P C Reinacher1, M T Krüger2, V A Coenen3, M Shah2, R Roelz2, C Jenkner4, K Egger5. 1. From the Departments of Stereotactic and Functional Neurosurgery (P.C.R., V.A.C.) peter.reinacher@uniklinik-freiburg.de. 2. Neurosurgery (M.T.K., M.S., R.R.). 3. From the Departments of Stereotactic and Functional Neurosurgery (P.C.R., V.A.C.). 4. Clinical Trial Unit (C.J.), Freiburg University Medical Center, Freiburg, Germany. 5. Neuroradiology (K.E.).
Abstract
BACKGROUND AND PURPOSE: New deep brain stimulation leads with electrode contacts that are split along their circumference allow steering of the electrical field in a predefined direction. However, imaging-assisted directional stimulation requires detailed knowledge of the exact orientation of the electrode array. The purpose of this study was to evaluate whether this information can be obtained by rotational 3D fluoroscopy. MATERIALS AND METHODS: Two directional leads were inserted into a 3D-printed plaster skull filled with gelatin. The torsion of the lead tip versus the lead at the burr-hole level was investigated. Then, 3 blinded raters evaluated 12 3D fluoroscopies with random lead orientations. They determined the lead orientation considering the x-ray marker only and considering the overlap of the gaps between the contact segments. Intraclass correlation coefficients and an extended version of the Bland-Altman plot were used to determine interrater reliability and agreement of the measurements of the different raters. RESULTS: Electrode torsion of up to 35° could be demonstrated. Evaluation of the lead rotation considering the x-ray marker only revealed limits of agreement of ±9.37° and an intraclass correlation coefficient of 0.9975. In addition, taking into account the lines resulting from overlapping of the gaps between the electrode segments, the limits of agreement to the mean were ±2.44° and an intraclass correlation coefficient of 0.9998. CONCLUSIONS: In directional deep brain stimulation systems, rotational 3D fluoroscopy combined with the described evaluation method allows for determining the exact orientation of the leads, enabling the full potential of imaging-assisted personalized programming.
BACKGROUND AND PURPOSE: New deep brain stimulation leads with electrode contacts that are split along their circumference allow steering of the electrical field in a predefined direction. However, imaging-assisted directional stimulation requires detailed knowledge of the exact orientation of the electrode array. The purpose of this study was to evaluate whether this information can be obtained by rotational 3D fluoroscopy. MATERIALS AND METHODS: Two directional leads were inserted into a 3D-printed plaster skull filled with gelatin. The torsion of the lead tip versus the lead at the burr-hole level was investigated. Then, 3 blinded raters evaluated 12 3D fluoroscopies with random lead orientations. They determined the lead orientation considering the x-ray marker only and considering the overlap of the gaps between the contact segments. Intraclass correlation coefficients and an extended version of the Bland-Altman plot were used to determine interrater reliability and agreement of the measurements of the different raters. RESULTS: Electrode torsion of up to 35° could be demonstrated. Evaluation of the lead rotation considering the x-ray marker only revealed limits of agreement of ±9.37° and an intraclass correlation coefficient of 0.9975. In addition, taking into account the lines resulting from overlapping of the gaps between the electrode segments, the limits of agreement to the mean were ±2.44° and an intraclass correlation coefficient of 0.9998. CONCLUSIONS: In directional deep brain stimulation systems, rotational 3D fluoroscopy combined with the described evaluation method allows for determining the exact orientation of the leads, enabling the full potential of imaging-assisted personalized programming.
Authors: Edgar Peña; Simeng Zhang; Remi Patriat; Joshua E Aman; Jerrold L Vitek; Noam Harel; Matthew D Johnson Journal: J Neural Eng Date: 2018-09-13 Impact factor: 5.379
Authors: Tushar M Athawale; Kara A Johnson; Christopher R Butson; Chris R Johnson Journal: Comput Methods Biomech Biomed Eng Imaging Vis Date: 2018-10-09
Authors: Alexandre Boutet; Robert Gramer; Christopher J Steele; Gavin J B Elias; Jürgen Germann; Ricardo Maciel; Walter Kucharczyk; Ludvic Zrinzo; Andres M Lozano; Alfonso Fasano Journal: Curr Neurol Neurosci Rep Date: 2019-05-30 Impact factor: 5.081
Authors: Chet Preston; Alexander M Alvarez; Andres Barragan; Jennifer Becker; Willard S Kasoff; Russell S Witte Journal: J Neural Eng Date: 2020-02-27 Impact factor: 5.379
Authors: Matthieu Béreau; Astrid Kibleur; Walid Bouthour; Emilie Tomkova Chaoui; Nicholas Maling; T A Khoa Nguyen; Shahan Momjian; Maria Isabel Vargas Gomez; André Zacharia; Julien F Bally; Vanessa Fleury; Laurent Tatu; Pierre R Burkhard; Paul Krack Journal: Front Neurol Date: 2020-07-02 Impact factor: 4.003
Authors: T A Khoa Nguyen; Milan Djilas; Andreas Nowacki; André Mercanzini; Michael Schüpbach; Philipp Renaud; Claudio Pollo Journal: PLoS One Date: 2019-06-19 Impact factor: 3.240
Authors: Jean-Philippe Lévy; T A Khoa Nguyen; Lenard Lachenmayer; Ines Debove; Gerd Tinkhauser; Katrin Petermann; Alba Segura Amil; Joan Michelis; Michael Schüpbach; Andreas Nowacki; Claudio Pollo Journal: Neuroimage Clin Date: 2020-11-02 Impact factor: 4.881