ArticleFrontiers in pediatrics2023
Quantitative identification of ventral/dorsal nerves through intraoperative neurophysiological monitoring by supervised machine learning.
Article in Frontiers in pediatrics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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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.
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Who cites it
2 citing papers in PubMed, 4 citations in OpenAlex.
- Envisioning the Future of the Neurosurgical Operating Room with the Concept of the Medical Metaverse.Journal of Korean Neurosurgical Society · 2025Article
- Effect of selective dorsal rhizotomy on bladder dysfunction in children with spastic cerebral palsy.Scientific reports · 2024Article
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: This study aimed to investigate the electro-neurophysiological characteristics of the ventral and dorsal nerves at the L2 segment in a quantitative manner. Methods: Medical records of consecutive patients who underwent single-level approach selective dorsal rhizotomy (SDR) from June 2019 to January 2022 were retrospectively reviewed. Intraoperative electro-neurophysiological data were analyzed. Results: A total of 74 males and 27 females were included in the current study with a mean age of 6.2 years old. Quadriceps and adductors were two main muscle groups innervated by L2 nerve roots in both ventral and dorsal nerve roots. Dorsal roots have a higher threshold than that of the ventral ones, and muscles that first reached 200 µV innervated by dorsal roots have longer latency and smaller compound muscle action potential (CMAP) than those of the ventral ones. Supervised machine learning can efficiently distinguish ventral/dorsal roots using threshold + latency or threshold + CMAP as predictors. Conclusion: Electro-neurophysiological parameters could be used to efficiently differentiate ventral/dorsal fibers during SDR.
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