Using Natural Language Processing of Free-Text Radiology Reports to Identify Type 1 Modic Endplate Changes.

Journal: Journal of digital imaging
Published Date: Feb 1, 2018

Abstract

Electronic medical record (EMR) systems provide easy access to radiology reports and offer great potential to support quality improvement efforts and clinical research. Harnessing the full potential of the EMR requires scalable approaches such as natural language processing (NLP) to convert text into variables used for evaluation or analysis. Our goal was to determine the feasibility of using NLP to identify patients with Type 1 Modic endplate changes using clinical reports of magnetic resonance (MR) imaging examinations of the spine. Identifying patients with Type 1 Modic change who may be eligible for clinical trials is important as these findings may be important targets for intervention. Four annotators identified all reports that contained Type 1 Modic change, using N = 458 randomly selected lumbar spine MR reports. We then implemented a rule-based NLP algorithm in Java using regular expressions. The prevalence of Type 1 Modic change in the annotated dataset was 10%. Results were recall (sensitivity) 35/50 = 0.70 (95% confidence interval (C.I.) 0.52-0.82), specificity 404/408 = 0.99 (0.97-1.0), precision (positive predictive value) 35/39 = 0.90 (0.75-0.97), negative predictive value 404/419 = 0.96 (0.94-0.98), and F1-score 0.79 (0.43-1.0). Our evaluation shows the efficacy of rule-based NLP approach for identifying patients with Type 1 Modic change if the emphasis is on identifying only relevant cases with low concern regarding false negatives. As expected, our results show that specificity is higher than recall. This is due to the inherent difficulty of eliciting all possible keywords given the enormous variability of lumbar spine reporting, which decreases recall, while availability of good negation algorithms improves specificity.

Authors

  • Hannu T Huhdanpaa
    Radia, Inc., Lynwood, WA, USA.
  • W Katherine Tan
    Department of Biostatistics, University of Washington, Seattle, WA, USA.
  • Sean D Rundell
    Department of Rehabilitation Medicine, University of Washington, Seattle, WA, USA.
  • Pradeep Suri
    Department of Rehabilitation Medicine, University of Washington, Seattle, WA, USA.
  • Falgun H Chokshi
    Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA, USA.
  • Bryan A Comstock
    Department of Biostatistics, University of Washington, Seattle, WA, USA.
  • Patrick J Heagerty
    Department of Biostatistics, University of Washington, Seattle, WA, USA.
  • Kathryn T James
    Comparative Effectiveness, Cost and Outcomes Research Center, University of Washington, Seattle, WA, USA.
  • Andrew L Avins
    Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA.
  • Srdjan S Nedeljkovic
    Department of Anesthesiology, Perioperative and Pain Medicine, Harvard Vanguard Medical Associates, Brigham and Women's Hospital and Spine Unit, Boston, MA, USA.
  • David R Nerenz
    Henry Ford Hospital, Neuroscience Institute, Detroit, MI, USA.
  • David F Kallmes
    Department of Radiology, Mayo Clinic, Rochester, MN, USA.
  • Patrick H Luetmer
    Department of Radiology, Mayo Clinic, Rochester, MN, USA.
  • Karen J Sherman
    Kaiser Permanente of Washington Research Institute, Seattle, WA, USA.
  • Nancy L Organ
    Department of Biostatistics, University of Washington, Seattle, WA, USA.
  • Brent Griffith
    Department of Radiology, Henry Ford Hospital, Detroit, MI, USA.
  • Curtis P Langlotz
    Stanford University, University Medical Line, Stanford, CA, 94305, US.
  • David Carrell
    Group Health Research Institute, Seattle, WA, USA.
  • Saeed Hassanpour
    Lia Harrington, Todd MacKenzie, and Saeed Hassanpour, Geisel School of Medicine at Dartmouth College, Hanover; Roberta diFlorio-Alexander, Katherine Trinh, and Arief Suriawinata, Dartmouth-Hitchcock Medical Center, Lebanon, NH.
  • Jeffrey G Jarvik
    Comparative Effectiveness, Cost and Outcomes Research Center, University of Washington, Seattle, WA, USA. jarvikj@uw.edu.

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