Automated posterior cranial fossa volumetry by MRI

Applications to Chiari malformation type I

A. M. Bagci, S. H. Lee, Natalya Nagornaya, Barth A Green, Noam Alperin

Research output: Contribution to journalArticle

Abstract

BACKGROUND AND PURPOSE: Quantification of PCF volume and the degree of PCF crowdedness were found beneficial for differential diagnosis of tonsillar herniation and prediction of surgical outcome inCMI. However, lack of automated methods limits the clinical use of PCF volumetry. An atlas-based method for automated PCF segmentation tailored for CMI is presented. The method performance is assessed in terms of accuracy and spatial overlap with manual segmentation. The degree of association between PCF volumes and the lengths of previously proposed linear landmarks is reported. MATERIALS AND METHODS: T1-weighted volumetric MR imaging data with 1-mm isotropic resolution obtained with the use of a 3T scanner from 14 patients with CMI and 3 healthy subjects were used for the study. Manually delineated PCF from 9 patients was used to establish a CMI-specific reference for an atlas-based automated PCF parcellation approach. Agreement between manual and automated segmentation of 5 different CMI datasets was verified by means of the t test. Measurement reproducibility was established through the use of 2 repeated scans from 3 healthy subjects. Degree of linear association between PCF volume and 6 linear landmarks was determined by means of Pearson correlation. RESULTS: PCF volumes measured by use of the automated method and with manual delineation were similar, 196.2 ± 8.7 mL versus 196.9 ± 11.0 mL, respectively. The mean relative difference of-0.3 ± 1.9% was not statistically significant. Low measurement variability, with a mean absolute percentage value of 0.6 ± 0.2%, was achieved. None of the PCF linear landmarks were significantly associated with PCF volume. CONCLUSIONS: PCF and tissue content volumes can be reliably measured in patients with CMI by use of an atlas-based automated segmentation method.

Original languageEnglish
Pages (from-to)1758-1763
Number of pages6
JournalAmerican Journal of Neuroradiology
Volume34
Issue number9
DOIs
StatePublished - Sep 1 2013

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Arnold-Chiari Malformation
Posterior Cranial Fossa
Atlases
Healthy Volunteers
Encephalocele
Differential Diagnosis

ASJC Scopus subject areas

  • Clinical Neurology
  • Radiology Nuclear Medicine and imaging

Cite this

Automated posterior cranial fossa volumetry by MRI : Applications to Chiari malformation type I. / Bagci, A. M.; Lee, S. H.; Nagornaya, Natalya; Green, Barth A; Alperin, Noam.

In: American Journal of Neuroradiology, Vol. 34, No. 9, 01.09.2013, p. 1758-1763.

Research output: Contribution to journalArticle

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abstract = "BACKGROUND AND PURPOSE: Quantification of PCF volume and the degree of PCF crowdedness were found beneficial for differential diagnosis of tonsillar herniation and prediction of surgical outcome inCMI. However, lack of automated methods limits the clinical use of PCF volumetry. An atlas-based method for automated PCF segmentation tailored for CMI is presented. The method performance is assessed in terms of accuracy and spatial overlap with manual segmentation. The degree of association between PCF volumes and the lengths of previously proposed linear landmarks is reported. MATERIALS AND METHODS: T1-weighted volumetric MR imaging data with 1-mm isotropic resolution obtained with the use of a 3T scanner from 14 patients with CMI and 3 healthy subjects were used for the study. Manually delineated PCF from 9 patients was used to establish a CMI-specific reference for an atlas-based automated PCF parcellation approach. Agreement between manual and automated segmentation of 5 different CMI datasets was verified by means of the t test. Measurement reproducibility was established through the use of 2 repeated scans from 3 healthy subjects. Degree of linear association between PCF volume and 6 linear landmarks was determined by means of Pearson correlation. RESULTS: PCF volumes measured by use of the automated method and with manual delineation were similar, 196.2 ± 8.7 mL versus 196.9 ± 11.0 mL, respectively. The mean relative difference of-0.3 ± 1.9{\%} was not statistically significant. Low measurement variability, with a mean absolute percentage value of 0.6 ± 0.2{\%}, was achieved. None of the PCF linear landmarks were significantly associated with PCF volume. CONCLUSIONS: PCF and tissue content volumes can be reliably measured in patients with CMI by use of an atlas-based automated segmentation method.",
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