Quantification of Nasal Septal Deviation With Computed Tomography Data.

BACKGROUND: Despite extensive literature on the classification and management of nasal septal deviation (NSD) for preoperative planning, standardized objective measures to evaluate the NSD severity remains challenging. In this study, we quantitatively analyzed NSD to determine the most predictive two-dimensional (2D) computed tomography (CT)-landmark for overall three-dimensional (3D) septal morphology derived from nasal airway segmentation. METHODS: A retrospective study was conducted at a large academic center. One hundred four patients who underwent CT scans of the face were selected from a computer imaging database. Demographic variables were screened to ensure an equal number of men and women in different age groups. Digital Imaging and Communications in Medicine files were imported for 3D nasal cavity segmentation using 3D Slicer software. A volumetric analysis was performed to determine 3D NSD ratios. These values were compared to previously reported methods of obtaining objective 2D NSD measures using OsiriX and MATLAB software. Maximum deviation values were calculated using OsiriX, while the root mean square values were retrieved using MATLAB. Deviation area and curve to line ratios were both quantified using OsiriX and MATLAB. RESULTS: The data set consisted of 52 men and 52 women patients aged 20 to 100 years (mean = 58 years, standard deviation = 23 years). There was a strong correlation between 3D NSD ratio and maximum deviation (r = 0.789, P < 0.001) and deviation area (r = 0.775, P < 0.001). Deviation area (r = 0.563, P < 0.001), root mean square (r = 0.594, P < 0.001), and curve to line ratio (r = 0.470, P < 0.001) had a positive correlation of moderate strength. The curve to line ratio was not significant (r = 0.019, P = 0.85). CONCLUSIONS: The 2D CT-based NSD landmarks maximum deviation and deviation area were the most predictive of the severity of NSD from 3D nasal cavity segmentation. We present a robust open-source method that may be useful in predicting the severity of NSD in CT images.

The Use of Three-Dimensional Photography and Printing in the Fabrication of a Nasal Prosthesis.

OBJECTIVE: Facial prosthetic rehabilitation using additive manufacturing technology relies on data acquisition from computed tomography or magnetic resonance imaging. Three-dimensional (3D) photography has become widespread in craniofacial and plastic surgery due to its ability to provide more comprehensive topographical data than radiographic techniques. Despite the rising popularity of 3D photography in preoperative planning, reports on the use of this technology for facial prosthetic rehabilitation are lacking. The present clinical report demonstrates the indirect fabrication of a nasal prosthesis using 3D surface-imaging by the VECTRA-M5 360 Head System. DESIGN: A 61-year-old woman presented with a nasal defect due to a partial rhinectomy secondary to multiple resections of recurrent basal cell carcinoma. After opting out of any further surgical intervention, the patient expressed a preference for prosthetic rehabilitation. Prosthesis fabrication using CAD/CAM technology typically relies on patient data from computed tomography or magnetic resonance imaging scans for the 3D printing of the replica of the nasal defect. In this case, facial data was acquired by a 3D surface-imaging system using a 3D photograph captured by the VECTRA-M5 360 Head System. CONCLUSIONS: Acquisition of facial data using 3D surface-imaging systems may be recommended for patients with external facial deformities to decrease subsequent radiation exposure. The integration of 3D photography and 3D printing provides a promising method for prosthetic rehabilitation that decreases total production time while minimizing radiation exposure.