Histopathology of diffusion imaging abnormalities in cerebral amyloid angiopathy

Objective We sought to determine the underlying mechanism for altered white matter diffusion tensor imaging (DTI) measures at the histopathologic level in patients with cerebral amyloid angiopathy (CAA). Methods Formalin-fixed intact hemispheres from 9 CAA cases and 2 elderly controls were scanned at 3-tesla MRI, including a diffusion-weighted sequence. DTI measures (i.e., fractional anisotropy [FA] and mean diffusivity [MD]) and histopathology measures were obtained from 2 tracts: the anterior thalamic radiation and inferior longitudinal fasciculus. Results FA was reduced in both tracts and MD was increased in cases with CAA compared to controls. Regional FA was significantly correlated with tissue rarefaction, myelin density, axonal density, and white matter microinfarcts. MD correlated significantly with tissue rarefaction, myelin density, and white matter microinfarcts, but not axonal density. FA and MD did not correlate with oligodendrocytes, astrocytes, or gliosis. Multivariate analysis revealed that tissue rarefaction (β = −0.32 ± 0.12, p = 0.009) and axonal density (β = 0.25 ± 0.12, p = 0.04) were both independently associated with FA, whereas myelin density was independently associated with MD (β = −0.32 ± 0.12, p = 0.013). Finally, we found an association between increased MD in the frontal white matter and CAA severity in the frontal cortex (p = 0.035). Conclusions These results suggest that overall tissue loss, and in particular axonal and myelin loss, are major components underlying CAA-related alterations in DTI properties observed in living patients. The findings allow for a more mechanistic interpretation of DTI parameters in small vessel disease and for mechanism-based selection of candidate treatments to prevent vascular cognitive impairment.

[1]  Ping Zhou,et al.  Age-Dependent Neurovascular Dysfunction and Damage in a Mouse Model of Cerebral Amyloid Angiopathy , 2014, Stroke.

[2]  Anders M. Dale,et al.  Cortical Surface-Based Analysis I. Segmentation and Surface Reconstruction , 1999, NeuroImage.

[3]  C. Beaulieu,et al.  The basis of anisotropic water diffusion in the nervous system – a technical review , 2002, NMR in biomedicine.

[4]  David M Holtzman,et al.  Cerebrovascular Dysfunction in Amyloid Precursor Protein Transgenic Mice: Contribution of Soluble and Insoluble Amyloid-β Peptide, Partial Restoration via γ-Secretase Inhibition , 2008, The Journal of Neuroscience.

[5]  T. Montine,et al.  White matter lesions defined by diffusion tensor imaging in older adults , 2011, Annals of neurology.

[6]  S. Leurgans,et al.  The Relationship of Cerebral Vessel Pathology to Brain Microinfarcts , 2017, Brain pathology.

[7]  Alexander Leemans,et al.  The B‐matrix must be rotated when correcting for subject motion in DTI data , 2009, Magnetic resonance in medicine.

[8]  K. Jellinger,et al.  Development, appraisal, validation and implementation of a consensus protocol for the assessment of cerebral amyloid angiopathy in post-mortem brain tissue. , 2014, American journal of neurodegenerative disease.

[9]  Geert Jan Biessels,et al.  Detection, risk factors, and functional consequences of cerebral microinfarcts , 2017, The Lancet Neurology.

[10]  Heidi Johansen-Berg,et al.  A combined post-mortem magnetic resonance imaging and quantitative histological study of multiple sclerosis pathology , 2012, Brain : a journal of neurology.

[11]  David G Norris,et al.  Diffusion tensor imaging and cognition in cerebral small vessel disease: the RUN DMC study. , 2012, Biochimica et biophysica acta.

[12]  Max A. Viergever,et al.  Partial volume effect as a hidden covariate in DTI analyses , 2011, NeuroImage.

[13]  P. Hof,et al.  The relationship between cerebral amyloid angiopathy and cortical microinfarcts in brain ageing and Alzheimer's disease , 2013, Neuropathology and applied neurobiology.

[14]  J. O'Brien,et al.  White matter lesions in an unselected cohort of the elderly: astrocytic, microglial and oligodendrocyte precursor cell responses , 2007, Neuropathology and applied neurobiology.

[15]  Tipu Z. Aziz,et al.  Diffusion imaging of whole, post-mortem human brains on a clinical MRI scanner , 2011, NeuroImage.

[16]  Panagiotis Fotiadis,et al.  Relationship between white matter connectivity loss and cortical thinning in cerebral amyloid angiopathy , 2017, Human brain mapping.

[17]  M. van Buchem,et al.  Cerebrovascular function in presymptomatic and symptomatic individuals with hereditary cerebral amyloid angiopathy: a case-control study , 2017, The Lancet Neurology.

[18]  Richard Frayne,et al.  Neurovascular decoupling is associated with severity of cerebral amyloid angiopathy , 2013, Neurology.

[19]  Jacob Cohen Statistical Power Analysis for the Behavioral Sciences , 1969, The SAGE Encyclopedia of Research Design.

[20]  T. Hortobágyi,et al.  Vascular cognitive impairment neuropathology guidelines (VCING): the contribution of cerebrovascular pathology to cognitive impairment. , 2016, Brain : a journal of neurology.

[21]  P. Basser,et al.  In vivo fiber tractography using DT‐MRI data , 2000, Magnetic resonance in medicine.

[22]  Jan Sijbers,et al.  Weighted linear least squares estimation of diffusion MRI parameters: Strengths, limitations, and pitfalls , 2013, NeuroImage.

[23]  J. Schneider,et al.  Vascular contributions to cognitive impairment and dementia including Alzheimer's disease , 2015, Alzheimer's & Dementia.

[24]  P. Basser,et al.  Toward a quantitative assessment of diffusion anisotropy , 1996, Magnetic resonance in medicine.

[25]  Peter A. Calabresi,et al.  Tract probability maps in stereotaxic spaces: Analyses of white matter anatomy and tract-specific quantification , 2008, NeuroImage.

[26]  Emilie T. McKinnon,et al.  Functional deficits induced by cortical microinfarcts , 2017, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[27]  Gareth J. Barker,et al.  Diffusion tensor imaging of post mortem multiple sclerosis brain , 2007, NeuroImage.

[28]  L. Concha,et al.  A macroscopic view of microstructure: Using diffusion-weighted images to infer damage, repair, and plasticity of white matter , 2014, Neuroscience.

[29]  Alexander Leemans,et al.  Structural network alterations and neurological dysfunction in cerebral amyloid angiopathy. , 2015, Brain : a journal of neurology.

[30]  S. Carmichael,et al.  Molecular disorganization of axons adjacent to human lacunar infarcts. , 2015, Brain : a journal of neurology.

[31]  P. Lachenbruch Statistical Power Analysis for the Behavioral Sciences (2nd ed.) , 1989 .

[32]  Geert Jan Biessels,et al.  Microbleed and microinfarct detection in amyloid angiopathy: a high-resolution MRI-histopathology study. , 2016, Brain : a journal of neurology.

[33]  Phillip B. Jones,et al.  Age-dependent cerebrovascular dysfunction in a transgenic mouse model of cerebral amyloid angiopathy. , 2007, Brain : a journal of neurology.

[34]  Andrew Dumas,et al.  Functional magnetic resonance imaging detection of vascular reactivity in cerebral amyloid angiopathy , 2012, Annals of neurology.

[35]  F. de Leeuw,et al.  A Novel Imaging Marker for Small Vessel Disease Based on Skeletonization of White Matter Tracts and Diffusion Histograms , 2016, Annals of neurology.

[36]  S. Greenberg,et al.  Diagnosis of Cerebral Amyloid Angiopathy: Evolution of the Boston Criteria. , 2018, Stroke.

[37]  Eric E. Smith,et al.  White Matter Alterations in Cerebral Amyloid Angiopathy Measured by Diffusion Tensor Imaging , 2006, Stroke.

[38]  Timothy Edward John Behrens,et al.  High resolution diffusion-weighted imaging in fixed human brain using diffusion-weighted steady state free precession , 2009, NeuroImage.

[39]  Sebastien Ourselin,et al.  The importance of correcting for signal drift in diffusion MRI , 2017, Magnetic resonance in medicine.

[40]  L. Pantoni Cerebral small vessel disease: from pathogenesis and clinical characteristics to therapeutic challenges , 2010, The Lancet Neurology.

[41]  Johannes E. Schindelin,et al.  Fiji: an open-source platform for biological-image analysis , 2012, Nature Methods.

[42]  Jeremy J. Flint,et al.  Postmortem interval alters the water relaxation and diffusion properties of rat nervous tissue — Implications for MRI studies of human autopsy samples , 2009, NeuroImage.

[43]  C. Iadecola,et al.  The Pathobiology of Vascular Dementia , 2013, Neuron.

[44]  D. Werring,et al.  Outcome markers for clinical trials in cerebral amyloid angiopathy , 2001, The Lancet Neurology.

[45]  W. M. van der Flier,et al.  Heterogeneity of small vessel disease: a systematic review of MRI and histopathology correlations , 2010, Journal of Neurology, Neurosurgery & Psychiatry.

[46]  W. Baaré,et al.  An ex vivo imaging pipeline for producing high‐quality and high‐resolution diffusion‐weighted imaging datasets , 2011, Human brain mapping.

[47]  Brian A. Wandell,et al.  Diffusion properties of major white matter tracts in young, typically developing children , 2014, NeuroImage.

[48]  O. Wu,et al.  Microinfarct disruption of white matter structure , 2014, Neurology.

[49]  H S Markus,et al.  Diffusion tensor MRI correlates with executive dysfunction in patients with ischaemic leukoaraiosis , 2004, Journal of Neurology, Neurosurgery & Psychiatry.

[50]  Jan Sijbers,et al.  ExploreDTI: a graphical toolbox for processing, analyzing, and visualizing diffusion MR data , 2009 .