly more accurate than unsculpted models (P < .05) at each slice thickness. CONCLUSIONS: Our study demonstrated that CT scans with slice thicknesses of 3.00 mm or smaller created statistically significantly more accurate models than models created from slice thicknesses of 5.00 mm. The digital sculpting process statistically significantly increased the accuracy of models and no loss of accuracy through the 3D printing process was observed.

Exploring CT pixel and voxel size effect on anatomic modeling in mandibular reconstruction.

BACKGROUND: Computer-aided modeling and design (CAM/CAD) of patient anatomy from computed tomography (CT) imaging and 3D printing technology enable the creation of tangible, patient-specific anatomic models that can be used for surgical guidance. These models have been associated with better patient outcomes; however, a lack of CT imaging guidelines risks the capture of unsuitable imaging for patient-specific modeling. This study aims to investigate how CT image pixel size (X-Y) and slice thickness (Z) impact the accuracy of mandibular models. METHODS: Six cadaver heads were CT scanned at varying slice thicknesses and pixel sizes and turned into CAD models of the mandible for each scan. The cadaveric mandibles were then dissected and surface scanned, producing a CAD model of the true anatomy to be used as the gold standard for digital comparison. The root mean square (RMS) value of these comparisons, and the percentage of points that deviated from the true cadaveric anatomy by over 2.00 mm were used to evaluate accuracy. Two-way ANOVA and Tukey-Kramer post-hoc tests were used to determine significant differences in accuracy. RESULTS: Two-way ANOVA demonstrated significant difference in RMS for slice thickness but not pixel size while post-hoc testing showed a significant difference in pixel size only between pixels of 0.32 mm and 1.32 mm. For slice thickness, post-hoc testing revealed significantly smaller RMS values for scans with slice thicknesses of 0.67 mm, 1.25 mm, and 3.00 mm compared to those with a slice thickness of 5.00 mm. No significant differences were found between 0.67 mm, 1.25 mm, and 3.00 mm slice thicknesses. Results for the percentage of points deviating from cadaveric anatomy greater than 2.00 mm agreed with those for RMS except when comparing pixel sizes of 0.75 mm and 0.818 mm against 1.32 mm in post-hoc testing, which showed a significant difference as well. CONCLUSION: This study suggests that slice thickness has a more significant impact on 3D model accuracy than pixel size, providing objective validation for guidelines favoring rigorous standards for slice thickness while recommending isotropic voxels. Additionally, our results indicate that CT scans up to 3.00 mm in slice thickness may provide an adequate 3D model for facial bony anatomy, such as the mandible, depending on the clinical indication.