Letter to the Editor: Correlation of diffusion tensor imaging and intraoperative macrostimulation

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TO THE EDITOR: We read with great interest the paper by Said et al.9 (Said N, Elias WJ, Raghavan P, et al: Correlation of diffusion tensor tractography and intraoperative macrostimulation during deep brain stimulation for Parkinson disease. J Neurosurg 121:929–935, October 2014). On deeper inspection we find that the conclusions drawn from the results of this work are based on scientific methods that are not consistent with the current state-of-the-art methods in the burgeoning field of “connectomic neurosurgery.”6 It is our belief that the authors’ conclusions need to be put into a more explicit context. 1) There cannot be a direct correlation between voltage (U) amplitude (applied during macrostimulation in deep brain stimulation [DBS] surgery) and the distance to the medial corticospinal tract (CST). There is some correlation that might be found between stimulation current (I) and distance,8 as we have used in subthalamic nucleus surgery previously.4 However, according to Ohm’s law (I = U/R), resistance (tissue impedance and others = R) needs to be correlation-evaluated. This in itself is difficult, and there might be ways to bring impedance, electrode geometry, and stimulation voltage into perspective in an attempt to draw conclusions on the distance to the medial CST border.2,3,7 In the currently performed fashion, a pure correlation between voltage and distance is not the most relevant measure. 2) The rendition of the CST with the diffusion tensor imaging (DTI) technology as shown in this work (Fig. 2) is not constructed using state-of-the-art methods and underestimates the spatial distribution of the pathway in the subthalamic region. This has implications for the measurements and, in turn, for the definition of the medial border of the CST, which are known limitations of deterministic tractography in this application.7 However, we agree that it is difficult to correctly judge the size and shape of the internal capsule and explicitly define the medial border of the CST on a patient-specific basis under any circumstances. This issue is compounded by the diversity of tracking algorithms that are available to the surgeon by commercial software systems, albeit not originally designed for this purpose, but rather to provide a gross estimate of structural connectivity.1 3) The inherent desire to trust software that the user may not fully understand represents a dangerous proposition when subsequently used for scientific analysis or clinical decision support, exemplified in Fig. 1 of Said et al.’s article, which depicts the CST in the wrong anatomical location relative to the patient anatomy (i.e., it should have been recognized on simple visual inspection that the CST should be situated lateral to the DBS electrode).

Several groups around the world, including both of our groups, are researching the application of diffusion-weighted imaging and tractography technology for the use in planning and performing DBS surgery in its various indications.5,10 We have shown in our previous work that tractography can be applied with a high enough accuracy to directly assist DBS surgery. It is not our intention to suppress results that might contradict our own work. However, conclusions should be based on proper scientific methods, and these should be debated openly. Our analysis suggests that this study represents an attempt to apply advanced imaging concepts with typical clinical imaging data sets whose collection were likely not appropriately designed for such a purpose, coupled with the use of overly simplified “push button” tractography provided in commercial software. We propose that an important basic goal for our field should be to establish a best-practices approach to preoperative MRI data collection and tractography analysis for future studies, for example, definition of minimum resolutions and signal-to-noise ratios for imaging data sets worthy of inclusion in scientific publications, as well as consensus-based identification of the most accurate and robust tractography metrics, specifically designed for the task at hand.

References

  • 1

    Bürgel UMädler BHoney CRThron AGilsbach JCoenen VA: Fiber tracking with distinct software tools results in a clear diversity in anatomical fiber tract portrayal. Cen Eur Neurosurg 70:27352009

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  • 2

    Butson CRMaks CBMcIntyre CC: Sources and effects of electrode impedance during deep brain stimulation. Clin Neurophysiol 117:4474542006

    • Search Google Scholar
    • Export Citation
  • 3

    Chaturvedi AButson CRLempka SFCooper SEMcIntyre CC: Patient-specific models of deep brain stimulation: influence of field model complexity on neural activation predictions. Brain stimul 3:65672010

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    • Export Citation
  • 4

    Coenen VAFromm CKronenbürger MRohde IReinacher PCBecker R: Electrophysiological proof of diffusion-weighted imaging-derived depiction of the deep-seated pyramidal tract in human. Zentralbl Neurochir 67:1171222006

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    • Export Citation
  • 5

    Coenen VASchlaepfer TEAllert NMadler B: Diffusion tensor imaging and neuromodulation: DTI as key technology for deep brain stimulation. Int Rev Neurobiol 107:2072342012

    • Search Google Scholar
    • Export Citation
  • 6

    Henderson JM: “Connectomic surgery”: diffusion tensor imaging (DTI) tractography as a targeting modality for surgical modulation of neural networks”. Front integr Neurosci 6:152012

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    • Export Citation
  • 7

    Mädler BCoenen VA: Explaining clinical effects of deep brain stimulation through simplified target-specific modeling of the volume of activated tissue. AJNR am J Neuroradiol 33:107210802012

    • Search Google Scholar
    • Export Citation
  • 8

    Ranck JB Jr: Which elements are excited in electrical stimulation of mammalian central nervous system: a review. Brain res 98:4174401975

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    • Export Citation
  • 9

    Said NElias WJRaghavan PCupino ATustison NFrysinger R: Correlation of diffusion tensor tractography and intraoperative macrostimulation during deep brain stimulation for Parkinson disease. J Neurosurg 121:9299352014

    • Search Google Scholar
    • Export Citation
  • 10

    Sweet JAWalter BLGunalan KChaturvedi AMcIntyre CCMiller JP: Fiber tractography of the axonal pathways linking the basal ganglia and cerebellum in Parkinson disease: implications for targeting in deep brain stimulation. J Neurosurg 120:9889962014

    • Search Google Scholar
    • Export Citation

Response

We thank Drs. Coenen and McIntyre for sharing their thoughts about our article. We must admit that we too were surprised by the negative results of our study, as we are also believers in the potential of DTI and advanced neuroimaging in general. However, we thought it important to publish these negative results to warn the neurosurgical community about the pitfalls of a simplistic application of DTI to neurosurgical guidance. As demonstrated by our results, the traditional macrostimulation in DBS surgery cannot be merely replaced by measuring a distance from electrodes to tracts on DTI. There are multiple reasons for this, including some related to physiology and physics, or others related to the variation in terms of the shape and size of the CST in individual patients. Another important source of potential error in the clinical setting is the diversity of DTI acquisition techniques and DTI processing algorithms. These multiple methods cannot be considered as being interchangeable, and the degree of specialization required to master the DTI technology challenges the widespread, safe utilization of DTI for neuronavigation in individual patients. Definitions of best practices are a desired goal, but they are extremely difficult to achieve considering the number of stakeholders involved (imaging manufacturers, processing software companies, users, and regulatory authorities). An easier alternative is for individual institutions to develop their expertise in the specific DTI tool that they select and to develop a detailed understanding of the strengths, limitations, and pitfalls of this tool.

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Article Information

INCLUDE WHEN CITING Published online May 22, 2015; DOI: 10.3171/2014.12.JNS142690.

DISCLOSURE Dr. Coenen has been a consultant for Medtronic and is a consultant for Precisis AG and received research support from Medtronic Europe and Boston Scientific. Dr. McIntyre reports that he is a consultant for Boston Scientific Neuromodulation and Surgical Information Sciences.

© AANS, except where prohibited by US copyright law.

Headings

References

  • 1

    Bürgel UMädler BHoney CRThron AGilsbach JCoenen VA: Fiber tracking with distinct software tools results in a clear diversity in anatomical fiber tract portrayal. Cen Eur Neurosurg 70:27352009

    • Search Google Scholar
    • Export Citation
  • 2

    Butson CRMaks CBMcIntyre CC: Sources and effects of electrode impedance during deep brain stimulation. Clin Neurophysiol 117:4474542006

    • Search Google Scholar
    • Export Citation
  • 3

    Chaturvedi AButson CRLempka SFCooper SEMcIntyre CC: Patient-specific models of deep brain stimulation: influence of field model complexity on neural activation predictions. Brain stimul 3:65672010

    • Search Google Scholar
    • Export Citation
  • 4

    Coenen VAFromm CKronenbürger MRohde IReinacher PCBecker R: Electrophysiological proof of diffusion-weighted imaging-derived depiction of the deep-seated pyramidal tract in human. Zentralbl Neurochir 67:1171222006

    • Search Google Scholar
    • Export Citation
  • 5

    Coenen VASchlaepfer TEAllert NMadler B: Diffusion tensor imaging and neuromodulation: DTI as key technology for deep brain stimulation. Int Rev Neurobiol 107:2072342012

    • Search Google Scholar
    • Export Citation
  • 6

    Henderson JM: “Connectomic surgery”: diffusion tensor imaging (DTI) tractography as a targeting modality for surgical modulation of neural networks”. Front integr Neurosci 6:152012

    • Search Google Scholar
    • Export Citation
  • 7

    Mädler BCoenen VA: Explaining clinical effects of deep brain stimulation through simplified target-specific modeling of the volume of activated tissue. AJNR am J Neuroradiol 33:107210802012

    • Search Google Scholar
    • Export Citation
  • 8

    Ranck JB Jr: Which elements are excited in electrical stimulation of mammalian central nervous system: a review. Brain res 98:4174401975

    • Search Google Scholar
    • Export Citation
  • 9

    Said NElias WJRaghavan PCupino ATustison NFrysinger R: Correlation of diffusion tensor tractography and intraoperative macrostimulation during deep brain stimulation for Parkinson disease. J Neurosurg 121:9299352014

    • Search Google Scholar
    • Export Citation
  • 10

    Sweet JAWalter BLGunalan KChaturvedi AMcIntyre CCMiller JP: Fiber tractography of the axonal pathways linking the basal ganglia and cerebellum in Parkinson disease: implications for targeting in deep brain stimulation. J Neurosurg 120:9889962014

    • Search Google Scholar
    • Export Citation

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