Facial mobility and recovery in patients with unilateral facial paralysis

Novel Baseline Facial Muscle Database Using Statistical Shape Modeling and In Silico Trials toward Decision Support for Facial Rehabilitation

Backgrounds and Objective: Facial palsy is a complex pathophysiological condition affecting the personal and professional lives of the involved patients. Sudden muscle weakness or paralysis needs to be rehabilitated to recover a symmetric and expressive face. Computer-aided decision support systems for facial rehabilitation have been developed. However, there is a lack of facial muscle baseline data to evaluate the patient states and guide as well as optimize the rehabilitation strategy. In this present study, we aimed to develop a novel baseline facial muscle database (static and dynamic behaviors) using the coupling between statistical shape modeling and in-silico trial approaches. Methods: 10,000 virtual subjects (5000 males and 5000 females) were generated from a statistical shape modeling (SSM) head model. Skull and muscle networks were defined so that they statistically fit with the head shapes. Two standard mimics: smiling and kissing were generated. The muscle strains of the lengths in neutral and mimic positions were computed and recorded thanks to the muscle insertion and attachment points on the animated head and skull meshes. For validation, five head and skull meshes were reconstructed from the five computed tomography (CT) image sets. Skull and muscle networks were then predicted from the reconstructed head meshes. The predicted skull meshes were compared with the reconstructed skull meshes based on the mesh-to-mesh distance metrics. The predicted muscle lengths were also compared with those manually defined on the reconstructed head and skull meshes. Moreover, the computed muscle lengths and strains were compared with those in our previous studies and the literature. Results: The skull prediction's median deviations from the CT-based models were 2.2236 mm, 2.1371 mm, and 2.1277 mm for the skull shape, skull mesh, and muscle attachment point regions, respectively. The median deviation of the muscle lengths was 4.8940 mm. The computed muscle strains were compatible with the reported values in our previous Kinect-based method and the literature. Conclusions: The development of our novel facial muscle database opens new avenues to accurately evaluate the facial muscle states of facial palsy patients. Based on the evaluated results, specific types of facial mimic rehabilitation exercises can also be selected optimally to train the target muscles. In perspective, the database of the computed muscle lengths and strains will be integrated into our available clinical decision support system for automatically detecting malfunctioning muscles and proposing patient-specific rehabilitation serious games.

Smile Reanimation with Masseteric-to-Facial Nerve Transfer plus Cross-Face Nerve Grafting in Patients with Segmental Midface Paresis: 3D Retrospective Quantitative Evaluation

Facial paresis involves functional and aesthetic problems with altered and asymmetric movement patterns. Surgical procedures and physical therapy can effectively reanimate the muscles. From our database, 10 patients (18–50 years) suffering from unilateral segmental midface paresis and rehabilitated by a masseteric-to-facial nerve transfer combined with a cross-face facial nerve graft, followed by physical therapy, were retrospectively analyzed. Standardized labial movements were measured using an optoelectronic motion capture system. Maximum teeth clenching, spontaneous smiles, and lip protrusion (kiss movement) were detected before and after surgery (21 ± 13 months). Preoperatively, during the maximum smile, the paretic side moved less than the healthy one (23.2 vs. 28.7 mm; activation ratio 69%, asymmetry index 18%). Postoperatively, no differences in total mobility were found. The activity ratio and the asymmetry index differed significantly (without/with teeth clenching: ratio 65% vs. 92%, p = 0.016; asymmetry index 21% vs. 5%, p = 0.016). Postoperatively, the mobility of the spontaneous smiles significantly reduced (healthy side, 25.1 vs. 17.2 mm, p = 0.043; paretic side 16.8 vs. 12.2 mm, p = 0.043), without modifications of the activity ratio and asymmetry index. Postoperatively, the paretic side kiss movement was significantly reduced (27 vs. 19.9 mm, p = 0.028). Overall, the treatment contributed to balancing the displacements between the two sides of the face with more symmetric movements.

Identifying Modulated Functional Connectivity in Corresponding Cerebral Networks in Facial Nerve Lesions Patients With Facial Asymmetry

Facial asymmetry is the major complaint of patients with unilateral facial nerve lesions. Frustratingly, although patients experience the same etiology, the extent of oral commissure asymmetry is highly heterogeneous. Emerging evidence indicates that cerebral plasticity has a large impact on clinical severity by promoting or impeding the progressive adaption of brain function. However, the precise link between cerebral plasticity and oral asymmetry has not yet been identified. In the present study, we performed functional magnetic resonance imaging on patients with unilateral facial nerve transections to acquire in vivo neural activity. We then identified the regions of interest corresponding to oral movement control using a smiling motor paradigm. Next, we established three local networks: the ipsilesional (left) intrahemispheric, contralesional (right) intrahemispheric, and interhemispheric networks. The functional connectivity of each pair of nodes within each network was then calculated. After thresholding for sparsity, we analyzed the mean intensity of each network connection between patients and controls by averaging the functional connectivity. For the objective assessment of facial deflection, oral asymmetry was calculated using FACEgram software. There was decreased connectivity in the contralesional network but increased connectivity in the ipsilesional and interhemispheric networks in patients with facial nerve lesions. In addition, connectivity in the ipsilesional network was significantly correlated with the extent of oral asymmetry. Our results suggest that motor deafferentation of unilateral facial nerve leads to the upregulated ipsilesional hemispheric connections, and results in positive interhemispheric inhibition effects to the contralesional hemisphere. Our findings provide preliminary information about the possible cortical etiology of facial asymmetry, and deliver valuable clues regarding spatial information, which will likely be useful for the development of therapeutic interventions.

Three-Dimensional Quantification of Facial Morphology and Movements Using a Wearable Helmet

This work proposes a 3D normative database of facial ranges of motion in adults free from facial disorders. Ten facial movements were analyzed, each targeting the activity of specific muscle groups innervated by the facial nerve. The experimental protocol included a test-retest reliability positioning procedure of 25 skin markers based on clinical expertise in facial morphology. Three maximal voluntary contractions were recorded for each facial movement studied, using a 3D facial motion capture helmet. We included 53 adults free from facial disorders (26 men; age $43\pm 14$ ), evaluated twice one week apart. The reliability of marker positioning was expressed as absolute measurement errors. The range of motion vectors of all markers from the best rest to the maximal voluntary contraction was calculated for each muscle group. Primary, secondary, and tertiary markers were extracted for each facial movement. 3D Procruste and asymmetry indices were developed. This allowed the identification of common thresholds of 10% for the asymmetry index and of 6 mm for the Procruste index, beyond which facial motions would be considered abnormally asymmetric. The normative database quantifies facial motions and allows assessment of the degree of clinical disorders by comparison. This protocol is currently being investigated in patients with chronic unilateral peripheral facial paresis.

Three-dimensional objective evaluation of facial palsy and follow-up of recovery with a handheld scanner

BACKGROUND

Clinicians need accurate, reproducible, fast, and cost-effective grading systems to determine facial functions. There is currently no internationally accepted objective method to report the loss of function at the onset of facial paralysis and subsequent recovery. Our study aimed to test a three-dimensional handheld light scanner's efficacy for grading facial paralysis and monitoring recovery.

METHODS

Sixty-one healthy volunteers (28 men and 33 women) aged between 20 and 75 years (mean 36.4 ± 11.9 years old) and 22 patients with facial palsy (10 male and 12 female patients) aged between 12 and 77 years (mean 47.6 ± 19.7 years old) were included in the study. The healthy individuals' and patients' facial scans were performed with a three-dimensional handheld scanner during different facial expressions at 3-month intervals. The asymmetry and intensity degree of each facial expression were determined in terms of the root mean square.

RESULTS

After facial paralysis, a significant larger asymmetry value (1.2 ± 0.4 mm vs. 2.0 ± 0.8 mm and p<0.05) was determined as compared to the control group, while a significant smaller intensity value (2.3 ± 1.2 mm vs. 1.7 ± 0.9 mm and p<0.05) was observed. At the end of 3 months, both parameters showed a tendency to recover.

CONCLUSION

Our findings suggest that three-dimensional morphological analyses may be an effective method to grade facial palsy. However, our data need to be confirmed by larger cohort size and more extended follow-up periods.

Kinect-driven Patient-specific Head, Skull, and Muscle Network Modelling for Facial Palsy Patients

BACKGROUND AND OBJECTIVE

Facial palsy negatively affects both professional and personal life qualities of involved patients. Classical facial rehabilitation strategies can recover facial mimics into their normal and symmetrical movements and appearances. However, there is a lack of objective, quantitative, and in-vivo facial texture and muscle activation bio-feedbacks for personalizing rehabilitation programs and diagnosing recovering progresses. Consequently, this study proposed a novel patient-specific modelling method for generating a full patient specific head model from a visual sensor and then computing the facial texture and muscle activation in real-time for further clinical decision making.

METHODS

The modeling workflow includes (1) Kinect-to-head, (2) head-to-skull, and (3) muscle network definition & generation processes. In the Kinect-to-head process, subject-specific data acquired from a new user in neutral mimic were used for generating his/her geometrical head model with facial texture. In particular, a template head model was deformed to optimally fit with high-definition facial points acquired by the Kinect sensor. Moreover, the facial texture was also merged from his/her facial images in left, right, and center points of view. In the head-to-skull process, a generic skull model was deformed so that its shape was statistically fitted with his/her geometrical head model. In the muscle network definition & generation process, a muscle network was defined from the head and skull models for computing muscle strains during facial movements. Muscle insertion points and muscle attachment points were defined as vertex positions on the head model and the skull model respectively based on the standard facial anatomy. Three healthy subjects and two facial palsy patients were selected for validating the proposed method. In neutral positions, magnetic resonance imaging (MRI)-based head and skull models were compared with Kinect-based head and skull models. In mimic positions, infrared depth-based head models in smiling and [u]-pronouncing mimics were compared with appropriate animated Kinect-driven head models. The Hausdorff distance metric was used for these comparisons. Moreover, computed muscle lengths and strains in the tested facial mimics were validated with reported values in literature.

RESULTS

With the current hardware configuration, the patient-specific head model with skull and muscle network could be fast generated within 17.16±0.37s and animated in real-time with the framerate of 40 fps. In neutral positions, the best mean error was 1.91 mm for the head models and 3.21 mm for the skull models. On facial regions, the best mean errors were 1.53 mm and 2.82 mm for head and skull models respectively. On muscle insertion/attachment point regions, the best mean errors were 1.09 mm and 2.16 mm for head and skull models respectively. In mimic positions, these errors were 2.02 mm in smiling mimics and 2.00 mm in [u]-pronouncing mimics for the head models on facial regions. All above error values were computed on a one-time validation procedure. Facial muscles exhibited muscle shortening and muscle elongating for smiling and pronunciation of sound [u] respectively. Extracted muscle features (i.e. muscle length and strain) are in agreement with experimental and literature data.

CONCLUSIONS

This study proposed a novel modeling method for fast generating and animating patient-specific biomechanical head model with facial texture and muscle activation bio-feedbacks. The Kinect-driven muscle strains could be applied for further real-time muscle-oriented facial paralysis grading and other facial analysis applications.

Nasolabial fold dynamics: Implications for facial paralysis and facial reanimation surgery

OBJECTIVES

In patients with facial paralysis, facial reanimation surgery may be needed to normalize facial soft tissue function/movements. Critical for this normalization is the dynamics of the nasolabial folds (NLFs). The objective of this prospective, observational study was to determine the 3D morphologic dynamics of the NLFs in patients with unilateral facial palsy and normal subjects.

SETTINGS AND SAMPLE POPULATION

3D facial soft tissue movement data collected from adults with unilateral, facial paralysis (Bell's Palsy, n = 36); and (2) an age- and sex-frequency matched control group (n = 68).

MATERIALS AND METHODS

Movement data were collected during repeated animations from participants using a video-based motion capture system. Movement in terms of displacement and asymmetry of the NLFs, nasal and circumoral regions were analyzed in the lateral, vertical and depth planes; as well as movement of the commissure and NLFs relative to the lower lip midline. Two-sample t tests were used to test for significant group differences.

RESULTS

Patients NLFs had less mean displacement, greater mean asymmetry and uncoordinated movements compared with the controls. For both groups during smiling, the NLF and commissure landmarks had approximately similar magnitudes of displacement (control range = 11-14mm; patient range = 7-10mm).

CONCLUSION

NLF dynamics during smiling were as significant as oral commissure excursion. Thus, an immobile NLF is an unnatural feature of facial animations. Surgical treatments that address impaired NFL movements must be considered to create a more natural surgical outcome especially during smiling.