论文信息 - An imaging informatics-based ePR (electronic patient record) system for providing decision support in evaluating dose optimization in stroke rehabilitation

An imaging informatics-based ePR (electronic patient record) system for providing decision support in evaluating dose optimization in stroke rehabilitation

Stroke is one of the major causes of death and disability in America. After stroke, about 65% of survivors still suffer from severe paresis, while rehabilitation treatment strategy after stroke plays an essential role in recovery. Currently, there is a clinical trial (NIH award #HD065438) to determine the optimal dose of rehabilitation for persistent recovery of arm and hand paresis. For DOSE (Dose Optimization Stroke Evaluation), laboratory-based measurements, such as the Wolf Motor Function test, behavioral questionnaires (e.g. Motor Activity Log-MAL), and MR, DTI, and Transcranial Magnetic Stimulation (TMS) imaging studies are planned. Current data collection processes are tedious and reside in various standalone systems including hardcopy forms. In order to improve the efficiency of this clinical trial and facilitate decision support, a web-based imaging informatics system has been implemented together with utilizing mobile devices (eg, iPAD, tablet PC's, laptops) for collecting input data and integrating all multi-media data into a single system. The system aims to provide clinical imaging informatics management and a platform to develop tools to predict the treatment effect based on the imaging studies and the treatment dosage with mathematical models. Since there is a large amount of information to be recorded within the DOSE project, the system provides clinical data entry through mobile device applications thus allowing users to collect data at the point of patient interaction without typing into a desktop computer, which is inconvenient. Imaging analysis tools will also be developed for structural MRI, DTI, and TMS imaging studies that will be integrated within the system and correlated with the clinical and behavioral data. This system provides a research platform for future development of mathematical models to evaluate the differences between prediction and reality and thus improve and refine the models rapidly and efficiently.

[1] S. Black,et al. The Fugl-Meyer Assessment of Motor Recovery after Stroke: A Critical Review of Its Measurement Properties , 2002, Neurorehabilitation and neural repair.

[2] J. P. Miller,et al. Effect of constraint-induced movement therapy on upper extremity function 3 to 9 months after stroke: the EXCITE randomized clinical trial. , 2006, JAMA.

[3] B. Dobkin. Rehabilitation after Stroke , 2005 .

[4] W. J. Powers,et al. Very Early Constraint-Induced Movement during Stroke Rehabilitation (VECTORS) , 2009, Neurology.

[5] A. Wing,et al. Motor control and learning principles for rehabilitation of upper limb movements after brain injury , 2003 .

[6] B. Dobkin. Clinical practice. Rehabilitation after stroke. , 2005, The New England journal of medicine.

[7] Sheng-Feng Sung,et al. The Impact of Timing and Dose of Rehabilitation Delivery on Functional Recovery of Stroke Patients , 2009, Journal of the Chinese Medical Association : JCMA.

[8] B. Dobkin. Strategies for stroke rehabilitation , 2004, The Lancet Neurology.

[9] Tobey Clark. PACS and Imaging Informatics: Basic Principles and Applications , 2006 .

[10] Michael A. Arbib,et al. Stroke Rehabilitation Reaches a Threshold , 2008, PLoS Comput. Biol..

[11] A. Fugl-Meyer,et al. The post-stroke hemiplegic patient. 1. a method for evaluation of physical performance. , 1975, Scandinavian journal of rehabilitation medicine.