QUANTITATIVE TRANSCRANIAL SONOGRAPHY EVALUATION OF SUBSTANTIA NIGRA HYPERECHOGENICITY IS USEFUL FOR PREDICTING LEVODOPA- INDUCED DYSKINESIA IN PARKINSON DISEASE

Levodopa dyskinesia (LID) is a common motor complication in Parkinson disease (PD). Abnormal substantia nigra hyperechogenicity (SN+), detected by transcranial sonography (TCS), plays an important role in the differential diagnosis of PD. The purpose of this study was to investigate the predictive per-formance of quantitative SN+ evaluations for LID. Five hundred sixty-two individuals were included in our anal-ysis, and 198 individuals were followed up. These individuals were divided into two groups at baseline: the PD with LID (PD+LID) group and the PD without LID (PD-LID) group. The association between total hyperecho-genic area of the SN on both sides (SNT) and LID was analyzed by binary logistic analysis. A binary logistic regression model including SNT was applied to establish a model for discriminating LID. At baseline, 105 (18.7%) individuals were diagnosed with LID. The PD+LID group had a longer disease duration, shorter educa-tion duration, higher levodopa equivalent doses, greater disease severity and larger SNT. A model combining clin-ical features and SNT was further established with better efficiency (area under the receiver operating characteristic curve = 0.839). One hundred ninety-eight individuals were followed up; individuals with a larger SNT and a higher predicted probability were more likely to develop LID in our follow-up. Our study determined that quantitative TCS evaluation of SN echogenicity is useful in predicting LID in PD. (E-mail: liuchunfeng@suda.edu.cn) (c) 2022 The Author(s). Published by Elsevier Inc. on behalf of World Federation for Ultrasound in Medicine & Biology. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Automated summary

This study aimed to investigate the predictive performance of quantitative substantia nigra (SN) evaluations using transcranial sonography for levodopa dyskinesia (LID) in Parkinson's disease (PD). The study found that the total hyperechogenic area of the SN was associated with LID. A model combining clinical features and the hyperechogenic area of the SN showed better efficiency in predicting LID development.