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Assessing age-related gray matter decline with voxel-based morphometry depends significantly on segmentation and normalization procedures.

Callaert DV, Ribbens A, Maes F, Swinnen SP, Wenderoth N - Front Aging Neurosci (2014)

Bottom Line: Comparing GM decline between 21 young subjects (mean age 23) and 18 elderly (mean age 66) revealed that volumetric measurements differed significantly between methods.Our findings suggest that algorithms that provide only limited degrees of freedom for local deformations (such as the unified segmentation and normalization of SPM5/SPM8) tend to overestimate between-group differences in VBM results when compared to methods providing more flexible warping.This difference seems to be most pronounced if the anatomy of one of the groups deviates from custom templates, a finding that is of particular importance when results are compared across studies using different VBM methods.

View Article: PubMed Central - PubMed

Affiliation: Movement Control and Neuroplasticity Research Group, Department of Kinesiology KU Leuven, Belgium ; CNRS, INCIA, UMR 5287, University of Bordeaux Talence, France.

ABSTRACT
Healthy ageing coincides with a progressive decline of brain gray matter (GM) ultimately affecting the entire brain. For a long time, manual delineation-based volumetry within predefined regions of interest (ROI) has been the gold standard for assessing such degeneration. Voxel-Based Morphometry (VBM) offers an automated alternative approach that, however, relies critically on the segmentation and spatial normalization of a large collection of images from different subjects. This can be achieved via different algorithms, with SPM5/SPM8, DARTEL of SPM8 and FSL tools (FAST, FNIRT) being three of the most frequently used. We complemented these voxel based measurements with a ROI based approach, whereby the ROIs are defined by transforms of an atlas (containing different tissue probability maps as well as predefined anatomic labels) to the individual subject images in order to obtain volumetric information at the level of the whole brain or within separate ROIs. Comparing GM decline between 21 young subjects (mean age 23) and 18 elderly (mean age 66) revealed that volumetric measurements differed significantly between methods. The unified segmentation/normalization of SPM5/SPM8 revealed the largest age-related differences and DARTEL the smallest, with FSL being more similar to the DARTEL approach. Method specific differences were substantial after segmentation and most pronounced for the cortical structures in close vicinity to major sulci and fissures. Our findings suggest that algorithms that provide only limited degrees of freedom for local deformations (such as the unified segmentation and normalization of SPM5/SPM8) tend to overestimate between-group differences in VBM results when compared to methods providing more flexible warping. This difference seems to be most pronounced if the anatomy of one of the groups deviates from custom templates, a finding that is of particular importance when results are compared across studies using different VBM methods.

No MeSH data available.


Related in: MedlinePlus

GM segmentations derived by SPM (A–C), DARTEL (D–F), and FSL (G–I) were normalized using the warping and modulation parameters of SPM (A,D,G), DARTEL (B,E,H) and FSL (C,F,I). Statistical parametric maps were either thresholded at p < 0.001 uncorrected (red) or p < 0.05 FWE corrected (yellow).
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Figure 4: GM segmentations derived by SPM (A–C), DARTEL (D–F), and FSL (G–I) were normalized using the warping and modulation parameters of SPM (A,D,G), DARTEL (B,E,H) and FSL (C,F,I). Statistical parametric maps were either thresholded at p < 0.001 uncorrected (red) or p < 0.05 FWE corrected (yellow).

Mentions: As a final control, we warped the GM segmentations to ICBM152 space using the warpings derived with SPM5/SPM8, DARTEL, and FSL. Figure 4 shows the VBM results in form of statistical parametric maps when GM differences are contrasted between the young and the elderly sample. Even though this analysis reveals purely qualitative information, it is apparent that the general results pattern is similar, but also that some differences persist after normalization, particularly when more stringent statistical thresholding is used. Figures 4A,E,I show the results revealed by the SPM5/SPM8 VBM, DARTEL VBM, and FSL VBM pipeline, respectively. Representative slices show that all methods reveal age-related differences around large sulci, like the lateral fissure, but that extent and peak location differ. In accordance to the segmentation results, DARTEL VBM revealed less age-related GM differences than the other methods. SPM5/SPM8 VBM and FSL VBM revealed age-related changes of similar extent but results of FSL VBM were located more medially and superior to those of SPM5/SPM8 VBM. Furthermore, we applied each normalization method to each segmentation result. Overall, SPM5/SPM8 normalization (Figures 4A,D,G) seems to further enhance age-related differences in comparison to DARTEL (Figures 4B,E,H) while the FSL provides an intermediate solution, particularly when thresholded at pFWE < 0.05 (note though that the FSL developers advise to use non-parametric statistics for VBM analyses). In summary, when age-related decline is estimated with VBM, method specific differences persist also after normalization.


Assessing age-related gray matter decline with voxel-based morphometry depends significantly on segmentation and normalization procedures.

Callaert DV, Ribbens A, Maes F, Swinnen SP, Wenderoth N - Front Aging Neurosci (2014)

GM segmentations derived by SPM (A–C), DARTEL (D–F), and FSL (G–I) were normalized using the warping and modulation parameters of SPM (A,D,G), DARTEL (B,E,H) and FSL (C,F,I). Statistical parametric maps were either thresholded at p < 0.001 uncorrected (red) or p < 0.05 FWE corrected (yellow).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4066859&req=5

Figure 4: GM segmentations derived by SPM (A–C), DARTEL (D–F), and FSL (G–I) were normalized using the warping and modulation parameters of SPM (A,D,G), DARTEL (B,E,H) and FSL (C,F,I). Statistical parametric maps were either thresholded at p < 0.001 uncorrected (red) or p < 0.05 FWE corrected (yellow).
Mentions: As a final control, we warped the GM segmentations to ICBM152 space using the warpings derived with SPM5/SPM8, DARTEL, and FSL. Figure 4 shows the VBM results in form of statistical parametric maps when GM differences are contrasted between the young and the elderly sample. Even though this analysis reveals purely qualitative information, it is apparent that the general results pattern is similar, but also that some differences persist after normalization, particularly when more stringent statistical thresholding is used. Figures 4A,E,I show the results revealed by the SPM5/SPM8 VBM, DARTEL VBM, and FSL VBM pipeline, respectively. Representative slices show that all methods reveal age-related differences around large sulci, like the lateral fissure, but that extent and peak location differ. In accordance to the segmentation results, DARTEL VBM revealed less age-related GM differences than the other methods. SPM5/SPM8 VBM and FSL VBM revealed age-related changes of similar extent but results of FSL VBM were located more medially and superior to those of SPM5/SPM8 VBM. Furthermore, we applied each normalization method to each segmentation result. Overall, SPM5/SPM8 normalization (Figures 4A,D,G) seems to further enhance age-related differences in comparison to DARTEL (Figures 4B,E,H) while the FSL provides an intermediate solution, particularly when thresholded at pFWE < 0.05 (note though that the FSL developers advise to use non-parametric statistics for VBM analyses). In summary, when age-related decline is estimated with VBM, method specific differences persist also after normalization.

Bottom Line: Comparing GM decline between 21 young subjects (mean age 23) and 18 elderly (mean age 66) revealed that volumetric measurements differed significantly between methods.Our findings suggest that algorithms that provide only limited degrees of freedom for local deformations (such as the unified segmentation and normalization of SPM5/SPM8) tend to overestimate between-group differences in VBM results when compared to methods providing more flexible warping.This difference seems to be most pronounced if the anatomy of one of the groups deviates from custom templates, a finding that is of particular importance when results are compared across studies using different VBM methods.

View Article: PubMed Central - PubMed

Affiliation: Movement Control and Neuroplasticity Research Group, Department of Kinesiology KU Leuven, Belgium ; CNRS, INCIA, UMR 5287, University of Bordeaux Talence, France.

ABSTRACT
Healthy ageing coincides with a progressive decline of brain gray matter (GM) ultimately affecting the entire brain. For a long time, manual delineation-based volumetry within predefined regions of interest (ROI) has been the gold standard for assessing such degeneration. Voxel-Based Morphometry (VBM) offers an automated alternative approach that, however, relies critically on the segmentation and spatial normalization of a large collection of images from different subjects. This can be achieved via different algorithms, with SPM5/SPM8, DARTEL of SPM8 and FSL tools (FAST, FNIRT) being three of the most frequently used. We complemented these voxel based measurements with a ROI based approach, whereby the ROIs are defined by transforms of an atlas (containing different tissue probability maps as well as predefined anatomic labels) to the individual subject images in order to obtain volumetric information at the level of the whole brain or within separate ROIs. Comparing GM decline between 21 young subjects (mean age 23) and 18 elderly (mean age 66) revealed that volumetric measurements differed significantly between methods. The unified segmentation/normalization of SPM5/SPM8 revealed the largest age-related differences and DARTEL the smallest, with FSL being more similar to the DARTEL approach. Method specific differences were substantial after segmentation and most pronounced for the cortical structures in close vicinity to major sulci and fissures. Our findings suggest that algorithms that provide only limited degrees of freedom for local deformations (such as the unified segmentation and normalization of SPM5/SPM8) tend to overestimate between-group differences in VBM results when compared to methods providing more flexible warping. This difference seems to be most pronounced if the anatomy of one of the groups deviates from custom templates, a finding that is of particular importance when results are compared across studies using different VBM methods.

No MeSH data available.


Related in: MedlinePlus