Neurologist consistency in interpreting information provided by an interactive visualization software for deep brain stimulation postoperative programming assistance.

Pallavaram S, Phibbs FT, Tolleson C, Davis TL, Fang J, Hedera P, Li R, Koyama T, Dawant BM, D'Haese PF
Neuromodulation. 2014 17 (1): 11-5; discussion 15

PMID: 23647701 · PMCID: PMC4039015 · DOI:10.1111/ner.12061

INTRODUCTION - Postoperative programming in deep brain stimulation (DBS) therapy for movement disorders can be challenging and time consuming. Providing the neurologist with tools to visualize the electrode location relative to the patient's anatomy along with models of tissue activation and statistical data can therefore be very helpful. In this study, we evaluate the consistency between neurologists in interpreting and using such information provided by our DBS programming assistance software.

METHODS - Five neurologists experienced in DBS programming were each given a dataset of 29 leads implanted in 17 patients. For each patient, probabilistic maps of stimulation response, anatomical images, models of tissue activation volumes, and electrode positions were presented inside a software framework called CRAnialVault Explorer (CRAVE) developed in house. Consistency between neurologists in optimal contact selection using the software was measured.

RESULTS - With only the efficacy map, the average consistency among the five neurologists with respect to the mode and mean of their selections was 97% and 95%, respectively, while these numbers were 93% and 89%, respectively, when both efficacy and an adverse effect map were used simultaneously. Fleiss' kappa statistic also showed very strong agreement among the neurologists (0.87 when using one map and 0.72 when using two maps).

CONCLUSION - Our five neurologists demonstrated high consistency in interpreting information provided by the CRAVE interactive visualization software for DBS postoperative programming assistance. Three of our five neurologists had no prior experience with the software, which suggests that the software has a short learning curve and contact selection is not dependent on familiarity with the program tools.

© 2013 Vanderbilt University.

MeSH Terms (17)

Brain Mapping Comprehension Deep Brain Stimulation Electrodes, Implanted Humans Imaging, Three-Dimensional Magnetic Resonance Imaging Models, Neurological Models, Statistical Movement Disorders Muscle Contraction Muscle Rigidity Neuroimaging Neurology Reproducibility of Results Software User-Computer Interface

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