Three-dimensional computer modeling of standard orbital mean shape in Asians

Quantification of global orbital shape variation

The complex anatomy of the orbit generates a complex orbital shape that can only be quantified approximatively by classic linear measurements such as maximum width and height. There is no global three-dimensional quantification of variations in orbital shape. The purpose of this study was to develop a method to quantify a global three-dimensional orbital shape variation in a healthy population and to test a series of explanatory factors. We investigated the hypotheses that orbital shape is related to gender(H1), orbital size(H2) and/or age(H3). Medical computed tomography(CT) images of 60 adult individuals were studied. The study sample consisted of 30 males and 30 females with a mean age of 25.1 years. Four anatomical landmarks and 140 semi-landmarks were measured on both positive and negative 3D reconstructed orbits and analyzed with geometric morphometrics. A principal component analysis(PCA) was computed to define a morphological space. Shape variation was visualized using vector distance maps and diagrams. The greatest variation was seen in the length of the superior orbital fissure. There was a gradient in terms of orbital shape ranging from short, wide orbits to tall, narrow orbits. The analysis did not highlight any significant age-, gender- or size-related impact in terms of orbital shape variation. Future avenues to explore include the study of other potential explanatory factors such as the different embryological origins of the orbital bones, the passage of vessels and nerves, and ethnic origins. This method can also be applied to the study of pathological orbits.

Automatic segmentation of orbital wall from CT images via a thin wall region supervision-based multi-scale feature search network

PURPOSE

Orbital wall segmentation is critical for orbital measurement and reconstruction. However, the orbital floor and medial wall are made up of thin walls (TW) with low gradient values, making it difficult to segment the blurred areas of the CT images. Clinically, doctors have to manually repair the missing parts of TW, which is time-consuming and laborious.

METHODS

To address these issues, this paper proposes an automatic orbital wall segmentation method based on TW region supervision using a multi-scale feature search network. First of all, in the encoding branch, the densely connected atrous spatial pyramid pooling based on the residual connection is adopted to achieve a multi-scale feature search. Then, for feature enhancement, multi-scale up-sampling and residual connection are applied to perform skip connection of features in multi-scale convolution. Finally, we explore a strategy for improving the loss function based on the TW region supervision, which effectively increases the TW region segmentation accuracy.

RESULTS

The test results show that the proposed network performs well in terms of automatic segmentation. For the whole orbital wall region, the Dice coefficient (Dice) of segmentation accuracy reaches 96.086 ± 1.049%, the Intersection over Union (IOU) reaches 92.486 ± 1.924%, and the 95% Hausdorff distance (HD) reaches 0.509 ± 0.166 mm. For the TW region, the Dice reaches 91.470 ± 1.739%, the IOU reaches 84.327 ± 2.938%, and the 95% HD reaches 0.481 ± 0.082 mm. Compared with other segmentation networks, the proposed network improves the segmentation accuracy while filling the missing parts in the TW region.

CONCLUSION

In the proposed network, the average segmentation time of each orbital wall is only 4.05 s, obviously improving the segmentation efficiency of doctors. In the future, it may have a practical significance in clinical applications such as preoperative planning for orbital reconstruction, orbital modeling, orbital implant design, and so on.

Implications of Applying New Technology in Cosmetic and Reconstructive Facial Plastic Surgery

The field of facial plastic and reconstructive surgery is privy to a myriad of technological advancements. As innovation in areas such as imaging, computer applications, and biomaterials progresses at breakneck speed, the potential for clinical application is endless. This review of recent progress in the implementation of new technologies in facial plastic surgery highlights some of the most innovative and impactful developments in the past few years of literature. Patient-specific surgical modeling has become the gold standard for oncologic and posttraumatic reconstructive surgery, with demonstrated improvements in operative times, restoration of anatomical structure, and patient satisfaction. Similarly, reductions in revision rates with improvements in learner technical proficiency have been noted with the use of patient-specific models in free flap reconstruction. In the cosmetic realm, simulation-based rhinoplasty implants have drastically reduced operative times while concurrently raising patient postoperative ratings of cosmetic appearance. Intraoperative imaging has also seen recent expansion in its adoption driven largely by reports of eradication of postoperative imaging and secondary-often complicated-revision reconstructions. A burgeoning area likely to deliver many advances in years to come is the integration of bioprinting into reconstructive surgery. Although yet to clearly make the translational leap, the implications of easily generatable induced pluripotent stem cells in replacing autologous, cadaveric, or synthetic tissues in surgical reconstruction are remarkable.