Microbleeds versus macrobleeds: evidence for distinct entities

Abstract

Background and purpose: Small, asymptomatic microbleeds commonly accompany larger symptomatic macrobleeds. It is unclear whether microbleeds and macrobleeds represent arbitrary categories within a single continuum versus truly distinct events with separate pathophysiologies.

Methods: We performed 2 complementary retrospective analyses. In a radiographic analysis, we measured and plotted the volumes of all hemorrhagic lesions detected by gradient-echo MRI among 46 consecutive patients with symptomatic primary lobar intracerebral hemorrhage diagnosed as probable or possible cerebral amyloid angiopathy. In a second neuropathologic analysis, we performed blinded qualitative and quantitative examinations of amyloid-positive vessel segments in 6 autopsied subjects whose MRI scans demonstrated particularly high microbleed counts (>50 microbleeds on MRI, n=3) or low microbleed counts (<3 microbleeds, n=3).

Results: Plotted on a logarithmic scale, the volumes of 163 hemorrhagic lesions identified on scans from the 46 subjects fell in a distinctly bimodal distribution with mean volumes for the 2 modes of 0.009 cm(3) and 27.5 cm(3). The optimal cut point for separating the 2 peaks (determined by receiver operating characteristics) corresponded to a lesion diameter of 0.57 cm. On neuropathologic analysis, the high microbleed-count autopsied subjects showed significantly thicker amyloid-positive vessel walls than the low microbleed-count subjects (proportional wall thickness 0.53+/-0.01 versus 0.37+/-0.01; P<0.0001; n=333 vessel segments analyzed).

Conclusions: These findings suggest that cerebral amyloid angiopathy-associated microbleeds and macrobleeds comprise distinct entities. Increased vessel wall thickness may predispose to formation of microbleeds relative to macrobleeds.

Figure 1

Bimodal distribution of hemorrhage volumes. Volumes of 163 individual hemorrhages from 46 subjects with probable or possible CAA are plotted on a natural logarithmic scale and shown as a histogram of probability densities. The superimposed dashed curves represent a mixture model comprised of a normal distribution for the smaller volumes (mean and standard deviation of log volumes −4.7 and 0.83 respectively) and a double exponential curve (mean and standard deviation of log volumes 3.31 and 1.17) for the larger volumes, selected by goodness of fit testing (p=0.86). The dashed vertical line shows a threshold volume of 0.098 cm³ (log volume −2.319) that optimally classifies values in the two distributions. The null hypothesis that these populations of log hemorrhage volumes fit a unimodal normal distribution can be rejected (p<.0001).

Figure 2

Representative MRI images from high and low microbleed-count subjects with subsequent neuropathological examination. Panel A shows axial GRE MRI images from subject 1 (62 microbleeds; see Table 2) and panel B from subject 4 (0 microbleeds). Each brain demonstrated definite CAA at autopsy.

Figure 3

Representative vessel segments from high and low microbleed-count CAA subjects. Panel A shows cross-sectional vessel profiles from occipital cortex of high microbleed subjects (1, 2, and 3 from left to right; see Table 2), panel B from low microbleed subjects (4, 5, and 6 from left to right). Vessel walls from high microbleed subjects were significantly thicker than from low microbleed subjects. All specimens were stained by luxol fast blue-hematoxylin-eosin with original magnification 40x.