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Hong R, Wu Z, Peng K, Zhang J, He Y, Zhang Z, Gao Y, Jin Y, Su X, Zhi H, Guan Q, Pan L, Jin L. Kinect-based objective assessment of the acute levodopa challenge test in parkinsonism: a feasibility study. Neurol Sci 2024; 45:2661-2670. [PMID: 38183553 DOI: 10.1007/s10072-023-07296-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2023] [Accepted: 12/28/2023] [Indexed: 01/08/2024]
Abstract
INTRODUCTION The acute levodopa challenge test (ALCT) is an important and valuable examination but there are still some shortcomings with it. We aimed to objectively assess ALCT based on a depth camera and filter out the best indicators. METHODS Fifty-nine individuals with parkinsonism completed ALCT and the improvement rate (IR, which indicates the change in value before and after levodopa administration) of the Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale part III (MDS-UPDRS III) was calculated. The kinematic features of the patients' movements in both the OFF and ON states were collected with an Azure Kinect depth camera. RESULTS The IR of MDS-UPDRS III was significantly correlated with the IRs of many kinematic features for arising from a chair, pronation-supination movements of the hand, finger tapping, toe tapping, leg agility, and gait (rs = - 0.277 ~ - 0.672, P < 0.05). Moderate to high discriminative values were found in the selected features in identifying a clinically significant response to levodopa with sensitivity, specificity, and area under the curve (AUC) in the range of 50-100%, 47.22%-97.22%, and 0.673-0.915, respectively. The resulting classifier combining kinematic features of toe tapping showed an excellent performance with an AUC of 0.966 (95% CI = 0.922-1.000, P < 0.001). The optimal cut-off value was 21.24% with sensitivity and specificity of 94.44% and 87.18%, respectively. CONCLUSION This study demonstrated the feasibility of measuring the effect of levodopa and objectively assessing ALCT based on kinematic data derived from an Azure Kinect-based system.
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Affiliation(s)
- Ronghua Hong
- Department of Neurology and Neurological Rehabilitation, Shanghai Disabled Persons' Federation Key Laboratory of Intelligent Rehabilitation Assistive Devices and Technologies, School of Medicine, Shanghai Yangzhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center), Tongji University, Shanghai, China
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration of Ministry of Education, Department of Neurology, School of Medicine, Neurotoxin Research CenterTongji HospitalTongji University, Shanghai, China
| | - Zhuang Wu
- Department of Neurology and Neurological Rehabilitation, Shanghai Disabled Persons' Federation Key Laboratory of Intelligent Rehabilitation Assistive Devices and Technologies, School of Medicine, Shanghai Yangzhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center), Tongji University, Shanghai, China
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration of Ministry of Education, Department of Neurology, School of Medicine, Neurotoxin Research CenterTongji HospitalTongji University, Shanghai, China
| | - Kangwen Peng
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration of Ministry of Education, Department of Neurology, School of Medicine, Neurotoxin Research CenterTongji HospitalTongji University, Shanghai, China
| | - Jingxing Zhang
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration of Ministry of Education, Department of Neurology, School of Medicine, Neurotoxin Research CenterTongji HospitalTongji University, Shanghai, China
| | - Yijing He
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration of Ministry of Education, Department of Neurology, School of Medicine, Neurotoxin Research CenterTongji HospitalTongji University, Shanghai, China
| | - Zhuoyu Zhang
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration of Ministry of Education, Department of Neurology, School of Medicine, Neurotoxin Research CenterTongji HospitalTongji University, Shanghai, China
| | - Yichen Gao
- IFLYTEK Suzhou Research Institute, Suzhou, China
| | - Yue Jin
- IFLYTEK Suzhou Research Institute, Suzhou, China
| | - Xiaoyun Su
- IFLYTEK Suzhou Research Institute, Suzhou, China
| | - Hongping Zhi
- IFLYTEK Suzhou Research Institute, Suzhou, China
| | - Qiang Guan
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration of Ministry of Education, Department of Neurology, School of Medicine, Neurotoxin Research CenterTongji HospitalTongji University, Shanghai, China
| | - Lizhen Pan
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration of Ministry of Education, Department of Neurology, School of Medicine, Neurotoxin Research CenterTongji HospitalTongji University, Shanghai, China.
| | - Lingjing Jin
- Department of Neurology and Neurological Rehabilitation, Shanghai Disabled Persons' Federation Key Laboratory of Intelligent Rehabilitation Assistive Devices and Technologies, School of Medicine, Shanghai Yangzhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center), Tongji University, Shanghai, China.
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration of Ministry of Education, Department of Neurology, School of Medicine, Neurotoxin Research CenterTongji HospitalTongji University, Shanghai, China.
- Collaborative Innovation Center for Brain Science, Tongji University, Shanghai, China.
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