3D planning of ear prosthesis and navigated flapless surgery for craniofacial implants: A pilot study

Digital Technologies: From Scientific to Clinical Applications in Orthodontic and Dental Communities

The significant progress made in our sector since the introduction of digital technologies has now made it possible to easily obtain all the information necessary to diagnose, design and perform interdisciplinary and complex therapies in a simpler and more reproducible way [...]

3D Virtual Modeling for Morphological Characterization of Pituitary Tumors: Preliminary Results on Its Predictive Role in Tumor Resection Rate

Among potential factors affecting the surgical resection in pituitary tumors, the role of tumor three-dimensional (3D) features is still unexplored. The aim of this study is to introduce the use of 3D virtual modeling for geometrical and morphological characterization of pituitary tumors and to evaluate its role as a predictor of total tumor removal. A total of 75 patients operated for a pituitary tumor have been retrospectively reviewed. Starting from patient imaging, a 3D tumor model was reconstructed, and 3D characterization based on tumor volume (Vol), area, sphericity (Spher), and convexity (Conv) was provided. The extent of tumor removal was then evaluated at post-operative imaging. Mean values were obtained for Vol (9117 ± 8423 mm3), area (2352 ± 1571 mm2), Spher (0.86 ± 0.08), and Conv (0.88 ± 0.08). Total tumor removal was achieved in 57 (75%) cases. The standard prognostic Knosp grade, Vol, and Conv were found to be independent factors, significantly predicting the extent of tumor removal. Total tumor resection correlated with lower Knosp grades (p = 0.032) and smaller Vol (p = 0.015). Conversely, tumors with a more irregular shape (low Conv) have an increased chance of incomplete tumor removal (p = 0.022). 3D geometrical and morphological features represent significant independent prognostic factors for pituitary tumor resection, and they should be considered in pre-operative planning to allow a more accurate decision-making process.

Ultrasound Imaging Offers Promising Alternative to Create 3-D Models for Personalised Auricular Implants

Three-dimensional imaging and advanced manufacturing are being applied in health care research to create novel diagnostic and surgical planning methods, as well as personalised treatments and implants. For ear reconstruction, where a cartilage-shaped implant is embedded underneath the skin to re-create shape and form, volumetric imaging and segmentation processing to capture patient anatomy are particularly challenging. Here, we introduce 3-D ultrasound (US) as an available option for imaging the external ear and underlying auricular cartilage structure, and compare it with computed tomography (CT) and magnetic resonance imaging (MRI) against micro-CT (µCT) as a high-resolution reference (gold standard). US images were segmented to create 3-D models of the auricular cartilage and compared against models generated from µCT to assess accuracy. We found that CT was significantly less accurate than the other methods (root mean square [RMS]: 1.30 ± 0.5 mm) and had the least contrast between tissues. There was no significant difference between MRI (RMS: 0.69 ± 0.2 mm) and US (0.55 ± 0.1 mm). US was also the least expensive imaging method at half the cost of MRI. These results unveil a novel use of ultrasound imaging that has not been presented before, as well as support its more widespread use in biofabrication as a low-cost imaging technique to create patient-specific 3D models and implants.