Thickness and design features of clinical cranial implants-what should automated methods strive to replicate?

PURPOSE: New deep learning and statistical shape modelling approaches aim to automate the design process for patient-specific cranial implants, as highlighted by the MICCAI AutoImplant Challenges. To ensure applicability, it is important to determine if the training data used in developing these algorithms represent the geometry of implants designed for clinical use. METHODS: Calavera Surgical Design provided a dataset of 206 post-craniectomy skull geometries and their clinically used implants. The MUG500+ dataset includes 29 post-craniectomy skull geometries and implants designed for automating design. For both implant and skull shapes, the inner and outer cortical surfaces were segmented, and the thickness between them was measured. For the implants, a 'rim' was defined that transitions from the repaired defect to the surrounding skull. For unilateral defect cases, skull implants were mirrored to the contra-lateral side and thickness differences were quantified. RESULTS: The average thickness of the clinically used implants was 6.0 ± 0.5 mm, which approximates the thickness on the contra-lateral side of the skull (relative difference of -0.3 ± 1.4 mm). The average thickness of the MUG500+ implants was 2.9 ± 1.0 mm, significantly thinner than the intact skull thickness (relative difference of 2.9 ± 1.2 mm). Rim transitions in the clinical implants (average width of 8.3 ± 3.4 mm) were used to cap and create a smooth boundary with the skull. CONCLUSIONS: For implant modelers or manufacturers, this shape analysis quantified differences of cranial implants (thickness, rim width, surface area, and volume) to help guide future automated design algorithms. After skull completion, a thicker implant can be more versatile for cases involving muscle hollowing or thin skulls, and wider rims can smooth over the defect margins to provide more stability. For clinicians, the differing measurements and implant designs can help inform the options available for their patient specific treatment.

Measuring 3D facial displacement of increasing smile expressions.

BACKGROUND: Following paralysis, facial reanimation surgery can restore movement by nerve and/or muscle transfer within the face. The subtleties of lip and cheek movements during smiling are important aspects in assessing reanimation. This study quantifies average 3D movement vectors of the face during smiling based on the diverse Binghamton University 3D facial expression database to yield normative measures of lip and cheek movement. METHODS: The analysis was conducted on 100 subjects with 3D facial scans in a neutral and 4 increasing smile intensities, as well as associated labeled 3D landmark points. Each subject set of 3D scans was rigidly registered to measure average displacement vectors (distance, azimuth, and elevation) between the neutral and happy expressions. RESULTS: The average lip commissure displacement was found to be 9.2, 11.4, 13.5, and 16.0 mm for increasing smile levels 1-4, respectively. Similarly, the average commissure azimuth angle across all 4 smile levels is ∼44 ± 21 degrees, and the average elevation angle across all 4 smile levels is ∼37 ± 15 degrees. The maximum cheek displacement from the neutral expression was 4.5, 5.7, 6.8, and 7.9 mm for the smile levels 1-4, respectively. The average cheek movement azimuth angle is outward (increasing 1-13 degrees), and the elevation angle is upward (increasing 51-59 degrees) from the face. CONCLUSIONS: These data quantifying 3D lip and cheek smile displacements improve the understanding of facial movement and may be applicable to future assessment/planning of facial reanimation surgeries.

Top-Down Control of Sweet and Bitter Taste in the Mammalian Brain.

Hardwired circuits encoding innate responses have emerged as an essential feature of the mammalian brain. Sweet and bitter evoke opposing predetermined behaviors. Sweet drives appetitive responses and consumption of energy-rich food sources, whereas bitter prevents ingestion of toxic chemicals. Here we identified and characterized the neurons in the brainstem that transmit sweet and bitter signals from the tongue to the cortex. Next we examined how the brain modulates this hardwired circuit to control taste behaviors. We dissect the basis for bitter-evoked suppression of sweet taste and show that the taste cortex and amygdala exert strong positive and negative feedback onto incoming bitter and sweet signals in the brainstem. Finally we demonstrate that blocking the feedback markedly alters responses to ethologically relevant taste stimuli. These results illustrate how hardwired circuits can be finely regulated by top-down control and reveal the neural basis of an indispensable behavioral response for all animals.

Modeling and measuring average nasal asymmetry by dorsum midline and nose tip lateral deviation.

In rhinoplasty and nasal reconstruction, achieving symmetry is critical for optimal patient outcomes and reducing re-operation rates. Assessing nasal asymmetry is challenging, both pre- and intra-operatively, if based on only a surgeons' visual perception to assess and adjust the small distances important to cosmesis (<2-3 mm). To measure nasal symmetry, we first developed an algorithm to analyze lateral nasal deviation on facial three-dimensional (3D) scans captured by external surface scanning. In this, nasal deviation is measured by first registering a 3D facial scan to orthogonal axes in order to remove tilt. The lateral position of the nasal midline is then found across transverse planes along the dorsum and nasal tip regions by probing midpoints 1 and 2 mm back from the local maximum projection. The nasal deviation measurement algorithm was validated on a simulated asymmetrical nose model with known nasal deviation. Simulated deviations were applied to the symmetrical average nose using an exponential twist away from the face, with control of the maximum deviation and degree of curvature. Modeled deviations were evaluated with the algorithm at clinically negligible (0.02-0.06 mm) average differences and for small lateral deviations (1-5 mm). Nasal deviation using the algorithms was then measured for the 100 multi-ethnic subjects in the Binghamton University 3D Facial Expression database. Average values for maximum lateral deviation, deviation across the whole nose, and deviation at the nose tip were measured to provide context to deviation measurements in surgical planning. This research presents a new nasal assessment tool that can be useful in improving symmetry in rhinoplasty and reconstruction.