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Research ArticleAdult Brain
Open Access

Cerebral Microbleeds Are Associated with Loss of White Matter Integrity

J.-Y. Liu, Y.-J. Zhou, F.-F. Zhai, F. Han, L.-X. Zhou, J. Ni, M. Yao, S. Zhang, Z. Jin, L. Cui and Y.-C. Zhu
American Journal of Neuroradiology August 2020, 41 (8) 1397-1404; DOI: https://doi.org/10.3174/ajnr.A6622
J.-Y. Liu
aFrom the Departments of Neurology (J.-Y.L., Y.-J.Z., F.-F.Z., F.H., L.-X.Z., J.N., M.Y., L.C., Y.-C.Z.), Radiology (Z.J.), and Cardiology (S.Z.), Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Science, Beijing, China.
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Y.-J. Zhou
aFrom the Departments of Neurology (J.-Y.L., Y.-J.Z., F.-F.Z., F.H., L.-X.Z., J.N., M.Y., L.C., Y.-C.Z.), Radiology (Z.J.), and Cardiology (S.Z.), Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Science, Beijing, China.
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F.-F. Zhai
aFrom the Departments of Neurology (J.-Y.L., Y.-J.Z., F.-F.Z., F.H., L.-X.Z., J.N., M.Y., L.C., Y.-C.Z.), Radiology (Z.J.), and Cardiology (S.Z.), Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Science, Beijing, China.
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F. Han
aFrom the Departments of Neurology (J.-Y.L., Y.-J.Z., F.-F.Z., F.H., L.-X.Z., J.N., M.Y., L.C., Y.-C.Z.), Radiology (Z.J.), and Cardiology (S.Z.), Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Science, Beijing, China.
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L.-X. Zhou
aFrom the Departments of Neurology (J.-Y.L., Y.-J.Z., F.-F.Z., F.H., L.-X.Z., J.N., M.Y., L.C., Y.-C.Z.), Radiology (Z.J.), and Cardiology (S.Z.), Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Science, Beijing, China.
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J. Ni
aFrom the Departments of Neurology (J.-Y.L., Y.-J.Z., F.-F.Z., F.H., L.-X.Z., J.N., M.Y., L.C., Y.-C.Z.), Radiology (Z.J.), and Cardiology (S.Z.), Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Science, Beijing, China.
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M. Yao
aFrom the Departments of Neurology (J.-Y.L., Y.-J.Z., F.-F.Z., F.H., L.-X.Z., J.N., M.Y., L.C., Y.-C.Z.), Radiology (Z.J.), and Cardiology (S.Z.), Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Science, Beijing, China.
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S. Zhang
aFrom the Departments of Neurology (J.-Y.L., Y.-J.Z., F.-F.Z., F.H., L.-X.Z., J.N., M.Y., L.C., Y.-C.Z.), Radiology (Z.J.), and Cardiology (S.Z.), Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Science, Beijing, China.
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Z. Jin
aFrom the Departments of Neurology (J.-Y.L., Y.-J.Z., F.-F.Z., F.H., L.-X.Z., J.N., M.Y., L.C., Y.-C.Z.), Radiology (Z.J.), and Cardiology (S.Z.), Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Science, Beijing, China.
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L. Cui
aFrom the Departments of Neurology (J.-Y.L., Y.-J.Z., F.-F.Z., F.H., L.-X.Z., J.N., M.Y., L.C., Y.-C.Z.), Radiology (Z.J.), and Cardiology (S.Z.), Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Science, Beijing, China.
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Y.-C. Zhu
aFrom the Departments of Neurology (J.-Y.L., Y.-J.Z., F.-F.Z., F.H., L.-X.Z., J.N., M.Y., L.C., Y.-C.Z.), Radiology (Z.J.), and Cardiology (S.Z.), Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Science, Beijing, China.
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    Fig 1.

    Flow diagram of the study population.

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    Fig 2.

    DTI parameters related to deep CMBs. Tract-Based Spatial Statistics analysis of FA and the CMB location (deep CMBs with or without lobar CMBs). Deep CMBs were associated with decreased FA and increased MD, axial diffusivity, and radial diffusivity, adjusted for age, sex, hypertension, hyperlipidemia, smoking, and diabetes (A), or age, sex, hypertension, hyperlipidemia, smoking, diabetes, white matter hyperintensity volume, and lacunes (B), thresholded at P < .05, and corrected for multiple comparisons. The red colormap indicates a positive relationship, and the blue colormap indicates a negative relationship. The statistical maps are superimposed onto the spatially normalized (Montreal Neurological Institute stereotactic space) and averaged (n = 931) FA map. Threshold-free cluster enhancement corrected P < .05.

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    Fig 3.

    DTI parameters related to strictly lobar CMB. Tract-Based Spatial Statistics analysis of FA and CMB location (strictly lobar). Lobar CMBs were associated with decreased FA and increased MD, axial diffusivity, and radial diffusivity, adjusted for age, sex, hypertension, hyperlipidemia, smoking, and diabetes (A), or age, sex, hypertension, hyperlipidemia, smoking, diabetes, white matter hyperintensity volume and lacunes (B), thresholded at P < .05 and corrected for multiple comparisons. The red colormap indicates a positive relationship, and the blue colormap indicates negative relationship. The statistical maps are superimposed onto the spatially normalized (Montreal Neurological Institute stereotactic space) and averaged (n = 922) FA map. Threshold-free cluster enhancement corrected P < .05.

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    Fig 4.

    FA and MD of the lesioned tract expressed as a ratio relative to the control tract. The x-axis shows the distance in millimeters from the microbleed location. Data show the mean and its 95% CI. The asterisk indicates that the difference was significant between the CMB tract and control tract (P < .05).

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    Table 1:

    Characteristics of the study populationa

    VariablesNormalDeep CMBsLobar CMBsPbPc
    Demographics
     Age (yr)55.3 (9.1)62.6 (7.5)60.8 (9.0)<.001.314
     Men296 (34%)36 (60%)20 (39%)<.001.048
    Cardiovascular risk factors
     Hypertension427 (49%)48 (80%)27 (53%)<.001.002b
     Diabetes mellites148 (17%)14 (23%)12 (24%).212.981
     Hyperlipidemia427 (49%)29 (48%)27 (53%).869.628
     Smoking231 (26.5%)25 (41.7%)15 (29.4%).038.180
    Neuroimaging characteristics
     Presence of lacunes122 (14%)35 (58%)15 (29%)<.001.002d
     WMH volume (mL)0.82 (0.25–2.62)5.82 (2.09–12.81)3.56 (0.99–7.11)<.001.086
     Total brain volume (mL)1402.7 (123.2)1421.0 (132.6)1424.2 (136.3).285.893
    CMB numbers–.003d
     1–29 (48.3%)36 (70.5%)
     2∼3–17 (28.3%)13 (25.5%)
     >4–14 (23.3%)2 (4.0%)
    DTI parameters
     Mean global FA, NAWM0.37 (0.02)0.35 (0.03)0.35 (0.02)<.001.143
     Mean global MD, ×10–3mm2/s, NAWM0.84 (0.04)0.89 (0.06)0.87 (0.05)<.001.031
     Axial diffusivity, ×10−3 mm2/s, NAWM1.18 (0.04)1.22 (0.05)1.20 (0.05)<.001.023
     Radial diffusivity, ×10−3 mm2/s, NAWM0.67 (0.05)0.73 (0.07)0.71 (0.06)<.001.042
    • Note:—–indicates no CMBs.

    • ↵a Data represent mean (SD), median (interquartile range), or frequency (percentage).

    • ↵b Significance test among 3 groups, using the ANOVA, χ2 test, or the Kruskal-Wallis test.

    • ↵c Post hoc analysis between the deep CMB and lobar CMB groups.

    • ↵d The difference was significant between deep CMBs and lobar CMBs groups (Bonferroni-corrected, P < .017).

    • View popup
    Table 2:

    Microbleeds (yes versus no) and white matter microstructure integritya

    FAMDAxial DiffusivityRadial Diffusivity
    βPβPβPβP
    Model 1−0.450 (−0.616 to −0.285)<.0010.433 (0.282−0.584)<.0010.378 (0.221−0.535)<.0010.446 (0.295−0.597)<.001
    Model 2−0.433 (−0.597 to −0.269)<.0010.420 (0.271−0.570)<.0010.368 (0.212−0.524)<.0010.432 (0.282−0.581)<.001
    Model 3−0.238 (−0.394 to −0.083).0030.204 (0.068−0.340).0030.165 (0.019−0.310).0260.217 (0.081−0.352).002
    Model 4−0.241 (−0.396 to −0.086).0020.206 (0.070−0.342).0030.167 (0.021−0.312).0250.218 (0.083−0.354).002
    • Note:—β indicates regression coefficient.

    • ↵a Values represent differences in z scores of mean FA, MD, axial diffusivity, and radial diffusivity of NAWM for the presence of any microbleeds compared with no microbleeds. Model 1: adjusted for age and sex; model 2: same as model 1, additionally adjusted for hypertension, hyperlipidemia, smoking, diabetes; model 3: adjusted for age, sex, lacunes, and white matter hyperintensity volume (log-transformed); model 4: adjusted for sex, cardiovascular risk factors as in model 2, and CSVD imaging markers as in model 3.

    • View popup
    Table 3:

    Microbleeds by location and white matter microstructure integritya

    FAMDAxial DiffusivityRadial Diffusivity
    βPβPβPβP
    None vs lobar
     Model 1−0.396 (−0.622 to −0.169).0010.339 (0.135−0.543).0010.270 (0.055−0.484).0140.363 (0.159−0.566)<.001
     Model 2−0.396 (−0.619 to −0.173).0010.340 (0.138−0.541).0010.270 (0.058−0.485).0130.362 (0.162−0.563)<.001
     Model 3−0.258 (−0.467 to −0.048).0160.191 (0.010−0.372).0380.131 (−0.065−0.327).1910.215 (0.034−0.395).020
     Model 4−0.264 (−0.472 to −0.056).0130.195 (0.014−0.376).0340.134 (−0.062−0.330).1800.218 (0.039−0.398).017
    None vs deep
     Model 1−0.509 (−0.726 to −0.293)<.0010.530 (0.335−0.725)<.0010.486 (0.283−0.689)<.0010.534 (0.339−0.729)<.001
     Model 2−0.481 (−0.697 to −0.266).0010.512 (0.317−0.706)<.0010.472 (0.268−0.675)<.0010.514 (0.319−0.708)<.001
     Model 3−0.244 (−0.450 to −0.038).0200.243 (0.065−0.421).0080.218 (0.028−0.408).0250.246 (0.068−0.424).007
     Model 4−0.242 (−0.448 to −0.036).0210.245 (0.071−0.424).0070.220 (0.029−0.411).0240.248 (0.069−0.426).007
    • Note:—β indicates regression coefficient.

    • ↵a Values represent differences in z scores of mean FA, MD, axial diffusivity and radial diffusivity of NAWM for the presence of any microbleeds by their location compared with no microbleeds. Model 1: adjusted for age and sex; model 2: same as model 1, additionally adjusted for hypertension, hyperlipidemia, smoking, diabetes; model 3: adjusted for age, sex, lacunes, white matter hyperintensity volume (log-transformed); model 4: adjusted for sex, cardiovascular risk factors as in model 2, and CSVD imaging markers as in model 3.

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J.-Y. Liu, Y.-J. Zhou, F.-F. Zhai, F. Han, L.-X. Zhou, J. Ni, M. Yao, S. Zhang, Z. Jin, L. Cui, Y.-C. Zhu
Cerebral Microbleeds Are Associated with Loss of White Matter Integrity
American Journal of Neuroradiology Aug 2020, 41 (8) 1397-1404; DOI: 10.3174/ajnr.A6622

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Cerebral Microbleeds Are Associated with Loss of White Matter Integrity
J.-Y. Liu, Y.-J. Zhou, F.-F. Zhai, F. Han, L.-X. Zhou, J. Ni, M. Yao, S. Zhang, Z. Jin, L. Cui, Y.-C. Zhu
American Journal of Neuroradiology Aug 2020, 41 (8) 1397-1404; DOI: 10.3174/ajnr.A6622
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