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White Matter Fiber Bundle Alterations Correlate with Gait and Cognitive Impairments in Parkinson’s Disease based on HARDI Data

Abstract

Background:

The neuroanatomical basis of white matter fiber tracts in gait impairments in individuals suffering from Parkinson’s Disease (PD) is unclear.

Methods:

Twenty-four individuals living with PD and 29 Healthy Controls (HCs) were included. For each participant, two-shell High Angular Resolution Diffusion Imaging (HARDI) and high-resolution 3D structural images were acquired using the 3T MRI. Diffusion-weighted data preprocessing was performed using the orientation distribution function to trace the main fiber tracts in PD individuals. Clinical characteristics between the two groups were compared, and the correlation between the FA value and behavioral data was analyzed. Quantitative gait and clinical parameters were recorded in PD at ON and OFF states, respectively.

Results:

The mean tract-specific FA values of the right Cingulum Cingulate (rCC) were statistically different between the PD group and the HC group ( =0.047). The FA value of 34-58 equidistant nodes in rCC was positively correlated with Mini-Mental State Examination (MMSE) (r=0.527, =0.024), Berg Balance Scale (BBS)-OFF (r=0.480, =0.040), and BBS-ON (r=0.528, =0.024) scores, while it was negatively correlated with the MDS-UPDRS-III-ON score (r=-0.502, =0.030). Regarding the gait analysis, the FA value was significantly correlated with velocity, cadence, and stride time of the pace and rhythm domains in both ‘ON’ and ‘OFF’ states, respectively (<0.05).

Conclusion:

This study served as an initial exploration to establish that HARDI sequences could be employed as a robust tool for analyzing microstructural alterations in white matter fiber bundles among PD patients, although the sample size was small. We confirmed microstructural integrity impairment of rCC to be significantly associated with both gait and cognitive deficits in patients with PD. Early detection of microstructural changes in rCC and targeted treatment can help improve behavioral disorders. In the future, we intend to further integrate multimodal data with assessments of patient behavior both prior to and following intervention. We will validate our findings within an independent cohort to monitor disease progression and evaluate the efficacy of therapeutic interventions.

This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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2025-01-14
2025-01-18
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References

  1. Elbaz A. Carcaillon L. Kab S. Moisan F. Epidemiology of Parkinson’s disease. Rev. Neurol. 2016 172 1 14 26 10.1016/j.neurol.2015.09.012 26718594
    [Google Scholar]
  2. Tolosa E. Garrido A. Scholz S.W. Poewe W. Challenges in the diagnosis of Parkinson’s disease. Lancet Neurol. 2021 20 5 385 397 10.1016/S1474‑4422(21)00030‑2 33894193
    [Google Scholar]
  3. Lang M. Hirche S. Pfister F.M.J. Frohner J. Abedinpour K. Pichler D. Fietzek U. Um T.T. Kulic D. Endo S. A multi-layer gaussian process for motor symptom estimation in people with Parkinson’s disease. IEEE Trans. Biomed. Eng. 2019 66 11 3038 3049 10.1109/TBME.2019.2900002 30794163
    [Google Scholar]
  4. Nóbrega L.R. Rocon E. Pereira A.A. Andrade A.O. A novel physical mobility task to assess freezers in Parkinson’s disease. Healthcare 2023 11 3 409
    [Google Scholar]
  5. Bonora G. Mancini M. Carpinella I. Chiari L. Horak F.B. Ferrarin M. Gait initiation is impaired in subjects with Parkinson’s disease in the OFF state: Evidence from the analysis of the anticipatory postural adjustments through wearable inertial sensors. Gait Posture 2017 51 218 221 10.1016/j.gaitpost.2016.10.017 27816900
    [Google Scholar]
  6. Worringham C.J. Wood J.M. Kerr G.K. Silburn P.A. Predictors of driving assessment outcome in Parkinson’s disease. Mov. Disord. 2006 21 2 230 235 10.1002/mds.20709 16161149
    [Google Scholar]
  7. Pimenta M. Moreira D. Nogueira T. Silva C. Pinto E.B. Valenca G.T. Almeida L.R.S. Anxiety independently contributes to severity of freezing of gait in people with Parkinson’s disease. J. Neuropsychiatry Clin. Neurosci. 2019 31 1 80 85 10.1176/appi.neuropsych.17090177 30187821
    [Google Scholar]
  8. Lord S. Galna B. Rochester L. Moving forward on gait measurement: Toward a more refined approach. Mov. Disord. 2013 28 11 1534 1543 10.1002/mds.25545 24132841
    [Google Scholar]
  9. Wei X. Wang Z. Zhang M. Li M. Chen Y.C. Lv H. Tuo H. Yang Z. Wang Z. Ba F. Brain surface area alterations correlate with gait impairments in Parkinson’s disease. Front. Aging Neurosci. 2022 14 806026 10.3389/fnagi.2022.806026 35153730
    [Google Scholar]
  10. Braak H. Ghebremedhin E. Rüb U. Bratzke H. Tredici D.K. Stages in the development of Parkinson’s disease-related pathology. Cell Tissue Res. 2004 318 1 121 134 10.1007/s00441‑004‑0956‑9 15338272
    [Google Scholar]
  11. Braak H. Tredici D.K. Neuropathological staging of brain pathology in sporadic Parkinson’s disease: Separating the wheat from the chaff. J. Parkinsons Dis. 2017 7 s1 S71 S85 10.3233/JPD‑179001 28282810
    [Google Scholar]
  12. Michely J. Volz L.J. Barbe M.T. Hoffstaedter F. Viswanathan S. Timmermann L. Eickhoff S.B. Fink G.R. Grefkes C. Dopaminergic modulation of motor network dynamics in Parkinson’s disease. Brain 2015 138 3 664 678 10.1093/brain/awu381 25567321
    [Google Scholar]
  13. Maiti B. Rawson K.S. Tanenbaum A.B. Koller J.M. Snyder A.Z. Campbell M.C. Earhart G.M. Perlmutter J.S. Functional connectivity of vermis correlates with future gait impairments in Parkinson’s disease. Mov. Disord. 2021 36 11 2559 2568 10.1002/mds.28684 34109682
    [Google Scholar]
  14. Joza S. Camicioli R. Martin W.R.W. Wieler M. Gee M. Ba F. Pedunculopontine nucleus dysconnectivity correlates with gait impairment in Parkinson’s disease: An exploratory study. Front. Aging Neurosci. 2022 14 874692 10.3389/fnagi.2022.874692 35875799
    [Google Scholar]
  15. Surkont J. Joza S. Camicioli R. Martin W.R.W. Wieler M. Ba F. Subcortical microstructural diffusion changes correlate with gait impairment in Parkinson’s disease. Parkinsonism Relat. Disord. 2021 87 111 118 10.1016/j.parkreldis.2021.05.005 34020302
    [Google Scholar]
  16. Shine J.M. Matar E. Ward P.B. Bolitho S.J. Gilat M. Pearson M. Naismith S.L. Lewis S.J.G. Exploring the cortical and subcortical functional magnetic resonance imaging changes associated with freezing in Parkinson’s disease. Brain 2013 136 4 1204 1215 10.1093/brain/awt049 23485851
    [Google Scholar]
  17. Zarkali A. McColgan P. Leyland L.A. Lees A.J. Rees G. Weil R.S. Fiber-specific white matter reductions in Parkinson hallucinations and visual dysfunction. Neurology 2020 94 14 e1525 e1538 10.1212/WNL.0000000000009014 32094242
    [Google Scholar]
  18. Yeatman J.D. Dougherty R.F. Myall N.J. Wandell B.A. Feldman H.M. Tract profiles of white matter properties: Automating fiber-tract quantification. PLoS One 2012 7 11 e49790 10.1371/journal.pone.0049790 23166771
    [Google Scholar]
  19. Chan L-L. Rumpel H. Yap K. Lee E. Loo H-V. Ho G-L. Chong F.S. Yuen Y. Tan E-K. Case control study of diffusion tensor imaging in Parkinson’s disease. J. Neurol. Neurosurg. Psychiatry 2007 78 12 1383 1386 10.1136/jnnp.2007.121525 17615165
    [Google Scholar]
  20. Poupon C. Clark C.A. Frouin V. Régis J. Bloch I. Bihan L.D. Mangin J.F. Regularization of diffusion-based direction maps for the tracking of brain white matter fascicles. Neuroimage 2000 12 2 184 195 10.1006/nimg.2000.0607 10913324
    [Google Scholar]
  21. Du J. Goh A. Qiu A. Diffeomorphic metric mapping of high angular resolution diffusion imaging based on Riemannian structure of orientation distribution functions. IEEE Trans. Med. Imaging 2012 31 5 1021 1033 10.1109/TMI.2011.2178253 22156979
    [Google Scholar]
  22. Tuch D.S. Q‐ball imaging. Magn. Reson. Med. 2004 52 6 1358 1372 10.1002/mrm.20279 15562495
    [Google Scholar]
  23. Mori S. Zhang J. Principles of diffusion tensor imaging and its applications to basic neuroscience research. Neuron 2006 51 5 527 539 10.1016/j.neuron.2006.08.012 16950152
    [Google Scholar]
  24. Figueiredo d.E.H.M.S.G. Borgonovi A.F.N.G. Doring T.M. Basic concepts of MR imaging, diffusion MR imaging, and diffusion tensor imaging. Magn. Reson. Imaging Clin. N. Am. 2011 19 1 1 22 10.1016/j.mric.2010.10.005 21129633
    [Google Scholar]
  25. Acqua D.F. Simmons A. Williams S.C.R. Catani M. Can spherical deconvolution provide more information than fiber orientations? Hindrance modulated orientational anisotropy, a true-tract specific index to characterize white matter diffusion. Hum. Brain Mapp. 2013 34 10 2464 2483 10.1002/hbm.22080 22488973
    [Google Scholar]
  26. Deng B. Zhang Y. Wang L. Peng K. Han L. Nie K. Yang H. Zhang L. Wang J. Diffusion tensor imaging reveals white matter changes associated with cognitive status in patients with Parkinson’s disease. Am. J. Alzheimers Dis. Other Demen. 2013 28 2 154 164 10.1177/1533317512470207 23271331
    [Google Scholar]
  27. Vaillancourt D.E. Spraker M.B. Prodoehl J. Abraham I. Corcos D.M. Zhou X.J. Comella C.L. Little D.M. High-resolution diffusion tensor imaging in the substantia nigra of de novo Parkinson disease. Neurology 2009 72 16 1378 1384 10.1212/01.wnl.0000340982.01727.6e 19129507
    [Google Scholar]
  28. Péran P. Cherubini A. Assogna F. Piras F. Quattrocchi C. Peppe A. Celsis P. Rascol O. Démonet J.F. Stefani A. Pierantozzi M. Pontieri F.E. Caltagirone C. Spalletta G. Sabatini U. Magnetic resonance imaging markers of Parkinson’s disease nigrostriatal signature. Brain 2010 133 11 3423 3433 10.1093/brain/awq212 20736190
    [Google Scholar]
  29. Wen M.C. Heng H.S.E. Hsu J.L. Xu Z. Liew G.M. Au W.L. Chan L.L. Tan L.C.S. Tan E.K. Structural connectome alterations in prodromal and de novo Parkinson’s disease patients. Parkinsonism Relat. Disord. 2017 45 21 27 10.1016/j.parkreldis.2017.09.019 28964628
    [Google Scholar]
  30. Wang M. Jiang S. Yuan Y. Zhang L. Ding J. Wang J. Zhang J. Zhang K. Wang J. Alterations of functional and structural connectivity of freezing of gait in Parkinson’s disease. J. Neurol. 2016 263 8 1583 1592 10.1007/s00415‑016‑8174‑4 27230857
    [Google Scholar]
  31. Herman T. Katz R.K. Jacob Y. Giladi N. Hausdorff J.M. Gray matter atrophy and freezing of gait in Parkinson’s disease: Is the evidence black‐on‐white? Mov. Disord. 2014 29 1 134 139 10.1002/mds.25697 24151091
    [Google Scholar]
  32. Tuch D.S. Reese T.G. Wiegell M.R. Makris N. Belliveau J.W. Wedeen V.J. High angular resolution diffusion imaging reveals intravoxel white matter fiber heterogeneity. Magn. Reson. Med. 2002 48 4 577 582 10.1002/mrm.10268 12353272
    [Google Scholar]
  33. Cousineau M. Jodoin P.M. Garyfallidis E. Côté M-A. Morency F.C. Rozanski V. Grand’Maison M. Bedell B.J. Descoteaux M. A test-retest study on Parkinson’s PPMI dataset yields statistically significant white matter fascicles. Neuroimage Clin. 2017 16 222 233 10.1016/j.nicl.2017.07.020 28794981
    [Google Scholar]
  34. Tournier J.D. Calamante F. Gadian D.G. Connelly A. Direct estimation of the fiber orientation density function from diffusion-weighted MRI data using spherical deconvolution. Neuroimage 2004 23 3 1176 1185 10.1016/j.neuroimage.2004.07.037 15528117
    [Google Scholar]
  35. Jeurissen B. Leemans A. Jones D.K. Tournier J.D. Sijbers J. Probabilistic fiber tracking using the residual bootstrap with constrained spherical deconvolution. Hum. Brain Mapp. 2011 32 3 461 479 10.1002/hbm.21032 21319270
    [Google Scholar]
  36. Hughes A.J. Daniel S.E. Shlomo B.Y. Lees A.J. The accuracy of diagnosis of parkinsonian syndromes in a specialist movement disorder service. Brain 2002 125 4 861 870 10.1093/brain/awf080 11912118
    [Google Scholar]
  37. Yan Y. Wang Z. Wei W. Yang Z. Guo L. Wang Z. Wei X. Correlation of brain iron deposition and freezing of gait in Parkinson’s disease: A cross-sectional study. Quant. Imaging Med. Surg. 2023 13 12 7961 7972 10.21037/qims‑23‑267 38106290
    [Google Scholar]
  38. Wei X. Wang S. Zhang M. Yan Y. Wang Z. Wei W. Tuo H. Wang Z. Gait impairment-related axonal degeneration in Parkinson’s disease by neurite orientation dispersion and density imaging. NPJ Parkinsons Dis. 2024 10 1 45 10.1038/s41531‑024‑00654‑w 38413647
    [Google Scholar]
  39. Jenkinson M. Beckmann C.F. Behrens T.E.J. Woolrich M.W. Smith S.M. Fsl. Neuroimage 2012 62 2 782 790 10.1016/j.neuroimage.2011.09.015 21979382
    [Google Scholar]
  40. Lamb M.R. The two sides of perception. Trends Cogn. Sci. 1998 2 5 200 201 10.1016/S1364‑6613(98)01165‑6 21227156
    [Google Scholar]
  41. Aron A.R. Poldrack R.A. Cortical and subcortical contributions to stop signal response inhibition: Role of the subthalamic nucleus. J. Neurosci. 2006 26 9 2424 2433 10.1523/JNEUROSCI.4682‑05.2006 16510720
    [Google Scholar]
  42. Kim S.M. Kim D.H. Yang Y. Ha S.W. Han J.H. Gait patterns in Parkinson’s disease with or without cognitive impairment. Dement. Neurocognitive Disord. 2018 17 2 57 65 10.12779/dnd.2018.17.2.57 30906393
    [Google Scholar]
  43. Harrington D.L. Shen Q. Wei X. Litvan I. Huang M. Lee R.R. Functional topologies of spatial cognition predict cognitive and motor progression in Parkinson’s. Front. Aging Neurosci. 2022 14 987225 10.3389/fnagi.2022.987225 36299614
    [Google Scholar]
  44. Bissett PG Logan GD Wouwe v.NC Tolleson CM Phibbs FT Claassen DO Generalized motor inhibitory deficit in Parkinson’s disease patients who freeze. J. Neural Trans. 2015 122 1693 1701 10.1007/s00702‑015‑1454‑9
    [Google Scholar]
  45. Snijders A.H. Leunissen I. Bakker M. Overeem S. Helmich R.C. Bloem B.R. Toni I. Gait-related cerebral alterations in patients with Parkinson’s disease with freezing of gait. Brain 2011 134 1 59 72 10.1093/brain/awq324 21126990
    [Google Scholar]
  46. Tessitore A. Amboni M. Esposito F. Russo A. Picillo M. Marcuccio L. Pellecchia M.T. Vitale C. Cirillo M. Tedeschi G. Barone P. Resting-state brain connectivity in patients with Parkinson’s disease and freezing of gait. Parkinsonism Relat. Disord. 2012 18 6 781 787 10.1016/j.parkreldis.2012.03.018 22510204
    [Google Scholar]
  47. Fling B.W. Cohen R.G. Mancini M. Nutt J.G. Fair D.A. Horak F.B. Asymmetric pedunculopontine network connectivity in parkinsonian patients with freezing of gait. Brain 2013 136 8 2405 2418 10.1093/brain/awt172 23824487
    [Google Scholar]
  48. Vogt B.A. Cingulate cortex in the three limbic subsystems. Handb. Clin. Neurol. 2019 166 39 51 10.1016/B978‑0‑444‑64196‑0.00003‑0 31731924
    [Google Scholar]
  49. Prange S. Metereau E. Maillet A. Lhommée E. Klinger H. Pelissier P. Ibarrola D. Heckemann R.A. Castrioto A. Tremblay L. Sgambato V. Broussolle E. Krack P. Thobois S. Early limbic microstructural alterations in apathy and depression in de novo Parkinson’s disease. Mov. Disord. 2019 34 11 1644 1654 10.1002/mds.27793 31309609
    [Google Scholar]
  50. Talwar P. Kushwaha S. Chaturvedi M. Mahajan V. Systematic review of different neuroimaging correlates in mild cognitive impairment and Alzheimer’s disease. Clin. Neuroradiol. 2021 31 4 953 967 10.1007/s00062‑021‑01057‑7 34297137
    [Google Scholar]
  51. Droby A. Pelosin E. Putzolu M. Bommarito G. Marchese R. Mazzella L. Avanzino L. Inglese M. A multimodal imaging approach demonstrates reduced midbrain functional network connectivity is associated with freezing of gait in Parkinson’s disease. Front. Neurol. 2021 12 583593 10.3389/fneur.2021.583593 33995237
    [Google Scholar]
  52. Sveinbjornsdottir S. The clinical symptoms of Parkinson’s disease. J. Neurochem. 2016 139 S1 318 324 10.1111/jnc.13691 27401947
    [Google Scholar]
  53. Vogt B.A. Cingulate cortex in Parkinson’s disease. Handb. Clin. Neurol. 2019 166 253 266 10.1016/B978‑0‑444‑64196‑0.00013‑3 31731914
    [Google Scholar]
  54. Rolls E.T. The cingulate cortex and limbic systems for emotion, action, and memory. Brain Struct. Funct. 2019 224 9 3001 3018 10.1007/s00429‑019‑01945‑2 31451898
    [Google Scholar]
  55. Jha A. Litvak V. Taulu S. Thevathasan W. Hyam J.A. Foltynie T. Limousin P. Bogdanovic M. Zrinzo L. Green A.L. Aziz T.Z. Friston K. Brown P. Functional connectivity of the pedunculopontine nucleus and surrounding region in Parkinson’s disease. Cereb. Cortex 2017 27 1 54 67 10.1093/cercor/bhw340 28316456
    [Google Scholar]
  56. Almeida Q.J. Lebold C.A. Freezing of gait in Parkinson’s disease: A perceptual cause for a motor impairment? J. Neurol. Neurosurg. Psychiatry 2010 81 5 513 518 10.1136/jnnp.2008.160580 19758982
    [Google Scholar]
  57. Iseki K. Hanakawa T. Shinozaki J. Nankaku M. Fukuyama H. Neural mechanisms involved in mental imagery and observation of gait. Neuroimage 2008 41 3 1021 1031 10.1016/j.neuroimage.2008.03.010 18450480
    [Google Scholar]
  58. Wennberg A.M.V. Savica R. Hagen C.E. Roberts R.O. Knopman D.S. Hollman J.H. Vemuri P. Jack C.R. Jr Petersen R.C. Mielke M.M. Cerebral amyloid deposition is associated with gait parameters in the mayo clinic study of aging. J. Am. Geriatr. Soc. 2017 65 4 792 799 10.1111/jgs.14670 27869301
    [Google Scholar]
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