Elsevier

NeuroImage

Volume 30, Issue 1, March 2006, Pages 1-11
NeuroImage

MRI-based volumetry of head compartments: Normative values of healthy adults

https://doi.org/10.1016/j.neuroimage.2005.09.063Get rights and content

Abstract

The size of head compartments (head and brain volume, intracranial volume, gray and white matter volume, cerebrospinal fluid volume) and their ratios were determined on the basis of magnetic resonance images of the head acquired in a reference population of 502 healthy subjects. Age-matched subgroups were selected to reveal gender-related differences and changes with age. Normative data are provided in the form of simple equations that allow transforming measured compartment volumes into z scores, offering the possibility to relate individual data to a larger population.

Introduction

Compartments of the human head may be recorded by magnetic resonance imaging (MRI) within a few minutes. A computer-based analysis of these imaging data allows a quantitative characterization of structures, tissues and their changes with time. The resulting extensive parameter sets may be used in further statistical studies, e.g., to classify brains, to draw conclusions about structural differences in subject groups (i.e., by gender, structural abnormalities) and to track individual changes with time (aging, CNS diseases, therapeutical interventions).

In this study, we determined the volume of several head compartments, namely, the head (HDV), the intracranial compartment (ICV), brain (BRV), gray and white matter (GMV, WMV) and the cerebrospinal fluid (CSFV) and several brain compartments, the left and right cerebral hemisphere (LHV, RHV), the left and right cerebellar hemisphere (LCV, RCV) and the brain stem (BSV) in a reference population of 502 healthy subjects. From this population, age-matched subgroups were selected to analyze gender-related differences and changes with age. The key idea is to provide normative data, i.e., similar to the CDC growth curves (Kuczmarski et al., 2000). Given age and gender, individual compartment volumes may be transformed by simple equations into z scores, offering the possibility to relate individual data to a larger population.

Data on the size of head compartments have been provided by numerous studies using different technology. First, autopsy studies have been carried out systematically for more than 100 years now (Blinkov and Glezer, 1968, Chrzanowska and Beben, 1973, Debakan and Sadowsky, 1978, Hwang et al., 1995, Miller et al., 1980, Peters et al., 2000, Svennerholm et al., 1997). Because real volumes and weights are measured, data from autopsy studies may be considered as the “gold standard”. However, inherent technical and logistical problems affect the measurements (e.g., the type of illness, intervals between death and brain removal, weighing in the fresh or fixed condition).

Human brain morphometry advanced dramatically by the invention of the modern neuroimaging methods. Following some initial studies using cranial computed tomography (CCT) (Abbott et al., 2000, Hahn et al., 1984, Schwartz et al., 1985), MRI quickly became the method of choice for data collection because MRI allows discriminating between several tissue types (Caviness et al., 1995, Cavinesse et al., 1999, Kennedy et al., 2003). Several studies focused on the determination of brain compartments and their gender differences (Allen et al., 2002, Allen et al., 2003, Blatter et al., 1995, Filipek et al., 1989, Filipek et al., 1994, Sato et al., 2003, Schlaepfer et al., 1995) and changes of compartment volumes with age (Blatter et al., 1995, Courchesne et al., 2000, Ge et al., 2002, Giedd et al., 1996, Harris et al., 1994, Jernigan et al., 2001, Pfefferbaum et al., 1994, Resnick et al., 2003) and tried to find MRI-detectable discriminators of healthy and pathological aging in neurodegenerative diseases (Edland et al., 2002, Jenkins et al., 2000, Wolf et al., 2003, Wolf et al., 2004). Often these studies include a small sample size or a few parameters only. Notably, image analysis procedures have matured over the past few years, offering now a fully automatic, bias-free measurement of compartment volumes.

In addition, we also provide normative data for several compartment ratios, e.g., the ratio brain volume/intracranial volume (BRV/ICV). Skull growth occurs along the suture lines and is determined by brain expansion, which takes place during the normal growth of the brain. Thus, in normal adults, a close relationship between the brain size and the intracranial volume is expected (Falkner, 1977). This relationship is used to estimate the premorbid brain size in degenerative brain diseases (Drachman, 2002, Edland et al., 2002, Jenkins et al., 2000, Wolf et al., 2003) or brain degeneration due to diffuse or focal brain damage.

In the following, we describe the population engaged in this study, the data acquisition and analysis, provide normative data for compartment volumes and discuss our results in relation to the previous studies mentioned above.

Section snippets

Subjects

The institute maintains a database of subjects enrolled for functional MRI experiments. Before admission, a brief history and physical inspection is taken by a physician. Subjects are included in this database if they comply with the informed consent for conducting general fMRI experiments, pass the examination and do not exhibit pathological features (e.g., unilateral ventricular enlargements, subarachnoidal cysts) in their MRI tomograms.

Normative data were determined for the whole database

Gender-related differences

All measured compartments were larger in males (see Table 1): the head volume (HDV, ΔV = +299 ml, 10.7%), the intracranial volume (ICV, ΔV = +121 ml, 7.8%), the brain volume (BRV, ΔV = +112.6 ml, 8.0%), the gray matter volume (GMV, ΔV = +45.1 ml, 6.1%) and the white matter volume (WMV, ΔV = +67.4 ml, 10.1%). The relative amount of gray matter is slightly higher in female brains which is also reflected in the lower ratio GMV/WMV in males (−3.53%). Similar volume differences were found for the

Results and discussion

Our results for the compartment volumes compare well with data published by Blatter et al. (1995) (see Table 5), except for the intracranial volume that is 5% larger in our sample of young adults. However, their reported CSF volumes appear quite low (only 7% of the ICV), while our results (11%) are consistent with other reports [10.8% (Alfano et al., 1998), 14% (Courchesne et al., 2000), 14.4% (Lemieux et al., 2003)] based on similar young sample groups. The brain volume determined for our

Discussion

The present study included a reference population of about 500 healthy subjects aged between 18 and 70 to establish normative data for the size of several head compartments and their ratios as revealed by MRI data of the head. Gender-related differences and changes with age were determined. Compartment volumes were transformed into z scores by simple equations, offering the possibility to relate individual data to a larger population. Analysis procedures applied here do not require user

Acknowledgments

This work was supported by the Bundesministerium für Bildung und Technology (BMB+F), Interdisziplinäres Zentrum für Klinische Forschung (IZKF) at the University of Leipzig, project C15.

References (53)

  • J.S. Allen et al.

    Normal neuroanatomical variation in the human brain: an MRI-volumetric study

    Am. J. Phys. Anthropol.

    (2002)
  • A.J. Bartley et al.

    Genetic variability of human brain size and cortical gyral patterns

    Brain

    (1997)
  • R.A. Becker et al.

    The New S Language

    (1988)
  • D.D. Blatter et al.

    Quantitative volumetric analysis of brain MR: normative database spanning 5 decades of life

    Am. J. Neuroradiol.

    (1995)
  • S.M. Blinkov et al.

    The Human Brain in Figures and Tables

    (1968)
  • P.A. Bottomley et al.

    A review of normal tissue hydrogen NMR relaxation times and relaxation mechanisms from 1–100 MHz: dependence on tissue type, NMR frequency, temperature, species, excision, and age

    Med. Phys.

    (1984)
  • V.A. Caviness et al.

    Advanced application of magnetic resonance imaging in human brain science

    Brain Develop.

    (1995)
  • V.A. Caviness et al.

    MRI-based brain volumetrics: emergence of a developmental brain science

    Brain Develop.

    (1999)
  • J.M. Chambers et al.

    Statistical Models in S

    (1992)
  • G. Chrzanowska et al.

    Weight of the brain and body height in man between ages of 20 and 89 years

    Folia Morphol.

    (1973)
  • Christensen, G.E., 1996. Deformable shape models for anatomy, Thesis, Washington University, St....
  • E. Courchesne et al.

    Normal brain development and aging: quantitative analysis at in vivo MR imaging in healthy volunteers

    Radiology

    (2000)
  • P.J.M. Davis et al.

    A new method for measuring cranial cavity volume and its application to the assessment of cerebral atrophy

    Neuropathol. Appl. Neurobiol.

    (1977)
  • A.S. Debakan et al.

    Changes in brain weight during the span of human life: relation of brain weights and body heights and body weights

    Ann. Neurol.

    (1978)
  • D.A. Drachman

    Hat size, brain size, intelligence, and dementia

    Neurology

    (2002)
  • S.D. Edland et al.

    Total intracranial volume: normative values and lack of association with Alzheimer's disease

    Neurology

    (2002)
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