Three-dimensional superimposition for patients with facial palsy: an innovative method for assessing the success of facial reanimation procedures

Correlation of 3D Morphometric Changes, Kinematics, and Muscle Activity During Smile

OBJECTIVE

Knowing the morphological, kinematic, and electrophysiological parameters of the smile in healthy individuals may contribute to evaluating, planning, and monitoring the smile reanimation. This study aimed to determine the correlation between 3D morphometric changes, movement kinematics, and muscle activity in the facial soft tissue of healthy individuals.

METHOD

In this cohort study, 20 volunteers were selected from healthy individuals with no facial disorders. During smiling, three-dimensional face scanning, facial motion capture, and surface electromyography (sEMG) were performed. The average displacement, velocity, and acceleration during facial movements were measured. The mean change in 3D surface morphometry and activation of the zygomaticus major were determined.

RESULTS

The volunteers, comprising 10 males and 10 females, had a mean age of 24 ± 10 years; for female, mean age was 23 ± 5 years and for men 26 ± 13 years. Significant correlations were found between kinematic and morphometric data (r = 0.51, p < 0.001), sEMG and morphometric (r = 0.50, p < 0.001) data, and sEMG and kinematic data (r = 0.49, p < 0.002). The maximum acceleration occurred during approximately 65% of the muscle activation time and 64% of the peak muscle activation value. Additionally, the maximum velocity was reached at around 73% of the muscle activation time and 67% of the peak muscle activation value. Furthermore, the maximum displacement values were observed at approximately 88% of the muscle activation time and 76% of the peak muscle activation value.

CONCLUSION

The findings may provide insights into the smile's functional parameters, contribute to understanding facial muscle-related disorders, and aid in improving the diagnosis and treatment of the smile.

LEVEL OF EVIDENCE

N/A Laryngoscope, 2024.

The evolution of facial reanimation techniques

This review article provides an updated discussion on evidence-based practices related to the evaluation and management of facial paralysis. Ultimately, the goals of facial reanimation include obtaining facial symmetry at rest, providing corneal protection, restoring smile symmetry and facial movement for functional and aesthetic purposes. The treatment of facial nerve injury is highly individualized, especially given the wide heterogeneity regarding the degree of initial neuronal insult and eventual functional outcome. Recent advancements in facial reanimation techniques have better equipped clinicians to approach challenging patient scenarios with reliable, effective strategies. We discuss how technology such as machine learning software has revolutionized pre- and post-intervention assessments and provide an overview of current controversies including timing of intervention, choice of donor nerve, and management of nonflaccid facial palsy with synkinesis. We highlight novel considerations to mainstay conservative management strategies and examine innovations in modern surgical techniques with a focus on gracilis free muscle transfer. Innervation sources, procedural staging, coaptation patterns, and multi-vector and multi-muscle paddle design are modifications that have significantly evolved over the past decade.

Comprehensive assessment of facial paralysis based on facial animation units

Quantitative grading and classification of the severity of facial paralysis (FP) are important for selecting the treatment plan and detecting subtle improvement that cannot be detected clinically. To date, none of the available FP grading systems have gained widespread clinical acceptance. The work presented here describes the development and testing of a system for FP grading and assessment which is part of a comprehensive evaluation system for FP. The system is based on the Kinect v2 hardware and the accompanying software SDK 2.0 in extracting the real time facial landmarks and facial animation units (FAUs). The aim of this paper is to describe the development and testing of the FP assessment phase (first phase) of a larger comprehensive evaluation system of FP. The system includes two phases; FP assessment and FP classification. A dataset of 375 records from 13 unilateral FP patients was compiled for this study. The FP assessment includes three separate modules. One module is the symmetry assessment of both facial sides at rest and while performing five voluntary facial movements. Another module is responsible for recognizing the facial movements. The last module assesses the performance of each facial movement for both sides of the face depending on the involved FAUs. The study validates that the FAUs captured using the Kinect sensor can be processed and used to develop an effective tool for the automatic evaluation of FP. The developed FP grading system provides a detailed quantitative report and has significant advantages over the existing grading scales. It is fast, easy to use, user-independent, low cost, quantitative, and automated and hence it is suitable to be used as a clinical tool.

Classification of facial paralysis based on machine learning techniques

Facial paralysis (FP) is an inability to move facial muscles voluntarily, affecting daily activities. There is a need for quantitative assessment and severity level classification of FP to evaluate the condition. None of the available tools are widely accepted. A comprehensive FP evaluation system has been developed by the authors. The system extracts real-time facial animation units (FAUs) using the Kinect V2 sensor and includes both FP assessment and classification. This paper describes the development and testing of the FP classification phase. A dataset of 375 records from 13 unilateral FP patients and 1650 records from 50 control subjects was compiled. Artificial Intelligence and Machine Learning methods are used to classify seven FP categories: the normal case and three severity levels: mild, moderate, and severe for the left and right sides. For better prediction results (Accuracy = 96.8%, Sensitivity = 88.9% and Specificity = 99%), an ensemble learning classifier was developed rather than one weak classifier. The ensemble approach based on SVMs was proposed for the high-dimensional data to gather the advantages of stacking and bagging. To address the problem of an imbalanced dataset, a hybrid strategy combining three separate techniques was used. Model robustness and stability was evaluated using fivefold cross-validation. The results showed that the classifier is robust, stable and performs well for different train and test samples. The study demonstrates that FAUs acquired by the Kinect sensor can be used in classifying FP. The developed FP assessment and classification system provides a detailed quantitative report and has significant advantages over existing grading scales.

Numerical Approach to Facial Palsy Using a Novel Registration Method with 3D Facial Landmark

Treatment of facial palsy is essential because neglecting this disorder can lead to serious sequelae and further damage. For an objective evaluation and consistent rehabilitation training program of facial palsy patients, a clinician's evaluation must be simultaneously performed alongside quantitative evaluation. Recent research has evaluated facial palsy using 68 facial landmarks as features. However, facial palsy has numerous features, whereas existing studies use relatively few landmarks; moreover, they do not confirm the degree of improvement in the patient. In addition, as the face of a normal person is not perfectly symmetrical, it must be compared with previous images taken at a different time. Therefore, we introduce three methods to numerically approach measuring the degree of facial palsy after extracting 478 3D facial landmarks from 2D RGB images taken at different times. The proposed numerical approach performs registration to compare the same facial palsy patients at different times. We scale landmarks by performing scale matching before global registration. After scale matching, coarse registration is performed with global registration. Point-to-plane ICP is performed using the transformation matrix obtained from global registration as the initial matrix. After registration, the distance symmetry, angular symmetry, and amount of landmark movement are calculated for the left and right sides of the face. The degree of facial palsy at a certain point in time can be approached numerically and can be compared with the degree of palsy at other times. For the same facial expressions, the degree of facial palsy at different times can be measured through distance and angle symmetry. For different facial expressions, the simultaneous degree of facial palsy in the left and right sides can be compared through the amount of landmark movement. Through experiments, the proposed method was tested using the facial palsy patient database at different times. The experiments involved clinicians and confirmed that using the proposed numerical approach can help assess the progression of facial palsy.

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.

Three-Dimensional Facial Anthropometric Analysis With and Without Landmark Labelling: Is There a Real Difference?

INTRODUCTION

The actual role of landmarks labeling before three-dimensional (3D) facial acquisition is still debated. In this study, several measurements were compared among textured labeled (TL), unlabeled (NL), and untextured (NTL) 3D facial models.

MATERIALS AND METHODS

The face of 50 subjects was acquired through stereophotogrammetry. Landmark coordinates were extracted from TL, NL, and NTL facial models, and 33 linear and angular measurements were calculated, together with surface area and volume. Accuracy of measurements among TL, NL, and NTL models was assessed through calculation of relative technical error of measurement (rTEM). The intra- and inter-observer errors for each type of facial model were calculated.

RESULTS

Intra- and inter-observer error of measurements increased passing from textured to NTL and NL 3D models. Average rTEMs between TL models, and NTL and NL models were 4.5 ± 2.6% and 4.7 ± 2.8%, respectively, almost all measurements being classified as "very good" or "good." Only for orbital height and its inclination, mandibular ramus length, nasal convexity, alar slope angle, and facial divergence, rTEM was classified as "moderate" or "poor."

CONCLUSIONS

Accuracy and precision of measurements decrease when landmarks are not previously labeled; attention must be taken when measurements have a low magnitude or involve landmarks requiring palpation.

Comparative analysis of the nerve transfer methodologies used during surgical treatment of peripheral facial paresis

Introduction. When considering the array of biomedical problems associated with facial nerve palsy (FNP), it is apparent that the problem of choosing an effective type of facial nerve transfer is of paramount relevance. Hence, it is to the pursuit of a solution to the above stated problem that our study is devoted.

Materials and methods. We analyzed the data obtained as a result of assessing the outcome of 149 patients with trauma-caused FNP who had undergone surgical treatments in the period between 2001-2018. The FN nerve transfer techniques utilized were as such: for group 1 – the use as a donor nerve the branch of the accessory nerve innervating the sternocleidomastoid muscle (n=87); group 2 – the descending branch of the hypoglossal and the branch of the accessory nerve (n=62).

Results. In groups 1–2, the FN nerve transfer significantly improved FN function (p <0.01; Wilcoxon Matched Pairs Test), and most patients (n=135; 90.6%) noted an improvement in the clinical status up to degree II-III on the House-Brackmann scale (good result).

Conclusion. The use of the accessory nerve branches to the sternocleidomastoid muscle, as donated, ensures restoration of FN function to levels II-III on the House-Brackmann scale in 89.7% of all operated patients, and the results it achieves do not differ from those of the technically more complex nerve transfer of FN by descending branch of the hypoglossal nerve with combination of branches of the accessory nerve.

Region Based Parallel Hierarchy Convolutional Neural Network for Automatic Facial Nerve Paralysis Evaluation

In this article, we propose a parallel hierarchy convolutional neural network (PHCNN) combining a Long Short-Term Memory (LSTM) network structure to quantitatively assess the grading of facial nerve paralysis (FNP) by considering the region-based asymmetric facial features and temporal variation of the image sequences. FNP, such as Bell's palsy, is the most common facial symptom of neuromotor dysfunctions. It causes the weakness of facial muscles for the normal emotional expression and movements. The subjective judgement by clinicians completely depends on individual experience, which may not lead to a uniform evaluation. Existing computer-aided methods mainly rely on some complicated imaging equipment, which is complicated and expensive for facial functional rehabilitation. Compared with the subjective judgment and complex imaging processing, the objective and intelligent measurement can potentially avoid this issue. Considering dynamic variation in both global and regional facial areas, the proposed hierarchical network with LSTM structure can effectively improve the diagnostic accuracy and extract paralysis detail from the low-level shape, contour to sematic level features. By segmenting the facial area into two palsy regions, the proposed method can discriminate FNP from normal face accurately and significantly reduce the effect caused by age wrinkles and unrepresentative organs with shape and position variations on feature learning. Experiment on the YouTube Facial Palsy Database and Extended CohnKanade Database shows that the proposed method is superior to the state of the art deep learning methods.

The Treatment of Facial Asymmetry with Botulinum Toxin: Current Concepts, Guidelines, and Future Trends

This article will describe facial asymmetry secondary to facial nerve paralysis (FNP), and review current concepts, guidelines, and future trends. Despite the increasing use of botulinum toxin (BoNTA) in treating FNP, ideal dosage, timing, and additional therapies are not unequivocally established. Facial asymmetry significantly impacts quality of life (QOL) by strongly affecting self-perception and social interactions; injectables may mediate great clinical improvement. This article provides practical guidelines for the use of BoNTA and provides schemes for accurate assessment and documentation. A systematic, stepwise approach is recommended with methodical assessment, meticulous placement, conservative dosage, and careful follow-up. Future trends include the potential use of newly developed toxins, muscle modification with fillers, improved imaging techniques, and targeted QOL studies. Hopefully, a growing number of aesthetic injectors may become technically proficient and join multidisciplinary teams for managing FNP.

Lipofilling of the upper eyelid to treat paralytic lagophthalmos

Lagophthalmos is one of the most unpleasant and dangerous conditions that affect patients with facial palsy. The lack of ocular protection leads to corneal problems (such as conjunctival infections, acute and chronic keratitis, corneal ulcerations, and blindness). A dynamic reanimation of blinking eyelids is the therapeutic gold standard. However, success is not guaranteed with these dynamic techniques; even if results are good, blinking is usually restored within a year of the initial operation. Procedures that act more rapidly and have a higher success rate are needed. We proposed that lipofilling of the upper eyelid would improve eye closure, exploit the advantages of using autologous fat, and avoid the risks of exposure or migration associated with loading the lid with gold. Between 2012 and September 2018, we did upper eyelid lipofilling procedures for 75 patients with unilateral facial palsy. The main favourable result of lipofilling of the upper lid was the immediate improvement in corneal discomfort. Everybody described a partial to total increase in corneal comfort postoperatively. In the treatment of paralytic lagophthalmos, lipofilling of the upper eyelid produces favourable aesthetic and functional results, ocular health is restored, and the patients' quality of life is improved.

Three-Dimensional Stereophotogrammetry Assessment of Facial Asymmetry in Facial Palsy

Three-dimensional stereophotogrammetry is not much used in assessing facial palsy and a comprehensive understanding of sources of variation in these measurements is lacking. The present study assessed intra- and interobserver reliability of a novel three-dimensional stereophotogrammetry measurement of facial asymmetry and examined sources of variation in these outcomes. Three photographs (rest, closed mouth smile, and maximum smile) were made of 60 participants, 30 facial palsy patients and 30 control subjects. All images were analyzed twice by 2 observers independently, to determine intra- and interobserver reliability. Variance component analysis was performed to investigate sources of variation in the outcomes. Intraobserver reliability was good with intraclass correlation coefficients ranging from 0.715 to 0.999. Interobserver reliability ranged from 0.442 to 0.929. Reliability of the smile image measurements was not clearly different from the rest images. Variation in measurement results was largely due to the status of a participant, facial palsy versus control. When splitting the sample, the facial expression was a major source of variation. Acceptable reliability of the proposed 3D facial asymmetry measurement was found, in facial palsy patients and control subjects. Interobserver reliability was marked less compared to intraobserver reliability. For follow-up data only one observer should assess 3D stereophotogrammetry measurements.