Three-dimensional orbital wall modeling using paranasal sinus segmentation.

PURPOSE: Three-dimensional orbital wall modeling is a time-consuming process because of the presence of pseudoforamina. We developed an automated three-dimensional modeling software to characterize the orbital wall, and evaluated it using data from fracture patients. METHODS: We first characterized the air and face regions using multiphase segmentation; the sinuses were segmented by applying morphological operations to air regions. Pseudoforamina of the orbital wall were offset with the segmented sinuses. Finally, the three-dimensional facial bone model, with orbital wall, was reconstructed from the segmented images. RESULTS: Ten computed tomography data sets were used to evaluate the proposed method. Results were compared with those obtained using the active contour model and manual segmentation. The process took 31.7 ± 8.0 s, which was 30-60 times faster than other methods. The average distances between surfaces obtained with the proposed method and those obtained with manual segmentation (normal side: 0.20 ± 0.06 mm; fractured side: 0.28 ± 0.10 mm) were approximately half those obtained using the active contour model. CONCLUSIONS: Three-dimensional orbital wall models, which were very similar to the manually segmented models, were archived within 1 min using the developed software, regardless of fracture presence. The proposed method might improve the safety and accuracy of surgical procedures.

3D computer simulation analysis of the flap volume change in total tongue reconstruction flaps.

BACKGROUND: A decreased flap volume can be an obstacle to proper phonation and swallowing. In this study we verified the proportion of volume decrease using 3D reconstructed images and identified the contributors to flap volume loss. METHODS: We retrospectively analyzed all patients who underwent radical excision of tongue cancer and reconstructive surgery in our institution from January 2003 to October 2016. Segmentation of the DICOM images, 3D rendering of the neotongue flap, and analysis of the reconstructed images were performed using SPlanner V1® software. RESULTS: The first postoperative imaging work-up was performed within an average of 22 days (T1). The last follow-up images were taken at an average of 6.25 months (T2). The mean flap volume at T2 was reduced to 82.99 per cent compared with T1, and flap height was reduced to 91.85 per cent, giving mean volume and height decreases of 17.01 per cent and 8.15 per cent, respectively. Neither the volume/height difference between T1 and T2 nor the flap volume/height discrepancy compared with the preoperative tongue affected speech or feeding function. The difference between the flap and preoperative tongue volumes was significantly related to the presence of complications (p = 0.0153). Initial flap volume was significantly related to the flap volume reduction (p = 0.0159). CONCLUSIONS: The mean flap volume reduction is the only factor significantly related to initial flap volume. Our realistic 3D reconstructed image and novel software enables us to more precisely predict the flap volume of the postoperative state and preoperatively evaluate the required flap size for covering defects.