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Automated posterior cranial fossa volumetry by MRI: applications to Chiari malformation type I.
AJNR Am J Neuroradiol. 2013 Sep; 34(9):1758-63.AA

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 in CMI. 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.

Authors+Show Affiliations

Departments of Radiology.No affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info available

Pub Type(s)

Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

23493894

Citation

Bagci, A M., et al. "Automated Posterior Cranial Fossa Volumetry By MRI: Applications to Chiari Malformation Type I." AJNR. American Journal of Neuroradiology, vol. 34, no. 9, 2013, pp. 1758-63.
Bagci AM, Lee SH, Nagornaya N, et al. Automated posterior cranial fossa volumetry by MRI: applications to Chiari malformation type I. AJNR Am J Neuroradiol. 2013;34(9):1758-63.
Bagci, A. M., Lee, S. H., Nagornaya, N., Green, B. A., & Alperin, N. (2013). Automated posterior cranial fossa volumetry by MRI: applications to Chiari malformation type I. AJNR. American Journal of Neuroradiology, 34(9), 1758-63. https://doi.org/10.3174/ajnr.A3435
Bagci AM, et al. Automated Posterior Cranial Fossa Volumetry By MRI: Applications to Chiari Malformation Type I. AJNR Am J Neuroradiol. 2013;34(9):1758-63. PubMed PMID: 23493894.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Automated posterior cranial fossa volumetry by MRI: applications to Chiari malformation type I. AU - Bagci,A M, AU - Lee,S H, AU - Nagornaya,N, AU - Green,B A, AU - Alperin,N, Y1 - 2013/03/14/ PY - 2013/3/16/entrez PY - 2013/3/16/pubmed PY - 2014/4/4/medline SP - 1758 EP - 63 JF - AJNR. American journal of neuroradiology JO - AJNR Am J Neuroradiol VL - 34 IS - 9 N2 - 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 in CMI. 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. SN - 1936-959X UR - https://www.unboundmedicine.com/medline/citation/23493894/Automated_posterior_cranial_fossa_volumetry_by_MRI:_applications_to_Chiari_malformation_type_I_ L2 - http://www.ajnr.org/cgi/pmidlookup?view=long&pmid=23493894 DB - PRIME DP - Unbound Medicine ER -