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Evaluation of the Skin to Epidural and Subarachnoid Space Distance in Young Children Using Magnetic Resonance Imaging
  1. Andrew D. Franklin, MD*,
  2. Amanda N. Lorinc, MD*,
  3. Matthew S. Shotwell, PhD†,
  4. Elton B. Greene, MD‡ and
  5. Curtis A. Wushensky, MD‡
  1. From the Departments of *Anesthesiology, †Biostatistics, and ‡Radiology, Vanderbilt University Medical Center, Nashville, TN
  1. Address correspondence to: Andrew D. Franklin, MD, Monroe Carell Jr. Children’s Hospital at Vanderbilt, 2200 Children’s Way, Suite 3115, Nashville, TN 37232 (e-mail: andrew.franklin{at}vanderbilt.edu).

Abstract

Background and Objectives Epidural catheters placed for perioperative analgesia in young children confer clinical benefits but are technically challenging to insert. Approximations of the skin to epidural space depth in this population are limited to direct needle measurement and ultrasonography. Magnetic resonance imaging (MRI) is the most comprehensive imaging modality of the spine. This study aims to produce a more clinically useful formula from MRI data to estimate pediatric epidural depth.

Methods Seventy children with normal lumbar spine MR images were enrolled. After determination of epidural depth, linear regression was used to estimate a weight-based formula. Analysis of variance and bootstrap methods were used to evaluate this formula against 4 commonly cited formulae. The quality of predictions was evaluated using the mean absolute prediction error.

Results The estimated weight-based formula as derived by MRI data is given by: skin to epidural depth (mm) = 9.00 + 0.62 * weight in kilograms. The mean absolute prediction error was 2.56 mm (95% confidence interval [95% CI], 2.12–3.04) for the new formula. Additional derived formulae are skin to dorsal dura depth (mm) = 13.52 + 0.71 * weight in kilograms (mean absolute prediction error, 2.48 mm; 95% CI, 2.00–3.03) and skin to ventral dural depth (mm) = 23.08 + 0.86 * weight in kilograms (mean absolute prediction error, 2.50 mm; 95% CI, 2.04–3.06).

Conclusions We provide the first predictive formulae, based on MRI data, for pediatric epidural depth estimation.

https://doi.org/10.1097/AAP.0000000000000234

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    Footnotes

    • The authors declare no conflict of interest.

      This work was funded solely by interdepartmental funds.

      This work was presented at the 2013 Society of Pediatric Anesthesia Annual Meeting in Las Vegas, NV.

      Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal’s Web site (www.rapm.org).