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Updated: Apr 19, 2026
Dynamic Quantitative Sensory Testing to Characterize Central Pain Processing
Published on: February 16, 2017
A novel, objective, quantitative method of evaluation of the back pain component using comparative computerized
P Rigoard1, K Nivole2, P Blouin2
1N(3)Lab (Neuromodulation & Neural Networks), Poitiers University Hospital, 86000 Poitiers, France; Department of Neurosurgery, Poitiers University Hospital, 86000 Poitiers, France.
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 and patients 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 assessment for those who undergo neurostimulation implantation.
Objectives, Material And Methods:
We developed a touch screen interface, in Poitiers University Hospital and N(3)Lab, called the "Neuro-Pain'T", to detect, record and quantify the painful area surface and intensity changes in an implanted patient within time. The second aim of this software is to analyse the link between a paraesthesia coverage generated by a type of neurostimulation and a potential analgesic effect, measured by pain surface reduction, pain intensity reduction within the painful surface and local change in pain characteristics distribution. The third aim of Neuro-Pain'T is to correlate these clinical parameters to global patient data and functional outcome analysis, via a network database (Neuro-Database), to be able to provide a concise but objective approach of the neurostimulation efficacy, summarized by an index called "RFG Index".
Results And Discussion:
This software has been used in more than 190 patients since 2012, leading us to define three clinical parameters grouped as a clinical component of the RFG Index, which might be helpful to assess neurostimulation efficacy and compare implanted devices.
Conclusion:
The Neuro-Pain'T is an original software designed to objectively and quantitatively characterize reduction of a painful area in a given individual, in terms of intensity, surface and pain typology, in response to a treatment strategy or implantation of an analgesic device. Because pain is a physical sensation, which integrates a psychological dimension, its assessment justifies the use of multidimensional and global evaluation scales. However, in the context of neurostimulation and comparative clinical trials designed to test the technical efficacy of a given device, a simple, objective and quantitative evaluation tool 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.
