Abstract
Introduction
One of the major challenges of neurostimulation is actually to address the back pain component in patients suffering from refractory chronic back and leg pain. Facing a tremendous expansion of neurostimulation techniques and available devices, implanters, patients and even industrial companies can still remain confused as they need to select the right tool for the right indication. To be able to evaluate and compare objectively patient outcomes, depending on therapeutical strategies, it appears essential to develop a rational and quantitative approach to pain assessement and neurostimulation outcomes for those who undergo neurostimulation implantation.
Material and Methods
Our neuroinformatics laboratory (N3Laboratory) located in Poitiers University Hospital, Department of Neurosurgery, enabled us to develop the Neuro-Mapping Tools software (N3MT) (Inter Deposit Digital Number: IDDN FR 001–1600002–000-R-P-2013–000–31230; Patent Applications n°PCT/EP2014/067231, n°PCT/FR 14/000 186 and n°PCT/FR 14/000 187). This tool consists of touch screen mapping, allowing the patient and/or the physician to interact by means of a tablet computer to delineate painful zones and paraesthesia coverage in the thoracolumbar region and legs.
Results
The Neuro-Mapping Tools software (N3MT) (Neuro-Pain'T, the Neuro-Mapping Locator and the Neuro-Data-Base) have been put together and used in more than 190 patients since 2012, leading us to describe new measurement parameters, divided into two categories: (1) Technical parameters, evaluating the implanted device itself, as “Device Performance, XP,” “Device Specificity, XS” and “Persistence of the Paresthesia Perception” on the long term (XP3). (2) Clinical parameters, evaluating patient response to the therapy: (a) pain surface reduction. This parameter is called YS. (b) pain intensity reduction. This parameter is called YI. (c) pain characteristics redistribution after implantation. This parameter is called YPC.
Conclusion
The N3MT software could help to guide tomorrow's treatment options by transforming personal convictions into a more robust scientific rationale based on data collection and data mining techniques.