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A Multi-modal Approach to Outcome Tracking in Facial Palsy

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Facial Palsy

Abstract

Facial palsy is a complex condition affecting multiple domains including quality of life, facial function, and cosmesis. Facial reanimation can dramatically improve the patient’s ability to move their face. Yet, in order to assess its impact on all of these domains, outcome assessment ought to be multi-modal, including patient-reported outcome measures, clinician-graded scoring systems, objective assessment tools, and layperson and smile spontaneity assessment. Patient-reported outcome measures are required to assess the psychosocial impact of facial nerve dysfunction, as experienced by patients. Clinician-graded scoring systems and objective assessment tools are needed to rate severity of disease and the effects of interventions. Layperson assessments are useful to determine impacts of facial palsy on attractiveness, disfigurement, and non-verbal communication. A novel approach using machine learning algorithms to assess the emotionality of smiling has been developed and shown to correlate with layperson assessments. A means of objectively quantifying spontaneity of smile has also been developed. In this article, we have described the most frequently used tools that capture each of the domains of a complete facial palsy assessment, and emerging techniques that have utilized machine learning approaches to objectively quantify outcomes and compare post-surgical outcomes to huge normative databases of normal facial expressions.

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Disclosure Statement

Dr. Hadlock, Dr. Dusseldorp, and Dr. Meares have nothing to disclose. No funding was received for this article.

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Authors and Affiliations

  1. Department of Otolaryngology/Head and Neck Surgery, Massachusetts Eye and Ear Infirmary and Harvard Medical School, Boston, MA, USA

    Joseph R. Dusseldorp & Tessa A. Hadlock

  2. Department of Plastic and Reconstructive Surgery, Royal Australasian College of Surgeons and University of Sydney, Sydney, NSW, Australia

    Joseph R. Dusseldorp & Charles Meares

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  1. Plastic and Reconstructive Surgery, Hospital of Divine Savior (Krankenhaus Goettlicher Heiland), Sigmund Freud University, TZOU MEDICAL, Vienna, Austria

    Chieh-Han John Tzou

  2. Department of Plastic and Maxillofacial Surgery and Department of Surgical Sciences, Uppsala University Hospital, Uppsala University, Uppsala, Sweden

    Andrés Rodríguez-Lorenzo

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Dusseldorp, J.R., Meares, C., Hadlock, T.A. (2021). A Multi-modal Approach to Outcome Tracking in Facial Palsy. In: Tzou, CH.J., Rodríguez-Lorenzo, A. (eds) Facial Palsy. Springer, Cham. https://doi.org/10.1007/978-3-030-50784-8_2

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