For the last century, the gold standard method for analysis of craniofacial development was cephalometry, with linear and angular measurements performed on lateral headfilms. However, as a 2-dimensional representation of 3-dimensional (3D) structures, lateral headfilms offer limited information about the airways. Information regarding axial cross-sectional areas and overall volumes can only be determined by 3D imaging modalities. Medical computed tomography is a 3D imaging modality used in medicine but not as a routine method for airway analysis because of its high cost both financially and in terms of radiation. These drawbacks were overcome with the introduction of cone-beam computed tomography (CBCT). CBCT is becoming a popular diagnostic method for visualizing and analyzing upper airways. Since its introduction in 1998, CBCT technology has been improved, with lower costs, less radiation exposure to patients, and better accuracy in identifying the boundaries of soft tissues and empty spaces (air). Furthermore, CBCT allows for the assessment of axial cross-sectional areas and volumes of the upper airways. The accuracy and reliability of CBCT for upper airway evaluation have been validated in previous studies, and the use of CBCT for airway evaluation has been reported in a systematic review of the literature.

The evaluation of the size, shape, and volume of the upper airway starts by defining the volume corresponding to the airway passages, a process called segmentation. In medical imaging, segmentation is defined as the construction of 3D virtual surface models (called segmentations ) to match the volumetric data. In other words, it means to separate a specific element (eg, upper airway) and remove all other structures of noninterest for better visualization and analysis. Upper airway segmentation can be either manual or semiautomatic. In the manual approach, the segmentation is performed slice by slice by the user. The software then combines all slices to form a 3D volume. This method is time-consuming and almost impractical for clinical application. In contrast, semiautomatic segmentation of the airway is significantly faster than manual segmentation. In the semiautomatic approach, the computer automatically differentiates the air and the surrounding soft tissues by using the differences in density values (grey levels) of these structures. In some programs, the semiautomatic segmentation includes 2 user-guided interactive steps: placement of initial seed regions in the axial, coronal, and sagittal slices, and selection of an initial threshold.

Image thresholding is the basis for segmentation. When the user determines a threshold interval, it means that all voxels with grey levels inside that interval will be selected to construct the 3D model (segmentation). Lenza et al reported the use of a single threshold value to segment the airway in each patient’s CBCT scan. This approach can generate errors, especially in volume analysis, but it is certainly more reproducible than the use of a dynamic threshold. However, there are few studies comparing the results of threshold filtering with different imaging software programs for airway assessment.

A growing number of software programs to manage and analyze digital imaging communications in medicine (DICOM) files are introduced in the market every year. Many of these have incorporated tools to segment and measure the airway. A systematic review of the literature reported 18 imaging software programs for viewing and analyzing the upper airway in CBCT. However, validation studies with a clear study design were performed in only 4 software programs. The systematic review suggested that studies assessing the accuracy and reliability of current and new software programs must be conducted before these imaging software programs can be implemented for airway analysis.

The aim of this study was to compare the precision and accuracy of 6 imaging software programs for measuring the oropharynx volume in CBCT images. The primary null hypothesis, that there are no significant differences in airway volume measurements among the 6 imaging software programs, was tested.

Material and methods

This study was approved by the ethical committee of Pontifical Catholic University of Rio Grande do Sul in Brazil. The records we used were obtained from the patient database of the Department of Orthodontics and consisted of the pretreatment CBCT scans of a preexisting rapid maxillary expansion sample. The sample included 33 growing patients (mean chronologic age, 10.7 years; range, 7.2-14.5 years) with transverse maxillary deficiency and no congenital malformations. Additionally, a custom-made oropharynx acrylic phantom with a known volume was used as the gold standard ( Fig 1 ). The oropharynx acrylic phantom consisted of an air-filled plastic rectangular prism surrounded by water. Water was the medium of choice because it has a similar attenuation value to soft tissue. The dimensions of the outer surface of the phantom were created to simulate the dimensions of a growing patient’s neck, and the rectangular prism to simulate the dimensions of the oropharynx. The oropharynx acrylic phantom’s dimensions were measured to the nearest 0.01 mm by using digital calipers (model 727; Starret, Itú, São Paulo, Brazil), and the volume was calculated multiplying the base area by the height. Additionally, the oropharynx acrylic phantom’s volume was confirmed by using the water weight equivalent. The oropharynx acrylic phantom was filled with distilled water, at 20°C, and the water weight was determined by using a digital scientific scale (model BG1000; Gehaka, São Paulo, São Paulo, Brazil).

A and B, Oropharynx acrylic phantom used as the gold standard; C, CBCT image of the oropharynx acrylic phantom in the axial view, with the inner part (prism) containing air as the region of interest for segmentation; D, example of a 3D model generated from oropharynx acrylic phantom segmentation.

Patients and the phantom were scanned with the i-CAT scanner (Imaging Sciences International, Hatfield, Pa) set at 120 kVp, 8 mA, scan time of 40 seconds, and 0.3-mm voxel dimension. The images were reconstructed with a 0.3-mm slice thickness and exported as DICOM files. Any CBCT scans with artifacts distorting the airway borders were excluded from this study. CBCT scans were imported into OsiriX software (version 4.0; Pixmeo, Geneva, Switzerland) for head orientation and definition of the oropharynx’s region of interest. The head orientation was performed by using the palatal plane as a reference (ANS-PNS parallel to the global horizontal plane in the sagittal view and perpendicular to the global horizontal plane in the axial view). After head orientation, a tool in OsiriX (Vol cutter) was used to select and crop the oropharynx, according to the following references: superior limit, extension of the palatal plane (ANS-PNS) to the posterior wall of the pharynx; inferior limit, a plane parallel to the palatal plane that passes through the most anteroinferior point of the second cervical vertebrae ; anterior limit, a perpendicular plane to palatal plane that passes through the posterior nasal spine; posterior limit, posteriorly to the posterior wall of pharynx ( Fig 2 , A and B ). The regions of noninterest were excluded, and the new volume, containing only the oropharynx region, was exported as the new DICOM file, with the same voxel resolution but a smaller file size ( Fig 2 , C ).

A and B, CBCT images after head reorientation with OsiriX software, in the axial and sagittal views, respectively, with the oropharynx’s region of interest delimited ( green box ) in the axial and sagittal images; C, 3D volume exported as a new DICOM file; D, from this new volume, the segmentation was performed and the oropharynx’s 3D model obtained for volume analysis; E, location of the oropharynx’s region of interest in the patient’s head.

Six imaging software programs were used to segment and compute volumes from the CBCT images of the patients’ oropharynx and the oropharynx acrylic phantom ( Figs 3 and 4 ). The specifications of each software program are shown in Table I . The oropharynx and the oropharynx acrylic phantom segmentations were performed according to each software manufacturer’s recommendations, with 2 techniques for semiautomatic segmentation: (1) interactive threshold interval, as used in a previous study, and (2) fixed threshold interval. In the interactive thresholding, the operator selected the best threshold interval based on a visual analysis of the anatomic boundaries of the oropharynx and the oropharynx acrylic phantom in the axial, sagittal, and coronal slices. In the fixed threshold, the threshold interval was fixed (–1000 to –587 grey levels) to test the variability among the software programs. The segmentations with interactive thresholding were performed with Mimics (version 14.12; Materialise, Leuven, Belgium), Dolphin3D (version 11.7; Dolphin Imaging & Management Solutions, Chatsworth, Calif), Ondemand3D (version 1.0.9.1451; CyberMed, Seoul, Korea), OsiriX (version 4.0; Pixmeo), and ITK-Snap (version 2.2.0; www.itksnap.org ) (except InVivo Dental [version 5.0; Anatomage, San Jose, Calif]), and those with fixed thresholding were InVivo Dental, Mimics, Ondemand3D, OsiriX, and ITK-Snap (except Dolphin3D).

Examples of the oropharynx segmentation process with 3 imaging software programs: A, D, and G, axial views and B, E, and H, sagittal views of the oropharynx segmentation processes in the CBCT images; C, F, and I, 3D models of a patient’s oropharynx obtained from segmentations. A – C, Segmentation process with Dolphin3D ( pink ) was based on addition and growth of seeds ( yellow circles ) that spread, matched, and filled the oropharynx airway. D – F, Segmentation with Ondemand3D ( orange ) showing, in the axial and sagittal views, empty spaces ( black ) without segmentation in some areas and overflowed in other regions. G – I, Segmentation with ITK-Snap ( red ). The segmentation matched precisely the oropharynx in the axial and sagittal views.

Examples of the oropharynx acrylic phantom segmentation process with 3 imaging software programs: A – C, axial views and D-F, sagittal views of the oropharynx acrylic phantom segmentation processes in CBCT images; G-I, 3D models of the oropharynx acrylic phantom obtained from segmentations. A, D, and G, Segmentation with Dolphin3D ( pink ). B, E, and H, Segmentation with Ondemand3D ( orange ) showing, in the axial and sagittal views, empty spaces ( black ) without segmentation in some areas and overflowed in other regions. C, F, and I, Segmentation with ITK-Snap ( red ). The segmentation matched precisely the oropharynx acrylic phantom in the axial and sagittal views.

Table I

CBCT imaging software compared in this study

Software	Description	Operational system
Dolphin3D	Version 11.7; Dolphin Imaging & Management Solutions, Chatsworth, Calif	Windows	Not free
InVivo Dental	Version 5.0; Anatomage, San Jose, Calif	Windows	Not free
Ondemand3D	Version 1.0.9.1451; CyberMed, Seoul, Korea	Windows	Not free
Mimics	Version 14.12; Materialise, Leuven, Belgium	Windows	Not free
OsiriX	Version 4.0; Pixmeo, Geneva, Switzerland	Mac OS X	Free open source
ITK-Snap	Version 2.2.0; www.itksnap.org	Windows Mac OS X Linux	Free open source