A Comparison Between Volumetric Data Generated by Voxel-Based Morphometry and Manual Parcellation of Multimodal Regions of the Frontal Lobe

References

1. 1.↵
   1. Fjell AM,
   2. Walhovd KB

   . Structural brain changes in aging: courses, causes and cognitive consequences. Rev Neurosci 2010;21:187–221

   CrossRefPubMed
2. 2.↵
   1. Shaw P,
   2. Kabani NJ,
   3. Lerch JP,
   4. et al

   . Neurodevelopmental trajectories of the human cerebral cortex. J Neurosci 2008;28:3586–94

   Abstract/FREE Full Text
3. 3.↵
   1. Raz N,
   2. Gunning-Dixon F,
   3. Head D,
   4. et al

   . Aging, sexual dimorphism, and hemispheric asymmetry of the cerebral cortex: replicability of regional differences in volume. Neurobiol Aging 2004;25:377–96

   CrossRefPubMedWeb of Science
4. 4.↵
   1. Tisserand DJ,
   2. Pruessner JC,
   3. Sanz Arigita EJ,
   4. et al

   . Regional frontal cortical volumes decrease differentially in aging: an MRI study to compare volumetric approaches and voxel-based morphometry. Neuroimage 2002;17:657–69

   CrossRefPubMedWeb of Science
5. 5.↵
   1. Westlye LT,
   2. Walhovd KB,
   3. Dale AM,
   4. et al

   . Differentiating maturational and aging-related changes of the cerebral cortex by use of thickness and signal intensity. Neuroimage 2010;52:172–85

   CrossRefPubMedWeb of Science
6. 6.↵
   1. Raz N,
   2. Lindenberger U,
   3. Rodrigue KM,
   4. et al

   . Regional brain changes in aging healthy adults: general trends, individual differences and modifiers. Cereb Cortex 2005;15:1676–89

   Abstract/FREE Full Text
7. 7.↵
   1. Walhovd KB,
   2. Westlye LT,
   3. Amlien I,
   4. et al

   . Consistent neuroanatomical age-related volume differences across multiple samples. Neurobiol Aging 2011;32:916–32

   CrossRefPubMedWeb of Science
8. 8.↵
   1. McGinnis SM,
   2. Brickhouse M,
   3. Pascual B,
   4. et al

   . Age-related changes in the thickness of cortical zones in humans. Brain Topogr 2011;24:279–91

   CrossRefPubMedWeb of Science
9. 9.↵
   1. Whitwell JL,
   2. Jack CR Jr.

   . Comparisons between Alzheimer disease, frontotemporal lobar degeneration, and normal aging with brain mapping. Top Magn Reson Imaging 2005;16:409–25

   CrossRefPubMed
10. 10.↵
    1. McEvoy LK,
    2. Fennema-Notestine C,
    3. Roddey JC,
    4. et al

    . Alzheimer disease: quantitative structural neuroimaging for detection and prediction of clinical and structural changes in mild cognitive impairment. Radiology 2009;251:195–205

    CrossRefPubMedWeb of Science
11. 11.↵
    1. Tartaglia MC,
    2. Rosen HJ,
    3. Miller BL

    . Neuroimaging in dementia. Neurotherapeutics 2011;8:82–92

    CrossRefPubMed
12. 12.↵
    1. Kim EJ,
    2. Sidhu M,
    3. Gaus SE,
    4. et al

    . Selective frontoinsular von Economo neuron and fork cell loss in early behavioral variant frontotemporal dementia. Cereb Cortex 2012;22:251–59

    Abstract/FREE Full Text
13. 13.↵
    1. Seeley WW,
    2. Carlin DA,
    3. Allman JM,
    4. et al

    . Early frontotemporal dementia targets neurons unique to apes and humans. Ann Neurol 2006;60:660–67

    CrossRefPubMedWeb of Science
14. 14.↵
    1. Mesulam MM

    . From sensation to cognition. Brain 1998;121 (Pt 6): 1013–52

    Abstract/FREE Full Text
15. 15.↵
    1. Fischl B,
    2. Rajendran N,
    3. Busa E,
    4. et al

    . Cortical folding patterns and predicting cytoarchitecture. Cereb Cortex 2008;18:1973–80

    Abstract/FREE Full Text
16. 16.↵
    1. Amunts K,
    2. Schleicher A,
    3. Zilles K

    . Cytoarchitecture of the cerebral cortex–more than localization. Neuroimage 2007;37:1061–65; discussion 1066–68

    CrossRefPubMedWeb of Science
17. 17.↵
    1. McCormick LM,
    2. Ziebell S,
    3. Nopoulos P,
    4. et al

    . Anterior cingulate cortex: an MRI-based parcellation method. Neuroimage 2006;32:1167–75

    CrossRefPubMedWeb of Science
18. 18.↵
    1. Fornito A,
    2. Wood SJ,
    3. Whittle S,
    4. et al

    . Variability of the paracingulate sulcus and morphometry of the medial frontal cortex: associations with cortical thickness, surface area, volume, and sulcal depth. Hum Brain Mapp 2008;29:222–36

    CrossRefPubMedWeb of Science
19. 19.↵
    1. Lindberg O,
    2. Ostberg P,
    3. Zandbelt BB,
    4. et al

    . Cortical morphometric subclassification of frontotemporal lobar degeneration. AJNR Am J Neuroradiol 2009;30:1233–39

    Abstract/FREE Full Text
20. 20.↵
    1. Looi JC,
    2. Lindberg O,
    3. Zandbelt BB,
    4. et al

    . Caudate nucleus volumes in frontotemporal lobar degeneration: differential atrophy in subtypes. AJNR Am J Neuroradiol 2008;29:1537–43

    Abstract/FREE Full Text
21. 21.↵
    1. Looi JC,
    2. Svensson L,
    3. Lindberg O,
    4. et al

    . Putaminal volume in frontotemporal lobar degeneration and Alzheimer disease: differential volumes in dementia subtypes and controls. AJNR Am J Neuroradiol 2009;30:1552–60

    Abstract/FREE Full Text
22. 22.↵
    1. Looi JC,
    2. Walterfang M,
    3. Styner M,
    4. et al

    . Shape analysis of the neostriatum in frontotemporal lobar degeneration, Alzheimer's disease, and controls. Neuroimage 2010;51:970–86

    CrossRefPubMedWeb of Science
23. 23.↵
    1. Looi JC,
    2. Walterfang M,
    3. Styner M,
    4. et al

    . Shape analysis of the neostriatum in subtypes of frontotemporal lobar degeneration: neuroanatomically significant regional morphologic change. Psychiatry Res 2011;191:98–111

    CrossRefPubMedWeb of Science
24. 24.↵
    1. Andersson C

    . Predictors of cognitive decline in memory clinic patients. Stockholm, Sweden: Karolinska Institute, 2007
25. 25.↵
    1. Neary D,
    2. Snowden JS,
    3. Gustafson L,
    4. et al

    . Frontotemporal lobar degeneration: a consensus on clinical diagnostic criteria. Neurology 1998;51:1546–54

    Abstract/FREE Full Text
26. 26.↵
    1. Suzuki M,
    2. Zhou SY,
    3. Takahashi T,
    4. et al

    . Differential contributions of prefrontal and temporolimbic pathology to mechanisms of psychosis. Brain 2005;128:2109–22

    Abstract/FREE Full Text
27. 27.↵
    1. Fornito A,
    2. Whittle S,
    3. Wood SJ,
    4. et al

    . The influence of sulcal variability on morphometry of the human anterior cingulate and paracingulate cortex. Neuroimage 2006;33:843–54

    CrossRefPubMedWeb of Science
28. 28.↵
    1. Crespo-Facorro B,
    2. Kim J,
    3. Andreasen NC,
    4. et al

    . Cerebral cortex: a topographic segmentation method using magnetic resonance imaging. Psychiatry Res 2000;100:97–126

    PubMedWeb of Science
29. 29.↵
    1. Malykhin NV,
    2. Bouchard TP,
    3. Ogilvie CJ,
    4. et al

    . Three-dimensional volumetric analysis and reconstruction of amygdala and hippocampal head, body and tail. Psychiatry Res 2007;155:155–65

    CrossRefPubMedWeb of Science
30. 30.↵
    1. Eritaia J,
    2. Wood SJ,
    3. Stuart GW,
    4. et al

    . An optimized method for estimating intracranial volume from magnetic resonance images. Magn Reson Med 2000;44:973–77

    CrossRefPubMedWeb of Science
31. 31.↵
    1. Ashburner J,
    2. Andersson JL,
    3. Friston KJ

    . Image registration using a symmetric prior–in three dimensions. Hum Brain Mapp 2000;9:212–25

    CrossRefPubMedWeb of Science
32. 32.↵
    1. Good CD,
    2. Johnsrude IS,
    3. Ashburner J,
    4. et al

    . A voxel-based morphometric study of ageing in 465 normal adult human brains. Neuroimage 2001;14:21–36

    CrossRefPubMedWeb of Science
33. 33.↵
    1. Smith SM,
    2. Jenkinson M,
    3. Woolrich MW,
    4. et al

    . Advances in functional and structural MR image analysis and implementation as FSL. Neuroimage 2004;23 (Suppl 1): S208–19

    CrossRefPubMedWeb of Science
34. 34.↵
    1. Smith SM

    . Fast robust automated brain extraction. Hum Brain Mapp 2002;17:143–55

    CrossRefPubMedWeb of Science
35. 35.↵
    1. Zhang Y,
    2. Brady M,
    3. Smith S

    . Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm. IEEE Trans Med Imaging 2001;20:45–57

    CrossRefPubMedWeb of Science
36. 36.↵
    1. Jenkinson M,
    2. Smith S

    . A global optimisation method for robust affine registration of brain images. Med Image Anal 2001;5:143–56

    CrossRefPubMedWeb of Science
37. 37.↵
    1. Jenkinson M,
    2. Bannister P,
    3. Brady M,
    4. et al

    . Improved optimization for the robust and accurate linear registration and motion correction of brain images. Neuroimage 2002;17:825–41

    CrossRefPubMedWeb of Science
38. 38.↵
    1. Shrout PE,
    2. Fleiss JL

    . Intraclass correlations: uses in assessing rater reliability. Psychol Bull 1979;86:420–28

    CrossRefPubMedWeb of Science
39. 39.↵
    1. Seeley WW,
    2. Crawford RK,
    3. Zhou J,
    4. et al

    . Neurodegenerative diseases target large-scale human brain networks. Neuron 2009;62:42–52

    CrossRefPubMedWeb of Science
40. 40.↵
    1. Seeley WW,
    2. Crawford R,
    3. Rascovsky K,
    4. et al

    . Frontal paralimbic network atrophy in very mild behavioral variant frontotemporal dementia. Arch Neurol 2008;65:249–55

    CrossRefPubMedWeb of Science