Volume estimation of biologic structures from the analysis of sections of structure of interest is a problem that often arises in biomedical studies. Mathematic formulae and techniques have thus been developed to address this problem leading to the so-called stereological methods. These methods are well recognized for their easy
implementation (compared, for example, to manual tracing methods), reliability, and high accuracy (
4.6.1.1 STEREOLOGICAL MEASUREMENT OF PARS OPERCULARIS AND PARS TRIANGULARIS VOLUMES
Doherty et al., 2000). Their efficiency depends on generating non-biased encounters between randomly sampled sectional images and grids of systematically spaced test points superimposed upon them; these test points have new random position and orientation on each section to insure unbiasedness. In particular, the stereological Cavalieri method applied here has been designed to estimate the volume of any brain structure regardless of its shape, e.g. Broca’s area (Keller et al., 2007), temporal lobe (Doherty et al., 2000), hippocampus (Keller et al., 2002), cerebellum (Karabekir et al., 2009), and brain tumor (Roberts et al., 2000). Despite the well- established advantages of the Cavalieri and point counting methods, they are not capable of correcting for the technical limitations of the MRI technique, which could compromise the precision and accuracy of the volume estimate. The use of Cavalieri method and point counting for volume estimation may be challenging when examining brain structures with irregular shapes and convolutions, such as the PTR, as a higher
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sampling attenuation is then required to estimate the volume with the same precision as when it is smooth (Garcia-Finana et al., 2003). Another source of error may be
produced by inter-rater differences in measurement when identifying structure boundaries on MR images. Even when investigators have sufficient experience in neuroanatomy and image analysis methods, a consistent demarcation of features of interest in MR images may be challenging. In particular, the finite resolution of the images is recognized as an important problem of the MRI technique which may lead to errors related to partial volume effect. Partial volume effect is the loss of blurring between two adjacent tissues in an image caused by insufficient spatial tissue type can occupy the sam and sufficiently hi unlikely to occupy the sam the MR images analyzed in the present study were obtained with relatively high resolution of 0.781 mm x 0.781 mm x 1.6 mm (which were re-sampled into 1 X 1 X 1 mm isotropic voxels), such resolution may unfortunately not be sufficient to solve the tissue border ambiguity. Such ambiguity was evident at the GM/CSF boundary, thereby influencing GM volume estimation, and at the GM/WM boundary, thereby influencing GM and WM volume estimation. Since the intersection of the upper right quadrant of the red cross was taken as the “point” in this study, it was sometimes difficult to indicate whether this small part of the red cross intersects GM, WM, or CSF pixel. Images were always displayed using consistent image window and display levels on the same monitor with fixed screen contrast settings; however, in cases of tissue border ambiguity, image window was enlarged to better visualize the ambiguous pixel. It should be noted that this problem involved only few red crosses in each slice and is not expected to change the results, especially with such high level of significance detected in GM volume of the left POP region (p<0.001). The latest generation of MR scanners allows the acquisition of higher resolution MR images, which can provide more accurate volume quantification. Also, methods for accurate classification of mixed voxels and correct estimation of the proportion of each pure tissue have been proposed (Acosta et
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al., 2008, Rueda et al., 2010), which may help to increase the precision of volume estimation in future studies.
Furthermore, another technical factor that may affect volume estimates of POP/PTR in the present study is inhomogeneities (e.g., shading) in signal intensity over the image field of view caused by the spatial variation in the transmission and reception
sensitivities of the radiofrequency coil. Intensity inhomogeneity in MRI might alter image intensities that would otherwise be constant for the same tissue type regardless of its position in an image (Vovk et al., 2007). This has an impact on the demarcation of tissue boundaries, which may subtly differ in contrast from one region to another in the MR image. Sophisticated intensity inhomogeneity correction algorithms (for review see (Vovk et al., 2007)) have been proposed and could be incorporated in future studies. Other technical problems could arise from chemical shift and susceptibility artifacts as well as field of view and slice thickness calibration inaccuracies, which can compromise the accuracy of stereological measurements.
In order to enhance image analysis studies on the GM compartment, future data acquisition at MARIARC is considering the use of 3D T1- weighted Modified Driven Equilibrium Fourier Transform (MDEFT) sequence designed by (Deichmann et al., 2004) to improve contrast between GM and WM. Also, most studies are now transferred to a new 3 Tesla MR system, which offers increased signal to noise ratio thereby increasing accuracy of acquired stereological measures.
In the present study, an automatic method was used to estimate cortical surface area of BA44/45. The rationale was to avoid introducing bias when using other methods for surface area estimation, such as stereology (
4.6.1.2 CORTICAL SURFACE AREA MEASUREMENT OF BA44/45
Haug, 1987, Steinmetz et al., 1989b). However, automatic methods are not free of limitations. First, brains were initially transformed to the Talairach space, which is a prerequisite step for achieving optimal results in BrainVoyager. This atlas is one of the most prevalent brain atlases of gross anatomy, the use of which is growing despite its well-known shortcomings (Steinmetz et al., 1989a, Nowinski, 2001, Nowinski and Thirunavuukarasuu, 2001, Maldjian et al., 2004, Nowinski, 2005). The coordinate system of Talairach space is based upon
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postmortem sections of a 60-year-old French female who had a smaller than average brain size (Talairach and Tournoux, 1988), which criticize the wide use of this
coordinate system in MR studies. Also, previous studies have pointed out segmentation inaccuracies (Maldjian et al., 2004, Nowinski, 2005) and low spatial consistency
(Nowinski and Thirunavuukarasuu, 2009) when using the Talairach coordinate system. It should be noted that the cortical parcellation scheme used in the present study was based not on cytoarchitecture, but on geometric features using outer anatomical landmarks determined by structural MRI. One could argue that BA44 and BA45 are strictly defined by cytoarchitecture, which cannot be directly observed in MRI scans. It has been assumed by many brain-mapping studies that the macroanatomical gyral and sulcal landmarks coincide with the borders of architectonic areas. That this hypothesis is not tenable in general has been shown previously (Rademacher et al., 1993, Amunts et al., 1999). For instance, Zilles and colleagues (Zilles et al., 1997) have noted that sulcal landmarks are not generally precise indicators of the borders of cytoarchitectonic areas. This concept is especially true in the case of Broca’s area. Amunts and
colleagues (Amunts et al., 1999) investigated the cytoarchitectural mapping of areas 44 and 45 in 10 human brains by means of an observer-independent technique. They reported that the cytoarchitectonic borders of these areas did not consistently coincide with sulcal contours and; consequently, they concluded that macroscopic features (sulcal landmarks) are not reliable landmarks of cytoarchitectonic borders. Furthermore, a great inter-subject variability in the microscopic (Amunts et al., 1999), and
macroscopic (sulcal morphology) (Tomaiuolo et al., 1999, Keller et al., 2007) anatomy of BA44/45 was observed. The extremely variable extent and spatial layout of the BA44/45 imply that the use of an atlas with a single-brain–based template, like the Talairach and Tournoux, to locate these regions may have only an approximate relationship to the location of individual sulci and Brodmann’s areas (Lancaster et al., 2000).
The main advantage of automatic methods for cortical surface-based analysis, such as that used in the present study, is the little requirement for user interaction and
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reasonable to use these methods when analyzing large cohorts. However, these methods neither guarantee accurate correspondences nor they directly make use of expert knowledge of the location and variability of specific sulcal features as in landmark-based methods (Pantazis et al., 2010). Even the most consistent gyri and sulci appearing in all normal subjects exhibit pronounced variability in size and configuration (Roland and Zilles, 1994). In accord, demarcation of sulcal landmarks of POP and PTR, such as the anterior ascending and diagonal sulci, was not always possible in the present study, thereby complicating the cortex-based alignment process. In this context, Pantazis and colleagues (Pantazis et al., 2010) compared automatic (using BrainVoyager and FreeSurfer image analysis softwares) and landmark-based methods for cortical surface registration and concluded that, in general, the landmark- based method is more reliable as it did not produce crude registration errors that are often present in automatic methods.
4.7 CONCLUSION
In conclusion, the present study has shown that male orchestral musicians had greater GM volume and cortical surface area of POP/BA44 in the left (dominant) hemisphere. These results corroborate those of the previous VBM study. I hypothesize that long- term skilful practice in the form of orchestral performance is an environmentally enriching activity resulting in structural reorganization through increased volume and cortical surface area of a brain region essential for such performance.
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