Evidence map›Paper›PMID 39651160›Full record

ArticlebioRxiv : the preprint server for biology2024

Frequency-dependent and capacitive tissue electrical properties in spinal cord stimulation models.

Niranjan Khadka, Boshuo Wang, Marom Bikson

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Niranjan KhadkaDepartment of Biomedical Engineering, The City College of New York, CUNY, New York, NY.ORCID 0000-0002-4930-5214
Boshuo WangDepartment of Psychiatry and Behavioral Sciences, Duke University, Durham, NC.ORCID 0000-0003-1680-5957
Marom BiksonDepartment of Biomedical Engineering, The City College of New York, CUNY, New York, NY.

Funding

G-RISE: Graduate Research Initiative for Student Advancement at The City College of New YorkT32GM136499 · NIGMS · CITY COLLEGE OF NEW YORK · PI RUTH E. STARK · 2020 to 2026
$4.9M
Open-source computational modeling of Spinal Cord Stimulation (SCS) to enhance dissemination of 1R01NS112996R01NS112996 · NINDS · CITY COLLEGE OF NEW YORK · PI BIKSON, MAROM · 2020 to 2024
$2.0M
The coupled vascular hypothesis for transcranial direct current stimulation (tDCS)R01NS101362 · NINDS · CITY COLLEGE OF NEW YORK · PI BIKSON, MAROM · 2017 to 2021
$1.7M
"Bridges to the Baccalaureate Research Training Program at LaGuardia Community College"T34GM137858 · NIGMS · LAGUARDIA COMMUNITY COLLEGE · PI BIKSON, MAROM, ORTIZ, BENJAMIN D., · 2020 to 2024
$1.5M
Non-Invasive Vagal Nerve Stimulation in Patients with Opioid Use Disorders UG3DA048502 · NIDA · EMORY UNIVERSITY · PI BREMNER, JAMES DOUGLAS, INAN, OMER TOLGA · 2020 to 2021
$844k
NIDA NIH HHS UG3 DA048502NIGMS NIH HHS T32 GM136499NIGMS NIH HHS T34 GM137858NINDS NIH HHS R01 NS101362NINDS NIH HHS R01 NS112996
6 · The paper itself

Abstract

Background: Models of spinal cord stimulation (SCS) simulate the electric fields (E-fields) generated in targeted tissues, which in turn can predict physiological and then behavioral outcomes. Notwithstanding increasing sophistication and use in optimizing therapy, SCS models typically calculate E-fields using the quasi-static approximation (QSA). QSA, as implemented in neuromodulation models, neglects the frequency dispersion of tissue conductivity, as well as propagation, capacitive, and inductive effects on the E-field. The reliability of QSA specifically for SCS has not been considered in detail, especially for higher-frequency SCS. Methods: We implemented a frequency-dependent finite element method (FEM) and solved a high-resolution RADO-SCS model with voltage-controlled (VC) and current-controlled (CC) stimulation to assess the impact of frequency-dependent conductivity (dispersion) and permittivity of spinal tissues on E-fields generated at three different spinal column locations (epidural space, spinal cord, and root) for frequencies spanning from 1 Hz to 10 MHz. Results were compared with predictions of QSA method, with varied conductivity values of purely resistive tissues. We further assessed the impact of frequency-dependent and capacitive tissue properties on spinal heating and distortion of the E-field waveform. Results: Tissue-specific electric properties around the energized leads and mode of stimulation-control impacted the magnitude of E-fields. In the spinal cord, the VC-SCS E-field generated with the frequency-dependent and capacitive properties was comparable to the QSA with 2X epidural fat conductivity, whereas the CC-SCS generated E-field was minimally impacted by frequency-dependent and capacitive properties up to 10 kHz. Spinal cord heating predicted by frequency-dependent and capacitive tissue properties was comparable to the QSA conditions with VC-SCS, whereas with CC-SCS, there was no impact of the frequency-dependent and capacitive tissue properties in spinal cord heating. E-field waveform distortion in the spinal cord, with CC-SCS at 1 kHz-specific electrical properties, was significant when fat capacitance (permittivity) was increased by 10X, whereas with VC-SCS, there was no effect of tissue capacitance. Conclusion: Regardless of the mode of SCS, QSA was still valid in predicting SCS-induced E-field and heating at the spinal tissues- across

Indexed as

Dielectric propertiesFrequency-dependent electrical propertiesQuasi-static approximationSpinal Cord StimulationTissue capacitance

Identifiers

PMID39651160
PMCPMC11623512

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.