Quantitative Neuroimaging Group (QNG)

Head of the quantitative neuroimaging group (QNG):

  • Professor Peter Bede

Members of quantitative neuroimaging group (QNG):  

  • Dr Colin Doherty
  • Prof Orla Hardiman
  • Dr Susan Byrne
  • Dr Russell McLaughlin
  • Dr Lilia Zaporojan
  • Dr Patricia McNamara
  • Dr Jennifer Williams
  • Dr Damien Ferguson 

The quantitative neuroimaging group (QNG) was founded in 2009 to develop imaging based biomarkers in neurodegenerative conditions. Quantitative neuroimaging is exciting interface between clinical neurology, neuroanatomy, computational radiology and neuropathology. The QNG is a small translational research group centred around biomarker development, with a vision to develop viable clinical applications and decipher patterns of anatomical spread in neurodegeneration. Our study hypotheses stem from clinical observations and our objectives are focused on improved individualised patient care.  We work closely with our international partners through the JPND-SOPHIA and NISALS consortia and the Irish and UK Motor Neuron Disease Associations.

Our initial projects focused primarily on descriptive analyses, characterising disease-specific changes in comparison to healthy individuals. These projects have been gradually expanded to describe phenotype-specific changes and explore clinico-radiological correlations. We have demonstrated that focal grey matter pathology correlates with functional disability, and that distinct atrophy patterns define the main clinical phenotypes. Using multiple, complementary imaging techniques, we have described genotype-specific imaging signatures confirming clinical observations in relation to pathological mutations. Our group has a special interest in the comprehensive characterisation of basal ganglia pathology in vivo, and the assessment of frontostriatal and cortico-basal networks integrity. These analyses have implications beyond motor disability and permit the assessment of multi-synaptic networks underpinning complex cognitive and behavioural functions. More recently, our attention turned to the development, testing and validation of complex machine-learning algorithms to enable accurate early-stage diagnosis and precise patient classification into prognostic, motor and cognitive phenotypes.

Our Sponsors

Our work is supported by the Health Research Board (HRB – Ireland), the Irish Institute of Clinical Neuroscience (IICN) - Novartis Ireland Research Grant, The Iris O'Brien Foundation, The Perrigo Clinician-Scientist Research Fellowship, and the Research Motor Neuron (RMN-Ireland) foundation, the EU-Joint Programme for Neurodegeneration (JPND) SOPHIA project.

  1. Peter Bede, Parameswaran M. Iyer, Eoin Finegan, Taha Omer, Orla Hardiman. Virtual brain biopsies in amyotrophic lateral sclerosis: diagnostic classification based on in vivo pathological patterns. Neuroimage Clinical 2017 Jun 9;15:653-658. doi: 10.1016/j.nicl.2017.06.010. eCollection 2017. PMID: 28664036
  2. Taha Omer, Eoin Finegan, Siobhan Hutchinson, Mark A. Doherty, Alice Vajda, Russell L. McLaughlin, Niall Pender, Orla Hardiman, Peter Bede. Neuroimaging patterns along the ALS-FTD spectrum: a multiparametric imaging study – Amyotroph Lateral Scler Frontotemporal Degener. 2017 May 31:1-13. doi: 10.1080/21678421.2017.1332077. PMID: 28562080 2017
  3. Jennifer Williams, Peter Bede, Colin Doherty. An exploration of the spectrum of peri-ictal MRI change; a comprehensive literature review. Seizure: European Journal of Epilepsy - Seizure. 2017 May 31;50:19-32. doi: 10.1016/j.seizure.2017.05.005.PMID: 28600921  Accepted
  4. Peter Bede, Eoin Finegan, Orla Hardiman. From pneumomyelography to cord tractography: historical perspectives on spinal imaging. Future Neurology. 2017
    Schuster C, Hardiman O, Bede P. Survival prediction in Amyotrophic lateral sclerosis based on MRI measures and clinical characteristics. BMC Neurol. 2017 Apr 17;17(1):73. doi: 10.1186/s12883-017-0854-x. PMID: 28412941
  5. Tarig Abkur, Peter Bede. Reversible gait ataxia: From wheelchair to independent mobility, Neurology  2017 Apr 11;88(15):e145-e149. doi: 10.1212/WNL.0000000000003815. PMID: 28396457
  6. Peter Bede. From qualitative radiological cues to machine learning: MRI-based diagnosis in neurodegeneration. Future Neurology. February 2017 ,Vol. 12, No. 1, Pages 5-8 , DOI 10.2217/fnl-2016-0029
  7. Christina Schuster, Orla Hardiman, Peter Bede. Development of an automated MRI-based diagnostic protocol for Amyotrophic Lateral Sclerosis using disease-specific pathognomonic features: a quantitative disease-state classification study. PLoS One. 2016 Dec 1;11(12):e0167331. PMID: 27907080
  8. Schuster C, Elamin M, Hardiman O, Bede P. The segmental diffusivity profile of ALS-associated white matter degeneration. Eur J Neurol. 2016 Aug;23(8):1361-71. doi: 10.1111/ene.13038.PMID: 27207250
  9. Bede P, Iyer PM, Schuster C, Elamin M, McLaughlin RL, Kenna K, Hardiman O. "The selective anatomical vulnerability of ALS - “disease-defining” and “disease-defying” brain regions" Amyotroph Lateral Scler Frontotemporal Degener. 2016 Apr 18:1-10. [Epub ahead of print] PMID: 27087114 DOI:10.3109/21678421.2016.1173702
  10. Iyer P, Doherty C, Bede P. Imaging biomarkers in neurodegenerative conditions (Book chapter) Neurodegenerative disorders: A clinical guide – Second Edition, Chapter 2, p 13-27, ISBN: ISBN 978-3-319-23308-6 Springer 2016. DOI 10.1007/978-3-319-23309-3
  11. Editors: Orla Hardiman, Colin P. Doherty, Marwa Elamin, Peter Bede
    Schuster C, Elamin M, Hardiman O, Bede P. Presymptomatic and longitudinal neuroimaging in neurodegeneration: from snapshots to motion picture - a systematic review. J Neurol Neurosurg Psychiatry. 2015 Oct;86(10):1089-96. doi: 10.1136/jnnp-2014-309888. PMID: 25632156
  12. Bede P, Elamin M, Byrne S, McLaughlin RL, Kenna K, Vajda A, Fagan A, Bradley DG, Hardiman O. Patterns of cerebral and cerebellar white matter degeneration in ALS. J Neurol Neurosurg Psychiatry. 2015 Apr;86(4):468-70. doi: 10.1136/jnnp-2014-308172. PMID: 25053771
  13. Bede P, Hardiman O. Lessons of ALS imaging: pitfalls, inconsistencies, and future directions – a critical review. Neuroimage Clin. 2014 Feb 27;4:436-443. PMID: 24624329
  14. Bede P, Elamin M, Byrne S, McLaughlin R, Kenna K, Vajda A, Pender N, Bradley DG, Hardiman O. Basal ganglia involvement in Amyotrophic Lateral Sclerosis. Neurology, 2013 Dec 10;81(24):2107-15. PMID: 24212388
  15. Bede P, Bokde ALW, Byrne S, Elamin M, McLaughlin R, Kenna K, Fagan AJ, Pender N, Bradley DG, Hardiman O. A multiparametric MRI study of ALS stratified for the C9orf72 genotype. Neurology. 2013 Jul 23;81(4):361-9. PMID: 23771489
  16. Bede P, Bokde AL, Elamin M, Bynre S, McLaughlin RL, Jordan N, Hampel H, Gallagher L, Lynch C, Fagan A, Pender N, Hardiman O. Grey matter correlates of clinical variables in Amyotrophic Lateral Sclerosis– a neuroimaging study of ALS motor phenotype heterogeneity and cortical focality. J Neurol Neurosurg Psychiatry. 2013 Jul;84(7):766-73. PMID: 23085933
  17. Bede P, Bokde AL, Byrne S, Elamin M, Fagan AJ, Hardiman O. Spinal cord markers in ALS: Diagnostic and biomarker considerations. Amyotroph Lateral Scler. 2012 Sep;13(5):407-15. PMID: 22329869
  18. Byrne S, Elamin M, Bede P, Shatunov A, Walsh C, Corr B, Heverin M, Jordan N, Kenna K, Lynch C, McLaughlin RL, Iyer PM, O'Brien C, Phukan J, Wynne B, Bokde AL, Bradley DG, Pender N, Al-Chalabi A, Hardiman O. Cognitive and clinical characteristics of patients with amyotrophic lateral sclerosis carrying a C9orf72 repeat expansion: a population-based cohort study. Lancet Neurol. 2012 Mar;11(3):232-40. PMID: 22305801