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  • 2018 (1)

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Article

Cerebellar tonsil ectopia measurement in type I Chiari malformation patients show poor inter-operator reliability

by Braden J. Lawrence; Aintzane Urbizu; Philip A. Allen; Francis Loth; R. Shane Tubbs; Alexander C. Bunck; Jan-Robert Kroeger; Brandon G. Rocque; Casey Madura; Jason A. Chen; Mark G. Luciano; Richard G. Ellenbogen; John Oshinski; Bermans J. Iskandar; Bryn A. Martin

2018

Subjects
  • Biology, Neuroscience
  • Engineering, Biomedical
  • Health Sciences, Medicine and Surgery
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Abstract:Close

Background: Type 1 Chiari malformation (CM-I) has been historically defined by cerebellar tonsillar position (TP) greater than 3-5 mm below the foramen magnum (FM). Often, the radiographic findings are highly variable, which may influence the clinical course and patient outcome. In this study, we evaluate the inter-operator reliability (reproducibility) of MRI-based measurement of TP in CM-I patients and healthy controls. Methods: Thirty-three T2-weighted MRI sets were obtained for 23 CM-I patients (11 symptomatic and 12 asymptomatic) and 10 healthy controls. TP inferior to the FM was measured in the mid-sagittal plane by seven expert operators with reference to McRae's line. Overall agreement between the operators was quantified by intraclass correlation coefficient (ICC). Results: The mean and standard deviation of cerebellar TP measurements for asymptomatic (CM-Ia) and symptomatic (CM-Is) patients in mid-sagittal plane was 6.38 ± 2.19 and 9.57 ± 2.63 mm, respectively. TP measurements for healthy controls was 0.48 ± 2.88 mm. The average range of TP measurements for all data sets analyzed was 7.7 mm. Overall operator agreement for TP measurements was relatively high with an ICC of 0.83. Conclusion: The results demonstrated a large average range (7.7 mm) of measurements among the seven expert operators and support that, if economically feasible, two radiologists should make independent measurements before radiologic diagnosis of CM-I and surgery is contemplated. In the future, an objective diagnostic parameter for CM-I that utilizes automated algorithms and results in smaller inter-operator variation may improve patient selection.
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