Individual Detection of Patients with Parkinson Disease using Support Vector Machine Analysis of Diffusion Tensor Imaging Data: Initial Results

References

1. 1.↵
   1. Oikawa H,
   2. Sasaki M,
   3. Tamakawa Y,
   4. et al

   . The substantia nigra in Parkinson disease: proton density-weighted spin-echo and fast short inversion time inversion-recovery MR findings. AJNR Am J Neuroradiol 2002; 23: 1747– 56

   Abstract/FREE Full Text
2. 2.↵
   1. Chan LL,
   2. Rumpel H,
   3. Yap K,
   4. et al

   . Case control study of diffusion tensor imaging in Parkinson's disease. J Neurol Neurosurg Psychiatry 2007; 78: 1383– 86

   Abstract/FREE Full Text
3. 3.↵
   1. Tessa C,
   2. Giannelli M,
   3. Della Nave R,
   4. et al

   . A whole-brain analysis in de novo Parkinson disease. AJNR Am J Neuroradiol 2008; 29: 674– 80

   Abstract/FREE Full Text
4. 4.↵
   1. Nicoletti G,
   2. Manners D,
   3. Novellino F,
   4. et al

   . Diffusion tensor MRI changes in cerebellar structures of patients with familial essential tremor. Neurology 2010; 74: 988– 94

   Abstract/FREE Full Text
5. 5.↵
   1. Gattellaro G,
   2. Minati L,
   3. Grisoli M,
   4. et al

   . White matter involvement in idiopathic Parkinson disease: a diffusion tensor imaging study. AJNR Am J Neuroradiol 2009; 30: 1222– 26

   Abstract/FREE Full Text
6. 6.↵
   1. Karagulle Kendi AT,
   2. Lehericy S,
   3. Luciana M,
   4. et al

   . Altered diffusion in the frontal lobe in Parkinson disease. AJNR Am J Neuroradiol 2008; 29: 501– 05

   Abstract/FREE Full Text
7. 7.↵
   1. Noble WS

   . What is a support vector machine? Nat Biotechnol 2006; 24: 1565– 67

   CrossRefPubMedWeb of Science
8. 8.↵
   1. Haller S,
   2. Lovblad KO,
   3. Giannakopoulos P

   . Principles of classification analyses in mild cognitive impairment (MCI) and Alzheimer disease. J Alzheimers Dis 2011; 26 (suppl 3): 389– 94

   CrossRefPubMed
9. 9.↵
   1. Della Nave R,
   2. Ginestroni A,
   3. Tessa C,
   4. et al

   . Brain white matter tracts degeneration in Friedreich ataxia: an in vivo MRI study using tract-based spatial statistics and voxel-based morphometry. Neuroimage 2008; 40: 19– 25

   CrossRefPubMed
10. 10.↵
    1. Della Nave R,
    2. Ginestroni A,
    3. Tessa C,
    4. et al

    . Brain white matter damage in SCA1 and SCA2: an in vivo study using voxel-based morphometry, histogram analysis of mean diffusivity and tract-based spatial statistics. Neuroimage 2008; 43: 10– 19

    CrossRefPubMed
11. 11.↵
    1. Haller S,
    2. Xekardaki A,
    3. Delaloye C,
    4. et al

    . Combined analysis of grey matter voxel-based morphometry and white matter tract-based spatial statistics in late-life bipolar disorder. J Psychiatry Neurosci 2011; 36: 391– 401

    CrossRefPubMedWeb of Science
12. 12.↵
    1. Agosta F,
    2. Pievani M,
    3. Sala S,
    4. et al

    . White matter damage in Alzheimer disease and its relationship to gray matter atrophy. Radiology 2011; 258: 853– 63

    CrossRefPubMedWeb of Science
13. 13.↵
    1. Smith SM,
    2. Jenkinson M,
    3. Johansen-Berg H,
    4. et al

    . Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data. Neuroimage 2006; 31: 1487– 505

    CrossRefPubMedWeb of Science
14. 14.↵
    1. Ashburner J,
    2. Friston KJ

    . Voxel-based morphometry: the methods. Neuroimage 2000; 11: 805– 21

    CrossRefPubMedWeb of Science
15. 15.↵
    1. Haller S,
    2. Nguyen D,
    3. Rodriguez C,
    4. et al

    . Individual prediction of cognitive decline in mild cognitive impairment using support vector machine-based analysis of diffusion tensor imaging data. J Alzheimers Dis 2010; 22: 315– 27

    PubMedWeb of Science
16. 16.↵
    1. Fazekas F,
    2. Chawluk JB,
    3. Alavi A,
    4. et al

    . MR signal abnormalities at 1.5 T in Alzheimer's dementia and normal aging. AJR Am J Roentgenol 1987; 149: 351– 56

    CrossRefPubMedWeb of Science
17. 17.↵
    1. Smith SM,
    2. Johansen-Berg H,
    3. Jenkinson M,
    4. et al

    . Acquisition and voxelwise analysis of multi-subject diffusion data with tract-based spatial statistics. Nat Protoc 2007; 2: 499– 503

    CrossRefPubMedWeb of Science
18. 18.↵
    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
19. 19.↵
    1. Smith SM,
    2. Nichols TE

    . Threshold-free cluster enhancement: addressing problems of smoothing, threshold dependence and localisation in cluster inference. Neuroimage 2009; 44: 83– 98

    CrossRefPubMedWeb of Science
20. 20.↵
    1. Kononenko I,
    2. Scaron;imec E,
    3. Robnik-Šikonja M

    . Overcoming the myopia of inductive learning algorithms with RELIEFF. Applied Intelligence 1997; 7: 39– 55

    CrossRef
21. 21.↵
    1. Platt J

    . Sequential minimal optimization: a fast algorithm for training support vector machines. Microsoft Research Technical Report MSR-TR-98, http://research.microsoft.com/en-us/um/people/jplatt/smoTR.pdf (Accessed April 21, 1998)
22. 22.↵
    1. Schölkopf B,
    2. Sung KK,
    3. Burges CJ,
    4. et al

    . Comparing support vector machines with Gaussian kernels to radial basis function classifiers. IEEE Transactions on Signal Processing 1997; 45: 2758– 65

    CrossRef
23. 23.↵
    1. Hoehn MM,
    2. Yahr MD

    . Parkinsonism: onset, progression and mortality. Neurology 1967; 17: 427– 42

    FREE Full Text
24. 24.↵
    1. Gilman S,
    2. Low PA,
    3. Quinn N,
    4. et al

    . Consensus statement on the diagnosis of multiple system atrophy. J Neurol Sci 1999; 163: 94– 98

    CrossRefPubMedWeb of Science
25. 25.↵
    1. Litvan I,
    2. Agid Y,
    3. Calne D,
    4. et al

    . Clinical research criteria for the diagnosis of progressive supranuclear palsy (Steele-Richardson-Olszewski syndrome): report of the NINDS-SPSP international workshop. Neurology 1996; 47: 1– 9

    Abstract/FREE Full Text
26. 26.↵
    1. McKeith IG,
    2. Dickson DW,
    3. Lowe J,
    4. et al

    . Diagnosis and management of dementia with Lewy bodies: third report of the DLB Consortium. Neurology 2005; 65: 1863– 72

    Abstract/FREE Full Text
27. 27.↵
    1. Roman GC,
    2. Tatemichi TK,
    3. Erkinjuntti T,
    4. et al

    . Vascular dementia: diagnostic criteria for research studies: report of the NINDS-AIREN International Workshop. Neurology 1993; 43: 250– 60

    Abstract/FREE Full Text
28. 28.↵
    1. Vaillancourt DE,
    2. Spraker MB,
    3. Prodoehl J,
    4. et al

    . High-resolution diffusion tensor imaging in the substantia nigra of de novo Parkinson disease. Neurology 2009; 72: 1378– 84

    Abstract/FREE Full Text
29. 29.↵
    1. Ibarretxe-Bilbao N,
    2. Junque C,
    3. Marti MJ,
    4. et al

    . Olfactory impairment in Parkinson's disease and white matter abnormalities in central olfactory areas: a voxel-based diffusion tensor imaging study. Mov Disord 2010; 25: 1888– 94

    CrossRefPubMed
30. 30.↵
    1. Li W,
    2. Liu J,
    3. Skidmore F,
    4. et al

    . White matter microstructure changes in the thalamus in Parkinson disease with depression: a diffusion tensor MR imaging study. AJNR Am J Neuroradiol 2010; 31: 1861– 66

    Abstract/FREE Full Text
31. 31.↵
    1. Boelmans K,
    2. Bodammer NC,
    3. Suchorska B,
    4. et al

    . Diffusion tensor imaging of the corpus callosum differentiates corticobasal syndrome from Parkinson's disease. Parkinsonism Relat Disord 2010; 16: 498– 502

    CrossRefPubMed
32. 32.↵
    1. Focke NK,
    2. Helms G,
    3. Pantel PM,
    4. et al

    . Differentiation of typical and atypical Parkinson syndromes by quantitative MR imaging. AJNR Am J Neuroradiol 2011; 32: 2087– 92

    Abstract/FREE Full Text
33. 33.↵
    1. Morgen K,
    2. Sammer G,
    3. Weber L,
    4. et al

    . Structural brain abnormalities in patients with Parkinson disease: a comparative voxel-based analysis using T1-weighted MR imaging and magnetization transfer imaging. AJNR Am J Neuroradiol 2011; 32: 2080– 86

    Abstract/FREE Full Text
34. 34.↵
    1. Thomalla G,
    2. Glauche V,
    3. Koch MA,
    4. et al

    . Diffusion tensor imaging detects early Wallerian degeneration of the pyramidal tract after ischemic stroke. Neuroimage 2004; 22: 1767– 74

    CrossRefPubMedWeb of Science
35. 35.↵
    1. Haller S,
    2. Bartsch A,
    3. Nguyen D,
    4. et al

    . Cerebral microhemorrhage and iron deposition in mild cognitive impairment: susceptibility-weighted MR imaging assessment. Radiology 2010; 257: 764– 73

    CrossRefPubMed
36. 36.↵
    1. Jeon HS,
    2. Han J,
    3. Yi WJ,
    4. et al

    . Classification of Parkinson gait and normal gait using spatial-temporal image of plantar pressure. Conf Proc IEEE Eng Med Biol Soc 2008; 2008: 4672– 75

    PubMed
37. 37.↵
    1. Brewer BR,
    2. Pradhan S,
    3. Carvell G Delitto A

    . Feature selection for classification based on fine motor signs of Parkinson's disease. Conf Proc IEEE Eng Med Biol Soc 2009; 2009: 214– 17

    PubMed
38. 38.↵
    1. Patel S,
    2. Lorincz K,
    3. Hughes R,
    4. et al

    . Monitoring motor fluctuations in patients with Parkinson's disease using wearable sensors. IEEE Trans Inf Technol Biomed 2009; 13: 864– 73

    CrossRefPubMed
39. 39.↵
    1. Chan J,
    2. Leung H Poizner H

    . Correlation among joint motions allows classification of Parkinsonian versus normal 3-D reaching. IEEE Trans Neural Syst Rehabil Eng 2010; 18: 142– 49

    CrossRefPubMed
40. 40.↵
    1. Ozcift A

    . SVM feature selection based rotation forest ensemble classifiers to improve computer-aided diagnosis of Parkinson disease. J Med Syst 2011 Mar 10. [Epub ahead of print]
41. 41.↵
    1. Focke NK,
    2. Helms G,
    3. Scheewe S,
    4. et al

    . Individual voxel-based subtype prediction can differentiate progressive supranuclear palsy from idiopathic Parkinson syndrome and healthy controls. Hum Brain Mapp 2011; 32: 1905– 15

    CrossRefPubMed
42. 42.↵
    1. Groschel K,
    2. Kastrup A,
    3. Litvan I Schulz JB

    . Penguins and hummingbirds: midbrain atrophy in progressive supranuclear palsy. Neurology 2006; 66: 949– 50

    FREE Full Text
43. 43.↵
    1. Kloppel S,
    2. Stonnington CM,
    3. Chu C,
    4. et al

    . Automatic classification of MR scans in Alzheimer's disease. Brain 2008; 131: 681– 89

    Abstract/FREE Full Text
44. 44.↵
    1. Plant C,
    2. Teipel SJ,
    3. Oswald A,
    4. et al

    . Automated detection of brain atrophy patterns based on MRI for the prediction of Alzheimer's disease. Neuroimage 2010; 50: 162– 74

    CrossRefPubMed
45. 45.↵
    1. Misra C,
    2. Fan Y Davatzikos C

    . Baseline and longitudinal patterns of brain atrophy in MCI patients, and their use in prediction of short-term conversion to AD: results from ADNI. Neuroimage 2009; 44: 1415– 22

    CrossRefPubMedWeb of Science
46. 46.↵
    1. Fan Y,
    2. Batmanghelich N,
    3. Clark CM,
    4. et al

    . Spatial patterns of brain atrophy in MCI patients, identified via high-dimensional pattern classification, predict subsequent cognitive decline. Neuroimage 2008; 39: 1731– 43

    CrossRefPubMedWeb of Science