Semi-automated Detection of Polysomnographic REM Sleep without Atonia (RSWA) in REM Sleep Behavioral Disorder

Contemporary diagnostic visual and automated polysomnographic REM sleep without atonia thresholds in isolated REM sleep behavior disorder

STUDY OBJECTIVES

Accurate diagnosis of isolated rapid eye movement (REM) sleep behavior disorder (iRBD) is crucial due to its injury potential and neurological prognosis. We aimed to analyze visual and automated REM sleep without atonia (RSWA) diagnostic thresholds applicable in varying clinical presentations in a contemporary cohort of patients with iRBD using submentalis (SM) and individual bilateral flexor digitorum superficialis (FDS) and anterior tibialis electromyography limb recordings during polysomnography.

METHODS

We analyzed RSWA in 20 patients with iRBD and 20 age-, REM-, apnea-hypopnea index-matched controls between 2017 and 2022 for phasic burst durations, density of phasic, tonic, and "any" muscle activity (number of 3-second mini-epochs containing phasic or tonic muscle activity divided by the total number of REM sleep 3-second mini-epochs), and automated Ferri REM atonia index (RAI). Group RSWA metrics were comparatively analyzed. Receiver operating characteristic curves determined optimized area under the curve (AUC) and maximized specificity and sensitivity diagnostic iRBD RSWA thresholds.

RESULTS

All mean RSWA metrics were higher in patients with iRBD than in controls (P < .05), except for selected anterior tibialis measures. Optimized, maximal specificity AUC diagnostic cutoffs for coprimary outcomes were: SM "any" 6.5%, 14.0% (AUC = 92.5%) and combined SM+FDS "any" 15.1%, 27.4% (AUC = 95.8%), while SM burst durations were 0.72, and 0.72 seconds (AUC 90.2%) and FDS RAI = 0.930, 0.888 (AUC 92.8%).

CONCLUSIONS

This study provides evidence for current quantitative RSWA diagnostic thresholds in chin and individual 4 limb muscles applicable in different iRBD clinical settings and confirms the key value of SM or SM+FDS to assure accurate iRBD diagnosis. Evolving iRBD recognition underscores the necessity of continuous assessment with future large, prospective, well-harmonized, multicenter polysomnographic analyses.

CITATION

Leclair-Visonneau L, Feemster JC, Bibi N, et al. Contemporary diagnostic visual and automated polysomnographic REM sleep without atonia thresholds in isolated REM sleep behavior disorder. J Clin Sleep Med. 2024;20(2):279-291.

Quantification of REM sleep without atonia: A review of study methods and meta-analysis of their performance for the diagnosis of RBD

The present review focuses on REM sleep without atonia (RSWA) scoring methods. In consideration of the numerous papers published in the last decade, that used different methods for the quantification of RSWA, their systematic revision is an emerging need. We made a search using the PubMed, Embase, Scopus and Web of Science Databases, from 2010 until December 2021, combining the search term "RSWA" with "scoring methods", "IRBD", "alfasyn disease", and "neurodegenerative disease", and with each of the specific sleep disorders, diagnosed according to current criteria, with the identification of the references of interest for the topic. Furthermore, a Meta-analysis of the diagnostic performance of RSWA scoring methods, in terms of sensitivity and specificity, was carried out. The comparison of the hierarchical summary receiver-operating characteristic curves obtained for visual methods and that obtained for the automated REM sleep atonia index (RAI), shows substantially similar prediction areas indicating a comparable performance. This systematic review and meta-analysis support the validity of a series of visual methods and of the automated RAI in the quantification of RSWA with the purpose to guide clinicians in the interpretation of their results and their correct and efficient use within the diagnostic work-up for REM sleep behavior disorder.

Neurophysiological Aspects of REM Sleep Behavior Disorder (RBD): A Narrative Review

REM sleep without atonia (RSWA) is the polysomnographic (PSG) hallmark of rapid eye movement (REM) sleep behavior disorder (RBD), a feature essential for the diagnosis of this condition. Several additional neurophysiological aspects of this complex disorder have also recently been investigated in depth, which constitute the focus of this narrative review, together with RSWA. First, we describe the complex neural network underlying REM sleep and its muscle atonia, focusing on the disordered mechanisms leading to RSWA. RSWA is then described in terms of its polysomnographic features, and the methods (visual and automatic) currently available for its scoring and quantification are exposed and discussed. Subsequently, more recent and advanced neurophysiological features of RBD are described, such as electroencephalography during wakefulness and sleep, transcranial magnetic stimulation, and vestibular evoked myogenic potentials. The role of the assessment of neurophysiological features in the study of RBD is then carefully discussed, highlighting their usefulness and sensitivity in detecting neurodegeneration in the early or prodromal stages of RBD, as well as their relationship with other proposed biomarkers for the diagnosis, prognosis, and monitoring of this condition. Finally, a future research agenda is proposed to help clarify the many still unclear aspects of RBD.

Neurophysiological Aspects of REM Sleep Behavior Disorder (RBD): A Narrative Review

REM sleep without atonia (RSWA) is the polysomnographic (PSG) hallmark of rapid eye movement (REM) sleep behavior disorder (RBD), a feature essential for the diagnosis of this condition. Several additional neurophysiological aspects of this complex disorder have also recently been investigated in depth, which constitute the focus of this narrative review, together with RSWA. First, we describe the complex neural network underlying REM sleep and its muscle atonia, focusing on the disordered mechanisms leading to RSWA. RSWA is then described in terms of its polysomnographic features, and the methods (visual and automatic) currently available for its scoring and quantification are exposed and discussed. Subsequently, more recent and advanced neurophysiological features of RBD are described, such as electroencephalography during wakefulness and sleep, transcranial magnetic stimulation, and vestibular evoked myogenic potentials. The role of the assessment of neurophysiological features in the study of RBD is then carefully discussed, highlighting their usefulness and sensitivity in detecting neurodegeneration in the early or prodromal stages of RBD, as well as their relationship with other proposed biomarkers for the diagnosis, prognosis, and monitoring of this condition. Finally, a future research agenda is proposed to help clarify the many still unclear aspects of RBD.