4.5 Article

Imaging Features to Predict Response to Olfactory Training in Post-Traumatic Olfactory Dysfunction

Journal

LARYNGOSCOPE
Volume 131, Issue 7, Pages E2243-E2250

Publisher

WILEY
DOI: 10.1002/lary.29392

Keywords

Olfactory dysfunction; olfactory training; Sniffin' Sticks test; head-trauma.

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A retrospective study on 52 patients undergoing olfactory training for post-traumatic olfactory dysfunction revealed imaging features that can predict responses to treatment. A scoring system was developed based on five variables to provide a good specificity for optimizing management options.
Objectives/Hypothesis Prognosis of post-traumatic olfactory dysfunction is poor, with medical treatment options showing limited success rates. Olfactory training (OT) has been introduced as a potential therapeutic option in olfactory dysfunction. We aimed to identify the imaging features that would predict a better response to OT and create an imaging-based prognostic scale. Methods We retrospectively reviewed 52 patients that underwent OT at our center for post-traumatic olfactory dysfunction. Olfactory functions at the time of initial presentation and at completion of OT were evaluated using Sniffin' Sticks test and threshold discrimination identification (TDI) scores were calculated. Patients were divided into responders (ROT group: 16 cases) and non-responders (n-ROT group: 36 cases) to OT based on TDI score change (cut-off 5.5 point). Morphological measurements of olfactory fossa, olfactory bulb volume and signal abnormalities, olfactory nerve filia integrity, siderosis, encephalomalacic changes in olfactory cortex, and other cortical regions were reviewed. Results There was no significant difference between the two groups in terms of age, gender distribution, olfactory dysfunction duration, head-trauma severity, and initial TDI scores. A model incorporating five variables: cribriform plate fracture, olfactory fossa depth (cut-off: 4.9 mm), olfactory bulb encephalomalacia, olfactory bulb volume (cut-off: 27.1 mm(3)), and siderosis was developed. This model had an area under the curve (AUC) of 0.950, and a cut-off value of 1 had 76.5% sensitivity and 97.1% specificity in prediction of response to OT. Conclusions We developed an imaging-based scoring system with good specificity that can be used as an adjunctive tool for patient counseling, and optimal selection of management options.

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