The Forward and Lateral Tilt Angle of the Neck and Trunk Measured by Three-Dimensional Gait and Motion Analysis as a Candidate for a Severity Index in Patients with Parkinson’s Disease

(1) Objective: To evaluate the usefulness of a three-dimensional motion-analysis system (AKIRA®) as a quantitative measure of motor symptoms in patients with Parkinson’s disease (PD). (2) Method: This study included 48 patients with PD. We measured their motion during 2 m of walking using AKIRA®, we calculated the tilt angles of the neck and trunk, ankle height, and gait speed, then we compared these parameters with the MDS-UPDRS and the Hoehn and Yahr scale. Furthermore, we measured these AKIRA indicators before and after 1 year of observation. (3) Results: The forward tilt angle of the neck showed a strong correlation with the scores on parts II, III, and the total MDS-UPDRS, and the tilt angle of the trunk showed a moderate correlation with those measures. The lateral tilt angle of the trunk showed a moderate correlation with a freezing of the gait and a postural instability. Regarding changes over the course of 1 year (n = 34), the total scores on part III of the MDS-UPDRS and the forward tilt angle of the neck improved, while the lateral tilt angle of the trunk worsened. (4) Conclusion: Taken together, the forward and lateral tilt angles of the neck and trunk as measured by AKIRA® can be a candidate for quantitative severity index in patients with PD

The Utility of Automated ASPECTS in Acute Ischemic Stroke for Intravenous Recombinant Tissue Plasminogen Activator (IV-rtPA) Therapy.

PURPOSE: This study aimed to investigate the accuracy and clinical significance of an artificial intelligence (AI)-based automated Alberta Stroke Program Early Computed Tomography (ASPECT) scoring software of head CT for the indication of intravenous recombinant tissue plasminogen activator (rt-PA) therapy. METHODS: This study included two populations of acute ischemic stroke: one comprised patients who had undergone head CT within 48 h of presentation (Population #1, n = 448), while the other included patients within 4.5 h from onset (Population #2, n = 132). The primary endpoint was the concordance rate of ASPECTS of the neurologists and AI software against the benchmark score. The secondary endpoints were to validate the accuracy of the neurologist and AI software in assessing the ability to rule out extensive infarction (ASPECTS of 0-5) in population #2. RESULTS: The reading accuracy of AI software was comparable to that of the board-certified vascular neurologists. The detection rate of cardiogenic cerebral embolism was better than that of atherothrombotic cerebral infarction. By excluding extensive infarction, AI-software showed a higher specificity and equivalent sensitivity compared to those of experts. CONCLUSIONS: The AI software for ASPECTS showed convincing agreement with expert evaluation and would be supportive in determining the indications of intravenous rt-PA therapy