Automated 'pain drawing' analysis by computer-controlled, patient-interactive neurological stimulation system.
We have developed a new method for the collection and analysis of pain drawings, as part of a computer-controlled, patient-interactive system for use with implanted neurological stimulators. The system has been tested in 44 patients with permanently implanted spinal cord stimulators for the relief of chronic, intractable pain. Patients interact directly with the system, using a graphics tablet, to enter pain drawings and corresponding outlines of their perceptions of stimulation paresthesias, for different stimulating pulse parameters and electrode geometries. Image analysis software has been developed to examine these data quantitatively. This precludes the inter-rater inconsistencies reported for manual pain drawing scoring techniques. A highly significant correlation has been observed between patients' analog ratings of the overlap of pain by paresthesias and the results of our automated analysis of graphic data. This in turn has been found to correlate with clinical observations of pain relief. The contemporary implantable stimulation devices supported by our system permit non-invasive selection of stimulating anodes and cathodes from a linear array of 4 electrodes. The 50 possible electrode combinations have certain geometric features, which we have entered into a multivariate statistical analysis, to determine their relationship with the overlap of pain by paresthesias. One particular configuration (cathode(s) flanked by anode(s) above and below) is significantly better, by this measure, than all the alternatives. This is consistent with prior clinical observations that this configuration is favored by patients whose systems have been adjusted by conventional, manual methods. Pain drawing' entry and analysis by a computerized, patient-interactive system has been useful in this specialized setting and may have broader applications.
North
Richard B
RB
Department of Neurosurgery, Johns Hopkins University, Baltimore, MD 21205 USA Department of Biostatistics, School of Medicine, Baltimore, MD 21205 USA Department of Applied Physics Laboratory, Johns Hopkins University, Baltimore, MD 21205 USA.
Nigrin
Daniel J
DJ
Fowler
Kim R
KR
Szymanski
Richard E
RE
Piantadosi
Steven
S
D000328:Adult; D001154:Art; D001331:Automation; D003936:Diagnosis, Computer-Assisted; D004599:Electric Stimulation Therapy; D005260:Female; D006801:Humans; D008297:Male; D009462:Neurology / Q000379:methods*; D010147:Pain Measurement / Q000379:methods*; D010166:Palliative Care / Q000379:methods*; D012044:Regression Analysis; D012647:Self-Assessment; D013116:Spinal Cord / Q000503:physiopathology; D013813:Therapy, Computer-Assisted