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Estimating Intracranial Volume in Brain Research: An Evaluation of Methods

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Abstract

Intracranial volume (ICV) is a standard measure often used in morphometric analyses to correct for head size in brain studies. Inaccurate ICV estimation could introduce bias in the outcome. The current study provides a decision aid in defining protocols for ICV estimation across different subject groups in terms of sampling frequencies that can be optimally used on the volumetric MRI data, and type of software most suitable for use in estimating the ICV measure. Four groups of 53 subjects are considered, including adult controls (AC, adults with Alzheimer’s disease (AD), pediatric controls (PC) and group of pediatric epilepsy subjects (PE). Reference measurements were calculated for each subject by manually tracing intracranial cavity without sub-sampling. The reliability of reference measurements were assured through intra- and inter- variation analyses. Three publicly well-known software packages (FreeSurfer Ver. 5.3.0, FSL Ver. 5.0, SPM8 and SPM12) were examined in their ability to automatically estimate ICV across the groups. Results on sub-sampling studies with a 95 % confidence showed that in order to keep the accuracy of the inter-leaved slice sampling protocol above 99 %, sampling period cannot exceed 20 mm for AC, 25 mm for PC, 15 mm for AD and 17 mm for the PE groups. The study assumes a priori knowledge about the population under study into the automated ICV estimation. Tuning of the parameters in FSL and the use of proper atlas in SPM showed significant reduction in the systematic bias and the error in ICV estimation via these automated tools. SPM12 with the use of pediatric template is found to be a more suitable candidate for PE group. SPM12 and FSL subjected to tuning are the more appropriate tools for the PC group. The random error is minimized for FS in AD group and SPM8 showed less systematic bias. Across the AC group, both SPM12 and FS performed well but SPM12 reported lesser amount of systematic bias.

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Acknowledgments

This work is supported by the National Science Foundation under grants CNS-0959985, CNS-1042341, HRD-0833093, and IIP-1230661. The support of the Ware Foundation is greatly appreciated. The authors would like to thank the anonymous reviewers for their comments and suggestions which significantly improved the quality of this work.

Conflict of Interests

The authors have no commercial, financial, or other relationship related to the subject of this paper that could constitute or suggest a conflict of interest.

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering, Florida International University, Miami, FL, USA

    Saman Sargolzaei, Arman Sargolzaei, Mercedes Cabrerizo, Mohammed Goryawala & Malek Adjouadi

  2. Scientific and Statistical Computing Core, NIMH/NIH/HHS, Bethesda, MD, USA

    Gang Chen

  3. Baptist Health Neuroscience Center, Baptist Hospital, Miami, FL, USA

    Alberto Pinzon-Ardila & Sergio M. Gonzalez-Arias

  4. Department of Neuroscience, Herbert Wertheim College of Medicine, Florida International University, Miami, FL, USA

    Sergio M. Gonzalez-Arias

  5. Department of Biomedical Engineering, Florida International University, Miami, FL, USA

    Malek Adjouadi

  6. 10555W. Flagler St, ECE 2220, Miami, FL, 33174, USA

    Malek Adjouadi

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  1. Saman Sargolzaei
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  2. Arman Sargolzaei
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  3. Mercedes Cabrerizo
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Sargolzaei, S., Sargolzaei, A., Cabrerizo, M. et al. Estimating Intracranial Volume in Brain Research: An Evaluation of Methods. Neuroinform 13, 427–441 (2015). https://doi.org/10.1007/s12021-015-9266-5

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