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