Repeatability and effect of different voxel sizes on linear and volumetric tooth and pulp measurements using cone-beam computed tomography
Cone-beam computed tomography (CBCT) allows three-dimensional imaging and evaluation of the hard tissues of the maxillofacial region. This radiological technique is widely used in dental practice today, and it has the complementary advantage of being not only a tool for diagnosis and treatment planning but also a measuring device . Recently, studies evaluating tooth/pulp volume measurements using CBCT images for age determination in forensic sciences have been published . These studies are used in research such as age estimation, forensic anthropology, craniofacial reconstruction, virtual autopsies, and identification . The accuracy of volumetric measurements in 3D images may vary depending on the exposure parameters, programs, and methods used. The image quality of CBCT is affected by the voxel size, which indicates the examined object, scanning unit, field of view (FOV), scanning time, tube voltage, milliampere setting, and spatial resolution . The voxel resolution and size directly affect the image quality . The voxel size, which consists of depth, height, and width measurements in three-dimensional images, is isotropic (all dimensions are equal), and it is an important factor in the image formation time and diagnostic quality of CBCT devices. CBCT units offer voxel sizes ranging from 0.075 to 0.4 mm. The voxel size directly affects both image resolution and noise . However, the higher the voxel resolution, the higher the radiation dose; thus, the optimum voxel resolution must be determined in three-dimensional images . Voxel resolution is positively correlated with image quality. Higher diagnostic values can be obtained using smaller voxel sizes to detect minor changes, such as root fractures and root resorption . Despite the advantages of this imaging method, no evidence-based voxel guide has been developed for this protocol . On the other hand, accurate measurement of pulp and tooth volume for determining dental age, which has been frequently used in forensic sciences in recent years, is a critical factor for obtaining more successful results in determining age . Few studies have evaluated the effect of voxel resolution on pulp and tooth volume measurements . To the best of our knowledge, no study has investigated both linear and volumetric tooth measurements using three different voxels. In our study, all images were acquired in a single FOV field using three different voxel sizes, which were measured by different observers. This study aimed to analyze the effect of voxel resolution on the linear and volume measurements of tooth and pulp in three-dimensional images obtained with different voxel sizes and to test the repeatability of the measurements. We also compared the agreement between inter-observers in linear measurements with pulp-tooth volumes in CBCT images obtained using different voxel sizes. Our null hypothesis was that there would be no significant difference in repeatability or between linear&volumetric measurements of the tooth and pulp in three-dimensional images obtained with different voxel sizes. 

Study design and sample detection This study was conducted in accordance with the Declaration of Helsinki and was approved by Gazi University Faculty of Dentistry Clinical Investigations Ethics Committee (Date: 26/05/2021, No: 93437). A power analysis was performed to determine the sample size of the study. The sample size was calculated as 30 (effect size w = 0.35 for Power: 0.95). Thirty single-rooted mandibular/maxillary incisors extracted for various reasons were included in the study. The exclusion criteria were caries, restoration, cracked, abrasion, root resorption, anomaly, excess root curvature, endodontic treatment, and pulp calcification. The teeth used in this study were washed under tap water to remove any residues. Image acquisition Three-dimensional images of the teeth were obtained using a Promax 3D-Mid unit (Planmeca Oy, Helsinki, Finland). The exposure parameters were 90 kV, 5–9 mA, and 4.0 × 5.0-cm FOV. Three-dimensional images of all teeth were obtained with voxel sizes of 0.1, 0.2, and 0.4-mm (Fig. ). Details of the scan parameters were shown on Table . Volumetric data were exported into DICOM (Digital Imaging and Communications in Medicine) format. Maintenance and calibration of the imaging device are routinely performed annually by authorized technical service. During the image acquisition process with three different voxel sizes, the teeth were fixed to a wax base and scanned in the same position. Measurements Two examiners (EKK, OY) with 3 years of experience in dentomaxillofacial radiology performed all measurements separately. Prior to measurements, observers were trained and calibrated by an 8-year-experienced maxillofacial radiologist (GA) on three-dimensional images of five teeth that were not included in the study group. Images in DICOM format were transferred to the open-source medical segmentation analysis program, ITK-SNAP (Version 3.8.0, Philadelphia, PA, USA), where linear and volumetric measurements were performed. The “thresholding” option, the “contrast” setting, and the “active contour” segmentation mode are available in the software. The optimum grayscale threshold value and contrast adjustment were selected for the images. Semi-automatic segmentation of each tooth and pulp was performed. Both observers followed the same procedure for all volume measurements. To define the region of interest (ROI) for segmentation, marking was made to include all borders of the tooth to be examined in multiplanar reconstructions. The volume measurements were performed by following three guided interactive building processes. (1) A threshold range was set to create the 3D model on all voxels with gray values ​​and determine the beginning and end of the segmentation process. Threshold selection was interactive. For segmentation of the pulp, it was done by setting the upper threshold between 1600 and 1850 and the lower threshold between − 500 and − 750 based on visual analysis of the anatomical boundaries between hard tissue (dentin) and soft tissue (pulp). (2) Seed-like geometries (bubble-like formation) were added by the observer to initiate the segmentation of the region to be measured. (3) Finally, the segmentation development, velocity, and end were selected, and the segmentation process was started gradually. After this process, a 3D reconstruction image of the relevant structure was created, and its volume was obtained as cubic millimeters (mm 3 ) (Fig. ). There was no time restriction on the measurements by observers. Linear measurements were performed on the coronal and axial sections. The tooth length, root length (distance from the cement-enamel junction to the root apex), and pulp length (distance from the pulp horn to the root apex) were measured (Fig. ). Two weeks after the first examination, both observers measured 20% of the samples again for intra-observer reliability. Statistical analysis Mean values and standard deviations of volume and linear measurements were calculated using descriptive analysis. The normality of the data was analyzed using the Kolmogorov-Smirnov test, and depending on this distributional violation, nonparametric statistical analyses were used. The comparison of the effect of different voxel sizes on volumetric measurements were analyzed using Friedman test for both observers. In this study, two compatibility analyses were performed for inter-observer reliability and intra-observer repeatability. To analyze inter-observer reliability, Kendall’s tau correlation coefficient was calculated. Correlation analysis results were also corroborated using the Wilcoxon signed-rank test by analyzing the difference between two matched pairs. Intra-observer repeatability was analyzed using the intraclass correlation coefficient (ICC). Statistical analyses were performed using IBM SPSS Statistics, Version 23·0 software (Armonk, New York, USA). The significance level was set at 0.05. 

This study was conducted in accordance with the Declaration of Helsinki and was approved by Gazi University Faculty of Dentistry Clinical Investigations Ethics Committee (Date: 26/05/2021, No: 93437). A power analysis was performed to determine the sample size of the study. The sample size was calculated as 30 (effect size w = 0.35 for Power: 0.95). Thirty single-rooted mandibular/maxillary incisors extracted for various reasons were included in the study. The exclusion criteria were caries, restoration, cracked, abrasion, root resorption, anomaly, excess root curvature, endodontic treatment, and pulp calcification. The teeth used in this study were washed under tap water to remove any residues. 

Three-dimensional images of the teeth were obtained using a Promax 3D-Mid unit (Planmeca Oy, Helsinki, Finland). The exposure parameters were 90 kV, 5–9 mA, and 4.0 × 5.0-cm FOV. Three-dimensional images of all teeth were obtained with voxel sizes of 0.1, 0.2, and 0.4-mm (Fig. ). Details of the scan parameters were shown on Table . Volumetric data were exported into DICOM (Digital Imaging and Communications in Medicine) format. Maintenance and calibration of the imaging device are routinely performed annually by authorized technical service. During the image acquisition process with three different voxel sizes, the teeth were fixed to a wax base and scanned in the same position. 

Two examiners (EKK, OY) with 3 years of experience in dentomaxillofacial radiology performed all measurements separately. Prior to measurements, observers were trained and calibrated by an 8-year-experienced maxillofacial radiologist (GA) on three-dimensional images of five teeth that were not included in the study group. Images in DICOM format were transferred to the open-source medical segmentation analysis program, ITK-SNAP (Version 3.8.0, Philadelphia, PA, USA), where linear and volumetric measurements were performed. The “thresholding” option, the “contrast” setting, and the “active contour” segmentation mode are available in the software. The optimum grayscale threshold value and contrast adjustment were selected for the images. Semi-automatic segmentation of each tooth and pulp was performed. Both observers followed the same procedure for all volume measurements. To define the region of interest (ROI) for segmentation, marking was made to include all borders of the tooth to be examined in multiplanar reconstructions. The volume measurements were performed by following three guided interactive building processes. (1) A threshold range was set to create the 3D model on all voxels with gray values ​​and determine the beginning and end of the segmentation process. Threshold selection was interactive. For segmentation of the pulp, it was done by setting the upper threshold between 1600 and 1850 and the lower threshold between − 500 and − 750 based on visual analysis of the anatomical boundaries between hard tissue (dentin) and soft tissue (pulp). (2) Seed-like geometries (bubble-like formation) were added by the observer to initiate the segmentation of the region to be measured. (3) Finally, the segmentation development, velocity, and end were selected, and the segmentation process was started gradually. After this process, a 3D reconstruction image of the relevant structure was created, and its volume was obtained as cubic millimeters (mm 3 ) (Fig. ). There was no time restriction on the measurements by observers. Linear measurements were performed on the coronal and axial sections. The tooth length, root length (distance from the cement-enamel junction to the root apex), and pulp length (distance from the pulp horn to the root apex) were measured (Fig. ). Two weeks after the first examination, both observers measured 20% of the samples again for intra-observer reliability. 

Mean values and standard deviations of volume and linear measurements were calculated using descriptive analysis. The normality of the data was analyzed using the Kolmogorov-Smirnov test, and depending on this distributional violation, nonparametric statistical analyses were used. The comparison of the effect of different voxel sizes on volumetric measurements were analyzed using Friedman test for both observers. In this study, two compatibility analyses were performed for inter-observer reliability and intra-observer repeatability. To analyze inter-observer reliability, Kendall’s tau correlation coefficient was calculated. Correlation analysis results were also corroborated using the Wilcoxon signed-rank test by analyzing the difference between two matched pairs. Intra-observer repeatability was analyzed using the intraclass correlation coefficient (ICC). Statistical analyses were performed using IBM SPSS Statistics, Version 23·0 software (Armonk, New York, USA). The significance level was set at 0.05. 

For the pulp and tooth volume measurements of Observer 1, the effect of voxel size was not found to be different between the groups ( p > 0.05). On the other hand, for Observer 2, the effect of voxel size on pulp volume was statistically significant ( p < 0.001). For Observer 2, the pulp volume measured on the 0.4-mm voxel was higher than that measured on the 0.1-mm and 0.2-mm voxel sizes. For the tooth volume measurements of Observer 2, no significant difference was observed between the three voxel sizes ( p > 0.05) [Table ]. The effect of voxel size on linear measurements was not statistically significant for both observers ( p > 0.05) [Table ]. Depending on the correlation analysis, interclass reliability was found to be statistically significant for all volume and linear measurements. The interclass reliability decreased as the voxel size increased [Table ]. Intraobserver repeatability was analyzed using ICC. For all measurements, intraclass correlations were statistically significant ( p > 0.05). ICC values indicated “good” and “excellent” reliability for all parameters measured on 0.1- and 0.2-mm voxels. A few “moderate” reliability were found on the 0.4-mm voxel. For most parameters, such as pulp volume, tooth volume, and tooth length, intraobserver repeatability decreased as the voxel size increased [Table ]. 

A 3D virtual surface model can be created by segmentation to map volumetric data so that the size, shape, and volume of the pulp cavity can be evaluated . Segmentation is an application that separates a particular object from surrounding structures and creates three-dimensional virtual models for better visualization and analysis. It can be performed in manual, semi-automatic, and automatic ways. Because manual segmentation takes a significant amount of time and automatic segmentation may not provide reliable results, previous studies have focused on semi-automatic segmentation. Segmentation applications can be made more effective because the semi-automatic segmentation methods are controlled by the user and are highly efficient and repeatable . The ITK-SNAP semi-automatic segmentation analysis program is used to segment the upper airways, paranasal sinuses, pulp cavity, periapical lesions, and osseous structures . This program has advantages, such as being a free-open source, having good segmentation control and sensitivity, controlling segmentation in 2D sections, and compatibility of threshold values with other imaging software . Weissheimer et al. used 6 different segmentation programs, including ITK-SNAP, for the segmentation of the upper airway and found that the success rate of ITK-SNAP was high . In another study, Gomes et al. demonstrated that ITK-SNAP can be used with high accuracy even on irregularly shaped objects on CBCT . In a recently published study, Aydogdu et al. measured 30 incisors using the water displacement method and compared it with manual and automatic tools using the ITK-SNAP program . Their results showed that no statistical difference was found between the water displacement method and ITK-SNAP in the voxels of 0.3, and 0.4-mm voxels. In the same study, researchers also compared ITK-SNAP’s manual and automatic segmentation methods, but found no statistical difference. Due to the advantages and high accuracy of the proposed program, we selected ITK-SNAP for the segmentation process. In the segmentation process, it is important to separate the objects that are visualized as precisely as possible. Recently, CBCT has been frequently used for segmentation of the maxillofacial region. Decreased image quality may result in loss of detail, which can affect the accuracy of threshold determination during segmentation. Factors such as FOV, voxel size, and image artifacts can significantly affect image quality; thus, threshold selection can also be affected . The voxel exposure parameter of CBCT is an important factor affecting image quality . The voxel size is an important parameter that affects the volumetric measurement of three-dimensional jaws . The smaller the voxel size, the more detailed images are produced, thereby increasing the image quality . Some studies have been performed using different voxel sizes in various regions . Dong et al. evaluated images of four different voxels (0.125-, 0.2-, 0.3-, 0.4-mm) in their study of samples from the pig mandible and reported that the deviation rate increased as the voxel size increased . Ye et al. compared voxels of 0.125-, 0.2-, 0.25-, 0.3-, and 0.4-mm to measure crown and root volumes and found that as the voxel size increased, the image volume tended to be larger . They stated that the reason for this may be halation due to the partial volume effect and scatter. The authors emphasized that as the voxel size increases, diagnostic ability also decreases . Maret et al. investigated the effects of different devices and voxels on tooth volume measurement. Researchers have reported that volumetric measurements with CBCT are similar for voxel sizes up to 0.2-mm, and the measurement reliability decreases at 0.3-mm and larger . Coutsiers Morell et al. reported that tooth images taken with a 0.30 mm voxel size were significantly larger than those with a 0.25-mm voxel size . Conversely, in a manual segmentation study, Sang et al. reported no statistical difference in volumetric measurements at voxel sizes of 0.15- and 0.3-mm . In a recent study, Aydogdu et al. used 0.3- and 0.4-mm voxel sizes to determine tooth volume using different segmentation programs . According to the results of that study, there was a difference in measurements of 0.4-mm voxel size in the 3D Doctor program, however, there was no difference in measurements of 0.3- and 0.4-mm voxel sizes in the ITK-SNAP program. In another recent study, Intarasuksanti et al. evaluated the root surface areas and image qualities of different teeth with voxel sizes varying between 0.15- and 0.4-mm on different CBCT devices . As a result of their research, although they could not find a statistical difference in root surface area measurements among different voxels, they reported that image quality decreased in large voxels. In this study, we examined 0.1-, 0.2-, and 0.4-mm voxel sizes using semi-automatic segmentation. The fact that linear&volumetric tooth measurements were not statistically significantly different in the three different voxels is consistent with the results of most previous studies and is compatible with our null hypothesis. However, as the voxel size increases, the volumetric measurement values ​​tend to increase. On the other hand, it is thought that the reason for the different results between the two observers in the pulp volume measurements in our study is that the pulp has a very thin structure, and it is difficult to clearly distinguish pulp boundaries due to the partial volume effect of CBCT. It has also been reported that increasing the voxel size reduces the sharpness of images, and a voxel size of 0.3 mm or larger makes specific structures, such as tooth cracks, less visible . To the best of our knowledge, no previous study has compared both intraobserver and interobserver agreement of linear and volumetric measurements of teeth and pulp on CBCT images obtained with different voxel sizes. In their study, Sonmez et al. created artificial external root resorptions and measured voxel sizes ranging from 0.075 to 0.2-mm and resorption volumes by two different observers, but they did not find any differences between observers . In our study, interobserver reliability was found to be statistically significant for all volume and linear measurements. However, inter-observer agreement was lower in pulp volume measurements than in other volume and linear measurements, and inter-class reliability decreased as the voxel size increased (especially at the 0.4-mm voxel size). Similarly, intraobserver repeatability decreased as the voxel size increased. These results show that there are difficulties in the volumetric measurement of small structures such as pulp. The fact that increasing the voxel size of CBCT affects measurement reliability is important in cases in which age determination is required, such as in forensic dentistry, or in scientific research in which tooth and pulp volume is evaluated. CBCT can be used for linear measurements and volumetric evaluations. In our study, we measured tooth, pulp, and root lengths. In the study of Sang et al., in which they evaluated tooth lengths, the researchers reported that a 0.15-mm voxel provided statistically less deviation than a 0.30-mm voxel . Waltrick et al., in their research on linear measurements, stated that a voxel size of 0.3 mm is a good compromise between image quality and low radiation dose . Liedke et al. used 0.2-, 0.3-, and 0.4-mm voxel values in their study examining the external root resorption length and found no significant difference . Aktan et al. evaluated the endodontic canal length in different voxels (0.1-, 0.15-, 0.2-, 0.4-mm), but did not find any statistically significant difference between voxels . In our study, there was no statistically significant difference in the linear measurements. The differences in the results may be due to differences in the segmentation methods, voxel sizes, measurement programs, and CBCT devices. In radiology applications, dose optimization should be performed to reduce unnecessary radiation exposure of patients and personnel. The lowest dose required to obtain optimal image quality in ionizing radiation exposure is also known as the ALARA (As Low As Reasonably Achievable) principle . Decreasing the voxel size or increasing the irradiation time leads to an increase in radiation dose . The different voxel sizes we used in our study affect both image quality and radiation dose. The fact that the 0.1-, and 0.2-mm voxel sizes determined in our study give similar results in the evaluation of tooth lengths and volumes may be guiding in dose, age determination and forensic science applications and studies. Adjusting the radiation dose is of great importance, especially in human studies. Many studies have investigated the linear and volumetric measurement accuracy of CBCT. Some authors have compared CBCT and micro-CT and tested the reliability of CBCT in volumetric measurements . The lack of use of micro-CT was a limitation of our study. However, previous studies have shown that CBCT is a reliable method for volume measurement. Carneiro et al. investigated the volumetric measurement of the pulp cavity using different CBCT units and compared it with micro-CT . The authors reported that semiautomatic segmentation of CBCT is feasible for the 3D modeling of pulp cavities . Shaheen et al. evaluated the dental segmentation success of CBCT using three different CBCT units and micro-CT . The results of their study showed that different CBCT protocols provided high accuracy for dental segmentation. The authors reported that this technique can be used for diagnostic and preoperative planning . Wang et al. also showed that CBCT provides the same precision as micro-CT for tooth volume measurements . In our study, we did not use micro-CT because our main purpose was not to measure the reliability of CBCT; we aimed to investigate which voxel could be measured with higher reliability and reproducibility of the method. Another limitation of our study was the use of a single segmentation measurement program. In the future studies, it will be recommended to compare different segmentation programs or CBCT devices for these measurements. 

The effects of voxel size on linear and volumetric tooth measurement were not found statistically significant. However, as the voxel size increased, the interclass reliability and intraobserver repeatability were reduced for linear and volumetric tooth and pulp measurements. In cases in which age determination is required, such as in forensic dentistry, or in scientific research in which pulp and tooth volume is evaluated, keeping the voxel size as small as possible is important for measurement reliability. 

Below is the link to the electronic supplementary material. Supplementary Material 1 

