Identifying diagnostic biomarkers in functional motor disorders through multimodal behavioral, neurophysiological, and imaging assessment using explainable machine learning.
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Gandolfi Marialuisa, Sandri Angela, Russo Michela, Sarasso Elisabetta, Gardoni Andrea, Basaia Silvia, Erro Roberto, Cuoco Sofia, Carotenuto Immacolata, Ricciardi Carlo, Amato Francesco, Vinciguerra Claudia, Botto Annibale, Amboni Marianna, Romano Daniele, Di Vico Ilaria Antonella, Fiorio Mirta, Pedrotti Giulia, Paolicelli Anna, Crestani Mauro, Fratucello Anna, Mansueto Giancarlo, Pizzini Francesca Benedetta, Barillari Marco, Lauriola Matteo Francesco, Tozzi Mariachiara, Rusciano Francesca, Geroin Christian, Fasoli Melania, Marotta Angela, Salaorni Francesca, Squintani Giovanna Maddalena, Mariotto Sara, Tamburin Stefano, Paio Fabio, De Biasi Giuseppe, Piscosquito Giuseppe, Zenere Lucia, Canu Elisa, Barone Paolo, Filippi Massimo, Agosta Federica, Pellecchia Maria Teresa, Tinazzi Michele
Аннотация
METHODS: In this multicenter cross-sectional study, consecutive adults with a clinically established FMDs diagnosis (n = 75, 74.7% female; mean age 44.20 ± 12.92) and age- and sex-matched HCs (n = 75; 58.6% female; 48.42 ± 11.67) were recruited. All participants underwent standardized behavioral, neurophysiological, and brain MRI assessment exploring motor, exteroceptive, and interoceptive domains. A Random Forest (RF) classifier combined with repeated stratified k-fold cross-validation was trained on the collected features. Predictive performance was evaluated using accuracy, sensitivity, specificity, precision, F1-score, and AUC-ROC. SHapley Additive exPlanations interpreted feature importance.
RESULTS: The strongest diagnostic biomarkers were lower dual-task effect scores for postural sway area under eyes-closed motor and cognitive conditions, and gait speed during the motor dual-task, followed by increased vDMN and basal ganglia networks functional connectivity, reduced baseline ipsilateral-contralateral R2 blink reflex area, and higher DNIC-to-baseline N2P2 amplitude ratios for the lower limb. The RF classifier achieved robust performance (accuracy 85.0%, sensitivity 83.9%, specificity 86.1%, F1-score 85.7%, AUC-ROC 0.921).
CONCLUSIONS: Motor, functional neuroimaging, and neurophysiological markers demonstrated diagnostic value in distinguishing FMDs from healthy controls, addressing the current lack of objective tools and supporting more confident and accurate diagnosis of these heterogeneous conditions.
TRIAL REGISTRATION: Trial registration number NCT06328790. Registered on 26 March 2024.