Objective: Essential tremor is among the most prevalent neurological diseases. Diagnosis is based entirely on neurological evaluation. Historically, there were few postmortem brain studies, hindering attempts to develop pathologically based criteria to distinguish essential tremor from control brains. However, an intensive effort to bank essential tremor brains over recent years has resulted in postmortem studies involving >200 brains, which have identified numerous degenerative changes in the essential tremor cerebellar cortex. Although essential tremor and controls have been compared with respect to individual metrics of pathology, there has been no overarching analysis to derive a combination of metrics to distinguish essential tremor from controls. We asked whether there is a constellation of pathological findings that separates essential tremor from controls, and how well that constellation performs.
Methods: Analyses included 100 essential tremor brains from the essential tremor centralized brain repository and 50 control brains. A standard tissue block from the cerebellar cortex was used to quantify 11 metrics of pathological change. Three supervised classification algorithms were investigated, with data divided into training and validation samples.
Results: Using three different algorithms, we illustrate the ability to correctly predict a diagnosis of essential tremor, with sensitivity and specificity >87%, and in the majority of situations, >90%. We also provide a web-based application that uses these metric values, and based on specified cutoffs, determines the likely diagnosis.
Interpretation: These analyses set the stage for use of pathologically based criteria to distinguish clinically diagnosed essential tremor cases from controls, at the time of postmortem.
© 2024 The Authors. Annals of Clinical and Translational Neurology published by Wiley Periodicals LLC on behalf of American Neurological Association.